From dc27f714a21b1c4ebdc13364aaa6ed864384d44a Mon Sep 17 00:00:00 2001
From: soerenray <soerenraymond@gmail.com>
Date: Fri, 20 Oct 2023 17:37:36 +0200
Subject: [PATCH 01/27] construction time plot

---
 .gitignore                       |   5 +-
 scripts/inspect_bottleneck.ipynb | 135 +++++++++++++++++++++++++++++++
 scripts/mesh2vec_times.png       | Bin 0 -> 44414 bytes
 3 files changed, 139 insertions(+), 1 deletion(-)
 create mode 100644 scripts/inspect_bottleneck.ipynb
 create mode 100644 scripts/mesh2vec_times.png

diff --git a/.gitignore b/.gitignore
index 0066896..12a5a6c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -4,4 +4,7 @@
 /docs/source/generated*
 __pycache__
 /data/tmp_*
-/data/*internal*
\ No newline at end of file
+/data/*internal*
+.DS_Store
+.venv/
+.ipynb_checkpoints
\ No newline at end of file
diff --git a/scripts/inspect_bottleneck.ipynb b/scripts/inspect_bottleneck.ipynb
new file mode 100644
index 0000000..067a773
--- /dev/null
+++ b/scripts/inspect_bottleneck.ipynb
@@ -0,0 +1,135 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "05ed44a9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mesh2vec.mesh2vec_cae import Mesh2VecCae\n",
+    "from pathlib import Path\n",
+    "from functools import wraps\n",
+    "import time\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d4510390",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "Credit: https://dev.to/kcdchennai/python-decorator-to-measure-execution-time-54hk\n",
+    "\"\"\"\n",
+    "\n",
+    "\n",
+    "def timeit(func):\n",
+    "    @wraps(func)\n",
+    "    def timeit_wrapper(*args, **kwargs):\n",
+    "        # time.perf_counter() more accurate than time.time()\n",
+    "        start_time = time.perf_counter()\n",
+    "        result = func(*args, **kwargs)\n",
+    "        end_time = time.perf_counter()\n",
+    "        total_time = end_time - start_time\n",
+    "        # result of construction irrelevant, we just want the elapsed time\n",
+    "        return total_time\n",
+    "    return timeit_wrapper\n",
+    "\n",
+    "\n",
+    "@timeit\n",
+    "def measure_from_ansa(distance):\n",
+    "    \"\"\"\n",
+    "    Collect time it takes to construct vector\n",
+    "    \"\"\"\n",
+    "    m2v = Mesh2VecCae.from_ansa_shell(\n",
+    "        distance,\n",
+    "        Path(\"../data/hat/Hatprofile.k\"),\n",
+    "        json_mesh_file=Path(\"../data/hat/cached_hat_key.json\")\n",
+    "    )\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "63d7ce86",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plot_dict = dict()\n",
+    "\n",
+    "for i in range(1, 41):\n",
+    "    time_elapsed = measure_from_ansa(i)\n",
+    "    plot_dict.update({str(i): time_elapsed})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d9fcead0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plot_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d5bffb97",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.figure(figsize=(12, 12))\n",
+    "plt.plot(plot_dict.keys(), plot_dict.values())\n",
+    "plt.xlabel(\"neighbors\")\n",
+    "plt.ylabel(\"construction time\")\n",
+    "\n",
+    "plt.savefig('mesh2vec_times.png')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c273fcc9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# next step: bottlenecks finden"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4c71e44b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/scripts/mesh2vec_times.png b/scripts/mesh2vec_times.png
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From bce5080299c29d408eba78a8c76efc82ff954616 Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Tue, 24 Oct 2023 11:08:19 +0200
Subject: [PATCH 02/27] test on Renumics PC

---
 scripts/mesh2vec_times.png                    | Bin 44414 -> 41634 bytes
 ...leneck.ipynb => plot_execution_time.ipynb} |  12 +-----------
 2 files changed, 1 insertion(+), 11 deletions(-)
 rename scripts/{inspect_bottleneck.ipynb => plot_execution_time.ipynb} (93%)

diff --git a/scripts/mesh2vec_times.png b/scripts/mesh2vec_times.png
index 93f52fbaefdca58a4f700dd075c44026d886c301..98cfda7a4005f58c616b5f07ea07e909230e75f1 100644
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diff --git a/scripts/inspect_bottleneck.ipynb b/scripts/plot_execution_time.ipynb
similarity index 93%
rename from scripts/inspect_bottleneck.ipynb
rename to scripts/plot_execution_time.ipynb
index 067a773..9ed3505 100644
--- a/scripts/inspect_bottleneck.ipynb
+++ b/scripts/plot_execution_time.ipynb
@@ -92,16 +92,6 @@
     "plt.show()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c273fcc9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# next step: bottlenecks finden"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -127,7 +117,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.6"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

From 5652cb66e8e27f0f054fd80770808424df4ab1a3 Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Tue, 24 Oct 2023 15:58:49 +0200
Subject: [PATCH 03/27] added profiling with stats to file and interactive
 profiling

---
 scripts/discover_bottlenecks.ipynb | 114 +++++
 scripts/profile_stats.txt          | 771 +++++++++++++++++++++++++++++
 2 files changed, 885 insertions(+)
 create mode 100644 scripts/discover_bottlenecks.ipynb
 create mode 100644 scripts/profile_stats.txt

diff --git a/scripts/discover_bottlenecks.ipynb b/scripts/discover_bottlenecks.ipynb
new file mode 100644
index 0000000..0d70f87
--- /dev/null
+++ b/scripts/discover_bottlenecks.ipynb
@@ -0,0 +1,114 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3f4b82e7",
+   "metadata": {},
+   "source": [
+    "## Methodology\n",
+    "\n",
+    "Inspect calc_adjacencies in mesh2vec.mesh2vec.helpers.py from different angles to pinpoint bottlenck(s):\n",
+    "- Use time as measurement to find obvious bottlenecks\n",
+    "- Use a profiler (in this case: cProfile) to inspect statistics about each section (e.g.: number of function calls, cumulative time spent on function, ..)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8089532b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "STATS_OUTPUT_FILE = \"profile_stats.txt\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f7caade1",
+   "metadata": {},
+   "source": [
+    "### Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7a8ff956",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# perf counter more accurate than using time.time()\n",
+    "from time import perf_counter\n",
+    "\n",
+    "from pstats import SortKey, Stats\n",
+    "import io\n",
+    "from cProfile import Profile\n",
+    "\n",
+    "from pathlib import Path\n",
+    "from mesh2vec.mesh2vec_cae import Mesh2VecCae"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d78841c7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pr = Profile()\n",
+    "pr.enable()\n",
+    "Mesh2VecCae.from_ansa_shell(25,Path(\"../data/hat/Hatprofile.k\"),\n",
+    "                                  json_mesh_file=Path(\"../data/hat/cached_hat_key.json\"))  \n",
+    "pr.disable()\n",
+    "s = io.StringIO()\n",
+    "sortby = SortKey.CUMULATIVE\n",
+    "ps = Stats(pr, stream=s).sort_stats(sortby)\n",
+    "ps.print_stats()\n",
+    "\n",
+    "# write profiling stats to file\n",
+    "with open(STATS_OUTPUT_FILE, 'w+') as f:\n",
+    "    f.write(s.getvalue())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "85e2e6d1",
+   "metadata": {},
+   "source": [
+    "## Interactive visualization of profiling results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "66cb58db",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext snakeviz\n",
+    "%snakeviz Mesh2VecCae.from_ansa_shell(25,Path(\"../data/hat/Hatprofile.k\"),json_mesh_file=Path(\"../data/hat/cached_hat_key.json\"))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/scripts/profile_stats.txt b/scripts/profile_stats.txt
new file mode 100644
index 0000000..67ef622
--- /dev/null
+++ b/scripts/profile_stats.txt
@@ -0,0 +1,771 @@
+         265989 function calls (259137 primitive calls) in 7.785 seconds
+
+   Ordered by: cumulative time
+
+   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
+        2    0.000    0.000    7.804    3.902 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/IPython/core/interactiveshell.py:3490(run_code)
+        2    0.000    0.000    7.804    3.902 {built-in method builtins.exec}
+        1    0.001    0.001    7.792    7.792 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:121(from_ansa_shell)
+        1    0.010    0.010    7.727    7.727 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:32(__init__)
+        1    0.006    0.006    7.696    7.696 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_base.py:34(__init__)
+        1    0.493    0.493    7.652    7.652 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/helpers.py:8(calc_adjacencies)
+      209    3.239    0.015    3.239    0.015 {built-in method numpy.array}
+       24    0.000    0.000    3.192    0.133 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:620(__matmul__)
+       24    0.000    0.000    3.192    0.133 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:505(_mul_dispatch)
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+        1    0.000    0.000    0.000    0.000 /usr/lib/python3.10/multiprocessing/process.py:189(name)
+        1    0.000    0.000    0.000    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/numpy/core/fromnumeric.py:2416(_all_dispatcher)
+        1    0.000    0.000    0.000    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/indexes/base.py:728(_constructor)
+        1    0.000    0.000    0.000    0.000 {method 'rstrip' of 'str' objects}
+        1    0.000    0.000    0.000    0.000 /usr/lib/python3.10/tempfile.py:1004(__enter__)
+        1    0.000    0.000    0.000    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/numpy/core/fromnumeric.py:1021(_argsort_dispatcher)
+        1    0.000    0.000    0.000    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/indexes/api.py:281(<listcomp>)
+        1    0.000    0.000    0.000    0.000 {method 'release' of '_thread.lock' objects}
+        1    0.000    0.000    0.000    0.000 {method '__enter__' of '_thread.lock' objects}
+        1    0.000    0.000    0.000    0.000 {built-in method builtins.abs}
+        1    0.000    0.000    0.000    0.000 {method 'utcoffset' of 'datetime.timezone' objects}
+        1    0.000    0.000    0.000    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/numpy/core/shape_base.py:19(_atleast_1d_dispatcher)
+        1    0.000    0.000    0.000    0.000 {function FrozenList.__getitem__ at 0x7f0ed407d5a0}
+
+

From 618365fce11c2ba0370922c056ccc62a2e989a5d Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Fri, 27 Oct 2023 11:01:19 +0200
Subject: [PATCH 04/27] exclude private files

---
 .gitignore | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.gitignore b/.gitignore
index 12a5a6c..1ef6f88 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,4 +7,5 @@ __pycache__
 /data/*internal*
 .DS_Store
 .venv/
-.ipynb_checkpoints
\ No newline at end of file
+.ipynb_checkpoints
+data/mb_private_data
\ No newline at end of file

From 29fdbfbe71766d71f0721bcd6c4cbddcf4ddf83d Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Mon, 30 Oct 2023 13:14:43 +0100
Subject: [PATCH 05/27] test run

---
 scripts/discover_bottlenecks.ipynb |    8 +
 scripts/profile_stats.txt          | 1149 +++++++++++++---------------
 2 files changed, 560 insertions(+), 597 deletions(-)

diff --git a/scripts/discover_bottlenecks.ipynb b/scripts/discover_bottlenecks.ipynb
index 0d70f87..c2a2085 100644
--- a/scripts/discover_bottlenecks.ipynb
+++ b/scripts/discover_bottlenecks.ipynb
@@ -88,6 +88,14 @@
     "%load_ext snakeviz\n",
     "%snakeviz Mesh2VecCae.from_ansa_shell(25,Path(\"../data/hat/Hatprofile.k\"),json_mesh_file=Path(\"../data/hat/cached_hat_key.json\"))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ac198351",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/scripts/profile_stats.txt b/scripts/profile_stats.txt
index 67ef622..e0206b0 100644
--- a/scripts/profile_stats.txt
+++ b/scripts/profile_stats.txt
@@ -1,771 +1,726 @@
-         265989 function calls (259137 primitive calls) in 7.785 seconds
+         1107221 function calls (1078620 primitive calls) in 47.052 seconds
 
    Ordered by: cumulative time
 
    ncalls  tottime  percall  cumtime  percall filename:lineno(function)
-        2    0.000    0.000    7.804    3.902 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/IPython/core/interactiveshell.py:3490(run_code)
-        2    0.000    0.000    7.804    3.902 {built-in method builtins.exec}
-        1    0.001    0.001    7.792    7.792 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:121(from_ansa_shell)
-        1    0.010    0.010    7.727    7.727 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:32(__init__)
-        1    0.006    0.006    7.696    7.696 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_base.py:34(__init__)
-        1    0.493    0.493    7.652    7.652 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/helpers.py:8(calc_adjacencies)
-      209    3.239    0.015    3.239    0.015 {built-in method numpy.array}
-       24    0.000    0.000    3.192    0.133 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:620(__matmul__)
-       24    0.000    0.000    3.192    0.133 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:505(_mul_dispatch)
-       24    0.001    0.000    3.191    0.133 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:506(_mul_sparse_matrix)
-       24    2.098    0.087    2.098    0.087 {built-in method scipy.sparse._sparsetools.csr_matmat}
-       24    1.085    0.045    1.085    0.045 {built-in method scipy.sparse._sparsetools.csr_matmat_maxnnz}
-       25    0.000    0.000    0.645    0.026 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:477(__sub__)
-       25    0.002    0.000    0.644    0.026 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:361(_sub_sparse)
-       25    0.001    0.000    0.642    0.026 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:1237(_binopt)
-       25    0.615    0.025    0.615    0.025 {built-in method scipy.sparse._sparsetools.csr_minus_csr}
-        5    0.000    0.000    0.087    0.017 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/numpy/lib/arraysetops.py:138(unique)
-        5    0.002    0.000    0.084    0.017 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/numpy/lib/arraysetops.py:323(_unique1d)
-        5    0.080    0.016    0.080    0.016 {method 'sort' of 'numpy.ndarray' objects}
-        1    0.000    0.000    0.035    0.035 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:669(_read_ansafile)
-        1    0.000    0.000    0.032    0.032 /usr/lib/python3.10/json/__init__.py:299(loads)
-        1    0.000    0.000    0.032    0.032 /usr/lib/python3.10/json/decoder.py:332(decode)
-        1    0.032    0.032    0.032    0.032 /usr/lib/python3.10/json/decoder.py:343(raw_decode)
-  101/100    0.001    0.000    0.030    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:25(__init__)
-      101    0.001    0.000    0.024    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:135(check_format)
-        1    0.000    0.000    0.023    0.023 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh_features.py:223(from_ansa_json)
-      126    0.001    0.000    0.020    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:1167(prune)
-      252    0.000    0.000    0.018    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/_lib/_util.py:144(_prune_array)
-       53    0.018    0.000    0.018    0.000 {method 'copy' of 'numpy.ndarray' objects}
-        1    0.012    0.012    0.015    0.015 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:79(<dictcomp>)
-        1    0.003    0.003    0.013    0.013 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_exceptions.py:52(check_vtx_ids)
-        1    0.003    0.003    0.013    0.013 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_exceptions.py:33(check_hyper_edges)
-     6684    0.004    0.000    0.011    0.000 {built-in method builtins.all}
-        1    0.002    0.002    0.010    0.010 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh_features.py:235(<listcomp>)
-     6667    0.004    0.000    0.008    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_base.py:81(<genexpr>)
-      232    0.002    0.000    0.008    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:1269(_get_index_dtype)
-   126052    0.007    0.000    0.007    0.000 {method 'append' of 'list' objects}
-    32266    0.005    0.000    0.006    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_exceptions.py:42(<genexpr>)
-      232    0.004    0.000    0.006    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_sputils.py:147(get_index_dtype)
-        6    0.000    0.000    0.005    0.001 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/frame.py:609(__init__)
-        4    0.000    0.000    0.005    0.001 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/internals/construction.py:423(dict_to_mgr)
-     6666    0.005    0.000    0.005    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_base.py:84(<listcomp>)
-       14    0.000    0.000    0.004    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/construction.py:493(sanitize_array)
-        4    0.000    0.000    0.004    0.001 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/internals/construction.py:100(arrays_to_mgr)
-  6730/64    0.002    0.000    0.003    0.000 {built-in method builtins.max}
-     6668    0.003    0.000    0.003    0.000 {method 'tolist' of 'numpy.ndarray' objects}
-40254/40246    0.003    0.000    0.003    0.000 {built-in method builtins.isinstance}
-       22    0.003    0.000    0.003    0.000 {built-in method numpy.asanyarray}
-        7    0.000    0.000    0.003    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:120(maybe_convert_platform)
-     6667    0.002    0.000    0.003    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/helpers.py:21(<genexpr>)
-        4    0.000    0.000    0.003    0.001 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/internals/construction.py:588(_homogenize)
-        1    0.000    0.000    0.003    0.003 /usr/lib/python3.10/pathlib.py:1129(read_text)
-        1    0.001    0.001    0.002    0.002 {method 'read' of '_io.TextIOWrapper' objects}
-       19    0.002    0.000    0.002    0.000 {pandas._libs.lib.maybe_convert_objects}
-        2    0.000    0.000    0.002    0.001 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/frame.py:3955(__setitem__)
-        2    0.000    0.000    0.002    0.001 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/frame.py:4164(_set_item)
-      3/2    0.000    0.000    0.002    0.001 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/util/_decorators.py:323(wrapper)
-        1    0.001    0.001    0.002    0.002 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh_features.py:230(<listcomp>)
-        5    0.002    0.000    0.002    0.000 {method 'flatten' of 'numpy.ndarray' objects}
+        2    0.000    0.000   47.293   23.646 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/IPython/core/interactiveshell.py:3490(run_code)
+        2    0.000    0.000   47.292   23.646 {built-in method builtins.exec}
+        1    0.004    0.004   47.137   47.137 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:121(from_ansa_shell)
+        1    0.044    0.044   46.760   46.760 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:32(__init__)
+        1    0.095    0.095   46.637   46.637 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_base.py:34(__init__)
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+       24    0.000    0.000   19.785    0.824 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:620(__matmul__)
+       24    0.000    0.000   19.785    0.824 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:505(_mul_dispatch)
+       24    0.001    0.000   19.784    0.824 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:506(_mul_sparse_matrix)
+      209   19.751    0.095   19.751    0.095 {built-in method numpy.array}
+       24   13.078    0.545   13.078    0.545 {built-in method scipy.sparse._sparsetools.csr_matmat}
+       24    6.696    0.279    6.696    0.279 {built-in method scipy.sparse._sparsetools.csr_matmat_maxnnz}
+       25    0.000    0.000    3.517    0.141 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:477(__sub__)
+       25    0.004    0.000    3.516    0.141 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:361(_sub_sparse)
+       25    0.001    0.000    3.512    0.140 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:1237(_binopt)
+       25    3.306    0.132    3.306    0.132 {built-in method scipy.sparse._sparsetools.csr_minus_csr}
+        5    0.000    0.000    0.415    0.083 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/numpy/lib/arraysetops.py:138(unique)
+        5    0.008    0.002    0.403    0.081 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/numpy/lib/arraysetops.py:323(_unique1d)
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+   140377    0.021    0.000    0.027    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_exceptions.py:42(<genexpr>)
+    28535    0.022    0.000    0.022    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_base.py:84(<listcomp>)
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+        4    0.001    0.000    0.017    0.004 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/internals/construction.py:423(dict_to_mgr)
+ 28599/64    0.007    0.000    0.016    0.000 {built-in method builtins.max}
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+        4    0.000    0.000    0.014    0.004 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/internals/construction.py:100(arrays_to_mgr)
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+169951/169943    0.010    0.000    0.010    0.000 {built-in method builtins.isinstance}
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+        1    0.007    0.007    0.008    0.008 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh_features.py:230(<listcomp>)
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+        1    0.006    0.006    0.006    0.006 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh_features.py:229(<listcomp>)
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+        1    0.000    0.000    0.000    0.000 {method 'release' of '_thread.lock' objects}
         1    0.000    0.000    0.000    0.000 {method 'utcoffset' of 'datetime.timezone' objects}
         1    0.000    0.000    0.000    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/numpy/core/shape_base.py:19(_atleast_1d_dispatcher)
-        1    0.000    0.000    0.000    0.000 {function FrozenList.__getitem__ at 0x7f0ed407d5a0}
+        1    0.000    0.000    0.000    0.000 {function FrozenList.__getitem__ at 0x7fddbdab1510}
 
 

From 6d2b640551fc96de8bba7d7a13561ce2a48fad49 Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Thu, 2 Nov 2023 12:40:35 +0100
Subject: [PATCH 06/27] BFS unoptimized

---
 mesh2vec/helpers.py       | 177 +++++++++++++++++++++++++++++++-------
 mesh2vec/mesh2vec_base.py |  17 +++-
 mesh2vec/test.py          |  37 ++++++++
 3 files changed, 196 insertions(+), 35 deletions(-)
 create mode 100644 mesh2vec/test.py

diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index 69cbef1..42e49d5 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -2,34 +2,149 @@
 from typing import OrderedDict, List, Tuple, Dict
 
 import numpy as np
-from scipy.sparse import csr_array, coo_array, eye
-
-
-def calc_adjacencies(
-    hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
-) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
-    """calc adjacencies for hyper nodes"""
-    # vtx_connectivity: holds for each vtx all connected vtx
-    adjacency_list = []
-    for vtxs in hyper_edges_idx.values():
-        for vtx_a in vtxs:
-            for vtx_b in vtxs:
-                adjacency_list.append([vtx_a, vtx_b])
-    adjacency_list_np = np.unique(np.array(adjacency_list), axis=0)
-
-    # adjacency matrix
-    n_vtx = max(max(v) for v in hyper_edges_idx.values()) + 1
-    data = np.array([1] * len(adjacency_list_np))
-    adjacency_matrix = coo_array(
-        (data, (adjacency_list_np[:, 1], adjacency_list_np[:, 0])), shape=(n_vtx, n_vtx)
-    ).tocsr()
-
-    # neighbors
-    adjacency_matrix_powers = {1: adjacency_matrix}
-    adjacency_matrix_powers_exclusive = {1: adjacency_matrix - csr_array(eye(n_vtx, dtype=int))}
-    for i in range(2, max_distance + 1):
-        adjacency_matrix_powers[i] = adjacency_matrix_powers[i - 1] @ adjacency_matrix
-        adjacency_matrix_powers[i].data = np.array([1] * adjacency_matrix_powers[i].nnz)
-        exclusive = (adjacency_matrix_powers[i] - adjacency_matrix_powers[i - 1]).tocsr()
-        adjacency_matrix_powers_exclusive[i] = exclusive
-    return adjacency_matrix_powers, adjacency_matrix_powers_exclusive
+from scipy.sparse import csr_array, coo_array, eye, csr_matrix, lil_matrix
+import igraph as ip
+from abc import ABC, abstractmethod
+import time
+
+"""
+Use strategy to implement multiple adjacency finding algorithms
+"""
+
+
+class AbstractAdjacencyStrategy(ABC):
+    @abstractmethod
+    def calc_adjacencies(
+        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
+    ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
+        pass
+
+
+class MatMulAdjacency(AbstractAdjacencyStrategy):
+    def calc_adjacencies(
+        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
+    ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
+        """calc adjacencies for hyper nodes with matrix multiplication to find adjacent nodes for a given distance"""
+        # vtx_connectivity: holds for each vtx all connected vtx
+
+        timer = time.time()
+        adjacency_list = []
+        for vtxs in hyper_edges_idx.values():
+            for vtx_a in vtxs:
+                for vtx_b in vtxs:
+                    adjacency_list.append([vtx_a, vtx_b])
+        adjacency_list_np = np.unique(np.array(adjacency_list), axis=0)
+        print("ADJACENCY LIST first element: ", adjacency_list_np[0])
+
+        # adjacency matrix
+        n_vtx = max(max(v) for v in hyper_edges_idx.values()) + 1
+        data = np.array([1] * len(adjacency_list_np))
+        adjacency_matrix = coo_array(
+            (data, (adjacency_list_np[:, 1], adjacency_list_np[:, 0])), shape=(n_vtx, n_vtx)
+        ).tocsr()
+
+        print("ADJACENCY LIMATRIX shape: ", adjacency_matrix.shape)
+
+        # neighbors
+        adjacency_matrix_powers = {1: adjacency_matrix}
+        adjacency_matrix_powers_exclusive = {
+            1: adjacency_matrix - csr_array(eye(n_vtx, dtype=int))
+        }
+        print("POWERS BEGINNING : ", adjacency_matrix_powers)
+        print("POWERS EXCLUSIVE BEGINNING: ", adjacency_matrix_powers_exclusive)
+        for i in range(2, max_distance + 1):
+            adjacency_matrix_powers[i] = adjacency_matrix_powers[i - 1] @ adjacency_matrix
+            adjacency_matrix_powers[i].data = np.array([1] * adjacency_matrix_powers[i].nnz)
+            exclusive = (adjacency_matrix_powers[i] - adjacency_matrix_powers[i - 1]).tocsr()
+            adjacency_matrix_powers_exclusive[i] = exclusive
+
+            print("POWERS BEGINNING ", str(i), " : ", adjacency_matrix_powers)
+            print("POWERS EXCLUSIVE", str(i), " : ", adjacency_matrix_powers_exclusive)
+
+        print("THIS TOOK: ", time.time() - timer)
+
+        return adjacency_matrix_powers, adjacency_matrix_powers_exclusive
+
+
+class BFSAdjacency(AbstractAdjacencyStrategy):
+    def calc_adjacencies(
+        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
+    ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
+        # convert hyper edges to graph; hyper_edges: key -> node, values -> edges to directly connected nodes
+        # as nodes are already integers, create graph from scratch
+        # note: some nodes are integers written as strings -> conversion necessary
+        timer = time.time()
+        graph = ip.Graph(
+            edges=[
+                (int(vertice), int(connected_vertice))
+                for vertice in hyper_edges_idx.keys()
+                for connected_vertice in hyper_edges_idx[vertice]
+                if (
+                    (type(vertice) in [str, int] or np.issubdtype(vertice.dtype, np.str_))
+                    and (
+                        type(connected_vertice) in [str, int]
+                        or np.issubdtype(connected_vertice.dtype, np.str_)
+                    )
+                )
+            ]
+        )
+
+        n_vtx = len(graph.vs)
+        print("NUMBER OF VERTICES: ",n_vtx)
+
+        adjacency_matrix_powers = {1: graph.get_adjacency_sparse()}
+        adjacency_matrix_powers_exclusive = {
+            1: graph.get_adjacency_sparse() - csr_matrix(eye(n_vtx, dtype=int))
+        }
+
+        print("POWERS BEGINNING : ", adjacency_matrix_powers)
+        print("POWERS EXCLUSIVE BEGINNING: ", adjacency_matrix_powers_exclusive)
+        ####################################################
+        # General idea: BFS for each vertex for each depth #
+        ####################################################
+
+        # convert once instead of every time in loop
+        vertices = [int(vertice) for vertice in hyper_edges_idx.keys()]
+
+        for depth in range(2, max_distance + 1):
+            adjacency_matrix = lil_matrix((n_vtx, n_vtx))
+            # grab the last cumulative matrix that we calculated as our base; LIL are more efficient than csr matrices
+            cumulative_matrix = adjacency_matrix_powers[depth - 1].tolil()
+            print("HAHA")
+            for vertex in vertices:
+                queue = [vertex]
+                visited = set()
+                current_depth = 0
+
+                while queue and current_depth <= depth:
+                    next_level = set()
+                    for v in queue:
+                        if v not in visited:
+                            visited.add(v)
+                            adjacency_matrix[vertex, v] = 1
+                            cumulative_matrix[vertex, v] = 1
+                            neighbors = graph.neighbors(v)
+                            next_level.update(neighbors)
+                    queue = list(next_level)
+                    current_depth += 1
+            print("BOO")
+            # convert powers matrix from previous depth from lil to csr, as we will not look at it anymore
+            adjacency_matrix_powers[depth - 1] = adjacency_matrix_powers[depth - 1].tocsr() - csr_matrix(eye(n_vtx, dtype=int))
+
+            print("LAUTRE")
+            # add adjacency matrix for specific depth
+            lil_result = adjacency_matrix - lil_matrix(eye(n_vtx, dtype=int))
+            adjacency_matrix_powers_exclusive[depth] = csr_matrix(lil_result)
+
+            print("HAMBURG")
+            # add cumulative to powers, not in csr yet; we need to use it in the next iteration
+            adjacency_matrix_powers[depth] = cumulative_matrix
+
+            print("POWERS BEGINNING ", str(depth), " : ", adjacency_matrix_powers)
+            print("POWERS EXCLUSIVE", str(depth), " : ", adjacency_matrix_powers_exclusive)
+
+        # convert last cumulative matrix to CSR
+        # adjacency_matrix_powers[max_distance] = csr_matrix(adjacency_matrix_powers[depth - 1]) - csr_matrix(eye(n_vtx, dtype=int))
+        print("THIS TOOK: ", time.time() - timer)
+
+        return adjacency_matrix_powers, adjacency_matrix_powers_exclusive
diff --git a/mesh2vec/mesh2vec_base.py b/mesh2vec/mesh2vec_base.py
index b67a171..4addb17 100644
--- a/mesh2vec/mesh2vec_base.py
+++ b/mesh2vec/mesh2vec_base.py
@@ -11,7 +11,7 @@
 # noinspection PyProtectedMember
 from pandas.api.types import is_string_dtype
 
-from mesh2vec.helpers import calc_adjacencies
+from mesh2vec.helpers import MatMulAdjacency, BFSAdjacency
 from mesh2vec.mesh2vec_exceptions import (
     check_distance_init_arg,
     check_distance_arg,
@@ -86,9 +86,18 @@ def __init__(
             for h_edge_id, vtx_ids in self._hyper_edges.items()
         )
 
-        self._adjacency_matrix_powers, self._adjacency_matrix_powers_exclusive = calc_adjacencies(
-            hyper_edges_idx, distance
-        )
+        # choose between BFSAdjacency and MatMulAdjacency
+        calc_strategy1 = MatMulAdjacency()
+        calc_strategy2 = BFSAdjacency()
+        (
+            self._adjacency_matrix_powers,
+            self._adjacency_matrix_powers_exclusive,
+        ) = calc_strategy1.calc_adjacencies(hyper_edges_idx, distance)
+        print("NEW STRATEGY")
+        (
+            self._adjacency_matrix_powers1,
+            self._adjacency_matrix_powers_exclusive1,
+        ) = calc_strategy2.calc_adjacencies(hyper_edges_idx, distance)
 
     @staticmethod
     def from_file(hg_file: Path, distance: int) -> "Mesh2VecBase":
diff --git a/mesh2vec/test.py b/mesh2vec/test.py
new file mode 100644
index 0000000..a73e26e
--- /dev/null
+++ b/mesh2vec/test.py
@@ -0,0 +1,37 @@
+from mesh2vec.mesh2vec_cae import Mesh2VecCae
+from pathlib import Path
+
+a = Mesh2VecCae.from_ansa_shell(
+    3,
+    Path("data/hat/Hatprofile.k"),
+    json_mesh_file=Path("data/hat/cached_hat_key.json"),
+)
+
+"""# empty adjacency rows to create a csr matrix later on
+            row_indices = []
+            column_indices = []
+            # fill adjacency matrix
+            for vertex in graph.vs:
+                neighbors = graph.neighborhood(vertices=vertex.index, order=1, mode="all")
+                row_indices.extend([vertex.index] * len(neighbors))
+                column_indices.extend(neighbors)
+
+            # Create a CSR sparse matrix from row, column, and data lists
+            adjacency_matrix = csr_matrix(
+                (np.ones(len(row_indices), dtype=int), (row_indices, column_indices)),
+                shape=(n_vtx, n_vtx),
+            )
+
+            # the desired output type is in array format, not matrix format
+            adjacency_matrix_powers_exclusive[depth] = {
+                "data": adjacent_matrix.data,
+                "indices": adjacent_matrix.indices,
+                "indptr": adjacent_matrix.indptr,
+                "shape": adjacent_matrix.shape,
+            }
+
+            adjacency_matrix_powers[depth] = (
+                adjacency_matrix_powers[depth - 1] + adjacency_matrix_powers_exclusive[depth]
+            )"""
+
+# 2002728 n_vtx, index: 1002224

From 13e8805859dd3aead4f0e1307ec5f59184d7ce33 Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Thu, 2 Nov 2023 16:02:23 +0100
Subject: [PATCH 07/27] still very slow

---
 mesh2vec/helpers.py       | 44 ++++++++++-----------------------------
 mesh2vec/mesh2vec_base.py |  3 +++
 mesh2vec/test.py          | 34 +++++++++++++++++++++++++++++-
 3 files changed, 47 insertions(+), 34 deletions(-)

diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index 42e49d5..3ac34cf 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -2,7 +2,7 @@
 from typing import OrderedDict, List, Tuple, Dict
 
 import numpy as np
-from scipy.sparse import csr_array, coo_array, eye, csr_matrix, lil_matrix
+from scipy.sparse import csr_array, coo_array, eye, csr_matrix, lil_matrix, coo_matrix
 import igraph as ip
 from abc import ABC, abstractmethod
 import time
@@ -103,48 +103,26 @@ def calc_adjacencies(
         # General idea: BFS for each vertex for each depth #
         ####################################################
 
-        # convert once instead of every time in loop
-        vertices = [int(vertice) for vertice in hyper_edges_idx.keys()]
-
         for depth in range(2, max_distance + 1):
+
             adjacency_matrix = lil_matrix((n_vtx, n_vtx))
-            # grab the last cumulative matrix that we calculated as our base; LIL are more efficient than csr matrices
-            cumulative_matrix = adjacency_matrix_powers[depth - 1].tolil()
+            cumulative_matrix = lil_matrix((n_vtx, n_vtx))
             print("HAHA")
-            for vertex in vertices:
-                queue = [vertex]
-                visited = set()
-                current_depth = 0
-
-                while queue and current_depth <= depth:
-                    next_level = set()
-                    for v in queue:
-                        if v not in visited:
-                            visited.add(v)
-                            adjacency_matrix[vertex, v] = 1
-                            cumulative_matrix[vertex, v] = 1
-                            neighbors = graph.neighbors(v)
-                            next_level.update(neighbors)
-                    queue = list(next_level)
-                    current_depth += 1
+
+            for vertex in graph.vs.indices:
+                exclusive_neighborhood = graph.neighborhood(vertices=vertex, mindist=depth, order=depth)
+                inclusive_neighborhood = graph.neighborhood(vertices=vertex, order=depth)
+                adjacency_matrix[vertex, exclusive_neighborhood] = 1
+                cumulative_matrix[vertex, inclusive_neighborhood] = 1 
             print("BOO")
-            # convert powers matrix from previous depth from lil to csr, as we will not look at it anymore
-            adjacency_matrix_powers[depth - 1] = adjacency_matrix_powers[depth - 1].tocsr() - csr_matrix(eye(n_vtx, dtype=int))
 
-            print("LAUTRE")
-            # add adjacency matrix for specific depth
-            lil_result = adjacency_matrix - lil_matrix(eye(n_vtx, dtype=int))
-            adjacency_matrix_powers_exclusive[depth] = csr_matrix(lil_result)
 
-            print("HAMBURG")
-            # add cumulative to powers, not in csr yet; we need to use it in the next iteration
-            adjacency_matrix_powers[depth] = cumulative_matrix
+            adjacency_matrix_powers_exclusive[depth] = (adjacency_matrix - csr_matrix(eye(n_vtx, dtype=int))).tocsr().toarray()
+            adjacency_matrix_powers[depth] = (cumulative_matrix - csr_matrix(eye(n_vtx, dtype=int))).tocsr().toarray()
 
             print("POWERS BEGINNING ", str(depth), " : ", adjacency_matrix_powers)
             print("POWERS EXCLUSIVE", str(depth), " : ", adjacency_matrix_powers_exclusive)
 
-        # convert last cumulative matrix to CSR
-        # adjacency_matrix_powers[max_distance] = csr_matrix(adjacency_matrix_powers[depth - 1]) - csr_matrix(eye(n_vtx, dtype=int))
         print("THIS TOOK: ", time.time() - timer)
 
         return adjacency_matrix_powers, adjacency_matrix_powers_exclusive
diff --git a/mesh2vec/mesh2vec_base.py b/mesh2vec/mesh2vec_base.py
index 4addb17..7916d7d 100644
--- a/mesh2vec/mesh2vec_base.py
+++ b/mesh2vec/mesh2vec_base.py
@@ -99,6 +99,9 @@ def __init__(
             self._adjacency_matrix_powers_exclusive1,
         ) = calc_strategy2.calc_adjacencies(hyper_edges_idx, distance)
 
+        print("Test auf Gleichheit: ", self._adjacency_matrix_powers == self._adjacency_matrix_powers1)
+        print("Test auf Gleichheit: ", self._adjacency_matrix_powers_exclusive == self._adjacency_matrix_powers_exclusive1)
+
     @staticmethod
     def from_file(hg_file: Path, distance: int) -> "Mesh2VecBase":
         # pylint: disable=line-too-long
diff --git a/mesh2vec/test.py b/mesh2vec/test.py
index a73e26e..17fb630 100644
--- a/mesh2vec/test.py
+++ b/mesh2vec/test.py
@@ -34,4 +34,36 @@
                 adjacency_matrix_powers[depth - 1] + adjacency_matrix_powers_exclusive[depth]
             )"""
 
-# 2002728 n_vtx, index: 1002224
+
+
+
+"""
+vertices = [int(vertice) for vertice in hyper_edges_idx.keys()]
+        for depth in range(2, max_distance + 1):
+            adjacency_matrix = lil_matrix((n_vtx, n_vtx))
+            # grab the last cumulative matrix that we calculated as our base; LIL are more efficient than csr matrices
+            cumulative_matrix = adjacency_matrix_powers[depth - 1].tolil()
+            print("HAHA")
+            for vertex in vertices:
+                queue = [vertex]
+                visited = set()
+                current_depth = 0
+
+                while queue and current_depth <= depth:
+                    next_level = set()
+                    for v in queue:
+                        if v not in visited:
+                            visited.add(v)
+                            adjacency_matrix[vertex, v] = 1
+                            cumulative_matrix[vertex, v] = 1
+                            neighbors = graph.neighbors(v)
+                            next_level.update(neighbors)
+                    queue = list(next_level)
+                    current_depth += 1
+
+ # convert last cumulative matrix to CSR
+        adjacency_matrix_powers[max_distance] = csr_matrix(adjacency_matrix_powers[max_distance]) - csr_matrix(eye(n_vtx, dtype=int))
+        print("POWERS BEGINNING ", str(depth), " : ", adjacency_matrix_powers)
+        print("POWERS EXCLUSIVE", str(depth), " : ", adjacency_matrix_powers_exclusive)
+        print("THIS TOOK: ", time.time() - timer)
+"""
\ No newline at end of file

From 907e82ea8e3cbd076908c45b1f43c49ac6794570 Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Fri, 3 Nov 2023 10:39:12 +0100
Subject: [PATCH 08/27] return list of lists for BFS

---
 mesh2vec/helpers.py       | 69 +++++++++++----------------------------
 mesh2vec/mesh2vec_base.py | 10 ++++--
 mesh2vec/test.py          | 62 +----------------------------------
 3 files changed, 28 insertions(+), 113 deletions(-)

diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index 3ac34cf..e628d59 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -34,7 +34,6 @@ def calc_adjacencies(
                 for vtx_b in vtxs:
                     adjacency_list.append([vtx_a, vtx_b])
         adjacency_list_np = np.unique(np.array(adjacency_list), axis=0)
-        print("ADJACENCY LIST first element: ", adjacency_list_np[0])
 
         # adjacency matrix
         n_vtx = max(max(v) for v in hyper_edges_idx.values()) + 1
@@ -43,24 +42,18 @@ def calc_adjacencies(
             (data, (adjacency_list_np[:, 1], adjacency_list_np[:, 0])), shape=(n_vtx, n_vtx)
         ).tocsr()
 
-        print("ADJACENCY LIMATRIX shape: ", adjacency_matrix.shape)
-
         # neighbors
         adjacency_matrix_powers = {1: adjacency_matrix}
         adjacency_matrix_powers_exclusive = {
             1: adjacency_matrix - csr_array(eye(n_vtx, dtype=int))
         }
-        print("POWERS BEGINNING : ", adjacency_matrix_powers)
-        print("POWERS EXCLUSIVE BEGINNING: ", adjacency_matrix_powers_exclusive)
+
         for i in range(2, max_distance + 1):
             adjacency_matrix_powers[i] = adjacency_matrix_powers[i - 1] @ adjacency_matrix
             adjacency_matrix_powers[i].data = np.array([1] * adjacency_matrix_powers[i].nnz)
             exclusive = (adjacency_matrix_powers[i] - adjacency_matrix_powers[i - 1]).tocsr()
             adjacency_matrix_powers_exclusive[i] = exclusive
 
-            print("POWERS BEGINNING ", str(i), " : ", adjacency_matrix_powers)
-            print("POWERS EXCLUSIVE", str(i), " : ", adjacency_matrix_powers_exclusive)
-
         print("THIS TOOK: ", time.time() - timer)
 
         return adjacency_matrix_powers, adjacency_matrix_powers_exclusive
@@ -74,55 +67,31 @@ def calc_adjacencies(
         # as nodes are already integers, create graph from scratch
         # note: some nodes are integers written as strings -> conversion necessary
         timer = time.time()
-        graph = ip.Graph(
-            edges=[
-                (int(vertice), int(connected_vertice))
-                for vertice in hyper_edges_idx.keys()
-                for connected_vertice in hyper_edges_idx[vertice]
-                if (
-                    (type(vertice) in [str, int] or np.issubdtype(vertice.dtype, np.str_))
-                    and (
-                        type(connected_vertice) in [str, int]
-                        or np.issubdtype(connected_vertice.dtype, np.str_)
-                    )
-                )
-            ]
-        )
-
-        n_vtx = len(graph.vs)
-        print("NUMBER OF VERTICES: ",n_vtx)
-
-        adjacency_matrix_powers = {1: graph.get_adjacency_sparse()}
-        adjacency_matrix_powers_exclusive = {
-            1: graph.get_adjacency_sparse() - csr_matrix(eye(n_vtx, dtype=int))
-        }
 
-        print("POWERS BEGINNING : ", adjacency_matrix_powers)
-        print("POWERS EXCLUSIVE BEGINNING: ", adjacency_matrix_powers_exclusive)
+        adjacency_list = []
+        for vtxs in hyper_edges_idx.values():
+            for vtx_a in vtxs:
+                for vtx_b in vtxs:
+                    adjacency_list.append([vtx_a, vtx_b])
+        adjacency_list_np = np.unique(np.array(adjacency_list), axis=0)
+
+        graph = ip.Graph(adjacency_list_np)
+
+        adj_list = graph.get_adjlist()
+        adjacency_list_exclusive = {1: adj_list}
+        adjacency_list_inclusive = {1: adj_list}
+
         ####################################################
         # General idea: BFS for each vertex for each depth #
         ####################################################
 
         for depth in range(2, max_distance + 1):
+            exclusive_neighborhood = graph.neighborhood(vertices=None, mindist=depth, order=depth)
+            inclusive_neighborhood = graph.neighborhood(vertices=None, order=depth)
 
-            adjacency_matrix = lil_matrix((n_vtx, n_vtx))
-            cumulative_matrix = lil_matrix((n_vtx, n_vtx))
-            print("HAHA")
-
-            for vertex in graph.vs.indices:
-                exclusive_neighborhood = graph.neighborhood(vertices=vertex, mindist=depth, order=depth)
-                inclusive_neighborhood = graph.neighborhood(vertices=vertex, order=depth)
-                adjacency_matrix[vertex, exclusive_neighborhood] = 1
-                cumulative_matrix[vertex, inclusive_neighborhood] = 1 
-            print("BOO")
-
-
-            adjacency_matrix_powers_exclusive[depth] = (adjacency_matrix - csr_matrix(eye(n_vtx, dtype=int))).tocsr().toarray()
-            adjacency_matrix_powers[depth] = (cumulative_matrix - csr_matrix(eye(n_vtx, dtype=int))).tocsr().toarray()
-
-            print("POWERS BEGINNING ", str(depth), " : ", adjacency_matrix_powers)
-            print("POWERS EXCLUSIVE", str(depth), " : ", adjacency_matrix_powers_exclusive)
+            adjacency_list_exclusive[depth] = exclusive_neighborhood
+            adjacency_list_inclusive[depth] = inclusive_neighborhood
 
         print("THIS TOOK: ", time.time() - timer)
 
-        return adjacency_matrix_powers, adjacency_matrix_powers_exclusive
+        return adjacency_list_inclusive, adjacency_list_exclusive
diff --git a/mesh2vec/mesh2vec_base.py b/mesh2vec/mesh2vec_base.py
index 7916d7d..5606061 100644
--- a/mesh2vec/mesh2vec_base.py
+++ b/mesh2vec/mesh2vec_base.py
@@ -99,8 +99,14 @@ def __init__(
             self._adjacency_matrix_powers_exclusive1,
         ) = calc_strategy2.calc_adjacencies(hyper_edges_idx, distance)
 
-        print("Test auf Gleichheit: ", self._adjacency_matrix_powers == self._adjacency_matrix_powers1)
-        print("Test auf Gleichheit: ", self._adjacency_matrix_powers_exclusive == self._adjacency_matrix_powers_exclusive1)
+        print(
+            "Test auf Gleichheit: ",
+            self._adjacency_matrix_powers == self._adjacency_matrix_powers1,
+        )
+        print(
+            "Test auf Gleichheit: ",
+            self._adjacency_matrix_powers_exclusive == self._adjacency_matrix_powers_exclusive1,
+        )
 
     @staticmethod
     def from_file(hg_file: Path, distance: int) -> "Mesh2VecBase":
diff --git a/mesh2vec/test.py b/mesh2vec/test.py
index 17fb630..bff3bdf 100644
--- a/mesh2vec/test.py
+++ b/mesh2vec/test.py
@@ -2,68 +2,8 @@
 from pathlib import Path
 
 a = Mesh2VecCae.from_ansa_shell(
-    3,
+    20,
     Path("data/hat/Hatprofile.k"),
     json_mesh_file=Path("data/hat/cached_hat_key.json"),
 )
 
-"""# empty adjacency rows to create a csr matrix later on
-            row_indices = []
-            column_indices = []
-            # fill adjacency matrix
-            for vertex in graph.vs:
-                neighbors = graph.neighborhood(vertices=vertex.index, order=1, mode="all")
-                row_indices.extend([vertex.index] * len(neighbors))
-                column_indices.extend(neighbors)
-
-            # Create a CSR sparse matrix from row, column, and data lists
-            adjacency_matrix = csr_matrix(
-                (np.ones(len(row_indices), dtype=int), (row_indices, column_indices)),
-                shape=(n_vtx, n_vtx),
-            )
-
-            # the desired output type is in array format, not matrix format
-            adjacency_matrix_powers_exclusive[depth] = {
-                "data": adjacent_matrix.data,
-                "indices": adjacent_matrix.indices,
-                "indptr": adjacent_matrix.indptr,
-                "shape": adjacent_matrix.shape,
-            }
-
-            adjacency_matrix_powers[depth] = (
-                adjacency_matrix_powers[depth - 1] + adjacency_matrix_powers_exclusive[depth]
-            )"""
-
-
-
-
-"""
-vertices = [int(vertice) for vertice in hyper_edges_idx.keys()]
-        for depth in range(2, max_distance + 1):
-            adjacency_matrix = lil_matrix((n_vtx, n_vtx))
-            # grab the last cumulative matrix that we calculated as our base; LIL are more efficient than csr matrices
-            cumulative_matrix = adjacency_matrix_powers[depth - 1].tolil()
-            print("HAHA")
-            for vertex in vertices:
-                queue = [vertex]
-                visited = set()
-                current_depth = 0
-
-                while queue and current_depth <= depth:
-                    next_level = set()
-                    for v in queue:
-                        if v not in visited:
-                            visited.add(v)
-                            adjacency_matrix[vertex, v] = 1
-                            cumulative_matrix[vertex, v] = 1
-                            neighbors = graph.neighbors(v)
-                            next_level.update(neighbors)
-                    queue = list(next_level)
-                    current_depth += 1
-
- # convert last cumulative matrix to CSR
-        adjacency_matrix_powers[max_distance] = csr_matrix(adjacency_matrix_powers[max_distance]) - csr_matrix(eye(n_vtx, dtype=int))
-        print("POWERS BEGINNING ", str(depth), " : ", adjacency_matrix_powers)
-        print("POWERS EXCLUSIVE", str(depth), " : ", adjacency_matrix_powers_exclusive)
-        print("THIS TOOK: ", time.time() - timer)
-"""
\ No newline at end of file

From 4b3f9f8262e67ebe15186f0c64ac5b3e4725e4e3 Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Tue, 7 Nov 2023 14:54:52 +0100
Subject: [PATCH 09/27] finished strateg pattern

---
 .gitignore                |  3 ++-
 mesh2vec/helpers.py       | 46 ++++++++++++++++++++++++++++-----------
 mesh2vec/mesh2vec_base.py | 37 +++++++++++--------------------
 mesh2vec/mesh2vec_cae.py  | 13 +++++++++--
 mesh2vec/test.py          |  8 ++++++-
 5 files changed, 66 insertions(+), 41 deletions(-)

diff --git a/.gitignore b/.gitignore
index 1ef6f88..40d3b02 100644
--- a/.gitignore
+++ b/.gitignore
@@ -8,4 +8,5 @@ __pycache__
 .DS_Store
 .venv/
 .ipynb_checkpoints
-data/mb_private_data
\ No newline at end of file
+data/mb_private_data
+plot_mb*
\ No newline at end of file
diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index e628d59..e49750f 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -2,10 +2,9 @@
 from typing import OrderedDict, List, Tuple, Dict
 
 import numpy as np
-from scipy.sparse import csr_array, coo_array, eye, csr_matrix, lil_matrix, coo_matrix
+from scipy.sparse import csr_array, coo_array, eye
 import igraph as ip
 from abc import ABC, abstractmethod
-import time
 
 """
 Use strategy to implement multiple adjacency finding algorithms
@@ -13,21 +12,35 @@
 
 
 class AbstractAdjacencyStrategy(ABC):
+    def __init__(self):
+        self.__adjacency_matrix_powers = None
+        self.__adjacency_matrix_powers_exclusive = None
+    
+    def set_matrices(self, matrix_powers, matrix_powers_exclusive):
+        self.__adjacency_matrix_powers = matrix_powers
+        self.__adjacency_matrix_powers_exclusive = matrix_powers_exclusive
+
     @abstractmethod
     def calc_adjacencies(
         self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
     ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
         pass
 
+    @abstractmethod
+    def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
+        pass
+
 
 class MatMulAdjacency(AbstractAdjacencyStrategy):
+    def __init__(self):
+        super().__init__()
+
     def calc_adjacencies(
         self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
     ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
         """calc adjacencies for hyper nodes with matrix multiplication to find adjacent nodes for a given distance"""
         # vtx_connectivity: holds for each vtx all connected vtx
 
-        timer = time.time()
         adjacency_list = []
         for vtxs in hyper_edges_idx.values():
             for vtx_a in vtxs:
@@ -54,19 +67,23 @@ def calc_adjacencies(
             exclusive = (adjacency_matrix_powers[i] - adjacency_matrix_powers[i - 1]).tocsr()
             adjacency_matrix_powers_exclusive[i] = exclusive
 
-        print("THIS TOOK: ", time.time() - timer)
-
+        self.set_matrices(adjacency_matrix_powers, adjacency_matrix_powers_exclusive)
         return adjacency_matrix_powers, adjacency_matrix_powers_exclusive
+    
+    def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
+        return self.__adjacency_matrix_powers_exclusive[distance][vtx_id]
+    
+    def __str__(self) -> str:
+        return "MatMulAdjacency"
 
 
 class BFSAdjacency(AbstractAdjacencyStrategy):
+    def __init__(self):
+        super().__init__()
+
     def calc_adjacencies(
         self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
     ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
-        # convert hyper edges to graph; hyper_edges: key -> node, values -> edges to directly connected nodes
-        # as nodes are already integers, create graph from scratch
-        # note: some nodes are integers written as strings -> conversion necessary
-        timer = time.time()
 
         adjacency_list = []
         for vtxs in hyper_edges_idx.values():
@@ -84,14 +101,17 @@ def calc_adjacencies(
         ####################################################
         # General idea: BFS for each vertex for each depth #
         ####################################################
-
         for depth in range(2, max_distance + 1):
             exclusive_neighborhood = graph.neighborhood(vertices=None, mindist=depth, order=depth)
             inclusive_neighborhood = graph.neighborhood(vertices=None, order=depth)
-
             adjacency_list_exclusive[depth] = exclusive_neighborhood
             adjacency_list_inclusive[depth] = inclusive_neighborhood
 
-        print("THIS TOOK: ", time.time() - timer)
-
+        self.set_matrices(adjacency_list_inclusive, adjacency_list_exclusive)
         return adjacency_list_inclusive, adjacency_list_exclusive
+    
+    def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
+        return self.__adjacency_matrix_powers_exclusive[distance][vtx_id]
+    
+    def __str__(self) -> str:
+        return "BFSAdjacency"
diff --git a/mesh2vec/mesh2vec_base.py b/mesh2vec/mesh2vec_base.py
index 5606061..ae136bb 100644
--- a/mesh2vec/mesh2vec_base.py
+++ b/mesh2vec/mesh2vec_base.py
@@ -11,7 +11,7 @@
 # noinspection PyProtectedMember
 from pandas.api.types import is_string_dtype
 
-from mesh2vec.helpers import MatMulAdjacency, BFSAdjacency
+from mesh2vec.helpers import MatMulAdjacency, AbstractAdjacencyStrategy
 from mesh2vec.mesh2vec_exceptions import (
     check_distance_init_arg,
     check_distance_arg,
@@ -36,6 +36,7 @@ def __init__(
         distance: int,
         hyper_edges: Dict[str, List[str]],
         vtx_ids: Optional[List[str]] = None,
+        calc_strategy: AbstractAdjacencyStrategy = None,
     ):
         r"""
         Create neighborhood sets on a hypergraph.
@@ -49,6 +50,7 @@ def __init__(
             hyper_edges: edge->connected vertices
             vtx_ids: provide a list of all vertices to control inernal order of vertices
                 (features, aggregated feature)
+            calc_strategy: choose the algorithm to calculate adjacencies
 
         Example:
             >>> from mesh2vec.mesh2vec_base import Mesh2VecBase
@@ -85,28 +87,13 @@ def __init__(
             )
             for h_edge_id, vtx_ids in self._hyper_edges.items()
         )
-
-        # choose between BFSAdjacency and MatMulAdjacency
-        calc_strategy1 = MatMulAdjacency()
-        calc_strategy2 = BFSAdjacency()
+        if calc_strategy is None:
+            calc_strategy = MatMulAdjacency()
+        self._calc_strategy = calc_strategy
         (
             self._adjacency_matrix_powers,
             self._adjacency_matrix_powers_exclusive,
-        ) = calc_strategy1.calc_adjacencies(hyper_edges_idx, distance)
-        print("NEW STRATEGY")
-        (
-            self._adjacency_matrix_powers1,
-            self._adjacency_matrix_powers_exclusive1,
-        ) = calc_strategy2.calc_adjacencies(hyper_edges_idx, distance)
-
-        print(
-            "Test auf Gleichheit: ",
-            self._adjacency_matrix_powers == self._adjacency_matrix_powers1,
-        )
-        print(
-            "Test auf Gleichheit: ",
-            self._adjacency_matrix_powers_exclusive == self._adjacency_matrix_powers_exclusive1,
-        )
+        ) = self._calc_strategy.calc_adjacencies(hyper_edges_idx, distance)
 
     @staticmethod
     def from_file(hg_file: Path, distance: int) -> "Mesh2VecBase":
@@ -180,9 +167,10 @@ def get_nbh(self, vtx: str, dist: int) -> List[str]:
         if dist == 0:
             return [vtx]
 
-        vertices_idx = self._adjacency_matrix_powers_exclusive[dist][
-            [self._vtx_ids_to_idx[vtx]], :
-        ].indices
+        vertices_idx = self._calc_strategy.get_neighbors_exclusive(dist, self._vtx_ids_to_idx[vtx]).indices
+        #vertices_idx = self._adjacency_matrix_powers_exclusive[dist][
+        #    [self._vtx_ids_to_idx[vtx]], :
+        #].indices
         return [self._vtx_idx_to_ids[i] for i in vertices_idx]
 
     def aggregate_categorical(
@@ -334,7 +322,8 @@ def _collect_feature_values(
             return [[feature] for feature in features]
 
         neighborhoods = [
-            self._adjacency_matrix_powers_exclusive[dist][[i], :].indices
+            # self._adjacency_matrix_powers_exclusive[dist][[i], :].indices
+            self._calc_strategy.get_neighbors_exclusive(dist, i).indices
             for i in range(len(self._features))
         ]
         values = [features[neighborhood] for neighborhood in neighborhoods]
diff --git a/mesh2vec/mesh2vec_cae.py b/mesh2vec/mesh2vec_cae.py
index 4c37042..783d42a 100644
--- a/mesh2vec/mesh2vec_cae.py
+++ b/mesh2vec/mesh2vec_cae.py
@@ -14,6 +14,7 @@
 import plotly.graph_objects as go
 
 from mesh2vec import mesh_features
+from mesh2vec.helpers import AbstractAdjacencyStrategy
 from mesh2vec.mesh_features import CaeShellMesh, is_tri, num_border, midpoint
 from mesh2vec.mesh2vec_base import Mesh2VecBase
 from mesh2vec.mesh2vec_exceptions import check_feature_available, AnsaNotFoundException
@@ -34,6 +35,7 @@ def __init__(
         distance: int,
         mesh: CaeShellMesh,
         mesh_info: pd.DataFrame,
+        calc_strategy: AbstractAdjacencyStrategy = None,
     ) -> None:
         # pylint: disable=line-too-long
         """
@@ -44,6 +46,7 @@ def __init__(
             mesh: points, point_ids/uids, connectivity and element_ids/uids
             mesh_info: additional info about the elements in mesh (same order is required)
                 columns "part_name", "part_id", "file_path", "element_id" are required
+            calc_strategy: choose the algorithm to calculate adjacencies
 
         Example:
             >>> import numpy as np
@@ -83,7 +86,12 @@ def __init__(
 
         hyper_vtx_ids = mesh.element_uid
 
-        super().__init__(distance, points_to_faces_str, vtx_ids=hyper_vtx_ids.tolist())
+        super().__init__(
+            distance,
+            points_to_faces_str,
+            vtx_ids=hyper_vtx_ids.tolist(),
+            calc_strategy=calc_strategy,
+        )
         self._mesh = mesh
         self._element_info = pd.DataFrame(
             {
@@ -127,6 +135,7 @@ def from_ansa_shell(
         ansa_executable: Optional[Path] = None,
         ansa_script: Optional[Path] = None,
         verbose: bool = False,
+        calc_strategy: AbstractAdjacencyStrategy = None,
     ) -> "Mesh2VecCae":
         """
         Read the given ANSA file and use the shell elements corresponding with ``partid`` to
@@ -170,7 +179,7 @@ def from_ansa_shell(
         )
         element_info["part_id"] = [element["__part__"] for element in elements]
         element_info["file_path"] = str(ansafile)
-        return Mesh2VecCae(distance, mesh, element_info)
+        return Mesh2VecCae(distance, mesh, element_info, calc_strategy)
 
     @staticmethod
     def from_d3plot_shell(distance: int, d3plot: Path, partid: str = None) -> "Mesh2VecCae":
diff --git a/mesh2vec/test.py b/mesh2vec/test.py
index bff3bdf..43f0c2a 100644
--- a/mesh2vec/test.py
+++ b/mesh2vec/test.py
@@ -1,3 +1,4 @@
+from mesh2vec.helpers import BFSAdjacency
 from mesh2vec.mesh2vec_cae import Mesh2VecCae
 from pathlib import Path
 
@@ -6,4 +7,9 @@
     Path("data/hat/Hatprofile.k"),
     json_mesh_file=Path("data/hat/cached_hat_key.json"),
 )
-
+b = Mesh2VecCae.from_ansa_shell(
+    20,
+    Path("data/hat/Hatprofile.k"),
+    json_mesh_file=Path("data/hat/cached_hat_key.json"),
+    calc_strategy=BFSAdjacency(),
+)

From 30d44cc4a15b063958bc366314704079a78adb3a Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Thu, 16 Nov 2023 15:49:00 +0100
Subject: [PATCH 10/27] implemented pure python bfs

---
 mesh2vec/helpers.py       | 197 ++++++++++++++++++++++++++++++++++----
 mesh2vec/mesh2vec_base.py |  14 ++-
 mesh2vec/test.py          |  46 ++++++++-
 3 files changed, 235 insertions(+), 22 deletions(-)

diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index e49750f..966377a 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -1,9 +1,11 @@
 """helper functions"""
 from typing import OrderedDict, List, Tuple, Dict
-
+from numba import njit
 import numpy as np
+from collections import deque
 from scipy.sparse import csr_array, coo_array, eye
 import igraph as ip
+import itertools
 from abc import ABC, abstractmethod
 
 """
@@ -11,14 +13,69 @@
 """
 
 
+@njit(parallel=True, fastmath=True)
+def numba_compute(adj_list, depth):
+    # prevent recalculating length
+    num_vertices = len(adj_list)
+    # "adjacency" list: position in aray -> node id, values: reachable nodes for depth
+    # lists instead of sets due to numba compatibility
+    reachable_nodes = [np.empty(0, dtype=np.int64) for _ in prange(num_vertices)]
+
+    for start_vertex in prange(num_vertices):
+        visited = np.zeros(num_vertices, dtype=np.bool_)
+        visited[start_vertex] = True
+
+        queue = np.zeros(num_vertices, dtype=np.int64)
+        front, rear = -1, -1
+
+        queue[0] = start_vertex
+        rear += 1
+
+        current_depth = 1
+
+        while front != rear and current_depth <= depth:
+            front += 1
+            current_vertex = queue[front]
+
+            for neighbor in adj_list[current_vertex]:
+                if not visited[neighbor]:
+                    visited[neighbor] = True
+                    # list in list append not supported in numba
+                    reachable_nodes[start_vertex] = np.append(
+                        reachable_nodes[start_vertex], neighbor
+                    )
+
+                    if current_depth < depth:
+                        queue[rear] = neighbor
+                        rear += 1
+
+            if front == rear - 1:
+                current_depth += 1
+
+    return reachable_nodes
+
+
 class AbstractAdjacencyStrategy(ABC):
     def __init__(self):
-        self.__adjacency_matrix_powers = None
-        self.__adjacency_matrix_powers_exclusive = None
-    
+        self.adjacency_matrix_powers = None
+        self.adjacency_matrix_powers_exclusive = None
+        self.idx_conversion = None
+        self.id_conversion = None
+
     def set_matrices(self, matrix_powers, matrix_powers_exclusive):
-        self.__adjacency_matrix_powers = matrix_powers
-        self.__adjacency_matrix_powers_exclusive = matrix_powers_exclusive
+        self.adjacency_matrix_powers = matrix_powers
+        self.adjacency_matrix_powers_exclusive = matrix_powers_exclusive
+
+    def set_idx_conversion(self, translation: OrderedDict):
+        # key -> vtx_id, value -> index
+        print(
+            list(translation.keys())[0], "translates to", translation[list(translation.keys())[0]]
+        )
+        self.idx_conversion = translation
+
+    def set_id_conversion(self, translation: OrderedDict):
+        # key -> vtx_idx, value -> vtx_id
+        self.id_conversion = translation
 
     @abstractmethod
     def calc_adjacencies(
@@ -27,7 +84,9 @@ def calc_adjacencies(
         pass
 
     @abstractmethod
-    def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
+    def get_neighbors_exclusive(
+        self, distance: int, vtx_id: int, transformation: bool = True
+    ) -> List[int]:
         pass
 
 
@@ -69,10 +128,22 @@ def calc_adjacencies(
 
         self.set_matrices(adjacency_matrix_powers, adjacency_matrix_powers_exclusive)
         return adjacency_matrix_powers, adjacency_matrix_powers_exclusive
-    
-    def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
-        return self.__adjacency_matrix_powers_exclusive[distance][vtx_id]
-    
+
+    def get_neighbors_exclusive(
+        self, distance: int, vtx_id: int, transformation: bool = True
+    ) -> List[int]:
+        row_index = self.idx_conversion[vtx_id]
+        # get the indices;
+        selected_row = self.adjacency_matrix_powers_exclusive[distance][[row_index], :]
+        # nonzero returns a tuple of ([row], [columns]); since we already selected the correct row:
+        # look at columns (= vtx_indices)
+        nonzero_indices = selected_row.nonzero()[1]
+        if transformation:
+            # convert to vtx_ids
+            nonzero_ids = [self.id_conversion[index] for index in nonzero_indices]
+            return nonzero_ids
+        return nonzero_indices
+
     def __str__(self) -> str:
         return "MatMulAdjacency"
 
@@ -84,13 +155,12 @@ def __init__(self):
     def calc_adjacencies(
         self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
     ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
-
         adjacency_list = []
         for vtxs in hyper_edges_idx.values():
             for vtx_a in vtxs:
                 for vtx_b in vtxs:
                     adjacency_list.append([vtx_a, vtx_b])
-        adjacency_list_np = np.unique(np.array(adjacency_list), axis=0)
+        adjacency_list_np: np.ndarray = np.unique(np.array(adjacency_list), axis=0)
 
         graph = ip.Graph(adjacency_list_np)
 
@@ -109,9 +179,104 @@ def calc_adjacencies(
 
         self.set_matrices(adjacency_list_inclusive, adjacency_list_exclusive)
         return adjacency_list_inclusive, adjacency_list_exclusive
-    
+
     def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
-        return self.__adjacency_matrix_powers_exclusive[distance][vtx_id]
-    
+        # TODO CONVERSION
+        return self.adjacency_matrix_powers_exclusive[distance][self.idx_conversion[vtx_id]]
+
     def __str__(self) -> str:
         return "BFSAdjacency"
+
+
+class BFSNumba(AbstractAdjacencyStrategy):
+    def __init__(self):
+        super().__init__()
+
+    def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
+        # TODO CONVERSION
+        return self.adjacency_matrix_powers_exclusive[distance][self.idx_conversion[vtx_id]]
+
+    def __str__(self) -> str:
+        return "BFSNumba"
+
+    def calc_adjacencies(
+        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
+    ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
+        adjacency_list = []
+        for vtxs in hyper_edges_idx.values():
+            for vtx_a in vtxs:
+                for vtx_b in vtxs:
+                    adjacency_list.append([vtx_a, vtx_b])
+
+        adjacency_list_np = np.unique(np.array(adjacency_list), axis=0)
+        adjacency_list_inclusive = {1: np.array([1, 2, 3])}
+        adjacency_list_exclusive = adjacency_list_inclusive
+        numba_compute(adjacency_list_np, 20)
+        return adjacency_list_inclusive, adjacency_list_exclusive
+
+
+class PurePythonBFS(AbstractAdjacencyStrategy):
+    def __init__(self):
+        super().__init__()
+
+    def __str__(self) -> str:
+        return "PurePythonBFS"
+
+    def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
+        row_index = self.idx_conversion[vtx_id]
+        print(self.adjacency_matrix_powers_exclusive[row_index])
+        idx_list = self.adjacency_matrix_powers_exclusive[row_index][distance]
+        return [self.id_conversion[idx] for idx in idx_list]
+
+    def get_neighbors_inclusive(self, distance: int, vtx_id: int) -> List[int]:
+        # join all sublists of neighbors into one
+        row_index = self.idx_conversion[vtx_id]
+        row_index = vtx_id
+        idx_list = itertools.chain(self.adjacency_matrix_powers_exclusive[row_index][:distance])
+        return [self.id_conversion[index] for index in idx_list]
+
+    def calc_adjacencies(
+        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
+    ) -> Tuple[List[List[int]], List[List[int]]]:
+        # hyper_edges keys are still in id format, while values are in index format
+        vertices = [self.idx_conversion[v_id] for v_id in list(hyper_edges_idx.keys())]
+
+        # each vertex has a list of lists where the index of the list corresponds to the depth of its contained neighbors
+        # e.g.: neighbor 300 at depth 2, neighbor 400 at depth 1 with max_distance 3 -> [[400], [300], []]
+        neighbors_at_depth = {vertex: [[] for _ in range(max_distance)] for vertex in vertices}
+
+        # for each vertex, do bfs separately
+        for start_vertex in vertices:
+            # Initialize the queue for BFS: (vertex, depth)
+            queue = deque([(start_vertex, 0)])
+
+            # Use a set to keep track of visited vertices
+            visited = set([start_vertex])
+
+            while queue:
+                # depth is saved in queue -> no tracking in loop
+                vertex, depth = queue.popleft()
+
+                # do not track vertex identity in neighbors; new vertices will not be duplicates due
+                # to visited set tracking
+                if vertex != start_vertex:
+                    # add found neighbor to start_vertex's neighbors
+                    neighbors_at_depth[start_vertex][depth].append(vertex)
+
+                # Check if we've reached the maximum depth; if not look for next level neighbors
+                # of found neighbor
+                if depth < max_distance:
+                    vtx_id = self.id_conversion[vertex]
+                    # Add unvisited neighbors to the queue; these are already in our dictionary
+                    # ATTENTION: Some vertices do not have neighbors and thus might NOT be in dict as key
+                    if vtx_id in hyper_edges_idx.keys():
+                        neighbors = set(hyper_edges_idx[vtx_id]) - visited
+                        queue.extend((neighbor, depth + 1) for neighbor in neighbors)
+                        visited.update(neighbors)
+
+        self.adjacency_matrix_powers_exclusive = neighbors_at_depth
+        self.set_matrices(neighbors_at_depth, neighbors_at_depth)
+
+        # constructing an inclusive neighbor matrix/ dictionary would be expensive; use get_neighbors_inclusive
+        # to get inclusive neighbors for specific vertex. This avoids computational overhead
+        return neighbors_at_depth, neighbors_at_depth
diff --git a/mesh2vec/mesh2vec_base.py b/mesh2vec/mesh2vec_base.py
index ae136bb..2b98b4e 100644
--- a/mesh2vec/mesh2vec_base.py
+++ b/mesh2vec/mesh2vec_base.py
@@ -90,6 +90,8 @@ def __init__(
         if calc_strategy is None:
             calc_strategy = MatMulAdjacency()
         self._calc_strategy = calc_strategy
+        self._calc_strategy.set_idx_conversion(self._vtx_ids_to_idx)
+        self._calc_strategy.set_id_conversion(self._vtx_idx_to_ids)
         (
             self._adjacency_matrix_powers,
             self._adjacency_matrix_powers_exclusive,
@@ -167,11 +169,12 @@ def get_nbh(self, vtx: str, dist: int) -> List[str]:
         if dist == 0:
             return [vtx]
 
-        vertices_idx = self._calc_strategy.get_neighbors_exclusive(dist, self._vtx_ids_to_idx[vtx]).indices
-        #vertices_idx = self._adjacency_matrix_powers_exclusive[dist][
+        vertices_ids = self._calc_strategy.get_neighbors_exclusive(dist, vtx)
+        # vertices_idx = self._adjacency_matrix_powers_exclusive[dist][
         #    [self._vtx_ids_to_idx[vtx]], :
-        #].indices
-        return [self._vtx_idx_to_ids[i] for i in vertices_idx]
+        # ].indices
+        # return [self._vtx_idx_to_ids[i] for i in vertices_idx]
+        return vertices_ids
 
     def aggregate_categorical(
         self,
@@ -321,9 +324,10 @@ def _collect_feature_values(
         if dist == 0:
             return [[feature] for feature in features]
 
+        # no transformation needed
         neighborhoods = [
             # self._adjacency_matrix_powers_exclusive[dist][[i], :].indices
-            self._calc_strategy.get_neighbors_exclusive(dist, i).indices
+            self._calc_strategy.get_neighbors_exclusive(dist, i, transformation=False)
             for i in range(len(self._features))
         ]
         values = [features[neighborhood] for neighborhood in neighborhoods]
diff --git a/mesh2vec/test.py b/mesh2vec/test.py
index 43f0c2a..57251d8 100644
--- a/mesh2vec/test.py
+++ b/mesh2vec/test.py
@@ -1,15 +1,59 @@
-from mesh2vec.helpers import BFSAdjacency
+from mesh2vec.helpers import BFSAdjacency, BFSNumba, PurePythonBFS, MatMulAdjacency
 from mesh2vec.mesh2vec_cae import Mesh2VecCae
 from pathlib import Path
+import time
 
+start = time.time()
+matm = MatMulAdjacency()
 a = Mesh2VecCae.from_ansa_shell(
     20,
     Path("data/hat/Hatprofile.k"),
     json_mesh_file=Path("data/hat/cached_hat_key.json"),
+    calc_strategy=matm,
 )
+print("MATMUL:", time.time() - start)
+
+print("EXCLUSIVE")
+print(matm.get_neighbors_exclusive(3, "4700000"))
+"""
+start = time.time()
 b = Mesh2VecCae.from_ansa_shell(
     20,
     Path("data/hat/Hatprofile.k"),
     json_mesh_file=Path("data/hat/cached_hat_key.json"),
     calc_strategy=BFSAdjacency(),
 )
+print("BFS: ",time.time() - start)"""
+start = time.time()
+pbfs = PurePythonBFS()
+d = Mesh2VecCae.from_ansa_shell(
+    20,
+    Path("data/hat/Hatprofile.k"),
+    json_mesh_file=Path("data/hat/cached_hat_key.json"),
+    calc_strategy=pbfs,
+)
+print("PurePythonBFS:", time.time() - start)
+
+print("EXCLUSIVE")
+print(pbfs.get_neighbors_exclusive(3, "4700000"))
+print("INCLUSIVE")
+print(pbfs.get_neighbors_inclusive(3, "4700000"))
+
+"""start = time.time()
+c = Mesh2VecCae.from_ansa_shell(
+    20,
+    Path("data/hat/Hatprofile.k"),
+    json_mesh_file=Path("data/hat/cached_hat_key.json"),
+    calc_strategy=BFSNumba(),
+)
+print("NUMBA:", time.time() - start)"""
+
+
+"""ADJACENCY LIST:  [[   0    0]
+ [   0    1]
+ [   0 2014]
+ ...
+ [6399 6328]
+ [6399 6396]
+ [6399 6399]]
+DICT 0:  1002224 [0, 2014, 2016, 2202]"""

From 4e0e6ce1d5d05891fdb1c3b2ccbe19d571475525 Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Thu, 16 Nov 2023 15:51:50 +0100
Subject: [PATCH 11/27] leave first list for distance 0 to avoid wrong indexing
 for distances

---
 mesh2vec/helpers.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index 966377a..43ef5d7 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -242,8 +242,8 @@ def calc_adjacencies(
         vertices = [self.idx_conversion[v_id] for v_id in list(hyper_edges_idx.keys())]
 
         # each vertex has a list of lists where the index of the list corresponds to the depth of its contained neighbors
-        # e.g.: neighbor 300 at depth 2, neighbor 400 at depth 1 with max_distance 3 -> [[400], [300], []]
-        neighbors_at_depth = {vertex: [[] for _ in range(max_distance)] for vertex in vertices}
+        # e.g.: neighbor 300 at depth 2, neighbor 400 at depth 1 with max_distance 3 -> [[], [400], [300], []]
+        neighbors_at_depth = {vertex: [[] for _ in range(max_distance + 1)] for vertex in vertices}
 
         # for each vertex, do bfs separately
         for start_vertex in vertices:

From e3d43e816cbdc00a8c3f4bd74dbe782660a4f05f Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Fri, 17 Nov 2023 11:30:45 +0100
Subject: [PATCH 12/27] adjacency_dict now right

---
 mesh2vec/helpers.py | 52 +++++++++++++++++++++++++++++++++------------
 1 file changed, 38 insertions(+), 14 deletions(-)

diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index 43ef5d7..80706b2 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -180,9 +180,14 @@ def calc_adjacencies(
         self.set_matrices(adjacency_list_inclusive, adjacency_list_exclusive)
         return adjacency_list_inclusive, adjacency_list_exclusive
 
-    def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
-        # TODO CONVERSION
-        return self.adjacency_matrix_powers_exclusive[distance][self.idx_conversion[vtx_id]]
+    def get_neighbors_exclusive(
+        self, distance: int, vtx_id: int, transformation: bool = True
+    ) -> List[int]:
+        if not transformation:
+            return self.adjacency_matrix_powers_exclusive[distance][self.idx_conversion[vtx_id]]
+
+        matrix = self.adjacency_matrix_powers_exclusive[distance][self.idx_conversion[vtx_id]]
+        return [self.id_conversion[vtx] for vtx in matrix]
 
     def __str__(self) -> str:
         return "BFSAdjacency"
@@ -222,31 +227,51 @@ def __init__(self):
     def __str__(self) -> str:
         return "PurePythonBFS"
 
-    def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
+    def get_neighbors_exclusive(
+        self, distance: int, vtx_id: int, transformation: bool = True
+    ) -> List[int]:
         row_index = self.idx_conversion[vtx_id]
         print(self.adjacency_matrix_powers_exclusive[row_index])
         idx_list = self.adjacency_matrix_powers_exclusive[row_index][distance]
-        return [self.id_conversion[idx] for idx in idx_list]
+        if transformation:
+            return [self.id_conversion[idx] for idx in idx_list]
+        return idx_list
 
-    def get_neighbors_inclusive(self, distance: int, vtx_id: int) -> List[int]:
+    def get_neighbors_inclusive(
+        self, distance: int, vtx_id: int, transformation: bool = True
+    ) -> List[int]:
         # join all sublists of neighbors into one
         row_index = self.idx_conversion[vtx_id]
         row_index = vtx_id
         idx_list = itertools.chain(self.adjacency_matrix_powers_exclusive[row_index][:distance])
-        return [self.id_conversion[index] for index in idx_list]
+        if transformation:
+            return [self.id_conversion[index] for index in idx_list]
+        return idx_list
 
     def calc_adjacencies(
         self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
     ) -> Tuple[List[List[int]], List[List[int]]]:
-        # hyper_edges keys are still in id format, while values are in index format
-        vertices = [self.idx_conversion[v_id] for v_id in list(hyper_edges_idx.keys())]
+        # construct adjacency dict
+        vtx_count = max([vtx_a for vtxs in hyper_edges_idx.values() for vtx_a in vtxs]) + 1
+        adjacency_dict = {self.idx_conversion[vtx]: [] for vtx in hyper_edges_idx}
+
+        for vtxs in hyper_edges_idx.values():
+            for vtx_a in vtxs:
+                for vtx_b in vtxs:
+                    adjacency_dict[vtx_a].append(vtx_b)
+                    adjacency_dict[vtx_b].append(vtx_a)
+        for i in range(len(adjacency_dict.keys())):
+            # eliminate duplicates
+            adjacency_dict[i] = list(set(adjacency_dict[i]))
 
         # each vertex has a list of lists where the index of the list corresponds to the depth of its contained neighbors
         # e.g.: neighbor 300 at depth 2, neighbor 400 at depth 1 with max_distance 3 -> [[], [400], [300], []]
-        neighbors_at_depth = {vertex: [[] for _ in range(max_distance + 1)] for vertex in vertices}
+        neighbors_at_depth = {
+            vertex: [[] for _ in range(max_distance + 1)] for vertex in adjacency_dict
+        }
 
         # for each vertex, do bfs separately
-        for start_vertex in vertices:
+        for start_vertex in adjacency_dict:
             # Initialize the queue for BFS: (vertex, depth)
             queue = deque([(start_vertex, 0)])
 
@@ -266,11 +291,10 @@ def calc_adjacencies(
                 # Check if we've reached the maximum depth; if not look for next level neighbors
                 # of found neighbor
                 if depth < max_distance:
-                    vtx_id = self.id_conversion[vertex]
                     # Add unvisited neighbors to the queue; these are already in our dictionary
                     # ATTENTION: Some vertices do not have neighbors and thus might NOT be in dict as key
-                    if vtx_id in hyper_edges_idx.keys():
-                        neighbors = set(hyper_edges_idx[vtx_id]) - visited
+                    if vertex in adjacency_dict:
+                        neighbors = set(adjacency_dict[vtx]) - visited
                         queue.extend((neighbor, depth + 1) for neighbor in neighbors)
                         visited.update(neighbors)
 

From 4c5cfc585a756bf9290df043c2b32bcfcb83e98b Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Fri, 17 Nov 2023 12:41:41 +0100
Subject: [PATCH 13/27] pure python correctly implemented

---
 mesh2vec/helpers.py | 40 ++++++++++++++++------------------------
 mesh2vec/test.py    | 16 ----------------
 2 files changed, 16 insertions(+), 40 deletions(-)

diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index 80706b2..d98ce0e 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -19,9 +19,9 @@ def numba_compute(adj_list, depth):
     num_vertices = len(adj_list)
     # "adjacency" list: position in aray -> node id, values: reachable nodes for depth
     # lists instead of sets due to numba compatibility
-    reachable_nodes = [np.empty(0, dtype=np.int64) for _ in prange(num_vertices)]
+    reachable_nodes = [np.empty(0, dtype=np.int64) for _ in range(num_vertices)]
 
-    for start_vertex in prange(num_vertices):
+    for start_vertex in range(num_vertices):
         visited = np.zeros(num_vertices, dtype=np.bool_)
         visited[start_vertex] = True
 
@@ -68,9 +68,6 @@ def set_matrices(self, matrix_powers, matrix_powers_exclusive):
 
     def set_idx_conversion(self, translation: OrderedDict):
         # key -> vtx_id, value -> index
-        print(
-            list(translation.keys())[0], "translates to", translation[list(translation.keys())[0]]
-        )
         self.idx_conversion = translation
 
     def set_id_conversion(self, translation: OrderedDict):
@@ -231,7 +228,6 @@ def get_neighbors_exclusive(
         self, distance: int, vtx_id: int, transformation: bool = True
     ) -> List[int]:
         row_index = self.idx_conversion[vtx_id]
-        print(self.adjacency_matrix_powers_exclusive[row_index])
         idx_list = self.adjacency_matrix_powers_exclusive[row_index][distance]
         if transformation:
             return [self.id_conversion[idx] for idx in idx_list]
@@ -242,8 +238,9 @@ def get_neighbors_inclusive(
     ) -> List[int]:
         # join all sublists of neighbors into one
         row_index = self.idx_conversion[vtx_id]
-        row_index = vtx_id
-        idx_list = itertools.chain(self.adjacency_matrix_powers_exclusive[row_index][:distance])
+        idx_list = list(
+            itertools.chain(*self.adjacency_matrix_powers_exclusive[row_index][:distance])
+        )
         if transformation:
             return [self.id_conversion[index] for index in idx_list]
         return idx_list
@@ -251,27 +248,25 @@ def get_neighbors_inclusive(
     def calc_adjacencies(
         self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
     ) -> Tuple[List[List[int]], List[List[int]]]:
-        # construct adjacency dict
+        # values in .values(): indices list -> maximum index + 1 is length of unique vertices
         vtx_count = max([vtx_a for vtxs in hyper_edges_idx.values() for vtx_a in vtxs]) + 1
-        adjacency_dict = {self.idx_conversion[vtx]: [] for vtx in hyper_edges_idx}
-
+        adjacency_list = [[] for _ in range(vtx_count)]
         for vtxs in hyper_edges_idx.values():
             for vtx_a in vtxs:
                 for vtx_b in vtxs:
-                    adjacency_dict[vtx_a].append(vtx_b)
-                    adjacency_dict[vtx_b].append(vtx_a)
-        for i in range(len(adjacency_dict.keys())):
-            # eliminate duplicates
-            adjacency_dict[i] = list(set(adjacency_dict[i]))
+                    adjacency_list[vtx_a].append(vtx_b)
+                    adjacency_list[vtx_b].append(vtx_a)
+        for i in range(len(adjacency_list)):
+            adjacency_list[i] = list(set(adjacency_list[i]))
 
         # each vertex has a list of lists where the index of the list corresponds to the depth of its contained neighbors
         # e.g.: neighbor 300 at depth 2, neighbor 400 at depth 1 with max_distance 3 -> [[], [400], [300], []]
         neighbors_at_depth = {
-            vertex: [[] for _ in range(max_distance + 1)] for vertex in adjacency_dict
+            vertex: [[] for _ in range(max_distance + 1)] for vertex in range(vtx_count)
         }
 
         # for each vertex, do bfs separately
-        for start_vertex in adjacency_dict:
+        for start_vertex in range(vtx_count):
             # Initialize the queue for BFS: (vertex, depth)
             queue = deque([(start_vertex, 0)])
 
@@ -291,12 +286,9 @@ def calc_adjacencies(
                 # Check if we've reached the maximum depth; if not look for next level neighbors
                 # of found neighbor
                 if depth < max_distance:
-                    # Add unvisited neighbors to the queue; these are already in our dictionary
-                    # ATTENTION: Some vertices do not have neighbors and thus might NOT be in dict as key
-                    if vertex in adjacency_dict:
-                        neighbors = set(adjacency_dict[vtx]) - visited
-                        queue.extend((neighbor, depth + 1) for neighbor in neighbors)
-                        visited.update(neighbors)
+                    neighbors = set(adjacency_list[vertex]) - visited
+                    queue.extend((neighbor, depth + 1) for neighbor in neighbors)
+                    visited.update(neighbors)
 
         self.adjacency_matrix_powers_exclusive = neighbors_at_depth
         self.set_matrices(neighbors_at_depth, neighbors_at_depth)
diff --git a/mesh2vec/test.py b/mesh2vec/test.py
index 57251d8..fa3edc1 100644
--- a/mesh2vec/test.py
+++ b/mesh2vec/test.py
@@ -13,8 +13,6 @@
 )
 print("MATMUL:", time.time() - start)
 
-print("EXCLUSIVE")
-print(matm.get_neighbors_exclusive(3, "4700000"))
 """
 start = time.time()
 b = Mesh2VecCae.from_ansa_shell(
@@ -34,10 +32,6 @@
 )
 print("PurePythonBFS:", time.time() - start)
 
-print("EXCLUSIVE")
-print(pbfs.get_neighbors_exclusive(3, "4700000"))
-print("INCLUSIVE")
-print(pbfs.get_neighbors_inclusive(3, "4700000"))
 
 """start = time.time()
 c = Mesh2VecCae.from_ansa_shell(
@@ -47,13 +41,3 @@
     calc_strategy=BFSNumba(),
 )
 print("NUMBA:", time.time() - start)"""
-
-
-"""ADJACENCY LIST:  [[   0    0]
- [   0    1]
- [   0 2014]
- ...
- [6399 6328]
- [6399 6396]
- [6399 6399]]
-DICT 0:  1002224 [0, 2014, 2016, 2202]"""

From bb8350ed37277c3cc5e067f0a01281d2783d3a61 Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Sat, 18 Nov 2023 14:29:52 +0100
Subject: [PATCH 14/27] all strategies with respective neighbor fetching
 correct

---
 mesh2vec/helpers.py | 106 ++++++++++++++++++++++++--------------------
 mesh2vec/test.py    |  23 +++++++---
 2 files changed, 75 insertions(+), 54 deletions(-)

diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index d98ce0e..e96da0b 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -1,6 +1,6 @@
 """helper functions"""
 from typing import OrderedDict, List, Tuple, Dict
-from numba import njit
+from numba import jit
 import numpy as np
 from collections import deque
 from scipy.sparse import csr_array, coo_array, eye
@@ -12,47 +12,47 @@
 Use strategy to implement multiple adjacency finding algorithms
 """
 
-
-@njit(parallel=True, fastmath=True)
-def numba_compute(adj_list, depth):
-    # prevent recalculating length
-    num_vertices = len(adj_list)
-    # "adjacency" list: position in aray -> node id, values: reachable nodes for depth
-    # lists instead of sets due to numba compatibility
-    reachable_nodes = [np.empty(0, dtype=np.int64) for _ in range(num_vertices)]
-
-    for start_vertex in range(num_vertices):
-        visited = np.zeros(num_vertices, dtype=np.bool_)
-        visited[start_vertex] = True
-
-        queue = np.zeros(num_vertices, dtype=np.int64)
-        front, rear = -1, -1
-
-        queue[0] = start_vertex
-        rear += 1
-
-        current_depth = 1
-
-        while front != rear and current_depth <= depth:
-            front += 1
-            current_vertex = queue[front]
-
-            for neighbor in adj_list[current_vertex]:
-                if not visited[neighbor]:
-                    visited[neighbor] = True
-                    # list in list append not supported in numba
-                    reachable_nodes[start_vertex] = np.append(
-                        reachable_nodes[start_vertex], neighbor
-                    )
-
-                    if current_depth < depth:
-                        queue[rear] = neighbor
-                        rear += 1
-
-            if front == rear - 1:
-                current_depth += 1
-
-    return reachable_nodes
+@jit(parallel=False, fastmath=True, forceobj=True)
+def numba_compute(adj_list, depth, vtx_count):
+    # each vertex has a list of lists where the index of the list corresponds to the depth of its contained neighbors
+    # e.g.: neighbor 300 at depth 2, neighbor 400 at depth 1 with max_distance 3 -> [[], [400], [300], []]
+    neighbors_at_depth = {
+        vertex: [np.array([], dtype=np.int64) for _ in range(depth + 1)] for vertex in range(vtx_count)
+    }
+
+    # for each vertex, do bfs separately
+    for start_vertex in range(vtx_count):
+        # Initialize the queue for BFS: (vertex, depth); numba does not support dequeue
+        queue = [(start_vertex, 0)]
+
+        # Use a set to keep track of visited vertices
+        visited = [start_vertex]
+
+        # queue not empty
+        while queue:
+            # depth is saved in queue -> no tracking in loop
+            vertex, depth = queue.pop()
+
+            # do not track vertex identity in neighbors; new vertices will not be duplicates due
+            # to visited set tracking
+            if vertex != start_vertex:
+                # add found neighbor to start_vertex's neighbors
+                neighbors_at_depth[start_vertex][depth] = np.append(neighbors_at_depth[start_vertex][depth], vertex)
+
+            # Check if we've reached the maximum depth; if not look for next level neighbors
+            # of found neighbor
+            if depth < depth:
+                # remove duplicates manually, as np.setdiff1d and - with lists is not supported
+                neighbors = np.unique(np.array(adj_list[vertex]))
+                removed_neighbors = np.array([neighbor for neighbor in neighbors if neighbor not in visited], dtype=np.int64)
+                        
+                for neighbor in removed_neighbors:
+                    # stack instead of appending
+                    queue.append((neighbor, depth + 1))
+                visited.extend(removed_neighbors)
+        
+
+    return neighbors_at_depth
 
 
 class AbstractAdjacencyStrategy(ABC):
@@ -204,17 +204,25 @@ def __str__(self) -> str:
     def calc_adjacencies(
         self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
     ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
-        adjacency_list = []
+        # values in .values(): indices list -> maximum index + 1 is length of unique vertices
+        vtx_count = max([vtx_a for vtxs in hyper_edges_idx.values() for vtx_a in vtxs]) + 1
+        adjacency_list = [[] for _ in range(vtx_count)]
         for vtxs in hyper_edges_idx.values():
             for vtx_a in vtxs:
                 for vtx_b in vtxs:
-                    adjacency_list.append([vtx_a, vtx_b])
+                    adjacency_list[vtx_a].append(vtx_b)
+                    adjacency_list[vtx_b].append(vtx_a)
+        for i in range(len(adjacency_list)):
+            adjacency_list[i] = list(set(adjacency_list[i]))
 
-        adjacency_list_np = np.unique(np.array(adjacency_list), axis=0)
-        adjacency_list_inclusive = {1: np.array([1, 2, 3])}
-        adjacency_list_exclusive = adjacency_list_inclusive
-        numba_compute(adjacency_list_np, 20)
-        return adjacency_list_inclusive, adjacency_list_exclusive
+        neighbors_at_depth = numba_compute(adjacency_list, max_distance, vtx_count)
+
+        self.adjacency_matrix_powers_exclusive = neighbors_at_depth
+        self.set_matrices(neighbors_at_depth, neighbors_at_depth)
+
+        # constructing an inclusive neighbor matrix/ dictionary would be expensive; use get_neighbors_inclusive
+        # to get inclusive neighbors for specific vertex. This avoids computational overhead
+        return neighbors_at_depth, neighbors_at_depth
 
 
 class PurePythonBFS(AbstractAdjacencyStrategy):
diff --git a/mesh2vec/test.py b/mesh2vec/test.py
index fa3edc1..faec627 100644
--- a/mesh2vec/test.py
+++ b/mesh2vec/test.py
@@ -12,16 +12,22 @@
     calc_strategy=matm,
 )
 print("MATMUL:", time.time() - start)
+matm_neighbors = sorted(matm.get_neighbors_exclusive(20, "4700000"))[:20]
+print(matm_neighbors)
+
 
-"""
 start = time.time()
+bfs = BFSAdjacency()
 b = Mesh2VecCae.from_ansa_shell(
     20,
     Path("data/hat/Hatprofile.k"),
     json_mesh_file=Path("data/hat/cached_hat_key.json"),
-    calc_strategy=BFSAdjacency(),
+    calc_strategy=bfs,
 )
-print("BFS: ",time.time() - start)"""
+print("BFS: ",time.time() - start)
+bfs_neighbors = sorted(bfs.get_neighbors_exclusive(20, "4700000"))[:20]
+print(bfs_neighbors)
+
 start = time.time()
 pbfs = PurePythonBFS()
 d = Mesh2VecCae.from_ansa_shell(
@@ -31,13 +37,20 @@
     calc_strategy=pbfs,
 )
 print("PurePythonBFS:", time.time() - start)
+pbfs_neighbors = sorted(matm.get_neighbors_exclusive(20, "4700000"))[:20]
+print(pbfs_neighbors)
 
 
-"""start = time.time()
+start = time.time()
 c = Mesh2VecCae.from_ansa_shell(
     20,
     Path("data/hat/Hatprofile.k"),
     json_mesh_file=Path("data/hat/cached_hat_key.json"),
     calc_strategy=BFSNumba(),
 )
-print("NUMBA:", time.time() - start)"""
+print("NUMBA:", time.time() - start)
+numba_neighbors = sorted(matm.get_neighbors_exclusive(20, "4700000"))[:20]
+print(numba_neighbors)
+
+trued_neighbors = numba_neighbors==pbfs_neighbors==matm_neighbors==bfs_neighbors
+print("IDENTICAL_NEIGHBORS: ", trued_neighbors)
\ No newline at end of file

From c32cd630e97a22cd6c4abc0b0c82d067a2f8e6da Mon Sep 17 00:00:00 2001
From: soeren <soerenraymond@gmail.com>
Date: Wed, 22 Nov 2023 12:59:59 +0100
Subject: [PATCH 15/27] removed unnecessary comment

---
 mesh2vec/helpers.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index e96da0b..14e858f 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -47,7 +47,6 @@ def numba_compute(adj_list, depth, vtx_count):
                 removed_neighbors = np.array([neighbor for neighbor in neighbors if neighbor not in visited], dtype=np.int64)
                         
                 for neighbor in removed_neighbors:
-                    # stack instead of appending
                     queue.append((neighbor, depth + 1))
                 visited.extend(removed_neighbors)
         

From a9e48209aa23bc1bcd3d4159b7985ce0950a7375 Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Mon, 4 Dec 2023 20:31:40 +0100
Subject: [PATCH 16/27] vtx_idx vs. vtx_id fixes

test fixed - take now very long


many more - test ok


wip add: from keyfile etc


eval


relock


pillow updated


formatting


add: numba and igraph


cleanup mesh2vec_base


more cleanups


cleanup
---
 .gitignore                         |    4 +-
 docs/examples/plot_stress.py       |   10 +-
 mesh2vec/helpers.py                |  526 +--
 mesh2vec/mesh2vec_base.py          |  175 +-
 mesh2vec/mesh2vec_cae.py           |   68 +-
 mesh2vec/mesh2vec_exceptions.py    |   14 +-
 mesh2vec/mesh_features.py          |   59 +
 mesh2vec/test.py                   |   56 -
 poetry.lock                        | 4820 +++++++++++++++-------------
 pyproject.toml                     |    4 +-
 scripts/discover_bottlenecks.ipynb |  122 -
 scripts/generate_test_data.py      |    7 -
 scripts/mesh2vec_times.png         |  Bin 41634 -> 0 bytes
 scripts/plot_execution_time.ipynb  |  125 -
 scripts/profile_stats.txt          |  726 -----
 tests/test_mesh2vec_base.py        |   58 +-
 tests/test_mesh2vec_cae.py         |   47 +
 17 files changed, 3184 insertions(+), 3637 deletions(-)
 delete mode 100644 mesh2vec/test.py
 delete mode 100644 scripts/discover_bottlenecks.ipynb
 delete mode 100644 scripts/generate_test_data.py
 delete mode 100644 scripts/mesh2vec_times.png
 delete mode 100644 scripts/plot_execution_time.ipynb
 delete mode 100644 scripts/profile_stats.txt

diff --git a/.gitignore b/.gitignore
index 40d3b02..12a5a6c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,6 +7,4 @@ __pycache__
 /data/*internal*
 .DS_Store
 .venv/
-.ipynb_checkpoints
-data/mb_private_data
-plot_mb*
\ No newline at end of file
+.ipynb_checkpoints
\ No newline at end of file
diff --git a/docs/examples/plot_stress.py b/docs/examples/plot_stress.py
index 8904f03..08bbc9d 100644
--- a/docs/examples/plot_stress.py
+++ b/docs/examples/plot_stress.py
@@ -19,11 +19,11 @@
     Path("../../data/hat/Hatprofile.k"),
     json_mesh_file=Path("../../data/hat/cached_hat_key.json"),
 )
-hg.add_feature_from_d3plot(
+name = hg.add_feature_from_d3plot(
     ArrayType.element_shell_stress,
     Path("../../data/hat/HAT.d3plot"),
-    timestep=1,
-    shell_layer=0,
+    timestep=-1,
+    shell_layer=np.mean,
 )
 
 
@@ -34,7 +34,7 @@
     pd.DataFrame(
         {
             "vtx_id": hg.vtx_ids(),
-            "y-stress": [v[1] for v in hg.features()[ArrayType.element_shell_stress + "_1_0"]],
+            "y-stress": [v for v in hg.features()[name]],
         }
     )
 )
@@ -49,7 +49,7 @@
 name = hg.aggregate("y-stress", 1, np.mean)
 fig = hg.get_visualization_plotly(str(name))
 fig.update_layout(title=name)
-fig
+fig.show()
 
 
 # %%
diff --git a/mesh2vec/helpers.py b/mesh2vec/helpers.py
index 14e858f..78f1653 100644
--- a/mesh2vec/helpers.py
+++ b/mesh2vec/helpers.py
@@ -1,107 +1,114 @@
 """helper functions"""
-from typing import OrderedDict, List, Tuple, Dict
+from typing import OrderedDict, List, Dict
+from collections import deque
+from abc import ABC, abstractmethod
+import time
+
 from numba import jit
 import numpy as np
-from collections import deque
 from scipy.sparse import csr_array, coo_array, eye
 import igraph as ip
-import itertools
-from abc import ABC, abstractmethod
-
-"""
-Use strategy to implement multiple adjacency finding algorithms
-"""
-
-@jit(parallel=False, fastmath=True, forceobj=True)
-def numba_compute(adj_list, depth, vtx_count):
-    # each vertex has a list of lists where the index of the list corresponds to the depth of its contained neighbors
-    # e.g.: neighbor 300 at depth 2, neighbor 400 at depth 1 with max_distance 3 -> [[], [400], [300], []]
-    neighbors_at_depth = {
-        vertex: [np.array([], dtype=np.int64) for _ in range(depth + 1)] for vertex in range(vtx_count)
-    }
+import numba
+import numba.typed
 
-    # for each vertex, do bfs separately
-    for start_vertex in range(vtx_count):
-        # Initialize the queue for BFS: (vertex, depth); numba does not support dequeue
-        queue = [(start_vertex, 0)]
-
-        # Use a set to keep track of visited vertices
-        visited = [start_vertex]
+# pylint: disable=invalid-name
+class AbstractAdjacencyStrategy(ABC):
+    # pylint: disable=too-few-public-methods
+    """
+    Abstract class for adjacency finding strategies
+    """
 
-        # queue not empty
-        while queue:
-            # depth is saved in queue -> no tracking in loop
-            vertex, depth = queue.pop()
+    @abstractmethod
+    def calc_adjacencies(
+        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
+    ) -> Dict[int, List[List[int]]]:
+        """
+        calculate adjacencies for hyper nodes with a given maximum distance
+        Args:
+            hyper_edges_idx: OrderedDict of hyper nodes with their indices
+            max_distance: maximum distance to find adjacencies for
+        Returns:
+            dict of lists of lists (distance, vertex, neighbors)
+        """
+
+
+def _hyper_edges_to_adj_np(hyper_edges_idx):
+    adjacency_list = []
+    for vtxs in hyper_edges_idx.values():
+        for vtx_a in vtxs:
+            for vtx_b in vtxs:
+                adjacency_list.append([vtx_a, vtx_b])
+    adjacency_list_np = np.unique(np.array(adjacency_list), axis=0)
+    return adjacency_list_np
+
+
+def _hyper_edges_to_adj_list(vtx_count, hyper_edges_idx, include_self=False):
+    adjacency_list = [[] for _ in range(vtx_count)]
+    for vtxs in hyper_edges_idx.values():
+        for vtx_a in vtxs:
+            for vtx_b in vtxs:
+                if include_self or not vtx_a == vtx_b:
+                    adjacency_list[vtx_a].append(vtx_b)
+                    adjacency_list[vtx_b].append(vtx_a)
+    adjacency_list = [list(set(adjacency)) for adjacency in adjacency_list]
+    return adjacency_list
 
-            # do not track vertex identity in neighbors; new vertices will not be duplicates due
-            # to visited set tracking
-            if vertex != start_vertex:
-                # add found neighbor to start_vertex's neighbors
-                neighbors_at_depth[start_vertex][depth] = np.append(neighbors_at_depth[start_vertex][depth], vertex)
 
-            # Check if we've reached the maximum depth; if not look for next level neighbors
-            # of found neighbor
-            if depth < depth:
-                # remove duplicates manually, as np.setdiff1d and - with lists is not supported
-                neighbors = np.unique(np.array(adj_list[vertex]))
-                removed_neighbors = np.array([neighbor for neighbor in neighbors if neighbor not in visited], dtype=np.int64)
-                        
-                for neighbor in removed_neighbors:
-                    queue.append((neighbor, depth + 1))
-                visited.extend(removed_neighbors)
-        
+class MatMulAdjacencySmart(AbstractAdjacencyStrategy):
+    """calc adjacencies using matrix multiplication with low memory footprint"""
 
-    return neighbors_at_depth
+    # pylint: disable=too-few-public-methods
+    def calc_adjacencies(
+        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
+    ) -> Dict[int, List[List[int]]]:
+        """calc adjacencies using matrix multiplication with low memory footprint"""
+        adjacency_list_np = _hyper_edges_to_adj_np(hyper_edges_idx)
 
+        # adjacency matrix
+        n_vtx = max(max(v) for v in hyper_edges_idx.values()) + 1
+        data = np.array([1] * len(adjacency_list_np))
+        adjacency_matrix = coo_array(
+            (data, (adjacency_list_np[:, 1], adjacency_list_np[:, 0])), shape=(n_vtx, n_vtx)
+        ).tocsr()
 
-class AbstractAdjacencyStrategy(ABC):
-    def __init__(self):
-        self.adjacency_matrix_powers = None
-        self.adjacency_matrix_powers_exclusive = None
-        self.idx_conversion = None
-        self.id_conversion = None
+        # neighbors
+        adjacency_matrix_powers_exclusive = {
+            1: adjacency_matrix - csr_array(eye(n_vtx, dtype=int)),
+            0: csr_array(eye(n_vtx, dtype=int)),
+        }
 
-    def set_matrices(self, matrix_powers, matrix_powers_exclusive):
-        self.adjacency_matrix_powers = matrix_powers
-        self.adjacency_matrix_powers_exclusive = matrix_powers_exclusive
+        all_neighbors = (
+            adjacency_matrix_powers_exclusive[1] + adjacency_matrix_powers_exclusive[0]
+        )
 
-    def set_idx_conversion(self, translation: OrderedDict):
-        # key -> vtx_id, value -> index
-        self.idx_conversion = translation
+        for i in range(2, max_distance + 1):
+            new = adjacency_matrix_powers_exclusive[i - 1] @ adjacency_matrix
+            new.data = np.array([1] * new.nnz)  # make all entries 1
 
-    def set_id_conversion(self, translation: OrderedDict):
-        # key -> vtx_idx, value -> vtx_id
-        self.id_conversion = translation
+            exclusive = new > all_neighbors
+            all_neighbors = all_neighbors + new
 
-    @abstractmethod
-    def calc_adjacencies(
-        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
-    ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
-        pass
+            adjacency_matrix_powers_exclusive[i] = exclusive
 
-    @abstractmethod
-    def get_neighbors_exclusive(
-        self, distance: int, vtx_id: int, transformation: bool = True
-    ) -> List[int]:
-        pass
+        neighborhoods = {}
+        for dist in range(1, max_distance + 1):
+            neighborhoods[dist] = [
+                adjacency_matrix_powers_exclusive[dist][[i], :].indices for i in range(n_vtx)
+            ]
+        return neighborhoods
 
 
 class MatMulAdjacency(AbstractAdjacencyStrategy):
-    def __init__(self):
-        super().__init__()
+    # pylint: disable=too-few-public-methods
+    """calc adjacencies using matrix multiplication with low memory footprint"""
 
     def calc_adjacencies(
         self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
-    ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
-        """calc adjacencies for hyper nodes with matrix multiplication to find adjacent nodes for a given distance"""
+    ) -> Dict[int, List[List[int]]]:
+        """calc adjacencies using matrix multiplication"""
         # vtx_connectivity: holds for each vtx all connected vtx
 
-        adjacency_list = []
-        for vtxs in hyper_edges_idx.values():
-            for vtx_a in vtxs:
-                for vtx_b in vtxs:
-                    adjacency_list.append([vtx_a, vtx_b])
-        adjacency_list_np = np.unique(np.array(adjacency_list), axis=0)
+        adjacency_list_np = _hyper_edges_to_adj_np(hyper_edges_idx)
 
         # adjacency matrix
         n_vtx = max(max(v) for v in hyper_edges_idx.values()) + 1
@@ -122,154 +129,153 @@ def calc_adjacencies(
             exclusive = (adjacency_matrix_powers[i] - adjacency_matrix_powers[i - 1]).tocsr()
             adjacency_matrix_powers_exclusive[i] = exclusive
 
-        self.set_matrices(adjacency_matrix_powers, adjacency_matrix_powers_exclusive)
-        return adjacency_matrix_powers, adjacency_matrix_powers_exclusive
-
-    def get_neighbors_exclusive(
-        self, distance: int, vtx_id: int, transformation: bool = True
-    ) -> List[int]:
-        row_index = self.idx_conversion[vtx_id]
-        # get the indices;
-        selected_row = self.adjacency_matrix_powers_exclusive[distance][[row_index], :]
-        # nonzero returns a tuple of ([row], [columns]); since we already selected the correct row:
-        # look at columns (= vtx_indices)
-        nonzero_indices = selected_row.nonzero()[1]
-        if transformation:
-            # convert to vtx_ids
-            nonzero_ids = [self.id_conversion[index] for index in nonzero_indices]
-            return nonzero_ids
-        return nonzero_indices
-
-    def __str__(self) -> str:
-        return "MatMulAdjacency"
+        ## neighborhoods key=distance, value=list of neighbors by index
+        neighborhoods = {}
+        for dist in range(1, max_distance + 1):
+            neighborhoods[dist] = [
+                adjacency_matrix_powers_exclusive[dist][[i], :].indices for i in range(n_vtx)
+            ]
+        return neighborhoods
 
 
 class BFSAdjacency(AbstractAdjacencyStrategy):
-    def __init__(self):
-        super().__init__()
+    """calc adjacencies using BFS from igraph"""
 
+    # pylint: disable=too-few-public-methods
     def calc_adjacencies(
         self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
-    ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
-        adjacency_list = []
-        for vtxs in hyper_edges_idx.values():
-            for vtx_a in vtxs:
-                for vtx_b in vtxs:
-                    adjacency_list.append([vtx_a, vtx_b])
-        adjacency_list_np: np.ndarray = np.unique(np.array(adjacency_list), axis=0)
+    ) -> Dict[int, List[List[int]]]:
+        """calc adjacencies using BFS from igraph"""
+        adjacency_list_np: np.ndarray = _hyper_edges_to_adj_np(hyper_edges_idx)
 
         graph = ip.Graph(adjacency_list_np)
 
-        adj_list = graph.get_adjlist()
-        adjacency_list_exclusive = {1: adj_list}
-        adjacency_list_inclusive = {1: adj_list}
-
         ####################################################
         # General idea: BFS for each vertex for each depth #
         ####################################################
-        for depth in range(2, max_distance + 1):
+        neighborhoods = {}
+        n_vtx = max(max(v) for v in hyper_edges_idx.values()) + 1
+
+        for depth in range(1, max_distance + 1):
+
             exclusive_neighborhood = graph.neighborhood(vertices=None, mindist=depth, order=depth)
-            inclusive_neighborhood = graph.neighborhood(vertices=None, order=depth)
-            adjacency_list_exclusive[depth] = exclusive_neighborhood
-            adjacency_list_inclusive[depth] = inclusive_neighborhood
+            neighborhoods[depth] = [
+                list(set(exclusive_neighborhood[i]) - {i}) for i in range(n_vtx)
+            ]
 
-        self.set_matrices(adjacency_list_inclusive, adjacency_list_exclusive)
-        return adjacency_list_inclusive, adjacency_list_exclusive
+        return neighborhoods
 
-    def get_neighbors_exclusive(
-        self, distance: int, vtx_id: int, transformation: bool = True
-    ) -> List[int]:
-        if not transformation:
-            return self.adjacency_matrix_powers_exclusive[distance][self.idx_conversion[vtx_id]]
 
-        matrix = self.adjacency_matrix_powers_exclusive[distance][self.idx_conversion[vtx_id]]
-        return [self.id_conversion[vtx] for vtx in matrix]
+class BFSNumba(AbstractAdjacencyStrategy):
+    """calc adjacencies using BFS in numba"""
 
-    def __str__(self) -> str:
-        return "BFSAdjacency"
+    # pylint: disable=too-few-public-methods
+    def calc_adjacencies(
+        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
+    ) -> Dict[int, List[List[int]]]:
+        """calc adjacencies using BFS in numba"""
+        vtx_count = max(vtx_a for vtxs in hyper_edges_idx.values() for vtx_a in vtxs) + 1
+
+        adjacency_list = _hyper_edges_to_adj_list(vtx_count, hyper_edges_idx)
+
+        print("building adjacency_list")
+        adjacency_list_numba = numba.typed.List()
+        for _ in range(vtx_count):
+            new = numba.typed.List()
+            new.append(1)
+            new.pop()
+            adjacency_list_numba.append(new)
+
+        for i, neighbors in enumerate(adjacency_list):
+            for neighbor in neighbors:
+                adjacency_list_numba[i].append(neighbor)
+
+        # neighbors_at_depth = List(List(  List([-1]) for _ in range(max_distance + 1))
+        #   for vertex in range(vtx_count))
+        print("building neighbors_at_depth")
+        neighbors_at_depth = numba.typed.List()
+        for i in range(vtx_count):
+            new = numba.typed.List()
+            for _ in range(max_distance + 1):
+                new_new = numba.typed.List()
+                new_new.append(1)
+                new_new.pop()
+                new.append(new_new)
+            neighbors_at_depth.append(new)
+
+        print("start numba")
+        start = time.time()
+
+        neighbors_at_depth = _numba_compute_bfs(
+            adjacency_list_numba, max_distance, vtx_count, neighbors_at_depth
+        )
+        print(f"end numba after second {time.time() - start}")
 
+        connectivity = {}
+        for d in range(1, max_distance + 1):
+            connectivity[d] = [list(neighbors_at_depth[i][d]) for i in range(vtx_count)]
+        return connectivity
 
-class BFSNumba(AbstractAdjacencyStrategy):
-    def __init__(self):
-        super().__init__()
 
-    def get_neighbors_exclusive(self, distance: int, vtx_id: int) -> List[int]:
-        # TODO CONVERSION
-        return self.adjacency_matrix_powers_exclusive[distance][self.idx_conversion[vtx_id]]
+@jit(nopython=True, parallel=False, fastmath=True)
+def _numba_compute_bfs(adj_list, max_depth, vtx_count, neighbors_at_depth):
+    """
+    compute bfs in numba
+    Args:
+        adj_list: adjacency list as numba typed list of lists
+        max_depth: maximum depth to search
+        vtx_count: number of vertices
+        neighbors_at_depth: empty list of lists of lists (vtx, depth, neighbors)
 
-    def __str__(self) -> str:
-        return "BFSNumba"
+    """
+    for start_vertex in range(vtx_count):
+        # Initialize the queue for BFS: (vertex, depth); numba does not support dequeue
+        queue = [(start_vertex, 0)]
 
-    def calc_adjacencies(
-        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
-    ) -> Tuple[Dict[int, csr_array], Dict[int, csr_array]]:
-        # values in .values(): indices list -> maximum index + 1 is length of unique vertices
-        vtx_count = max([vtx_a for vtxs in hyper_edges_idx.values() for vtx_a in vtxs]) + 1
-        adjacency_list = [[] for _ in range(vtx_count)]
-        for vtxs in hyper_edges_idx.values():
-            for vtx_a in vtxs:
-                for vtx_b in vtxs:
-                    adjacency_list[vtx_a].append(vtx_b)
-                    adjacency_list[vtx_b].append(vtx_a)
-        for i in range(len(adjacency_list)):
-            adjacency_list[i] = list(set(adjacency_list[i]))
+        # Use a set to keep track of visited vertices
+        # visited = {start_vertex}
+        visited_array = np.array([False] * vtx_count)
+
+        # queue not empty
+        while queue:
+            # depth is saved in queue -> no tracking in loop
+            vertex, depth = queue.pop(0)
 
-        neighbors_at_depth = numba_compute(adjacency_list, max_distance, vtx_count)
+            # do not track vertex identity in neighbors; new vertices will not be duplicates due
+            # to visited set tracking
+            if vertex != start_vertex:
+                # add found neighbor to start_vertex's neighbors
+                neighbors_at_depth[start_vertex][depth].append(vertex)
 
-        self.adjacency_matrix_powers_exclusive = neighbors_at_depth
-        self.set_matrices(neighbors_at_depth, neighbors_at_depth)
+            # Check if we've reached the maximum depth; if not look for next level neighbors
+            # of found neighbor
+            if depth < max_depth:
+                neighbors = [x for x in adj_list[vertex] if not visited_array[x]]
+                for neighbor in neighbors:
+                    queue.append((neighbor, depth + 1))
+                    visited_array[neighbor] = True
 
-        # constructing an inclusive neighbor matrix/ dictionary would be expensive; use get_neighbors_inclusive
-        # to get inclusive neighbors for specific vertex. This avoids computational overhead
-        return neighbors_at_depth, neighbors_at_depth
+    return neighbors_at_depth
 
 
 class PurePythonBFS(AbstractAdjacencyStrategy):
-    def __init__(self):
-        super().__init__()
-
-    def __str__(self) -> str:
-        return "PurePythonBFS"
-
-    def get_neighbors_exclusive(
-        self, distance: int, vtx_id: int, transformation: bool = True
-    ) -> List[int]:
-        row_index = self.idx_conversion[vtx_id]
-        idx_list = self.adjacency_matrix_powers_exclusive[row_index][distance]
-        if transformation:
-            return [self.id_conversion[idx] for idx in idx_list]
-        return idx_list
-
-    def get_neighbors_inclusive(
-        self, distance: int, vtx_id: int, transformation: bool = True
-    ) -> List[int]:
-        # join all sublists of neighbors into one
-        row_index = self.idx_conversion[vtx_id]
-        idx_list = list(
-            itertools.chain(*self.adjacency_matrix_powers_exclusive[row_index][:distance])
-        )
-        if transformation:
-            return [self.id_conversion[index] for index in idx_list]
-        return idx_list
+    # pylint: disable=too-few-public-methods
+    """calc adjacencies using BFS in pure python"""
 
     def calc_adjacencies(
         self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
-    ) -> Tuple[List[List[int]], List[List[int]]]:
+    ) -> Dict[int, List[List[int]]]:
+        """calc adjacencies using BFS in pure python"""
         # values in .values(): indices list -> maximum index + 1 is length of unique vertices
-        vtx_count = max([vtx_a for vtxs in hyper_edges_idx.values() for vtx_a in vtxs]) + 1
-        adjacency_list = [[] for _ in range(vtx_count)]
-        for vtxs in hyper_edges_idx.values():
-            for vtx_a in vtxs:
-                for vtx_b in vtxs:
-                    adjacency_list[vtx_a].append(vtx_b)
-                    adjacency_list[vtx_b].append(vtx_a)
-        for i in range(len(adjacency_list)):
-            adjacency_list[i] = list(set(adjacency_list[i]))
+        vtx_count = max(vtx_a for vtxs in hyper_edges_idx.values() for vtx_a in vtxs) + 1
+        adjacency_list = _hyper_edges_to_adj_list(vtx_count, hyper_edges_idx)
 
-        # each vertex has a list of lists where the index of the list corresponds to the depth of its contained neighbors
-        # e.g.: neighbor 300 at depth 2, neighbor 400 at depth 1 with max_distance 3 -> [[], [400], [300], []]
+        # each vertex has a list of lists where the index of the list corresponds
+        #   to the depth of its contained neighbors
+        # e.g.: neighbor 300 at depth 2, neighbor 400 at depth 1 with
+        #    max_distance 3 -> [[], [400], [300], []]
         neighbors_at_depth = {
-            vertex: [[] for _ in range(max_distance + 1)] for vertex in range(vtx_count)
+            dist: [[] for vertex in range(vtx_count)] for dist in range(max_distance + 1)
         }
 
         # for each vertex, do bfs separately
@@ -284,11 +290,11 @@ def calc_adjacencies(
                 # depth is saved in queue -> no tracking in loop
                 vertex, depth = queue.popleft()
 
-                # do not track vertex identity in neighbors; new vertices will not be duplicates due
-                # to visited set tracking
+                # do not track vertex identity in neighbors; new vertices will not be
+                #  duplicates due to visited set tracking
                 if vertex != start_vertex:
                     # add found neighbor to start_vertex's neighbors
-                    neighbors_at_depth[start_vertex][depth].append(vertex)
+                    neighbors_at_depth[depth][start_vertex].append(vertex)
 
                 # Check if we've reached the maximum depth; if not look for next level neighbors
                 # of found neighbor
@@ -296,10 +302,128 @@ def calc_adjacencies(
                     neighbors = set(adjacency_list[vertex]) - visited
                     queue.extend((neighbor, depth + 1) for neighbor in neighbors)
                     visited.update(neighbors)
+        connectivity = {}
+        for d in range(1, max_distance + 1):
+            connectivity[d] = [list(neighbors_at_depth[d][i]) for i in range(vtx_count)]
+        return connectivity
+
+
+class PurePythonDFS(AbstractAdjacencyStrategy):
+    # pylint: disable=too-few-public-methods
+    """calc adjacencies using DFS in pure python"""
 
-        self.adjacency_matrix_powers_exclusive = neighbors_at_depth
-        self.set_matrices(neighbors_at_depth, neighbors_at_depth)
+    def calc_adjacencies(
+        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
+    ) -> Dict[int, List[List[int]]]:
+        """calc adjacencies using DFS in pure python"""
+        # pylint: disable=too-many-locals
+        # values in .values(): indices list -> maximum index + 1 is length of unique vertices
+        vtx_count = max(vtx_a for vtxs in hyper_edges_idx.values() for vtx_a in vtxs) + 1
+        adjacency_list = _hyper_edges_to_adj_list(vtx_count, hyper_edges_idx)
 
-        # constructing an inclusive neighbor matrix/ dictionary would be expensive; use get_neighbors_inclusive
-        # to get inclusive neighbors for specific vertex. This avoids computational overhead
-        return neighbors_at_depth, neighbors_at_depth
+        neighbors_at_depth = {
+            dist: [[] for vertex in range(vtx_count)] for dist in range(max_distance + 1)
+        }
+        for vertex in range(vtx_count):
+            neighbors_at_depth[1][vertex] = adjacency_list[vertex].copy()
+            neighbors_at_depth[0][vertex] = [vertex]
+
+        neighbors = [set(adjacency_list[vertex] + [vertex]) for vertex in range(vtx_count)]
+
+        for dist in range(2, max_distance + 1):
+            for v in range(vtx_count):
+                new_cands = set(
+                    x for nn in adjacency_list[v] for x in neighbors_at_depth[dist - 1][nn]
+                )
+                new = new_cands - neighbors[v]
+                neighbors[v].update(new)
+                neighbors_at_depth[dist][v] = list(new)
+        return neighbors_at_depth
+
+
+class DFSNumba(AbstractAdjacencyStrategy):
+    # pylint: disable=too-few-public-methods,too-many-locals
+    """calc adjacencies using DFS in numba"""
+
+    def calc_adjacencies(
+        self, hyper_edges_idx: OrderedDict[str, List[int]], max_distance: int
+    ) -> Dict[int, List[List[int]]]:
+        """calc adjacencies using DFS in numba"""
+        # values in .values(): indices list -> maximum index + 1 is length of unique vertices
+        vtx_count = max(vtx_a for vtxs in hyper_edges_idx.values() for vtx_a in vtxs) + 1
+        adjacency_list = _hyper_edges_to_adj_list(vtx_count, hyper_edges_idx)
+
+        print("building adjacency_list")
+        adjacency_list_numba = numba.typed.List()
+        for _ in range(vtx_count):
+            new = numba.typed.List()
+            new.append(1)
+            new.pop()
+            adjacency_list_numba.append(new)
+
+        for i, neighbors in enumerate(adjacency_list):
+            for neighbor in neighbors:
+                adjacency_list_numba[i].append(neighbor)
+
+        print("building neighbors_at_depth")
+        neighbors_at_depth = numba.typed.List()
+        for i in range(vtx_count):
+            new = numba.typed.List()
+
+            vtx_self = numba.typed.List()
+            vtx_self.append(i)
+            new.append(vtx_self)  # 0
+
+            adjs = numba.typed.List()
+            for nn in adjacency_list_numba[i]:
+                adjs.append(nn)
+
+            new.append(adjs)  # 1
+
+            for _ in range(max_distance + 1):
+                new_new = numba.typed.List()
+                new_new.append(1)
+                new_new.pop()
+                new.append(new_new)
+            neighbors_at_depth.append(new)
+
+        print("start numba")
+        start = time.time()
+
+        neighbors_at_depth = _numba_compute_dfs(
+            adjacency_list_numba, max_distance, vtx_count, neighbors_at_depth
+        )
+        print(f"end numba after second {time.time() - start}")
+
+        connectivity = {}
+        for d in range(1, max_distance + 1):
+            connectivity[d] = [list(neighbors_at_depth[i][d]) for i in range(vtx_count)]
+        return connectivity
+
+
+@jit(nopython=True, parallel=False, fastmath=True)
+def _numba_compute_dfs(adj_list, max_distance, vtx_count, neighbors_at_depth):
+    """
+    compute dfs in numba
+    Args:
+        adj_list: adjacency list as numba typed list of lists
+        max_distance: maximum depth to search
+        vtx_count: number of vertices
+        neighbors_at_depth: empty list of lists of lists (vtx, depth, neighbors)
+
+    """
+    neighbors = numba.typed.List()
+    for vertex in range(vtx_count):
+        neighbors_current = set(adj_list[vertex])
+        neighbors_current.add(vertex)
+        neighbors.append(neighbors_current)
+
+    for dist in range(2, max_distance + 1):
+        for v in range(vtx_count):
+            hood = set()
+            for nn in adj_list[v]:
+                hood.update(neighbors_at_depth[nn][dist - 1])
+            hood = hood - neighbors[v]
+            neighbors[v].update(hood)
+            neighbors_at_depth[v][dist] = numba.typed.List(hood)
+    return neighbors_at_depth
diff --git a/mesh2vec/mesh2vec_base.py b/mesh2vec/mesh2vec_base.py
index 2b98b4e..138aeb8 100644
--- a/mesh2vec/mesh2vec_base.py
+++ b/mesh2vec/mesh2vec_base.py
@@ -6,7 +6,7 @@
 import networkx
 import numpy as np
 import pandas as pd
-from scipy.sparse import csr_array
+import joblib
 
 # noinspection PyProtectedMember
 from pandas.api.types import is_string_dtype
@@ -89,13 +89,23 @@ def __init__(
         )
         if calc_strategy is None:
             calc_strategy = MatMulAdjacency()
-        self._calc_strategy = calc_strategy
-        self._calc_strategy.set_idx_conversion(self._vtx_ids_to_idx)
-        self._calc_strategy.set_id_conversion(self._vtx_idx_to_ids)
-        (
-            self._adjacency_matrix_powers,
-            self._adjacency_matrix_powers_exclusive,
-        ) = self._calc_strategy.calc_adjacencies(hyper_edges_idx, distance)
+        elif isinstance(calc_strategy, type):
+            calc_strategy = calc_strategy()
+
+        self._neighborhoods = calc_strategy.calc_adjacencies(hyper_edges_idx, distance)
+
+    def save(self, path: Path):
+        """
+        Save the Mesh2Vec object to a file with joblib
+        """
+        joblib.dump(self, path)
+
+    @staticmethod
+    def load(path: Path):
+        """
+        Load the Mesh2Vec object from a file with joblib
+        """
+        return joblib.load(path)
 
     @staticmethod
     def from_file(hg_file: Path, distance: int) -> "Mesh2VecBase":
@@ -169,12 +179,10 @@ def get_nbh(self, vtx: str, dist: int) -> List[str]:
         if dist == 0:
             return [vtx]
 
-        vertices_ids = self._calc_strategy.get_neighbors_exclusive(dist, vtx)
-        # vertices_idx = self._adjacency_matrix_powers_exclusive[dist][
-        #    [self._vtx_ids_to_idx[vtx]], :
-        # ].indices
-        # return [self._vtx_idx_to_ids[i] for i in vertices_idx]
-        return vertices_ids
+        vtx_idx = self._vtx_ids_to_idx[vtx]
+        neighbors_idx = self._neighborhoods[dist][vtx_idx]
+        neighbors_ids = [self._vtx_idx_to_ids[i] for i in neighbors_idx]
+        return neighbors_ids
 
     def aggregate_categorical(
         self,
@@ -220,7 +228,7 @@ def aggregate_categorical(
             feature_categories = np.unique(self._features[feature])
 
         for distance in dist_list:
-            values = self._collect_feature_values(feature, distance, default_value)
+            values = self._collect_feature_values(feature, distance, default_value, aggr=np.array)
 
             for category in feature_categories:
                 feature_name = f"{feature}-cat-{category}-{distance}"
@@ -289,49 +297,132 @@ def aggregate(
         if aggr_name is None:
             aggr_name = aggr.__name__
 
-        feature_names = []
+        agg_values_to_add = OrderedDict()
         for distance in dist_list:
-            values = self._collect_feature_values(feature, distance, default_value)
             if agg_add_ref:
-                ref_values = self._collect_feature_values(feature, 0, default_value)
-                agg_values = np.nan_to_num(
-                    [aggr(value, ref_value) for value, ref_value in zip(values, ref_values)],
-                    nan=default_value,
+                ref_values = self._collect_feature_values(feature, 0, default_value, aggr=None)
+            else:
+                values = self._collect_feature_values(feature, distance, default_value, aggr)
+
+            if agg_add_ref:
+                agg_values = self._collect_feature_values(
+                    feature, distance, default_value, aggr, ref_values
                 )
             else:
-                agg_values = np.nan_to_num([aggr(value) for value in values], nan=default_value)
+                agg_values = values
 
             feature_name = f"{feature}-{aggr_name}-{distance}"
-            self._aggregated_features[feature_name] = agg_values
-            feature_names.append(feature_name)
-        if len(feature_names) == 1:
-            return feature_names[0]
-        return feature_names
+            agg_values_to_add[feature_name] = agg_values
+
+        self._aggregated_features = self._aggregated_features.assign(
+            **agg_values_to_add,
+        )
+        if len(agg_values_to_add) == 1:
+            return list(agg_values_to_add.keys())[0]
+        return list(agg_values_to_add.keys())
+
+    # # pylint: disable=too-many-arguments
+    # def aggregate_many(
+    #     self,
+    #     feature_list: List[str],
+    #     dist_list: List[int],
+    #     aggr_list: Callable,
+    #     aggr_name_list: str = None,
+    #     agg_add_ref: bool = False,
+    #     default_value: float = 0.0,
+    # ) -> Union[str, List[str]]:
+    #     # pylint: disable=line-too-long
+
+    #     for feature in feature_list:
+    #         check_feature_available(feature, self)
+
+    #     for dist_to_check in dist_list:
+    #         check_distance_arg(dist_to_check, self)
+
+    #     if aggr_name_list is None:
+    #         aggr_name_list = [aggr.__name__ for aggr in aggr_list]
+
+    #     agg_values_to_add = OrderedDict()
+    #     for distance in dist_list:
+    #         values = self._collect_feature_list_values(feature_list, distance, default_value)
+    #         if agg_add_ref:
+    #             ref_values = self._collect_feature_list_values(feature_list, 0, default_value)
+    #             agg_values = np.nan_to_num(
+    #                 [aggr(value, ref_value) for value, ref_value in zip(values, ref_values)],
+    #                 nan=default_value,
+    #             )
+    #         else:
+    #             agg_values = values
+    #             # agg_values = np.nan_to_num([np.mean(value) for value in values], nan=default_value)
+
+    #         feature_name = f"{feature}-all-{distance}"
+    #         agg_values_to_add["all"] = agg_values
+
+    #     # self._aggregated_features = self._aggregated_features.assign(
+    #     #    **agg_values_to_add,
+    #     # )
+    #     if len(agg_values_to_add) == 1:
+    #         return list(agg_values_to_add.keys())[0]
+    #     return list(agg_values_to_add.keys())
+
+    # def _collect_feature_list_values(
+    #     self,
+    #     feature_list: str,
+    #     dist: int,
+    #     default_value: Optional[Union[float, int, str]],
+    # ) -> List[List[Union[float, int, str]]]:
+    #     """helper method to collect data from all hyper nodes during aggregation"""
+    #     check_distance_arg(dist, self)
+
+    #     if default_value is None:
+    #         default_value = "NONE" if is_string_dtype(self._features[feature]) else np.nan
+    #     features = self._features[feature_list].fillna(default_value).to_numpy()
+
+    #     if dist == 0:
+    #         return features
+
+    #     values = [
+    #         [np.mean(feature[neighborhood]) for neighborhood in self._neighborhoods[dist]]
+    #         for feature in features.T
+    #     ]
+    #     return values
 
     def _collect_feature_values(
         self,
-        feature: str,
+        feature_name: str,
         dist: int,
         default_value: Optional[Union[float, int, str]],
+        aggr: Optional[Callable] = None,
+        ref_values: Optional[List[Union[float, int, str]]] = None,
     ) -> List[List[Union[float, int, str]]]:
-        """helper method to collect data from all hyper nodes during aggregation"""
+        """helper method to collect and aggregate data from all hyper nodes"""
         check_distance_arg(dist, self)
 
         if default_value is None:
-            default_value = "NONE" if is_string_dtype(self._features[feature]) else np.nan
-        features = self._features[feature].fillna(default_value).to_numpy()
+            default_value = "NONE" if is_string_dtype(self._features[feature_name]) else np.nan
+        feature = self._features[feature_name].fillna(default_value).to_numpy()
 
         if dist == 0:
-            return [[feature] for feature in features]
+            return feature
+
+        if ref_values is None:
+            try:  # fast: use nan_to_num over the whole array
+                return np.nan_to_num(
+                    [aggr(feature[neighborhood]) for neighborhood in self._neighborhoods[dist]],
+                    default_value,
+                ).tolist()
+            except ValueError:  # slow: use nan_to_num for each element (different dimensions)
+                return [
+                    np.nan_to_num(aggr(feature[neighborhood]), default_value)
+                    for neighborhood in self._neighborhoods[dist]
+                ]
 
-        # no transformation needed
-        neighborhoods = [
-            # self._adjacency_matrix_powers_exclusive[dist][[i], :].indices
-            self._calc_strategy.get_neighbors_exclusive(dist, i, transformation=False)
-            for i in range(len(self._features))
+        # compare to reference value is needed
+        ref_values_list = ref_values.tolist()
+        return [
+            np.nan_to_num(aggr(feature[neighborhood], ref_values_list[i]), default_value)
+            for i, neighborhood in enumerate(self._neighborhoods[dist])
         ]
-        values = [features[neighborhood] for neighborhood in neighborhoods]
-        return values
 
     def add_features_from_csv(
         self,
@@ -422,9 +513,3 @@ def features(self) -> pd.DataFrame:
         Returns a Pandas dataframe with all feature columns.
         """
         return self._features.copy()
-
-    def ajacency_matrix_powers_exclusive(self) -> Dict[int, csr_array]:
-        """
-        Return the adjacency_matrix of different max distances
-        """
-        return self._adjacency_matrix_powers_exclusive
diff --git a/mesh2vec/mesh2vec_cae.py b/mesh2vec/mesh2vec_cae.py
index 783d42a..c260306 100644
--- a/mesh2vec/mesh2vec_cae.py
+++ b/mesh2vec/mesh2vec_cae.py
@@ -17,7 +17,11 @@
 from mesh2vec.helpers import AbstractAdjacencyStrategy
 from mesh2vec.mesh_features import CaeShellMesh, is_tri, num_border, midpoint
 from mesh2vec.mesh2vec_base import Mesh2VecBase
-from mesh2vec.mesh2vec_exceptions import check_feature_available, AnsaNotFoundException
+from mesh2vec.mesh2vec_exceptions import (
+    check_feature_available,
+    AnsaNotFoundException,
+    check_vtx_id_match,
+)
 
 
 class Mesh2VecCae(Mesh2VecBase):
@@ -100,9 +104,7 @@ def __init__(
             }
         )
 
-        assert all(
-            x in mesh_info.keys() for x in ["part_name", "part_id", "file_path", "element_id"]
-        )
+        assert all(x in mesh_info.keys() for x in ["file_path", "element_id"])
         assert len(mesh_info) == len(self._element_info)
         assert all(mesh_info["element_id"] == self._element_info["element_id"])
         mesh_info = mesh_info.drop(["element_id"], axis=1)
@@ -223,6 +225,17 @@ def from_d3plot_shell(distance: int, d3plot: Path, partid: str = None) -> "Mesh2
 
         return Mesh2VecCae(distance, mesh, element_info)
 
+    @staticmethod
+    def from_keyfile_shell(distance: int, keyfile: Path) -> "Mesh2VecCae":
+        """
+        Read the given keyfile and use the shell elements to generate a hypergraph, using mesh
+        nodes as hyperedges, and adjacent elements as hypervertices.
+        """
+        mesh = CaeShellMesh.from_keyfile(keyfile)
+        element_info = pd.DataFrame({"element_id": mesh.element_ids})
+        element_info["file_path"] = str(keyfile)
+        return Mesh2VecCae(distance, mesh, element_info)
+
     def get_elements_info(self) -> pd.DataFrame:
         """
         Return a Pandas dataframe containing a row for each element in the hypergraph
@@ -240,12 +253,12 @@ def get_elements_info(self) -> pd.DataFrame:
     def add_features_from_ansa(
         self,
         features: List[str],
-        ansafile: Optional[Path],
+        ansafile: Optional[Path] = None,
         json_mesh_file: Optional[Path] = None,
         ansa_executable: Optional[Path] = None,
         ansa_script: Optional[Path] = None,
         verbose: bool = False,
-    ) -> None:
+    ) -> List[str]:
         """
         Add values derived or calculated from ANSA shell elements (currently restricted to
         LSDYNA models) for each element.
@@ -260,7 +273,7 @@ def add_features_from_ansa(
 
             * aspect: The aspect ratio of each element (ansafile is required)
             * warpage: (ansafile is required)
-            * num_borders: number of border edges
+            * num_border: number of border edges
             * is_tria
             * midpoint x,y,z
             * normal vector x,y,z (ansafile is required)
@@ -340,6 +353,7 @@ def _err_to_nan(elements: List[Dict[Any, Any]], name: str) -> np.ndarray:
                     ["vtx_id"] + [feature for feature in features if feature in okay_inplace]
                 ]
             )
+        return features
 
     # pylint: disable=too-many-arguments, too-many-branches. too-many-statements
     def get_feature_from_d3plot(
@@ -359,7 +373,7 @@ def get_feature_from_d3plot(
             >>> from lasso.dyna import ArrayType, D3plot
             >>> from mesh2vec.mesh2vec_cae import Mesh2VecCae
             >>> m2v =  Mesh2VecCae.from_d3plot_shell(3, Path("data/hat/HAT.d3plot"))
-            >>> names, values = m2v.get_feature_from_d3plot(
+            >>> names, values, ids = m2v.get_feature_from_d3plot(
             ...    ArrayType.element_shell_strain,
             ...    D3plot(Path("data/hat/HAT.d3plot").as_posix()),
             ...    timestep=1, shell_layer=0)
@@ -471,7 +485,11 @@ def _get_d3plot_layer_array_names() -> List[str]:
             ]
             feature_name = feature
 
-        return feature_name, new_feature
+        return (
+            feature_name,
+            new_feature,
+            [str(x) for x in d3plot_data.arrays["element_shell_ids"]],
+        )
 
     def add_feature_from_d3plot(
         self,
@@ -510,14 +528,17 @@ def add_feature_from_d3plot(
 
         d3plot_data = D3plot(d3plot.as_posix()) if not isinstance(d3plot, D3plot) else d3plot
 
-        feature_name, feature_values = self.get_feature_from_d3plot(
+        feature_name, feature_values, element_shell_ids = self.get_feature_from_d3plot(
             feature=feature,
             d3plot_data=d3plot_data,
             timestep=timestep,
             shell_layer=shell_layer,
             history_var_index=history_var_index,
         )
-        new_features = pd.DataFrame({"vtx_id": self._mesh.element_ids})
+
+        check_vtx_id_match(self._mesh.element_ids, element_shell_ids)
+
+        new_features = pd.DataFrame({"vtx_id": element_shell_ids})
         new_features[feature_name] = feature_values
         self._features = self._features.merge(  # type: ignore
             new_features, how="left", on="vtx_id", validate="1:1"
@@ -531,6 +552,7 @@ def aggregate_angle_diff(
         aggr: Optional[Callable] = None,
         agg_add_ref: bool = True,
         default_value: float = 0.0,
+        skip_arcos: bool = False,
     ) -> Union[str, List[str]]:
         # pylint: disable=line-too-long
 
@@ -551,6 +573,7 @@ def aggregate_angle_diff(
                 reference as 2nd argument. (default is True)
             default_value:  value to use in aggregation when a feature is missing for a neighbor
                 or no neighor with the given dist exist.
+            skip_arcos: if True, the angle difference is not calculated, but the dot product of the normal vectors is used.
 
         Example:
             >>> from pathlib import Path
@@ -577,12 +600,23 @@ def aggregate_angle_diff(
 
         def _mean_dir_diff(values: List[List[float]], ref_value: List[float]) -> float:
             """direction difference of values to ref_value (in radian)"""
-            assert aggr is not None
-            angle_diff = [
-                np.arccos(np.clip(np.dot(np.array(value), np.array(ref_value[0])), -1.0, 1.0))
-                for value in values
-            ]
-            return aggr(angle_diff)
+
+            def vectorize_angle_diff(values, ref_value):
+                try:
+                    values_array = np.array(values.tolist())
+                except AttributeError:
+                    values_array = np.array(values)
+
+                ref_value_array = np.array(ref_value)
+                dot_products = np.dot(values_array, ref_value_array)
+                if skip_arcos:
+                    return dot_products
+                angle_diff = np.arccos(np.clip(dot_products, -1.0, 1.0))
+                return angle_diff
+
+            angle_diff_b = vectorize_angle_diff(values, ref_value)
+
+            return aggr(angle_diff_b)
 
         return self.aggregate(
             "normal",
diff --git a/mesh2vec/mesh2vec_exceptions.py b/mesh2vec/mesh2vec_exceptions.py
index d7aeca9..579ab8c 100644
--- a/mesh2vec/mesh2vec_exceptions.py
+++ b/mesh2vec/mesh2vec_exceptions.py
@@ -12,7 +12,7 @@ def check_distance_init_arg(distance: int) -> None:
     """check argument to rise exception or log warning if needed."""
     if distance < 0:
         raise InvalidDistanceArgumentException("distance must be > 0")
-    if distance > 10:
+    if distance > 30:
         logger.warning("Calculating neighborhoods for distances > 10 can take much time")
 
 
@@ -102,3 +102,15 @@ def check_vtx_ids_column(vtx_ids_column: List[str]) -> None:
     """check argument to rise exception or log warning if needed."""
     if not all(isinstance(v, str) for v in vtx_ids_column):
         raise InvalidVtxIdArgument("All values in vtx_id column must be of type str")
+
+
+def check_vtx_id_match(vtx_ids_stored, new_vtx_ids):
+    """
+    Exception raised when the vtx_ids of the d3plot do not match the vtx_ids of
+    the loaded mesh
+    """
+    if not set(vtx_ids_stored) == set(new_vtx_ids):
+        raise InvalidVtxIdsArgument(
+            "The element_shell_ids of the d3plot must contain exactly all of "
+            "the elements ids of the loaded mesh."
+        )
diff --git a/mesh2vec/mesh_features.py b/mesh2vec/mesh_features.py
index 90a40c6..086b502 100644
--- a/mesh2vec/mesh_features.py
+++ b/mesh2vec/mesh_features.py
@@ -235,3 +235,62 @@ def from_ansa_json(elements: List[Any], nodes: List[Any]) -> "CaeShellMesh":
             [[pnt_idx[element[f"N{i}"]] for i in range(1, 5)] for element in elements]
         )  # duplicate ids allowed?
         return CaeShellMesh(point_coordinates, pnt_ids, elem_ids, elem_node_idxs)
+
+    @staticmethod
+    def from_keyfile(keyfile: str) -> "CaeShellMesh":
+        """create CaeShellMesh from keyfile"""
+
+        def parse_contents(file_contents):
+            lines = file_contents.split("\n")
+            current_section = ""
+
+            point_coordinates = []
+            pnt_ids = []
+
+            elem_ids = []
+            elem_node_ids = []
+
+            for line in lines:
+                if line.startswith("*"):
+                    current_section = line.split()[0].upper()
+                    continue
+                if line.startswith("$#"):  # comment
+                    continue
+
+                if current_section == "*NODE":
+                    data = line.split()
+                    if data:
+                        point_coordinates.append([float(data[1]), float(data[2]), float(data[3])])
+                        pnt_ids.append(data[0])
+
+                elif "*ELEMENT_SHELL" in current_section:
+                    data = line.split()
+                    if data:
+                        # check for floats - floats are a hint of options like THICKNESS
+                        if (
+                            not data[2].isdigit()
+                            or not data[3].isdigit()
+                            or not data[4].isdigit()
+                            or not data[5].isdigit()
+                        ):
+                            continue
+                        elem_node_ids.append([data[2], data[3], data[4], data[5]])
+                        elem_ids.append(data[0])
+            pnt_idx = {pnt_id: i for i, pnt_id in enumerate(pnt_ids)}
+
+            elem_node_idx = np.array(
+                [[pnt_idx[elem_node_id[i]] for i in range(4)] for elem_node_id in elem_node_ids]
+            )
+
+            return point_coordinates, pnt_ids, elem_ids, elem_node_idx
+
+        with open(keyfile, "r", encoding="utf-8") as file:
+            file_contents = file.read()
+        point_coordinates, pnt_ids, elem_ids, elem_node_idx = parse_contents(file_contents)
+
+        return CaeShellMesh(
+            np.array(point_coordinates),
+            np.array(pnt_ids),
+            np.array(elem_ids),
+            np.array(elem_node_idx),
+        )
diff --git a/mesh2vec/test.py b/mesh2vec/test.py
deleted file mode 100644
index faec627..0000000
--- a/mesh2vec/test.py
+++ /dev/null
@@ -1,56 +0,0 @@
-from mesh2vec.helpers import BFSAdjacency, BFSNumba, PurePythonBFS, MatMulAdjacency
-from mesh2vec.mesh2vec_cae import Mesh2VecCae
-from pathlib import Path
-import time
-
-start = time.time()
-matm = MatMulAdjacency()
-a = Mesh2VecCae.from_ansa_shell(
-    20,
-    Path("data/hat/Hatprofile.k"),
-    json_mesh_file=Path("data/hat/cached_hat_key.json"),
-    calc_strategy=matm,
-)
-print("MATMUL:", time.time() - start)
-matm_neighbors = sorted(matm.get_neighbors_exclusive(20, "4700000"))[:20]
-print(matm_neighbors)
-
-
-start = time.time()
-bfs = BFSAdjacency()
-b = Mesh2VecCae.from_ansa_shell(
-    20,
-    Path("data/hat/Hatprofile.k"),
-    json_mesh_file=Path("data/hat/cached_hat_key.json"),
-    calc_strategy=bfs,
-)
-print("BFS: ",time.time() - start)
-bfs_neighbors = sorted(bfs.get_neighbors_exclusive(20, "4700000"))[:20]
-print(bfs_neighbors)
-
-start = time.time()
-pbfs = PurePythonBFS()
-d = Mesh2VecCae.from_ansa_shell(
-    20,
-    Path("data/hat/Hatprofile.k"),
-    json_mesh_file=Path("data/hat/cached_hat_key.json"),
-    calc_strategy=pbfs,
-)
-print("PurePythonBFS:", time.time() - start)
-pbfs_neighbors = sorted(matm.get_neighbors_exclusive(20, "4700000"))[:20]
-print(pbfs_neighbors)
-
-
-start = time.time()
-c = Mesh2VecCae.from_ansa_shell(
-    20,
-    Path("data/hat/Hatprofile.k"),
-    json_mesh_file=Path("data/hat/cached_hat_key.json"),
-    calc_strategy=BFSNumba(),
-)
-print("NUMBA:", time.time() - start)
-numba_neighbors = sorted(matm.get_neighbors_exclusive(20, "4700000"))[:20]
-print(numba_neighbors)
-
-trued_neighbors = numba_neighbors==pbfs_neighbors==matm_neighbors==bfs_neighbors
-print("IDENTICAL_NEIGHBORS: ", trued_neighbors)
\ No newline at end of file
diff --git a/poetry.lock b/poetry.lock
index 8a43b72..b6b1856 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,59 +1,97 @@
+# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+
 [[package]]
 name = "alabaster"
 version = "0.7.13"
 description = "A configurable sidebar-enabled Sphinx theme"
-category = "dev"
 optional = false
 python-versions = ">=3.6"
+files = [
+    {file = "alabaster-0.7.13-py3-none-any.whl", hash = "sha256:1ee19aca801bbabb5ba3f5f258e4422dfa86f82f3e9cefb0859b283cdd7f62a3"},
+    {file = "alabaster-0.7.13.tar.gz", hash = "sha256:a27a4a084d5e690e16e01e03ad2b2e552c61a65469419b907243193de1a84ae2"},
+]
 
 [[package]]
 name = "anyio"
-version = "3.6.2"
+version = "4.1.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
-category = "main"
 optional = false
-python-versions = ">=3.6.2"
+python-versions = ">=3.8"
+files = [
+    {file = "anyio-4.1.0-py3-none-any.whl", hash = "sha256:56a415fbc462291813a94528a779597226619c8e78af7de0507333f700011e5f"},
+    {file = "anyio-4.1.0.tar.gz", hash = "sha256:5a0bec7085176715be77df87fc66d6c9d70626bd752fcc85f57cdbee5b3760da"},
+]
 
 [package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
 sniffio = ">=1.1"
 
 [package.extras]
-doc = ["packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["contextlib2", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (<0.15)", "uvloop (>=0.15)"]
-trio = ["trio (>=0.16,<0.22)"]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.23)"]
 
 [[package]]
 name = "appnope"
 version = "0.1.3"
 description = "Disable App Nap on macOS >= 10.9"
-category = "main"
 optional = false
 python-versions = "*"
+files = [
+    {file = "appnope-0.1.3-py2.py3-none-any.whl", hash = "sha256:265a455292d0bd8a72453494fa24df5a11eb18373a60c7c0430889f22548605e"},
+    {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
+]
 
 [[package]]
 name = "argon2-cffi"
-version = "21.3.0"
-description = "The secure Argon2 password hashing algorithm."
-category = "main"
+version = "23.1.0"
+description = "Argon2 for Python"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
+files = [
+    {file = "argon2_cffi-23.1.0-py3-none-any.whl", hash = "sha256:c670642b78ba29641818ab2e68bd4e6a78ba53b7eff7b4c3815ae16abf91c7ea"},
+    {file = "argon2_cffi-23.1.0.tar.gz", hash = "sha256:879c3e79a2729ce768ebb7d36d4609e3a78a4ca2ec3a9f12286ca057e3d0db08"},
+]
 
 [package.dependencies]
 argon2-cffi-bindings = "*"
 
 [package.extras]
-dev = ["cogapp", "coverage[toml] (>=5.0.2)", "furo", "hypothesis", "pre-commit", "pytest", "sphinx", "sphinx-notfound-page", "tomli"]
-docs = ["furo", "sphinx", "sphinx-notfound-page"]
-tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"]
+dev = ["argon2-cffi[tests,typing]", "tox (>4)"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-copybutton", "sphinx-notfound-page"]
+tests = ["hypothesis", "pytest"]
+typing = ["mypy"]
 
 [[package]]
 name = "argon2-cffi-bindings"
 version = "21.2.0"
 description = "Low-level CFFI bindings for Argon2"
-category = "main"
 optional = false
 python-versions = ">=3.6"
+files = [
+    {file = "argon2-cffi-bindings-21.2.0.tar.gz", hash = "sha256:bb89ceffa6c791807d1305ceb77dbfacc5aa499891d2c55661c6459651fc39e3"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:ccb949252cb2ab3a08c02024acb77cfb179492d5701c7cbdbfd776124d4d2367"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9524464572e12979364b7d600abf96181d3541da11e23ddf565a32e70bd4dc0d"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b746dba803a79238e925d9046a63aa26bf86ab2a2fe74ce6b009a1c3f5c8f2ae"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:58ed19212051f49a523abb1dbe954337dc82d947fb6e5a0da60f7c8471a8476c"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:bd46088725ef7f58b5a1ef7ca06647ebaf0eb4baff7d1d0d177c6cc8744abd86"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-musllinux_1_1_i686.whl", hash = "sha256:8cd69c07dd875537a824deec19f978e0f2078fdda07fd5c42ac29668dda5f40f"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:f1152ac548bd5b8bcecfb0b0371f082037e47128653df2e8ba6e914d384f3c3e"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-win32.whl", hash = "sha256:603ca0aba86b1349b147cab91ae970c63118a0f30444d4bc80355937c950c082"},
+    {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-win_amd64.whl", hash = "sha256:b2ef1c30440dbbcba7a5dc3e319408b59676e2e039e2ae11a8775ecf482b192f"},
+    {file = "argon2_cffi_bindings-21.2.0-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:e415e3f62c8d124ee16018e491a009937f8cf7ebf5eb430ffc5de21b900dad93"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:3e385d1c39c520c08b53d63300c3ecc28622f076f4c2b0e6d7e796e9f6502194"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2c3e3cc67fdb7d82c4718f19b4e7a87123caf8a93fde7e23cf66ac0337d3cb3f"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6a22ad9800121b71099d0fb0a65323810a15f2e292f2ba450810a7316e128ee5"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f9f8b450ed0547e3d473fdc8612083fd08dd2120d6ac8f73828df9b7d45bb351"},
+    {file = "argon2_cffi_bindings-21.2.0-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:93f9bf70084f97245ba10ee36575f0c3f1e7d7724d67d8e5b08e61787c320ed7"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:3b9ef65804859d335dc6b31582cad2c5166f0c3e7975f324d9ffaa34ee7e6583"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d4966ef5848d820776f5f562a7d45fdd70c2f330c961d0d745b784034bd9f48d"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:20ef543a89dee4db46a1a6e206cd015360e5a75822f76df533845c3cbaf72670"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ed2937d286e2ad0cc79a7087d3c272832865f779430e0cc2b4f3718d3159b0cb"},
+    {file = "argon2_cffi_bindings-21.2.0-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:5e00316dabdaea0b2dd82d141cc66889ced0cdcbfa599e8b471cf22c620c329a"},
+]
 
 [package.dependencies]
 cffi = ">=1.0.1"
@@ -64,22 +102,33 @@ tests = ["pytest"]
 
 [[package]]
 name = "arrow"
-version = "1.2.3"
+version = "1.3.0"
 description = "Better dates & times for Python"
-category = "main"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
+files = [
+    {file = "arrow-1.3.0-py3-none-any.whl", hash = "sha256:c728b120ebc00eb84e01882a6f5e7927a53960aa990ce7dd2b10f39005a67f80"},
+    {file = "arrow-1.3.0.tar.gz", hash = "sha256:d4540617648cb5f895730f1ad8c82a65f2dad0166f57b75f3ca54759c4d67a85"},
+]
 
 [package.dependencies]
 python-dateutil = ">=2.7.0"
+types-python-dateutil = ">=2.8.10"
+
+[package.extras]
+doc = ["doc8", "sphinx (>=7.0.0)", "sphinx-autobuild", "sphinx-autodoc-typehints", "sphinx_rtd_theme (>=1.3.0)"]
+test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (==3.*)"]
 
 [[package]]
 name = "astroid"
-version = "2.14.2"
+version = "2.15.8"
 description = "An abstract syntax tree for Python with inference support."
-category = "dev"
 optional = false
 python-versions = ">=3.7.2"
+files = [
+    {file = "astroid-2.15.8-py3-none-any.whl", hash = "sha256:1aa149fc5c6589e3d0ece885b4491acd80af4f087baafa3fb5203b113e68cd3c"},
+    {file = "astroid-2.15.8.tar.gz", hash = "sha256:6c107453dffee9055899705de3c9ead36e74119cee151e5a9aaf7f0b0e020a6a"},
+]
 
 [package.dependencies]
 lazy-object-proxy = ">=1.4.0"
@@ -91,59 +140,78 @@ wrapt = [
 
 [[package]]
 name = "asttokens"
-version = "2.2.1"
+version = "2.4.1"
 description = "Annotate AST trees with source code positions"
-category = "main"
 optional = false
 python-versions = "*"
+files = [
+    {file = "asttokens-2.4.1-py2.py3-none-any.whl", hash = "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24"},
+    {file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"},
+]
 
 [package.dependencies]
-six = "*"
+six = ">=1.12.0"
 
 [package.extras]
-test = ["astroid", "pytest"]
+astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"]
+test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
 
 [[package]]
 name = "attrs"
-version = "22.2.0"
+version = "23.1.0"
 description = "Classes Without Boilerplate"
-category = "main"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
+files = [
+    {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"},
+    {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
+]
 
 [package.extras]
-cov = ["attrs[tests]", "coverage-enable-subprocess", "coverage[toml] (>=5.3)"]
-dev = ["attrs[docs,tests]"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope.interface"]
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+cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
+dev = ["attrs[docs,tests]", "pre-commit"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
+tests = ["attrs[tests-no-zope]", "zope-interface"]
+tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 
 [[package]]
 name = "babel"
-version = "2.11.0"
+version = "2.13.1"
 description = "Internationalization utilities"
-category = "dev"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
+files = [
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+]
 
 [package.dependencies]
-pytz = ">=2015.7"
+pytz = {version = ">=2015.7", markers = "python_version < \"3.9\""}
+
+[package.extras]
+dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
 
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 name = "backcall"
 version = "0.2.0"
 description = "Specifications for callback functions passed in to an API"
-category = "main"
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 python-versions = "*"
+files = [
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+]
 
 [[package]]
 name = "beautifulsoup4"
-version = "4.11.2"
+version = "4.12.2"
 description = "Screen-scraping library"
-category = "main"
 optional = false
 python-versions = ">=3.6.0"
+files = [
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+]
 
 [package.dependencies]
 soupsieve = ">1.2"
@@ -156,9 +224,22 @@ lxml = ["lxml"]
 name = "black"
 version = "22.12.0"
 description = "The uncompromising code formatter."
-category = "dev"
 optional = false
 python-versions = ">=3.7"
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+]
 
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 click = ">=8.0.0"
@@ -176,70 +257,249 @@ uvloop = ["uvloop (>=0.15.2)"]
 
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+version = "6.1.0"
 description = "An easy safelist-based HTML-sanitizing tool."
-category = "main"
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-python-versions = ">=3.7"
+python-versions = ">=3.8"
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+]
 
 [package.dependencies]
 six = ">=1.9.0"
 webencodings = "*"
 
 [package.extras]
-css = ["tinycss2 (>=1.1.0,<1.2)"]
+css = ["tinycss2 (>=1.1.0,<1.3)"]
+
+[[package]]
+name = "blinker"
+version = "1.7.0"
+description = "Fast, simple object-to-object and broadcast signaling"
+optional = false
+python-versions = ">=3.8"
+files = [
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+[[package]]
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+version = "4.0"
+description = "Define boolean algebras, create and parse boolean expressions and create custom boolean DSL."
+optional = false
+python-versions = "*"
+files = [
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+version = "0.13.1"
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-category = "dev"
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-python-versions = ">=3.6"
+python-versions = ">=3.7"
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+requests = ">=2.16.0"
 
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+version = "2023.11.17"
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 [package.dependencies]
 pycparser = "*"
 
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 optional = false
-python-versions = "*"
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+]
 
 [[package]]
 name = "check-wheel-contents"
 version = "0.3.4"
 description = "Check your wheels have the right contents"
-category = "dev"
 optional = false
 python-versions = "~=3.6"
+files = [
+    {file = "check-wheel-contents-0.3.4.tar.gz", hash = "sha256:056cc04a66416e5a52b66c294199865081b163ef92abac723126d6838466c11d"},
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+]
 
 [package.dependencies]
 attrs = ">=18.1"
@@ -251,23 +511,29 @@ wheel-filename = ">=1.1,<2.0"
 
 [[package]]
 name = "cleo"
-version = "2.0.1"
+version = "2.1.0"
 description = "Cleo allows you to create beautiful and testable command-line interfaces."
-category = "main"
 optional = false
 python-versions = ">=3.7,<4.0"
+files = [
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+    {file = "cleo-2.1.0.tar.gz", hash = "sha256:0b2c880b5d13660a7ea651001fb4acb527696c01f15c9ee650f377aa543fd523"},
+]
 
 [package.dependencies]
 crashtest = ">=0.4.1,<0.5.0"
-rapidfuzz = ">=2.2.0,<3.0.0"
+rapidfuzz = ">=3.0.0,<4.0.0"
 
 [[package]]
 name = "click"
-version = "8.1.3"
+version = "8.1.7"
 description = "Composable command line interface toolkit"
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
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+    {file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"},
+]
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
@@ -276,103 +542,203 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
+files = [
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+]
 
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 name = "comm"
-version = "0.1.2"
+version = "0.2.0"
 description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
-category = "main"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
+files = [
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+    {file = "comm-0.2.0.tar.gz", hash = "sha256:a517ea2ca28931c7007a7a99c562a0fa5883cfb48963140cf642c41c948498be"},
+]
 
 [package.dependencies]
-traitlets = ">=5.3"
+traitlets = ">=4"
 
 [package.extras]
 test = ["pytest"]
 
 [[package]]
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-version = "1.0.7"
+version = "1.1.1"
 description = "Python library for calculating contours of 2D quadrilateral grids"
-category = "main"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
-numpy = ">=1.16"
+numpy = {version = ">=1.16,<2.0", markers = "python_version <= \"3.11\""}
 
 [package.extras]
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-docs = ["furo", "sphinx-copybutton"]
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-test = ["Pillow", "matplotlib", "pytest"]
-test-no-images = ["pytest"]
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+docs = ["furo", "sphinx (>=7.2)", "sphinx-copybutton"]
+mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.4.1)", "types-Pillow"]
+test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
+test-no-images = ["pytest", "pytest-cov", "wurlitzer"]
 
 [[package]]
 name = "crashtest"
 version = "0.4.1"
 description = "Manage Python errors with ease"
-category = "main"
 optional = false
 python-versions = ">=3.7,<4.0"
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 [[package]]
 name = "cycler"
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+version = "0.12.1"
 description = "Composable style cycles"
-category = "main"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
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+
+[package.extras]
+docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
+tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "cyclonedx-python-lib"
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 description = "A library for producing CycloneDX SBOM (Software Bill of Materials) files."
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 optional = false
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-toml = ">=0.10.0,<0.11.0"
 
 [[package]]
 name = "debugpy"
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+version = "1.8.0"
 description = "An implementation of the Debug Adapter Protocol for Python"
-category = "main"
 optional = false
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 name = "decorator"
 version = "5.1.1"
 description = "Decorators for Humans"
-category = "main"
 optional = false
 python-versions = ">=3.5"
+files = [
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 version = "0.7.1"
 description = "XML bomb protection for Python stdlib modules"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+files = [
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+]
 
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 name = "dill"
-version = "0.3.6"
-description = "serialize all of python"
-category = "dev"
+version = "0.3.7"
+description = "serialize all of Python"
 optional = false
 python-versions = ">=3.7"
+files = [
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+]
 
 [package.extras]
 graph = ["objgraph (>=1.7.2)"]
@@ -381,57 +747,100 @@ graph = ["objgraph (>=1.7.2)"]
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 description = "Docutils -- Python Documentation Utilities"
-category = "dev"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
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+]
+
+[[package]]
+name = "entrypoints"
+version = "0.4"
+description = "Discover and load entry points from installed packages."
+optional = false
+python-versions = ">=3.6"
+files = [
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+]
 
 [[package]]
 name = "exceptiongroup"
-version = "1.1.0"
+version = "1.2.0"
 description = "Backport of PEP 654 (exception groups)"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
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+]
 
 [package.extras]
 test = ["pytest (>=6)"]
 
 [[package]]
 name = "executing"
-version = "1.2.0"
+version = "2.0.1"
 description = "Get the currently executing AST node of a frame, and other information"
-category = "main"
 optional = false
-python-versions = "*"
+python-versions = ">=3.5"
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 [package.extras]
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+tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
 
 [[package]]
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-version = "2.16.2"
+version = "2.19.0"
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-category = "main"
 optional = false
 python-versions = "*"
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+]
 
 [package.extras]
 devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"]
 
+[[package]]
+name = "filelock"
+version = "3.13.1"
+description = "A platform independent file lock."
+optional = false
+python-versions = ">=3.8"
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+typing = ["typing-extensions (>=4.8)"]
+
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+version = "2.3.3"
 description = "A simple framework for building complex web applications."
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
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 [package.dependencies]
-click = ">=8.0"
+blinker = ">=1.6.2"
+click = ">=8.1.3"
 importlib-metadata = {version = ">=3.6.0", markers = "python_version < \"3.10\""}
-itsdangerous = ">=2.0"
-Jinja2 = ">=3.0"
-Werkzeug = ">=2.2.2"
+itsdangerous = ">=2.1.2"
+Jinja2 = ">=3.1.2"
+Werkzeug = ">=2.3.7"
 
 [package.extras]
 async = ["asgiref (>=3.2)"]
@@ -439,14 +848,57 @@ dotenv = ["python-dotenv"]
 
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+]
+
+[package.dependencies]
+texttable = ">=1.6.2"
+
+[package.extras]
+cairo = ["cairocffi (>=1.2.0)"]
+doc = ["Sphinx (>=7.0.0)", "pydoctor (>=23.4.0)", "sphinx-gallery (>=0.14.0)", "sphinx-rtd-theme (>=1.3.0)"]
+matplotlib = ["matplotlib (>=3.6.0)"]
+plotly = ["plotly (>=5.3.0)"]
+plotting = ["cairocffi (>=1.2.0)"]
+test = ["Pillow (>=9)", "cairocffi (>=1.2.0)", "matplotlib (>=3.6.0)", "networkx (>=2.5)", "numpy (>=1.19.0)", "pandas (>=1.1.0)", "plotly (>=5.3.0)", "pytest (>=7.0.1)", "pytest-timeout (>=2.1.0)", "scipy (>=1.5.0)"]
+test-musl = ["cairocffi (>=1.2.0)", "networkx (>=2.5)", "pytest (>=7.0.1)", "pytest-timeout (>=2.1.0)"]
 
 [[package]]
 name = "imagesize"
 version = "1.4.1"
 description = "Getting image size from png/jpeg/jpeg2000/gif file"
-category = "dev"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
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+]
 
 [[package]]
 name = "importlib-metadata"
-version = "6.0.0"
+version = "6.8.0"
 description = "Read metadata from Python packages"
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
+    {file = "importlib_metadata-6.8.0-py3-none-any.whl", hash = "sha256:3ebb78df84a805d7698245025b975d9d67053cd94c79245ba4b3eb694abe68bb"},
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+]
 
 [package.dependencies]
 zipp = ">=0.5"
@@ -537,38 +1142,47 @@ zipp = ">=0.5"
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 perf = ["ipython"]
-testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
+testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)", "pytest-ruff"]
 
 [[package]]
 name = "importlib-resources"
-version = "5.12.0"
+version = "6.1.1"
 description = "Read resources from Python packages"
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
+    {file = "importlib_resources-6.1.1-py3-none-any.whl", hash = "sha256:e8bf90d8213b486f428c9c39714b920041cb02c184686a3dee24905aaa8105d6"},
+    {file = "importlib_resources-6.1.1.tar.gz", hash = "sha256:3893a00122eafde6894c59914446a512f728a0c1a45f9bb9b63721b6bacf0b4a"},
+]
 
 [package.dependencies]
 zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-ruff", "zipp (>=3.17)"]
 
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
+    {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
+]
 
 [[package]]
 name = "ipykernel"
-version = "6.21.2"
+version = "6.27.1"
 description = "IPython Kernel for Jupyter"
-category = "main"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "ipykernel-6.27.1-py3-none-any.whl", hash = "sha256:dab88b47f112f9f7df62236511023c9bdeef67abc73af7c652e4ce4441601686"},
+    {file = "ipykernel-6.27.1.tar.gz", hash = "sha256:7d5d594b6690654b4d299edba5e872dc17bb7396a8d0609c97cb7b8a1c605de6"},
+]
 
 [package.dependencies]
 appnope = {version = "*", markers = "platform_system == \"Darwin\""}
@@ -576,7 +1190,7 @@ comm = ">=0.1.1"
 debugpy = ">=1.6.5"
 ipython = ">=7.23.1"
 jupyter-client = ">=6.1.12"
-jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 matplotlib-inline = ">=0.1"
 nest-asyncio = "*"
 packaging = "*"
@@ -594,11 +1208,14 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio"
 
 [[package]]
 name = "ipython"
-version = "8.10.0"
+version = "8.12.3"
 description = "IPython: Productive Interactive Computing"
-category = "main"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "ipython-8.12.3-py3-none-any.whl", hash = "sha256:b0340d46a933d27c657b211a329d0be23793c36595acf9e6ef4164bc01a1804c"},
+    {file = "ipython-8.12.3.tar.gz", hash = "sha256:3910c4b54543c2ad73d06579aa771041b7d5707b033bd488669b4cf544e3b363"},
+]
 
 [package.dependencies]
 appnope = {version = "*", markers = "sys_platform == \"darwin\""}
@@ -609,10 +1226,11 @@ jedi = ">=0.16"
 matplotlib-inline = "*"
 pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
 pickleshare = "*"
-prompt-toolkit = ">=3.0.30,<3.1.0"
+prompt-toolkit = ">=3.0.30,<3.0.37 || >3.0.37,<3.1.0"
 pygments = ">=2.4.0"
 stack-data = "*"
 traitlets = ">=5"
+typing-extensions = {version = "*", markers = "python_version < \"3.10\""}
 
 [package.extras]
 all = ["black", "curio", "docrepr", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.21)", "pandas", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
@@ -631,17 +1249,23 @@ test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.21)", "pa
 name = "ipython-genutils"
 version = "0.2.0"
 description = "Vestigial utilities from IPython"
-category = "main"
 optional = false
 python-versions = "*"
+files = [
+    {file = "ipython_genutils-0.2.0-py2.py3-none-any.whl", hash = "sha256:72dd37233799e619666c9f639a9da83c34013a73e8bbc79a7a6348d93c61fab8"},
+    {file = "ipython_genutils-0.2.0.tar.gz", hash = "sha256:eb2e116e75ecef9d4d228fdc66af54269afa26ab4463042e33785b887c628ba8"},
+]
 
 [[package]]
 name = "isoduration"
 version = "20.11.0"
 description = "Operations with ISO 8601 durations"
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "isoduration-20.11.0-py3-none-any.whl", hash = "sha256:b2904c2a4228c3d44f409c8ae8e2370eb21a26f7ac2ec5446df141dde3452042"},
+    {file = "isoduration-20.11.0.tar.gz", hash = "sha256:ac2f9015137935279eac671f94f89eb00584f940f5dc49462a0c4ee692ba1bd9"},
+]
 
 [package.dependencies]
 arrow = ">=0.15.0"
@@ -650,9 +1274,12 @@ arrow = ">=0.15.0"
 name = "isort"
 version = "5.12.0"
 description = "A Python utility / library to sort Python imports."
-category = "dev"
 optional = false
 python-versions = ">=3.8.0"
+files = [
+    {file = "isort-5.12.0-py3-none-any.whl", hash = "sha256:f84c2818376e66cf843d497486ea8fed8700b340f308f076c6fb1229dff318b6"},
+    {file = "isort-5.12.0.tar.gz", hash = "sha256:8bef7dde241278824a6d83f44a544709b065191b95b6e50894bdc722fcba0504"},
+]
 
 [package.extras]
 colors = ["colorama (>=0.4.3)"]
@@ -664,33 +1291,42 @@ requirements-deprecated-finder = ["pip-api", "pipreqs"]
 name = "itsdangerous"
 version = "2.1.2"
 description = "Safely pass data to untrusted environments and back."
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "itsdangerous-2.1.2-py3-none-any.whl", hash = "sha256:2c2349112351b88699d8d4b6b075022c0808887cb7ad10069318a8b0bc88db44"},
+    {file = "itsdangerous-2.1.2.tar.gz", hash = "sha256:5dbbc68b317e5e42f327f9021763545dc3fc3bfe22e6deb96aaf1fc38874156a"},
+]
 
 [[package]]
 name = "jedi"
-version = "0.18.2"
+version = "0.19.1"
 description = "An autocompletion tool for Python that can be used for text editors."
-category = "main"
 optional = false
 python-versions = ">=3.6"
+files = [
+    {file = "jedi-0.19.1-py2.py3-none-any.whl", hash = "sha256:e983c654fe5c02867aef4cdfce5a2fbb4a50adc0af145f70504238f18ef5e7e0"},
+    {file = "jedi-0.19.1.tar.gz", hash = "sha256:cf0496f3651bc65d7174ac1b7d043eff454892c708a87d1b683e57b569927ffd"},
+]
 
 [package.dependencies]
-parso = ">=0.8.0,<0.9.0"
+parso = ">=0.8.3,<0.9.0"
 
 [package.extras]
 docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alabaster (==0.7.12)", "babel (==2.9.1)", "chardet (==4.0.0)", "commonmark (==0.8.1)", "docutils (==0.17.1)", "future (==0.18.2)", "idna (==2.10)", "imagesize (==1.2.0)", "mock (==1.0.1)", "packaging (==20.9)", "pyparsing (==2.4.7)", "pytz (==2021.1)", "readthedocs-sphinx-ext (==2.1.4)", "recommonmark (==0.5.0)", "requests (==2.25.1)", "six (==1.15.0)", "snowballstemmer (==2.1.0)", "sphinx (==1.8.5)", "sphinx-rtd-theme (==0.4.3)", "sphinxcontrib-serializinghtml (==1.1.4)", "sphinxcontrib-websupport (==1.2.4)", "urllib3 (==1.26.4)"]
-qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
-testing = ["Django (<3.1)", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
+qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
+testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 
 [[package]]
 name = "jinja2"
 version = "3.1.2"
 description = "A very fast and expressive template engine."
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "Jinja2-3.1.2-py3-none-any.whl", hash = "sha256:6088930bfe239f0e6710546ab9c19c9ef35e29792895fed6e6e31a023a182a61"},
+    {file = "Jinja2-3.1.2.tar.gz", hash = "sha256:31351a702a408a9e7595a8fc6150fc3f43bb6bf7e319770cbc0db9df9437e852"},
+]
 
 [package.dependencies]
 MarkupSafe = ">=2.0"
@@ -700,39 +1336,50 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "joblib"
-version = "1.2.0"
+version = "1.3.2"
 description = "Lightweight pipelining with Python functions"
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "joblib-1.3.2-py3-none-any.whl", hash = "sha256:ef4331c65f239985f3f2220ecc87db222f08fd22097a3dd5698f693875f8cbb9"},
+    {file = "joblib-1.3.2.tar.gz", hash = "sha256:92f865e621e17784e7955080b6d042489e3b8e294949cc44c6eac304f59772b1"},
+]
 
 [[package]]
 name = "jsonpointer"
-version = "2.3"
+version = "2.4"
 description = "Identify specific nodes in a JSON document (RFC 6901)"
-category = "main"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
+files = [
+    {file = "jsonpointer-2.4-py2.py3-none-any.whl", hash = "sha256:15d51bba20eea3165644553647711d150376234112651b4f1811022aecad7d7a"},
+    {file = "jsonpointer-2.4.tar.gz", hash = "sha256:585cee82b70211fa9e6043b7bb89db6e1aa49524340dde8ad6b63206ea689d88"},
+]
 
 [[package]]
 name = "jsonschema"
-version = "4.17.3"
+version = "4.20.0"
 description = "An implementation of JSON Schema validation for Python"
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
+    {file = "jsonschema-4.20.0-py3-none-any.whl", hash = "sha256:ed6231f0429ecf966f5bc8dfef245998220549cbbcf140f913b7464c52c3b6b3"},
+    {file = "jsonschema-4.20.0.tar.gz", hash = "sha256:4f614fd46d8d61258610998997743ec5492a648b33cf478c1ddc23ed4598a5fa"},
+]
 
 [package.dependencies]
-attrs = ">=17.4.0"
+attrs = ">=22.2.0"
 fqdn = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
 idna = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
 importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
 isoduration = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
 jsonpointer = {version = ">1.13", optional = true, markers = "extra == \"format-nongpl\""}
+jsonschema-specifications = ">=2023.03.6"
 pkgutil-resolve-name = {version = ">=1.3.10", markers = "python_version < \"3.9\""}
-pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2"
+referencing = ">=0.28.4"
 rfc3339-validator = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
 rfc3986-validator = {version = ">0.1.0", optional = true, markers = "extra == \"format-nongpl\""}
+rpds-py = ">=0.7.1"
 uri-template = {version = "*", optional = true, markers = "extra == \"format-nongpl\""}
 webcolors = {version = ">=1.11", optional = true, markers = "extra == \"format-nongpl\""}
 
@@ -740,55 +1387,81 @@ webcolors = {version = ">=1.11", optional = true, markers = "extra == \"format-n
 format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
 format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"]
 
+[[package]]
+name = "jsonschema-specifications"
+version = "2023.11.1"
+description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jsonschema_specifications-2023.11.1-py3-none-any.whl", hash = "sha256:f596778ab612b3fd29f72ea0d990393d0540a5aab18bf0407a46632eab540779"},
+    {file = "jsonschema_specifications-2023.11.1.tar.gz", hash = "sha256:c9b234904ffe02f079bf91b14d79987faa685fd4b39c377a0996954c0090b9ca"},
+]
+
+[package.dependencies]
+importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
+referencing = ">=0.31.0"
+
 [[package]]
 name = "jupyter-client"
-version = "8.0.3"
+version = "7.4.9"
 description = "Jupyter protocol implementation and client libraries"
-category = "main"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.7"
+files = [
+    {file = "jupyter_client-7.4.9-py3-none-any.whl", hash = "sha256:214668aaea208195f4c13d28eb272ba79f945fc0cf3f11c7092c20b2ca1980e7"},
+    {file = "jupyter_client-7.4.9.tar.gz", hash = "sha256:52be28e04171f07aed8f20e1616a5a552ab9fee9cbbe6c1896ae170c3880d392"},
+]
 
 [package.dependencies]
-importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
-jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
+entrypoints = "*"
+jupyter-core = ">=4.9.2"
+nest-asyncio = ">=1.5.4"
 python-dateutil = ">=2.8.2"
 pyzmq = ">=23.0"
 tornado = ">=6.2"
-traitlets = ">=5.3"
+traitlets = "*"
 
 [package.extras]
-docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
-test = ["codecov", "coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
+doc = ["ipykernel", "myst-parser", "sphinx (>=1.3.6)", "sphinx-rtd-theme", "sphinxcontrib-github-alt"]
+test = ["codecov", "coverage", "ipykernel (>=6.12)", "ipython", "mypy", "pre-commit", "pytest", "pytest-asyncio (>=0.18)", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "jupyter-core"
-version = "5.2.0"
+version = "5.5.0"
 description = "Jupyter core package. A base package on which Jupyter projects rely."
-category = "main"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "jupyter_core-5.5.0-py3-none-any.whl", hash = "sha256:e11e02cd8ae0a9de5c6c44abf5727df9f2581055afe00b22183f621ba3585805"},
+    {file = "jupyter_core-5.5.0.tar.gz", hash = "sha256:880b86053bf298a8724994f95e99b99130659022a4f7f45f563084b6223861d3"},
+]
 
 [package.dependencies]
 platformdirs = ">=2.5"
-pywin32 = {version = ">=1.0", markers = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\""}
+pywin32 = {version = ">=300", markers = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\""}
 traitlets = ">=5.3"
 
 [package.extras]
-docs = ["myst-parser", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"]
 test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "jupyter-events"
-version = "0.6.3"
+version = "0.9.0"
 description = "Jupyter Event System library"
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
+    {file = "jupyter_events-0.9.0-py3-none-any.whl", hash = "sha256:d853b3c10273ff9bc8bb8b30076d65e2c9685579db736873de6c2232dde148bf"},
+    {file = "jupyter_events-0.9.0.tar.gz", hash = "sha256:81ad2e4bc710881ec274d31c6c50669d71bbaa5dd9d01e600b56faa85700d399"},
+]
 
 [package.dependencies]
-jsonschema = {version = ">=3.2.0", extras = ["format-nongpl"]}
+jsonschema = {version = ">=4.18.0", extras = ["format-nongpl"]}
 python-json-logger = ">=2.0.4"
 pyyaml = ">=5.3"
+referencing = "*"
 rfc3339-validator = "*"
 rfc3986-validator = ">=0.1.1"
 traitlets = ">=5.3"
@@ -796,47 +1469,54 @@ traitlets = ">=5.3"
 [package.extras]
 cli = ["click", "rich"]
 docs = ["jupyterlite-sphinx", "myst-parser", "pydata-sphinx-theme", "sphinxcontrib-spelling"]
-test = ["click", "coverage", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "pytest-console-scripts", "pytest-cov", "rich"]
+test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "pytest-console-scripts", "rich"]
 
 [[package]]
 name = "jupyter-server"
-version = "2.3.0"
+version = "2.11.1"
 description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
-category = "main"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "jupyter_server-2.11.1-py3-none-any.whl", hash = "sha256:4b3a16e3ed16fd202588890f10b8ca589bd3e29405d128beb95935f059441373"},
+    {file = "jupyter_server-2.11.1.tar.gz", hash = "sha256:fe80bab96493acf5f7d6cd9a1575af8fbd253dc2591aa4d015131a1e03b5799a"},
+]
 
 [package.dependencies]
 anyio = ">=3.1.0"
 argon2-cffi = "*"
 jinja2 = "*"
 jupyter-client = ">=7.4.4"
-jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
-jupyter-events = ">=0.4.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+jupyter-events = ">=0.9.0"
 jupyter-server-terminals = "*"
 nbconvert = ">=6.4.4"
 nbformat = ">=5.3.0"
+overrides = "*"
 packaging = "*"
 prometheus-client = "*"
 pywinpty = {version = "*", markers = "os_name == \"nt\""}
 pyzmq = ">=24"
-send2trash = "*"
+send2trash = ">=1.8.2"
 terminado = ">=0.8.3"
 tornado = ">=6.2.0"
 traitlets = ">=5.6.0"
 websocket-client = "*"
 
 [package.extras]
-docs = ["docutils (<0.20)", "ipykernel", "jinja2", "jupyter-client", "jupyter-server", "mistune (<1.0.0)", "myst-parser", "nbformat", "prometheus-client", "pydata-sphinx-theme", "send2trash", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-openapi", "sphinxcontrib-spelling", "sphinxemoji", "tornado"]
-test = ["ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.4)", "pytest-timeout", "requests"]
+docs = ["ipykernel", "jinja2", "jupyter-client", "jupyter-server", "myst-parser", "nbformat", "prometheus-client", "pydata-sphinx-theme", "send2trash", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-openapi (>=0.8.0)", "sphinxcontrib-spelling", "sphinxemoji", "tornado", "typing-extensions"]
+test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.4)", "pytest-timeout", "requests"]
 
 [[package]]
 name = "jupyter-server-terminals"
 version = "0.4.4"
 description = "A Jupyter Server Extension Providing Terminals."
-category = "main"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "jupyter_server_terminals-0.4.4-py3-none-any.whl", hash = "sha256:75779164661cec02a8758a5311e18bb8eb70c4e86c6b699403100f1585a12a36"},
+    {file = "jupyter_server_terminals-0.4.4.tar.gz", hash = "sha256:57ab779797c25a7ba68e97bcfb5d7740f2b5e8a83b5e8102b10438041a7eac5d"},
+]
 
 [package.dependencies]
 pywinpty = {version = ">=2.0.3", markers = "os_name == \"nt\""}
@@ -848,27 +1528,137 @@ test = ["coverage", "jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-cov",
 
 [[package]]
 name = "jupyterlab-pygments"
-version = "0.2.2"
+version = "0.3.0"
 description = "Pygments theme using JupyterLab CSS variables"
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
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+    {file = "jupyterlab_pygments-0.3.0.tar.gz", hash = "sha256:721aca4d9029252b11cfa9d185e5b5af4d54772bb8072f9b7036f4170054d35d"},
+]
 
 [[package]]
 name = "kiwisolver"
-version = "1.4.4"
+version = "1.4.5"
 description = "A fast implementation of the Cassowary constraint solver"
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
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 tornado = {version = "*", markers = "python_version > \"2.7\""}
 
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 description = "Python logging made (stupidly) simple"
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 [package.dependencies]
 contourpy = ">=1.0.1"
@@ -971,20 +1959,22 @@ cycler = ">=0.10"
 fonttools = ">=4.22.0"
 importlib-resources = {version = ">=3.2.0", markers = "python_version < \"3.10\""}
 kiwisolver = ">=1.0.1"
-numpy = ">=1.20"
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 packaging = ">=20.0"
 pillow = ">=6.2.0"
 pyparsing = ">=2.3.1"
 python-dateutil = ">=2.7"
-setuptools_scm = ">=7"
 
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 version = "0.1.6"
 description = "Inline Matplotlib backend for Jupyter"
-category = "main"
 optional = false
 python-versions = ">=3.5"
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 [package.dependencies]
 traitlets = "*"
@@ -993,41 +1983,131 @@ traitlets = "*"
 name = "mccabe"
 version = "0.7.0"
 description = "McCabe checker, plugin for flake8"
-category = "dev"
 optional = false
 python-versions = ">=3.6"
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 name = "mdurl"
 version = "0.1.2"
 description = "Markdown URL utilities"
-category = "main"
 optional = false
 python-versions = ">=3.7"
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+]
 
 [package.dependencies]
 jupyter-client = ">=6.1.12"
-jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 nbformat = ">=5.1"
-traitlets = ">=5.3"
+traitlets = ">=5.4"
 
 [package.extras]
 dev = ["pre-commit"]
-docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphinx (>=1.7)", "sphinx-book-theme"]
-test = ["ipykernel", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"]
+docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling"]
+test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"]
 
 [[package]]
 name = "nbconvert"
-version = "7.2.9"
+version = "7.11.0"
 description = "Converting Jupyter Notebooks"
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
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+    {file = "nbconvert-7.11.0.tar.gz", hash = "sha256:abedc01cf543177ffde0bfc2a69726d5a478f6af10a332fc1bf29fcb4f0cf000"},
+]
 
 [package.dependencies]
 beautifulsoup4 = "*"
-bleach = "*"
+bleach = "!=5.0.0"
 defusedxml = "*"
 importlib-metadata = {version = ">=3.6", markers = "python_version < \"3.10\""}
 jinja2 = ">=3.0"
 jupyter-core = ">=4.7"
 jupyterlab-pygments = "*"
 markupsafe = ">=2.0"
-mistune = ">=2.0.3,<3"
+mistune = ">=2.0.3,<4"
 nbclient = ">=0.5.0"
-nbformat = ">=5.1"
+nbformat = ">=5.7"
 packaging = "*"
 pandocfilters = ">=1.4.1"
 pygments = ">=2.4.1"
 tinycss2 = "*"
-traitlets = ">=5.0"
+traitlets = ">=5.1"
 
 [package.extras]
 all = ["nbconvert[docs,qtpdf,serve,test,webpdf]"]
@@ -1130,16 +2222,19 @@ docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sp
 qtpdf = ["nbconvert[qtpng]"]
 qtpng = ["pyqtwebengine (>=5.15)"]
 serve = ["tornado (>=6.1)"]
-test = ["ipykernel", "ipywidgets (>=7)", "pre-commit", "pytest", "pytest-dependency"]
-webpdf = ["pyppeteer (>=1,<1.1)"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7)", "pytest"]
+webpdf = ["playwright"]
 
 [[package]]
 name = "nbformat"
-version = "5.7.3"
+version = "5.9.2"
 description = "The Jupyter Notebook format"
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
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+    {file = "nbformat-5.9.2.tar.gz", hash = "sha256:5f98b5ba1997dff175e77e0c17d5c10a96eaed2cbd1de3533d1fc35d5e111192"},
+]
 
 [package.dependencies]
 fastjsonschema = "*"
@@ -1153,19 +2248,25 @@ test = ["pep440", "pre-commit", "pytest", "testpath"]
 
 [[package]]
 name = "nest-asyncio"
-version = "1.5.6"
+version = "1.5.8"
 description = "Patch asyncio to allow nested event loops"
-category = "main"
 optional = false
 python-versions = ">=3.5"
+files = [
+    {file = "nest_asyncio-1.5.8-py3-none-any.whl", hash = "sha256:accda7a339a70599cb08f9dd09a67e0c2ef8d8d6f4c07f96ab203f2ae254e48d"},
+    {file = "nest_asyncio-1.5.8.tar.gz", hash = "sha256:25aa2ca0d2a5b5531956b9e273b45cf664cae2b145101d73b86b199978d48fdb"},
+]
 
 [[package]]
 name = "networkx"
 version = "2.8.8"
 description = "Python package for creating and manipulating graphs and networks"
-category = "main"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "networkx-2.8.8-py3-none-any.whl", hash = "sha256:e435dfa75b1d7195c7b8378c3859f0445cd88c6b0375c181ed66823a9ceb7524"},
+    {file = "networkx-2.8.8.tar.gz", hash = "sha256:230d388117af870fce5647a3c52401fcf753e94720e6ea6b4197a5355648885e"},
+]
 
 [package.extras]
 default = ["matplotlib (>=3.4)", "numpy (>=1.19)", "pandas (>=1.3)", "scipy (>=1.8)"]
@@ -1176,25 +2277,28 @@ test = ["codecov (>=2.1)", "pytest (>=7.2)", "pytest-cov (>=4.0)"]
 
 [[package]]
 name = "notebook"
-version = "6.5.2"
+version = "6.5.6"
 description = "A web-based notebook environment for interactive computing"
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "notebook-6.5.6-py3-none-any.whl", hash = "sha256:c1e2eb2e3b6079a0552a04974883a48d04c3c05792170d64a4b23d707d453181"},
+    {file = "notebook-6.5.6.tar.gz", hash = "sha256:b4625a4b7a597839dd3156b140d5ba2c7123761f98245a3290f67a8b8ee048d9"},
+]
 
 [package.dependencies]
 argon2-cffi = "*"
 ipykernel = "*"
 ipython-genutils = "*"
 jinja2 = "*"
-jupyter-client = ">=5.3.4"
+jupyter-client = ">=5.3.4,<8"
 jupyter-core = ">=4.6.1"
 nbclassic = ">=0.4.7"
 nbconvert = ">=5"
 nbformat = "*"
 nest-asyncio = ">=1.5"
 prometheus-client = "*"
-pyzmq = ">=17"
+pyzmq = ">=17,<25"
 Send2Trash = ">=1.8.0"
 terminado = ">=0.8.3"
 tornado = ">=6.1"
@@ -1207,53 +2311,167 @@ test = ["coverage", "nbval", "pytest", "pytest-cov", "requests", "requests-unixs
 
 [[package]]
 name = "notebook-shim"
-version = "0.2.2"
+version = "0.2.3"
 description = "A shim layer for notebook traits and config"
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
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+    {file = "notebook_shim-0.2.3.tar.gz", hash = "sha256:f69388ac283ae008cd506dda10d0288b09a017d822d5e8c7129a152cbd3ce7e9"},
+]
 
 [package.dependencies]
 jupyter-server = ">=1.8,<3"
 
 [package.extras]
-test = ["pytest", "pytest-console-scripts", "pytest-tornasync"]
+test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"]
+
+[[package]]
+name = "numba"
+version = "0.58.1"
+description = "compiling Python code using LLVM"
+optional = false
+python-versions = ">=3.8"
+files = [
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+[package.dependencies]
+importlib-metadata = {version = "*", markers = "python_version < \"3.9\""}
+llvmlite = "==0.41.*"
+numpy = ">=1.22,<1.27"
 
 [[package]]
 name = "numpy"
-version = "1.24.2"
+version = "1.24.4"
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-category = "main"
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 python-versions = ">=3.8"
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 [[package]]
 name = "packageurl-python"
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 description = "A purl aka. Package URL parser and builder"
-category = "dev"
 optional = false
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 [package.extras]
 build = ["wheel"]
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 [[package]]
 name = "packaging"
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 description = "Core utilities for Python packages"
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 optional = false
 python-versions = ">=3.7"
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 [[package]]
 name = "pandas"
 version = "1.5.3"
 description = "Powerful data structures for data analysis, time series, and statistics"
-category = "main"
 optional = false
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 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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 python-versions = ">=3.6"
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+]
 
 [package.extras]
-docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-issues (>=3.0.1)", "sphinx-removed-in", "sphinxext-opengraph"]
+docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-removed-in", "sphinxext-opengraph"]
 tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "pip"
-version = "23.0.1"
+version = "23.3.1"
 description = "The PyPA recommended tool for installing Python packages."
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "pip-23.3.1-py3-none-any.whl", hash = "sha256:55eb67bb6171d37447e82213be585b75fe2b12b359e993773aca4de9247a052b"},
+    {file = "pip-23.3.1.tar.gz", hash = "sha256:1fcaa041308d01f14575f6d0d2ea4b75a3e2871fe4f9c694976f908768e14174"},
+]
 
 [[package]]
 name = "pip-api"
 version = "0.0.30"
 description = "An unofficial, importable pip API"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "pip-api-0.0.30.tar.gz", hash = "sha256:a05df2c7aa9b7157374bcf4273544201a0c7bae60a9c65bcf84f3959ef3896f3"},
+    {file = "pip_api-0.0.30-py3-none-any.whl", hash = "sha256:2a0314bd31522eb9ffe8a99668b0d07fee34ebc537931e7b6483001dbedcbdc9"},
+]
 
 [package.dependencies]
 pip = "*"
 
 [[package]]
 name = "pip-audit"
-version = "2.4.14"
+version = "2.6.1"
 description = "A tool for scanning Python environments for known vulnerabilities"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "pip_audit-2.6.1-py3-none-any.whl", hash = "sha256:8a32bb67dca6a76c244bbccebed562c0f6957b1fc9d34d59a9ec0fbff0672ae0"},
+    {file = "pip_audit-2.6.1.tar.gz", hash = "sha256:55c9bd18b0fe3959f73397db08d257c6012ad1826825e3d74cb6c3f79e95c245"},
+]
 
 [package.dependencies]
-CacheControl = {version = ">=0.12.10", extras = ["filecache"]}
-cyclonedx-python-lib = ">=2.0.0,<2.5.0 || >2.5.0"
+CacheControl = {version = ">=0.13.0", extras = ["filecache"]}
+cyclonedx-python-lib = ">=4.0,<5.0"
 html5lib = ">=1.1"
 packaging = ">=23.0.0"
 pip-api = ">=0.0.28"
 pip-requirements-parser = ">=32.0.0"
-resolvelib = ">=0.8.0"
+requests = ">=2.31.0"
 rich = ">=12.4"
 toml = ">=0.10"
 
 [package.extras]
 dev = ["build", "bump (>=1.3.2)", "pip-audit[doc,lint,test]"]
 doc = ["pdoc"]
-lint = ["black (>=22.3.0)", "interrogate", "isort", "mypy", "ruff (<0.0.228)", "types-html5lib", "types-requests", "types-toml"]
+lint = ["black (>=22.3.0)", "interrogate", "isort", "mypy", "ruff (<0.0.281)", "types-html5lib", "types-requests", "types-toml"]
 test = ["coverage[toml]", "pretend", "pytest", "pytest-cov"]
 
 [[package]]
 name = "pip-requirements-parser"
 version = "32.0.1"
 description = "pip requirements parser - a mostly correct pip requirements parsing library because it uses pip's own code."
-category = "dev"
 optional = false
 python-versions = ">=3.6.0"
+files = [
+    {file = "pip-requirements-parser-32.0.1.tar.gz", hash = "sha256:b4fa3a7a0be38243123cf9d1f3518da10c51bdb165a2b2985566247f9155a7d3"},
+    {file = "pip_requirements_parser-32.0.1-py3-none-any.whl", hash = "sha256:4659bc2a667783e7a15d190f6fccf8b2486685b6dba4c19c3876314769c57526"},
+]
 
 [package.dependencies]
 packaging = "*"
@@ -1390,40 +2690,53 @@ testing = ["aboutcode-toolkit (>=6.0.0)", "black", "pytest (>=6,!=7.0.0)", "pyte
 name = "pkgutil-resolve-name"
 version = "1.3.10"
 description = "Resolve a name to an object."
-category = "main"
 optional = false
 python-versions = ">=3.6"
+files = [
+    {file = "pkgutil_resolve_name-1.3.10-py3-none-any.whl", hash = "sha256:ca27cc078d25c5ad71a9de0a7a330146c4e014c2462d9af19c6b828280649c5e"},
+    {file = "pkgutil_resolve_name-1.3.10.tar.gz", hash = "sha256:357d6c9e6a755653cfd78893817c0853af365dd51ec97f3d358a819373bbd174"},
+]
 
 [[package]]
 name = "platformdirs"
-version = "3.0.0"
+version = "4.0.0"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "platformdirs-4.0.0-py3-none-any.whl", hash = "sha256:118c954d7e949b35437270383a3f2531e99dd93cf7ce4dc8340d3356d30f173b"},
+    {file = "platformdirs-4.0.0.tar.gz", hash = "sha256:cb633b2bcf10c51af60beb0ab06d2f1d69064b43abf4c185ca6b28865f3f9731"},
+]
 
 [package.extras]
-docs = ["furo (>=2022.12.7)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-autodoc-typehints (>=1.22,!=1.23.4)"]
-test = ["appdirs (==1.4.4)", "covdefaults (>=2.2.2)", "pytest (>=7.2.1)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.1)", "sphinx-autodoc-typehints (>=1.24)"]
+test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)"]
 
 [[package]]
 name = "plotly"
-version = "5.13.0"
+version = "5.18.0"
 description = "An open-source, interactive data visualization library for Python"
-category = "main"
 optional = false
 python-versions = ">=3.6"
+files = [
+    {file = "plotly-5.18.0-py3-none-any.whl", hash = "sha256:23aa8ea2f4fb364a20d34ad38235524bd9d691bf5299e800bca608c31e8db8de"},
+    {file = "plotly-5.18.0.tar.gz", hash = "sha256:360a31e6fbb49d12b007036eb6929521343d6bee2236f8459915821baefa2cbb"},
+]
 
 [package.dependencies]
+packaging = "*"
 tenacity = ">=6.2.0"
 
 [[package]]
 name = "pluggy"
-version = "1.0.0"
+version = "1.3.0"
 description = "plugin and hook calling mechanisms for python"
-category = "dev"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
+files = [
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+    {file = "pluggy-1.3.0.tar.gz", hash = "sha256:cf61ae8f126ac6f7c451172cf30e3e43d3ca77615509771b3a984a0730651e12"},
+]
 
 [package.extras]
 dev = ["pre-commit", "tox"]
@@ -1431,41 +2744,76 @@ testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
 name = "prometheus-client"
-version = "0.16.0"
+version = "0.19.0"
 description = "Python client for the Prometheus monitoring system."
-category = "main"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
+files = [
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+]
 
 [package.extras]
 twisted = ["twisted"]
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.36"
+version = "3.0.41"
 description = "Library for building powerful interactive command lines in Python"
-category = "main"
 optional = false
-python-versions = ">=3.6.2"
+python-versions = ">=3.7.0"
+files = [
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+]
 
 [package.dependencies]
 wcwidth = "*"
 
 [[package]]
 name = "protobuf"
-version = "4.22.0"
+version = "4.25.1"
 description = ""
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
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+    {file = "protobuf-4.25.1.tar.gz", hash = "sha256:57d65074b4f5baa4ab5da1605c02be90ac20c8b40fb137d6a8df9f416b0d0ce2"},
+]
 
 [[package]]
 name = "psutil"
-version = "5.9.4"
+version = "5.9.6"
 description = "Cross-platform lib for process and system monitoring in Python."
-category = "main"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
+files = [
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+    {file = "psutil-5.9.6-cp36-cp36m-win_amd64.whl", hash = "sha256:ff18b8d1a784b810df0b0fff3bcb50ab941c3b8e2c8de5726f9c71c601c611aa"},
+    {file = "psutil-5.9.6-cp37-abi3-win32.whl", hash = "sha256:a6f01f03bf1843280f4ad16f4bde26b817847b4c1a0db59bf6419807bc5ce05c"},
+    {file = "psutil-5.9.6-cp37-abi3-win_amd64.whl", hash = "sha256:6e5fb8dc711a514da83098bc5234264e551ad980cec5f85dabf4d38ed6f15e9a"},
+    {file = "psutil-5.9.6-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:daecbcbd29b289aac14ece28eca6a3e60aa361754cf6da3dfb20d4d32b6c7f57"},
+    {file = "psutil-5.9.6.tar.gz", hash = "sha256:e4b92ddcd7dd4cdd3f900180ea1e104932c7bce234fb88976e2a3b296441225a"},
+]
 
 [package.extras]
 test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
@@ -1474,17 +2822,23 @@ test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
 name = "ptyprocess"
 version = "0.7.0"
 description = "Run a subprocess in a pseudo terminal"
-category = "main"
 optional = false
 python-versions = "*"
+files = [
+    {file = "ptyprocess-0.7.0-py2.py3-none-any.whl", hash = "sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35"},
+    {file = "ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220"},
+]
 
 [[package]]
 name = "pure-eval"
 version = "0.2.2"
 description = "Safely evaluate AST nodes without side effects"
-category = "main"
 optional = false
 python-versions = "*"
+files = [
+    {file = "pure_eval-0.2.2-py3-none-any.whl", hash = "sha256:01eaab343580944bc56080ebe0a674b39ec44a945e6d09ba7db3cb8cec289350"},
+    {file = "pure_eval-0.2.2.tar.gz", hash = "sha256:2b45320af6dfaa1750f543d714b6d1c520a1688dec6fd24d339063ce0aaa9ac3"},
+]
 
 [package.extras]
 tests = ["pytest"]
@@ -1493,25 +2847,82 @@ tests = ["pytest"]
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 version = "1.11.0"
 description = "library with cross-python path, ini-parsing, io, code, log facilities"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+files = [
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+    {file = "py-1.11.0.tar.gz", hash = "sha256:51c75c4126074b472f746a24399ad32f6053d1b34b68d2fa41e558e6f4a98719"},
+]
+
+[[package]]
+name = "py-serializable"
+version = "0.11.1"
+description = "Library for serializing and deserializing Python Objects to and from JSON and XML."
+optional = false
+python-versions = ">=3.7,<4.0"
+files = [
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+]
+
+[package.dependencies]
+defusedxml = ">=0.7.1,<0.8.0"
 
 [[package]]
 name = "pycparser"
 version = "2.21"
 description = "C parser in Python"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
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+    {file = "pycparser-2.21.tar.gz", hash = "sha256:e644fdec12f7872f86c58ff790da456218b10f863970249516d60a5eaca77206"},
+]
 
 [[package]]
 name = "pydantic"
-version = "1.10.5"
+version = "1.10.13"
 description = "Data validation and settings management using python type hints"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
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 [package.dependencies]
 typing-extensions = ">=4.2.0"
@@ -1522,33 +2933,43 @@ email = ["email-validator (>=1.0.3)"]
 
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+version = "1.5.28"
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-category = "main"
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-category = "main"
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-python-versions = ">=3.6"
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 [package.extras]
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+version = "2.17.7"
 description = "python code static checker"
-category = "dev"
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 python-versions = ">=3.7.2"
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 colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
 dill = [
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@@ -1567,33 +2988,30 @@ testutils = ["gitpython (>3)"]
 
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+version = "3.1.1"
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 [package.extras]
 diagrams = ["jinja2", "railroad-diagrams"]
 
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-category = "main"
-optional = false
-python-versions = ">=3.7"
-
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-category = "dev"
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@@ -1602,120 +3020,376 @@ pluggy = ">=0.12,<2.0"
 tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
-testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"]
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 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
-
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 charset-normalizer = ">=2,<4"
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 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
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-category = "dev"
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-python-versions = "*"
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-[package.extras]
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-release = ["build", "towncrier", "twine"]
-test = ["commentjson", "packaging", "pytest"]
-
 [[package]]
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-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
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@@ -1724,33 +3398,169 @@ six = "*"
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+    {file = "sniffio-1.3.0-py3-none-any.whl", hash = "sha256:eecefdce1e5bbfb7ad2eeaabf7c1eeb404d7757c379bd1f7e5cce9d8bf425384"},
+    {file = "sniffio-1.3.0.tar.gz", hash = "sha256:e60305c5e5d314f5389259b7f22aaa33d8f7dee49763119234af3755c55b9101"},
+]
 
 [[package]]
 name = "snowballstemmer"
 version = "2.2.0"
 description = "This package provides 29 stemmers for 28 languages generated from Snowball algorithms."
-category = "dev"
 optional = false
 python-versions = "*"
+files = [
+    {file = "snowballstemmer-2.2.0-py2.py3-none-any.whl", hash = "sha256:c8e1716e83cc398ae16824e5572ae04e0d9fc2c6b985fb0f900f5f0c96ecba1a"},
+    {file = "snowballstemmer-2.2.0.tar.gz", hash = "sha256:09b16deb8547d3412ad7b590689584cd0fe25ec8db3be37788be3810cbf19cb1"},
+]
 
 [[package]]
 name = "sortedcontainers"
 version = "2.4.0"
 description = "Sorted Containers -- Sorted List, Sorted Dict, Sorted Set"
-category = "dev"
 optional = false
 python-versions = "*"
+files = [
+    {file = "sortedcontainers-2.4.0-py2.py3-none-any.whl", hash = "sha256:a163dcaede0f1c021485e957a39245190e74249897e2ae4b2aa38595db237ee0"},
+    {file = "sortedcontainers-2.4.0.tar.gz", hash = "sha256:25caa5a06cc30b6b83d11423433f65d1f9d76c4c6a0c90e3379eaa43b9bfdb88"},
+]
 
 [[package]]
 name = "soupsieve"
-version = "2.4"
+version = "2.5"
 description = "A modern CSS selector implementation for Beautiful Soup."
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
+    {file = "soupsieve-2.5-py3-none-any.whl", hash = "sha256:eaa337ff55a1579b6549dc679565eac1e3d000563bcb1c8ab0d0fefbc0c2cdc7"},
+    {file = "soupsieve-2.5.tar.gz", hash = "sha256:5663d5a7b3bfaeee0bc4372e7fc48f9cff4940b3eec54a6451cc5299f1097690"},
+]
 
 [[package]]
 name = "sphinx"
 version = "5.3.0"
 description = "Python documentation generator"
-category = "dev"
 optional = false
 python-versions = ">=3.6"
+files = [
+    {file = "Sphinx-5.3.0.tar.gz", hash = "sha256:51026de0a9ff9fc13c05d74913ad66047e104f56a129ff73e174eb5c3ee794b5"},
+    {file = "sphinx-5.3.0-py3-none-any.whl", hash = "sha256:060ca5c9f7ba57a08a1219e547b269fadf125ae25b06b9fa7f66768efb652d6d"},
+]
 
 [package.dependencies]
 alabaster = ">=0.7,<0.8"
@@ -1888,9 +3690,12 @@ test = ["cython", "html5lib", "pytest (>=4.6)", "typed_ast"]
 name = "sphinx-autobuild"
 version = "2021.3.14"
 description = "Rebuild Sphinx documentation on changes, with live-reload in the browser."
-category = "dev"
 optional = false
 python-versions = ">=3.6"
+files = [
+    {file = "sphinx-autobuild-2021.3.14.tar.gz", hash = "sha256:de1ca3b66e271d2b5b5140c35034c89e47f263f2cd5db302c9217065f7443f05"},
+    {file = "sphinx_autobuild-2021.3.14-py3-none-any.whl", hash = "sha256:8fe8cbfdb75db04475232f05187c776f46f6e9e04cacf1e49ce81bdac649ccac"},
+]
 
 [package.dependencies]
 colorama = "*"
@@ -1904,25 +3709,31 @@ test = ["pytest", "pytest-cov"]
 name = "sphinx-gallery"
 version = "0.11.1"
 description = "A Sphinx extension that builds an HTML version of any Python script and puts it into an examples gallery."
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "sphinx-gallery-0.11.1.tar.gz", hash = "sha256:56ccb29a0c2c4767d2a66617ba6ea7893e3a3885b6d972c62783a3b45b583ea5"},
+    {file = "sphinx_gallery-0.11.1-py3-none-any.whl", hash = "sha256:b165cb366a5768a0f36e60e5bc6828fbf55fd1831e71645310167375223aa25c"},
+]
 
 [package.dependencies]
 sphinx = ">=3"
 
 [[package]]
 name = "sphinx-rtd-theme"
-version = "1.2.0"
+version = "1.3.0"
 description = "Read the Docs theme for Sphinx"
-category = "dev"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
+files = [
+    {file = "sphinx_rtd_theme-1.3.0-py2.py3-none-any.whl", hash = "sha256:46ddef89cc2416a81ecfbeaceab1881948c014b1b6e4450b815311a89fb977b0"},
+    {file = "sphinx_rtd_theme-1.3.0.tar.gz", hash = "sha256:590b030c7abb9cf038ec053b95e5380b5c70d61591eb0b552063fbe7c41f0931"},
+]
 
 [package.dependencies]
 docutils = "<0.19"
-sphinx = ">=1.6,<7"
-sphinxcontrib-jquery = {version = ">=2.0.0,<3.0.0 || >3.0.0", markers = "python_version > \"3\""}
+sphinx = ">=1.6,<8"
+sphinxcontrib-jquery = ">=4,<5"
 
 [package.extras]
 dev = ["bump2version", "sphinxcontrib-httpdomain", "transifex-client", "wheel"]
@@ -1931,9 +3742,12 @@ dev = ["bump2version", "sphinxcontrib-httpdomain", "transifex-client", "wheel"]
 name = "sphinxcontrib-applehelp"
 version = "1.0.4"
 description = "sphinxcontrib-applehelp is a Sphinx extension which outputs Apple help books"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "sphinxcontrib-applehelp-1.0.4.tar.gz", hash = "sha256:828f867945bbe39817c210a1abfd1bc4895c8b73fcaade56d45357a348a07d7e"},
+    {file = "sphinxcontrib_applehelp-1.0.4-py3-none-any.whl", hash = "sha256:29d341f67fb0f6f586b23ad80e072c8e6ad0b48417db2bde114a4c9746feb228"},
+]
 
 [package.extras]
 lint = ["docutils-stubs", "flake8", "mypy"]
@@ -1943,9 +3757,12 @@ test = ["pytest"]
 name = "sphinxcontrib-devhelp"
 version = "1.0.2"
 description = "sphinxcontrib-devhelp is a sphinx extension which outputs Devhelp document."
-category = "dev"
 optional = false
 python-versions = ">=3.5"
+files = [
+    {file = "sphinxcontrib-devhelp-1.0.2.tar.gz", hash = "sha256:ff7f1afa7b9642e7060379360a67e9c41e8f3121f2ce9164266f61b9f4b338e4"},
+    {file = "sphinxcontrib_devhelp-1.0.2-py2.py3-none-any.whl", hash = "sha256:8165223f9a335cc1af7ffe1ed31d2871f325254c0423bc0c4c7cd1c1e4734a2e"},
+]
 
 [package.extras]
 lint = ["docutils-stubs", "flake8", "mypy"]
@@ -1955,9 +3772,12 @@ test = ["pytest"]
 name = "sphinxcontrib-htmlhelp"
 version = "2.0.1"
 description = "sphinxcontrib-htmlhelp is a sphinx extension which renders HTML help files"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "sphinxcontrib-htmlhelp-2.0.1.tar.gz", hash = "sha256:0cbdd302815330058422b98a113195c9249825d681e18f11e8b1f78a2f11efff"},
+    {file = "sphinxcontrib_htmlhelp-2.0.1-py3-none-any.whl", hash = "sha256:c38cb46dccf316c79de6e5515e1770414b797162b23cd3d06e67020e1d2a6903"},
+]
 
 [package.extras]
 lint = ["docutils-stubs", "flake8", "mypy"]
@@ -1965,22 +3785,28 @@ test = ["html5lib", "pytest"]
 
 [[package]]
 name = "sphinxcontrib-jquery"
-version = "2.0.0"
+version = "4.1"
 description = "Extension to include jQuery on newer Sphinx releases"
-category = "dev"
 optional = false
 python-versions = ">=2.7"
+files = [
+    {file = "sphinxcontrib-jquery-4.1.tar.gz", hash = "sha256:1620739f04e36a2c779f1a131a2dfd49b2fd07351bf1968ced074365933abc7a"},
+    {file = "sphinxcontrib_jquery-4.1-py2.py3-none-any.whl", hash = "sha256:f936030d7d0147dd026a4f2b5a57343d233f1fc7b363f68b3d4f1cb0993878ae"},
+]
 
 [package.dependencies]
-setuptools = "*"
+Sphinx = ">=1.8"
 
 [[package]]
 name = "sphinxcontrib-jsmath"
 version = "1.0.1"
 description = "A sphinx extension which renders display math in HTML via JavaScript"
-category = "dev"
 optional = false
 python-versions = ">=3.5"
+files = [
+    {file = "sphinxcontrib-jsmath-1.0.1.tar.gz", hash = "sha256:a9925e4a4587247ed2191a22df5f6970656cb8ca2bd6284309578f2153e0c4b8"},
+    {file = "sphinxcontrib_jsmath-1.0.1-py2.py3-none-any.whl", hash = "sha256:2ec2eaebfb78f3f2078e73666b1415417a116cc848b72e5172e596c871103178"},
+]
 
 [package.extras]
 test = ["flake8", "mypy", "pytest"]
@@ -1989,9 +3815,12 @@ test = ["flake8", "mypy", "pytest"]
 name = "sphinxcontrib-qthelp"
 version = "1.0.3"
 description = "sphinxcontrib-qthelp is a sphinx extension which outputs QtHelp document."
-category = "dev"
 optional = false
 python-versions = ">=3.5"
+files = [
+    {file = "sphinxcontrib-qthelp-1.0.3.tar.gz", hash = "sha256:4c33767ee058b70dba89a6fc5c1892c0d57a54be67ddd3e7875a18d14cba5a72"},
+    {file = "sphinxcontrib_qthelp-1.0.3-py2.py3-none-any.whl", hash = "sha256:bd9fc24bcb748a8d51fd4ecaade681350aa63009a347a8c14e637895444dfab6"},
+]
 
 [package.extras]
 lint = ["docutils-stubs", "flake8", "mypy"]
@@ -2001,9 +3830,12 @@ test = ["pytest"]
 name = "sphinxcontrib-serializinghtml"
 version = "1.1.5"
 description = "sphinxcontrib-serializinghtml is a sphinx extension which outputs \"serialized\" HTML files (json and pickle)."
-category = "dev"
 optional = false
 python-versions = ">=3.5"
+files = [
+    {file = "sphinxcontrib-serializinghtml-1.1.5.tar.gz", hash = "sha256:aa5f6de5dfdf809ef505c4895e51ef5c9eac17d0f287933eb49ec495280b6952"},
+    {file = "sphinxcontrib_serializinghtml-1.1.5-py2.py3-none-any.whl", hash = "sha256:352a9a00ae864471d3a7ead8d7d79f5fc0b57e8b3f95e9867eb9eb28999b92fd"},
+]
 
 [package.extras]
 lint = ["docutils-stubs", "flake8", "mypy"]
@@ -2011,11 +3843,14 @@ test = ["pytest"]
 
 [[package]]
 name = "stack-data"
-version = "0.6.2"
+version = "0.6.3"
 description = "Extract data from python stack frames and tracebacks for informative displays"
-category = "main"
 optional = false
 python-versions = "*"
+files = [
+    {file = "stack_data-0.6.3-py3-none-any.whl", hash = "sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695"},
+    {file = "stack_data-0.6.3.tar.gz", hash = "sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9"},
+]
 
 [package.dependencies]
 asttokens = ">=2.1.0"
@@ -2027,22 +3862,28 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
 [[package]]
 name = "tenacity"
-version = "8.2.1"
+version = "8.2.3"
 description = "Retry code until it succeeds"
-category = "main"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
+files = [
+    {file = "tenacity-8.2.3-py3-none-any.whl", hash = "sha256:ce510e327a630c9e1beaf17d42e6ffacc88185044ad85cf74c0a8887c6a0f88c"},
+    {file = "tenacity-8.2.3.tar.gz", hash = "sha256:5398ef0d78e63f40007c1fb4c0bff96e1911394d2fa8d194f77619c05ff6cc8a"},
+]
 
 [package.extras]
 doc = ["reno", "sphinx", "tornado (>=4.5)"]
 
 [[package]]
 name = "terminado"
-version = "0.17.1"
+version = "0.18.0"
 description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
+    {file = "terminado-0.18.0-py3-none-any.whl", hash = "sha256:87b0d96642d0fe5f5abd7783857b9cab167f221a39ff98e3b9619a788a3c0f2e"},
+    {file = "terminado-0.18.0.tar.gz", hash = "sha256:1ea08a89b835dd1b8c0c900d92848147cef2537243361b2e3f4dc15df9b6fded"},
+]
 
 [package.dependencies]
 ptyprocess = {version = "*", markers = "os_name != \"nt\""}
@@ -2052,14 +3893,29 @@ tornado = ">=6.1.0"
 [package.extras]
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
 test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"]
+typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
+
+[[package]]
+name = "texttable"
+version = "1.7.0"
+description = "module to create simple ASCII tables"
+optional = false
+python-versions = "*"
+files = [
+    {file = "texttable-1.7.0-py2.py3-none-any.whl", hash = "sha256:72227d592c82b3d7f672731ae73e4d1f88cd8e2ef5b075a7a7f01a23a3743917"},
+    {file = "texttable-1.7.0.tar.gz", hash = "sha256:2d2068fb55115807d3ac77a4ca68fa48803e84ebb0ee2340f858107a36522638"},
+]
 
 [[package]]
 name = "tinycss2"
 version = "1.2.1"
 description = "A tiny CSS parser"
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "tinycss2-1.2.1-py3-none-any.whl", hash = "sha256:2b80a96d41e7c3914b8cda8bc7f705a4d9c49275616e886103dd839dfc847847"},
+    {file = "tinycss2-1.2.1.tar.gz", hash = "sha256:8cff3a8f066c2ec677c06dbc7b45619804a6938478d9d73c284b29d14ecb0627"},
+]
 
 [package.dependencies]
 webencodings = ">=0.4"
@@ -2072,1972 +3928,332 @@ test = ["flake8", "isort", "pytest"]
 name = "toml"
 version = "0.10.2"
 description = "Python Library for Tom's Obvious, Minimal Language"
-category = "dev"
 optional = false
 python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
+    {file = "toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b"},
+    {file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
+]
 
 [[package]]
 name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
-category = "main"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
+    {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
+]
 
 [[package]]
 name = "tomlkit"
-version = "0.11.6"
+version = "0.12.3"
 description = "Style preserving TOML library"
-category = "dev"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
+files = [
+    {file = "tomlkit-0.12.3-py3-none-any.whl", hash = "sha256:b0a645a9156dc7cb5d3a1f0d4bab66db287fcb8e0430bdd4664a095ea16414ba"},
+    {file = "tomlkit-0.12.3.tar.gz", hash = "sha256:75baf5012d06501f07bee5bf8e801b9f343e7aac5a92581f20f80ce632e6b5a4"},
+]
 
 [[package]]
 name = "tornado"
-version = "6.2"
+version = "6.4"
 description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
-category = "main"
 optional = false
-python-versions = ">= 3.7"
+python-versions = ">= 3.8"
+files = [
+    {file = "tornado-6.4-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:02ccefc7d8211e5a7f9e8bc3f9e5b0ad6262ba2fbb683a6443ecc804e5224ce0"},
+    {file = "tornado-6.4-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:27787de946a9cffd63ce5814c33f734c627a87072ec7eed71f7fc4417bb16263"},
+    {file = "tornado-6.4-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f7894c581ecdcf91666a0912f18ce5e757213999e183ebfc2c3fdbf4d5bd764e"},
+    {file = "tornado-6.4-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e43bc2e5370a6a8e413e1e1cd0c91bedc5bd62a74a532371042a18ef19e10579"},
+    {file = "tornado-6.4-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f0251554cdd50b4b44362f73ad5ba7126fc5b2c2895cc62b14a1c2d7ea32f212"},
+    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:fd03192e287fbd0899dd8f81c6fb9cbbc69194d2074b38f384cb6fa72b80e9c2"},
+    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:88b84956273fbd73420e6d4b8d5ccbe913c65d31351b4c004ae362eba06e1f78"},
+    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:71ddfc23a0e03ef2df1c1397d859868d158c8276a0603b96cf86892bff58149f"},
+    {file = "tornado-6.4-cp38-abi3-win32.whl", hash = "sha256:6f8a6c77900f5ae93d8b4ae1196472d0ccc2775cc1dfdc9e7727889145c45052"},
+    {file = "tornado-6.4-cp38-abi3-win_amd64.whl", hash = "sha256:10aeaa8006333433da48dec9fe417877f8bcc21f48dda8d661ae79da357b2a63"},
+    {file = "tornado-6.4.tar.gz", hash = "sha256:72291fa6e6bc84e626589f1c29d90a5a6d593ef5ae68052ee2ef000dfd273dee"},
+]
 
 [[package]]
 name = "traitlets"
-version = "5.9.0"
+version = "5.14.0"
 description = "Traitlets Python configuration system"
-category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
+files = [
+    {file = "traitlets-5.14.0-py3-none-any.whl", hash = "sha256:f14949d23829023013c47df20b4a76ccd1a85effb786dc060f34de7948361b33"},
+    {file = "traitlets-5.14.0.tar.gz", hash = "sha256:fcdaa8ac49c04dfa0ed3ee3384ef6dfdb5d6f3741502be247279407679296772"},
+]
 
 [package.extras]
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
-test = ["argcomplete (>=2.0)", "pre-commit", "pytest", "pytest-mock"]
+test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
 
 [[package]]
 name = "trimesh"
-version = "3.20.0"
+version = "3.23.5"
 description = "Import, export, process, analyze and view triangular meshes."
-category = "main"
 optional = false
 python-versions = "*"
+files = [
+    {file = "trimesh-3.23.5-py3-none-any.whl", hash = "sha256:9cfc592c7ad6475ebfe51c90b0a1e686d627735cea6e6e18e40745be3ecfaab9"},
+    {file = "trimesh-3.23.5.tar.gz", hash = "sha256:bdfd669eccc4b3faff2328200a49408cd5ecad9f19b6022c4adb554bbb3a2621"},
+]
 
 [package.dependencies]
 numpy = "*"
 
 [package.extras]
-all = ["chardet", "colorlog", "glooey", "jsonschema", "lxml", "mapbox-earcut", "meshio", "msgpack", "networkx", "pillow", "psutil", "pycollada", "pyglet (<2)", "python-fcl", "requests", "rtree", "scikit-image", "scipy", "setuptools", "shapely", "svg.path", "sympy", "xatlas", "xxhash"]
-easy = ["chardet", "colorlog", "jsonschema", "lxml", "mapbox-earcut", "msgpack", "networkx", "pillow", "pycollada", "requests", "rtree", "scipy", "setuptools", "shapely", "svg.path", "sympy", "xxhash"]
-test = ["autopep8", "coveralls", "ezdxf", "pyinstrument", "pytest", "pytest-cov", "ruff"]
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diff --git a/pyproject.toml b/pyproject.toml
index 8912747..2cedb6d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -21,11 +21,13 @@ loguru = "^0.6.0"
 notebook = "^6.5.2"
 plotly = "^5.11.0"
 joblib = "^1.2.0"
-pillow = "^9.3.0"
+pillow = "^10.0.1"
 py = "^1.11.0"
 cleo = "^2.0.1"
 werkzeug = "^2.2.3"
 ipython = "^8.10.0"
+numba = "^0.58.1"
+igraph = "^0.11.3"
 
 [tool.poetry.dev-dependencies]
 pytest = "^7.2"
diff --git a/scripts/discover_bottlenecks.ipynb b/scripts/discover_bottlenecks.ipynb
deleted file mode 100644
index c2a2085..0000000
--- a/scripts/discover_bottlenecks.ipynb
+++ /dev/null
@@ -1,122 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "3f4b82e7",
-   "metadata": {},
-   "source": [
-    "## Methodology\n",
-    "\n",
-    "Inspect calc_adjacencies in mesh2vec.mesh2vec.helpers.py from different angles to pinpoint bottlenck(s):\n",
-    "- Use time as measurement to find obvious bottlenecks\n",
-    "- Use a profiler (in this case: cProfile) to inspect statistics about each section (e.g.: number of function calls, cumulative time spent on function, ..)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8089532b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "STATS_OUTPUT_FILE = \"profile_stats.txt\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f7caade1",
-   "metadata": {},
-   "source": [
-    "### Imports"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7a8ff956",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# perf counter more accurate than using time.time()\n",
-    "from time import perf_counter\n",
-    "\n",
-    "from pstats import SortKey, Stats\n",
-    "import io\n",
-    "from cProfile import Profile\n",
-    "\n",
-    "from pathlib import Path\n",
-    "from mesh2vec.mesh2vec_cae import Mesh2VecCae"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d78841c7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "pr = Profile()\n",
-    "pr.enable()\n",
-    "Mesh2VecCae.from_ansa_shell(25,Path(\"../data/hat/Hatprofile.k\"),\n",
-    "                                  json_mesh_file=Path(\"../data/hat/cached_hat_key.json\"))  \n",
-    "pr.disable()\n",
-    "s = io.StringIO()\n",
-    "sortby = SortKey.CUMULATIVE\n",
-    "ps = Stats(pr, stream=s).sort_stats(sortby)\n",
-    "ps.print_stats()\n",
-    "\n",
-    "# write profiling stats to file\n",
-    "with open(STATS_OUTPUT_FILE, 'w+') as f:\n",
-    "    f.write(s.getvalue())"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "85e2e6d1",
-   "metadata": {},
-   "source": [
-    "## Interactive visualization of profiling results"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "66cb58db",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%load_ext snakeviz\n",
-    "%snakeviz Mesh2VecCae.from_ansa_shell(25,Path(\"../data/hat/Hatprofile.k\"),json_mesh_file=Path(\"../data/hat/cached_hat_key.json\"))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ac198351",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.12"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/scripts/generate_test_data.py b/scripts/generate_test_data.py
deleted file mode 100644
index 636d935..0000000
--- a/scripts/generate_test_data.py
+++ /dev/null
@@ -1,7 +0,0 @@
-"""script code to generate test data"""
-import math
-
-if __name__ == "__main__":
-    for i in range(15):
-        sq_i = math.sqrt(i)
-        print(f"vtx{i:02d}, {(i % 2) == 0}, {(i % 3) == 0}, {i * i}, {sq_i}")
diff --git a/scripts/mesh2vec_times.png b/scripts/mesh2vec_times.png
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diff --git a/scripts/plot_execution_time.ipynb b/scripts/plot_execution_time.ipynb
deleted file mode 100644
index 9ed3505..0000000
--- a/scripts/plot_execution_time.ipynb
+++ /dev/null
@@ -1,125 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "05ed44a9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from mesh2vec.mesh2vec_cae import Mesh2VecCae\n",
-    "from pathlib import Path\n",
-    "from functools import wraps\n",
-    "import time\n",
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d4510390",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\"\"\"\n",
-    "Credit: https://dev.to/kcdchennai/python-decorator-to-measure-execution-time-54hk\n",
-    "\"\"\"\n",
-    "\n",
-    "\n",
-    "def timeit(func):\n",
-    "    @wraps(func)\n",
-    "    def timeit_wrapper(*args, **kwargs):\n",
-    "        # time.perf_counter() more accurate than time.time()\n",
-    "        start_time = time.perf_counter()\n",
-    "        result = func(*args, **kwargs)\n",
-    "        end_time = time.perf_counter()\n",
-    "        total_time = end_time - start_time\n",
-    "        # result of construction irrelevant, we just want the elapsed time\n",
-    "        return total_time\n",
-    "    return timeit_wrapper\n",
-    "\n",
-    "\n",
-    "@timeit\n",
-    "def measure_from_ansa(distance):\n",
-    "    \"\"\"\n",
-    "    Collect time it takes to construct vector\n",
-    "    \"\"\"\n",
-    "    m2v = Mesh2VecCae.from_ansa_shell(\n",
-    "        distance,\n",
-    "        Path(\"../data/hat/Hatprofile.k\"),\n",
-    "        json_mesh_file=Path(\"../data/hat/cached_hat_key.json\")\n",
-    "    )\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "63d7ce86",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "plot_dict = dict()\n",
-    "\n",
-    "for i in range(1, 41):\n",
-    "    time_elapsed = measure_from_ansa(i)\n",
-    "    plot_dict.update({str(i): time_elapsed})"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d9fcead0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "plot_dict"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d5bffb97",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "plt.figure(figsize=(12, 12))\n",
-    "plt.plot(plot_dict.keys(), plot_dict.values())\n",
-    "plt.xlabel(\"neighbors\")\n",
-    "plt.ylabel(\"construction time\")\n",
-    "\n",
-    "plt.savefig('mesh2vec_times.png')\n",
-    "\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4c71e44b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.12"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/scripts/profile_stats.txt b/scripts/profile_stats.txt
deleted file mode 100644
index e0206b0..0000000
--- a/scripts/profile_stats.txt
+++ /dev/null
@@ -1,726 +0,0 @@
-         1107221 function calls (1078620 primitive calls) in 47.052 seconds
-
-   Ordered by: cumulative time
-
-   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
-        2    0.000    0.000   47.293   23.646 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/IPython/core/interactiveshell.py:3490(run_code)
-        2    0.000    0.000   47.292   23.646 {built-in method builtins.exec}
-        1    0.004    0.004   47.137   47.137 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:121(from_ansa_shell)
-        1    0.044    0.044   46.760   46.760 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:32(__init__)
-        1    0.095    0.095   46.637   46.637 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_base.py:34(__init__)
-        1    2.928    2.928   46.387   46.387 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/helpers.py:8(calc_adjacencies)
-       24    0.000    0.000   19.785    0.824 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:620(__matmul__)
-       24    0.000    0.000   19.785    0.824 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:505(_mul_dispatch)
-       24    0.001    0.000   19.784    0.824 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:506(_mul_sparse_matrix)
-      209   19.751    0.095   19.751    0.095 {built-in method numpy.array}
-       24   13.078    0.545   13.078    0.545 {built-in method scipy.sparse._sparsetools.csr_matmat}
-       24    6.696    0.279    6.696    0.279 {built-in method scipy.sparse._sparsetools.csr_matmat_maxnnz}
-       25    0.000    0.000    3.517    0.141 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_base.py:477(__sub__)
-       25    0.004    0.000    3.516    0.141 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:361(_sub_sparse)
-       25    0.001    0.000    3.512    0.140 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:1237(_binopt)
-       25    3.306    0.132    3.306    0.132 {built-in method scipy.sparse._sparsetools.csr_minus_csr}
-        5    0.000    0.000    0.415    0.083 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/numpy/lib/arraysetops.py:138(unique)
-        5    0.008    0.002    0.403    0.081 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/numpy/lib/arraysetops.py:323(_unique1d)
-        5    0.390    0.078    0.390    0.078 {method 'sort' of 'numpy.ndarray' objects}
-  101/100    0.001    0.000    0.211    0.002 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:25(__init__)
-      101    0.001    0.000    0.203    0.002 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:135(check_format)
-      126    0.001    0.000    0.199    0.002 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/sparse/_compressed.py:1167(prune)
-       53    0.198    0.004    0.198    0.004 {method 'copy' of 'numpy.ndarray' objects}
-      252    0.000    0.000    0.197    0.001 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/scipy/_lib/_util.py:144(_prune_array)
-        1    0.000    0.000    0.194    0.194 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:669(_read_ansafile)
-        1    0.000    0.000    0.183    0.183 /usr/lib/python3.10/json/__init__.py:299(loads)
-        1    0.000    0.000    0.183    0.183 /usr/lib/python3.10/json/decoder.py:332(decode)
-        1    0.183    0.183    0.183    0.183 /usr/lib/python3.10/json/decoder.py:343(raw_decode)
-        1    0.002    0.002    0.155    0.155 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh_features.py:223(from_ansa_json)
-        1    0.012    0.012    0.099    0.099 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh_features.py:235(<listcomp>)
-        1    0.047    0.047    0.059    0.059 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_cae.py:79(<dictcomp>)
-        1    0.016    0.016    0.057    0.057 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_exceptions.py:33(check_hyper_edges)
-        1    0.015    0.015    0.053    0.053 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_exceptions.py:52(check_vtx_ids)
-    28553    0.017    0.000    0.049    0.000 {built-in method builtins.all}
-    28536    0.017    0.000    0.039    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_base.py:81(<genexpr>)
-   555553    0.030    0.000    0.030    0.000 {method 'append' of 'list' objects}
-   140377    0.021    0.000    0.027    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_exceptions.py:42(<genexpr>)
-    28535    0.022    0.000    0.022    0.000 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/mesh2vec/mesh2vec_base.py:84(<listcomp>)
-        6    0.000    0.000    0.017    0.003 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/frame.py:609(__init__)
-        4    0.001    0.000    0.017    0.004 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/internals/construction.py:423(dict_to_mgr)
- 28599/64    0.007    0.000    0.016    0.000 {built-in method builtins.max}
-       14    0.001    0.000    0.015    0.001 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/construction.py:493(sanitize_array)
-        4    0.000    0.000    0.014    0.004 /home/soeren/mesh2vec/.venv/lib/python3.10/site-packages/pandas/core/internals/construction.py:100(arrays_to_mgr)
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diff --git a/tests/test_mesh2vec_base.py b/tests/test_mesh2vec_base.py
index c40f9a6..4a030a5 100644
--- a/tests/test_mesh2vec_base.py
+++ b/tests/test_mesh2vec_base.py
@@ -16,6 +16,26 @@
     FeatureDoesNotExistException,
 )
 
+from mesh2vec.helpers import (
+    MatMulAdjacency,
+    BFSAdjacency,
+    BFSNumba,
+    PurePythonBFS,
+    PurePythonDFS,
+    DFSNumba,
+    MatMulAdjacencySmart,
+)
+
+
+strategies = [
+    MatMulAdjacency,
+    BFSAdjacency,
+    BFSNumba,
+    PurePythonBFS,
+    PurePythonDFS,
+    DFSNumba,
+    MatMulAdjacencySmart,
+]
 
 # pylint: disable=protected-access
 def _csr_equal(csr_a: csr_matrix, csr_b: csr_matrix) -> bool:
@@ -32,10 +52,7 @@ def test_init() -> None:
     hg = Mesh2VecBase(3, edges)
     assert hg._distance == 3
     assert "y" in hg._vtx_ids_to_idx.keys()
-    assert _csr_equal(hg._adjacency_matrix_powers[2], hg._adjacency_matrix_powers[1])
-    assert hg._adjacency_matrix_powers[3][0, 1]  # a->b
-    assert hg._adjacency_matrix_powers[3][0, 2]  # a->c
-    assert not hg._adjacency_matrix_powers[3][0, 3]  # a->x
+    assert set(hg._neighborhoods[1][0]) == {1, 2}  # a->b,c
 
 
 def test_invalid_hyperedges() -> None:
@@ -71,14 +88,6 @@ def test_from_txt_file() -> None:
     assert hg._distance == 3
     assert "vtx02" in hg._vtx_ids_to_idx.keys()
 
-    assert not _csr_equal(hg._adjacency_matrix_powers[2], hg._adjacency_matrix_powers[1])
-
-    assert _csr_a_gte_b(hg._adjacency_matrix_powers[2], hg._adjacency_matrix_powers[1])
-    assert _csr_equal(
-        hg._adjacency_matrix_powers_exclusive[3],
-        hg._adjacency_matrix_powers[3] - hg._adjacency_matrix_powers[2],
-    )
-
 
 def test_from_csv_file() -> None:
     """test import of csv file creates a consistent hypergraph"""
@@ -86,7 +95,7 @@ def test_from_csv_file() -> None:
 
     # write pair-wise connectivity to csv
     connections = []
-    connectivity_list = [x[:].indices for x in hg1._adjacency_matrix_powers[1]]
+    connectivity_list = [x for x in hg1._neighborhoods[1]]
     for vtx_a, vtx_a_neigbors in enumerate(connectivity_list):
         for vtx_b in vtx_a_neigbors:
             connections.append([hg1._vtx_idx_to_ids[vtx_a], hg1._vtx_idx_to_ids[vtx_b]])
@@ -98,9 +107,8 @@ def test_from_csv_file() -> None:
 
     # adj_mat must be equal
     for i in range(1, 3 + 1):
-        assert all(
-            hg2._adjacency_matrix_powers[i].indices == hg1._adjacency_matrix_powers[i].indices
-        )
+        for j in range(13):
+            assert all(hg2._neighborhoods[i][j] == hg1._neighborhoods[i][j])
 
     # hyper edges of hg1 that are not fully contained in larger other hyper edge form a clique
     # and should be contained in hyper edges of hg2
@@ -119,10 +127,11 @@ def test_from_csv_file() -> None:
             assert sorted(hyper_edge) in sorted_hg2_hyper_edges
 
 
-def test_get_nbh() -> None:
+@pytest.mark.parametrize("strategy", strategies)
+def test_get_nbh(strategy) -> None:
     """test get_nbh"""
     edges = {"first": ["a", "b", "c"], "second": ["x", "y"], "third": ["x", "a"]}
-    hg = Mesh2VecBase(3, edges)
+    hg = Mesh2VecBase(3, edges, calc_strategy=strategy)
     assert {"b"} == set(hg.get_nbh("b", 0))
     assert {"a", "c"} == set(hg.get_nbh("b", 1))
     assert {"x"} == set(hg.get_nbh("y", 1))
@@ -264,10 +273,11 @@ def test_aggregates_raise_feature_not_available() -> None:
         _ = hg.aggregate_categorical("f_not_exist", 1)
 
 
-def test_aggregate_simple() -> None:
+@pytest.mark.parametrize("strategy", strategies)
+def test_aggregate_simple(strategy) -> None:
     """test aggregation with simple graph"""
     edges = {"first": ["a", "b", "c"], "second": ["x", "y"]}
-    hg = Mesh2VecBase(3, edges)
+    hg = Mesh2VecBase(3, edges, calc_strategy=strategy)
     df1 = pd.DataFrame({"vtx_id": ["a", "b", "c", "x", "y"], "f1": [2, 4, 8, 16, 32]})
     hg.add_features_from_dataframe(df1)
     name = hg.aggregate("f1", 1, np.mean)
@@ -284,17 +294,13 @@ def test_aggregate_simple_two_dists() -> None:
     hg = Mesh2VecBase(3, edges)
     df1 = pd.DataFrame({"vtx_id": ["a", "b", "c", "x", "y"], "f1": [2, 4, 8, 16, 32]})
     hg.add_features_from_dataframe(df1)
-    names = hg.aggregate("f1", [1, 1], np.mean)
+    names = hg.aggregate("f1", [1, 2], np.mean)
     assert hg._aggregated_features[names[0]].iloc[0] == np.mean([4, 8])
     assert hg._aggregated_features[names[0]].iloc[1] == np.mean([2, 8])
     assert hg._aggregated_features[names[0]].iloc[2] == np.mean([2, 4])
     assert hg._aggregated_features[names[0]].iloc[3] == np.mean([32])
     assert hg._aggregated_features[names[0]].iloc[4] == np.mean([16])
-    assert hg._aggregated_features[names[1]].iloc[0] == np.mean([4, 8])
-    assert hg._aggregated_features[names[1]].iloc[1] == np.mean([2, 8])
-    assert hg._aggregated_features[names[1]].iloc[2] == np.mean([2, 4])
-    assert hg._aggregated_features[names[1]].iloc[3] == np.mean([32])
-    assert hg._aggregated_features[names[1]].iloc[4] == np.mean([16])
+    assert hg._aggregated_features[names[1]].iloc[0] == 0
 
 
 def test_aggregate_complex() -> None:
diff --git a/tests/test_mesh2vec_cae.py b/tests/test_mesh2vec_cae.py
index 5ce0567..c2be107 100644
--- a/tests/test_mesh2vec_cae.py
+++ b/tests/test_mesh2vec_cae.py
@@ -2,6 +2,7 @@
 from pathlib import Path
 from functools import partial
 
+from tempfile import TemporaryDirectory
 import numpy as np
 import pandas as pd
 from scipy.sparse import csr_matrix
@@ -93,6 +94,36 @@ def test_shell_from_ansa() -> None:
     assert len(m2v.vtx_ids()) == 6400
 
 
+def test_from_keyfile_shell() -> None:
+    """test ansa shell is loaded"""
+    m2v = Mesh2VecCae.from_keyfile_shell(
+        4,
+        Path("data/hat/Hatprofile.k"),
+    )
+
+    m2v_ansa = Mesh2VecCae.from_ansa_shell(
+        4,
+        Path("data/hat/Hatprofile.k"),
+        json_mesh_file=Path("data/hat/cached_hat_key.json"),
+    )
+    all(
+        [
+            sorted(m2v._hyper_edges[k]) == sorted(m2v_ansa._hyper_edges[k])
+            for k in m2v._hyper_edges.keys()
+        ]
+    )
+    set(m2v.vtx_ids()) == set(m2v_ansa.vtx_ids())
+
+
+def test_patch2vec() -> None:
+    m2v = Mesh2VecCae.from_keyfile_shell(
+        4,
+        Path("/home/markus/Downloads/Patch2.key"),
+    )
+    name = m2v.add_features_from_ansa(["num_border"])[0]
+    name = m2v.aggregate(name, 2, np.mean)
+
+
 def test_shell_from_ansa_partid() -> None:
     """test ansa shell is loaded with and without partid"""
     m2v1 = Mesh2VecCae.from_ansa_shell(
@@ -171,6 +202,22 @@ def test_add_feature_from_d3plot_accumulated() -> None:
         )
 
 
+def test_save_load() -> None:
+    """test saving and loading works"""
+    m2v = Mesh2VecCae.from_d3plot_shell(3, Path("data/hat/HAT.d3plot"))
+    d3plot_data = D3plot(Path("data/hat/HAT.d3plot").as_posix())
+    axis_0_sum = partial(np.sum, axis=0)
+    axis_0_sum.__name__ = "axis0sum"  # type: ignore
+    for feature in features_reduced:
+        m2v.add_feature_from_d3plot(
+            feature, d3plot_data, timestep=1, shell_layer=axis_0_sum, history_var_index=1
+        )
+    with TemporaryDirectory() as tmpdir:
+        m2v.save(Path(tmpdir) / "test.h5")
+        m2v_loaded = Mesh2VecCae.load(Path(tmpdir) / "test.h5")
+        assert m2v_loaded._features.equals(m2v._features)
+
+
 def test_add_feature_from_d3plot_to_ansa_shell() -> None:
     """test adding features from ansa works"""
     ansafile = Path("data/hat/Hatprofile.k")

From b6f1fbf830438b90653a7003d32a141363c7517c Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Thu, 30 Nov 2023 08:49:13 +0100
Subject: [PATCH 17/27] add: numba and igraph

---
 poetry.lock | 35 ++++++++++++++++++++++++++++++++++-
 1 file changed, 34 insertions(+), 1 deletion(-)

diff --git a/poetry.lock b/poetry.lock
index 31fbbe7..b6b1856 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1753,6 +1753,39 @@ files = [
 six = "*"
 tornado = {version = "*", markers = "python_version > \"2.7\""}
 
+[[package]]
+name = "llvmlite"
+version = "0.41.1"
+description = "lightweight wrapper around basic LLVM functionality"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "llvmlite-0.41.1-cp38-cp38-win32.whl", hash = "sha256:2d92c51e6e9394d503033ffe3292f5bef1566ab73029ec853861f60ad5c925d0"},
+    {file = "llvmlite-0.41.1-cp38-cp38-win_amd64.whl", hash = "sha256:df75594e5a4702b032684d5481db3af990b69c249ccb1d32687b8501f0689432"},
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+    {file = "llvmlite-0.41.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:bf14aa0eb22b58c231243dccf7e7f42f7beec48970f2549b3a6acc737d1a4ba4"},
+    {file = "llvmlite-0.41.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:92c32356f669e036eb01016e883b22add883c60739bc1ebee3a1cc0249a50828"},
+    {file = "llvmlite-0.41.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:24091a6b31242bcdd56ae2dbea40007f462260bc9bdf947953acc39dffd54f8f"},
+    {file = "llvmlite-0.41.1-cp39-cp39-win32.whl", hash = "sha256:880cb57ca49e862e1cd077104375b9d1dfdc0622596dfa22105f470d7bacb309"},
+    {file = "llvmlite-0.41.1-cp39-cp39-win_amd64.whl", hash = "sha256:92f093986ab92e71c9ffe334c002f96defc7986efda18397d0f08534f3ebdc4d"},
+    {file = "llvmlite-0.41.1.tar.gz", hash = "sha256:f19f767a018e6ec89608e1f6b13348fa2fcde657151137cb64e56d48598a92db"},
+]
+
 [[package]]
 name = "loguru"
 version = "0.6.0"
@@ -4223,4 +4256,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8, <3.12"
-content-hash = "d0c50e7153f79c7126e6e17dc4cee88b7fc9eb2526622983f715af1d8e861ac2"
+content-hash = "616997f5becffd637b1e397f159135017fb3ff9eadbbef4685260f3dbbeb3c88"

From 9fa757a1e13be0b99d84c8a6fb9cd009a109ac33 Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Tue, 5 Dec 2023 10:24:53 +0100
Subject: [PATCH 18/27] cleanups

---
 docs/examples/plot_stress.py | 36 ++++++++++++++------------------
 mesh2vec/mesh2vec_base.py    | 14 ++++++-------
 mesh2vec/mesh2vec_cae.py     | 40 ++++++++++++++++++++----------------
 mesh2vec/mesh_features.py    |  8 +++++++-
 tests/test_mesh2vec_base.py  |  2 +-
 tests/test_mesh2vec_cae.py   | 39 +++++++++++++++++++----------------
 6 files changed, 73 insertions(+), 66 deletions(-)

diff --git a/docs/examples/plot_stress.py b/docs/examples/plot_stress.py
index 08bbc9d..e409db8 100644
--- a/docs/examples/plot_stress.py
+++ b/docs/examples/plot_stress.py
@@ -10,6 +10,9 @@
 from lasso.dyna import ArrayType
 from mesh2vec.mesh2vec_cae import Mesh2VecCae
 
+import os
+
+os.chdir(os.path.dirname(__file__))
 
 # %%
 # Load Shell from ANSA, simulation results from d3plot
@@ -19,37 +22,28 @@
     Path("../../data/hat/Hatprofile.k"),
     json_mesh_file=Path("../../data/hat/cached_hat_key.json"),
 )
-name = hg.add_feature_from_d3plot(
+
+
+def y_all_layers(v):
+    """get y stress component of all layers"""
+    return v[:, 1]
+
+
+fature_name = hg.add_feature_from_d3plot(
     ArrayType.element_shell_stress,
     Path("../../data/hat/HAT.d3plot"),
-    timestep=-1,
-    shell_layer=np.mean,
+    timestep=1,
+    shell_layer=y_all_layers,
 )
 
 
-# %%
-# Plot Feature locally
-# ------------------------
-hg.add_features_from_dataframe(
-    pd.DataFrame(
-        {
-            "vtx_id": hg.vtx_ids(),
-            "y-stress": [v for v in hg.features()[name]],
-        }
-    )
-)
-name = hg.aggregate("y-stress", 0, np.mean)
-fig = hg.get_visualization_plotly(str(name))
-fig.update_layout(title=name)
-fig
-
 # %%
 # Aggregate Feature and plot
 # ---------------------------
-name = hg.aggregate("y-stress", 1, np.mean)
+name = hg.aggregate(fature_name, 1, lambda x: np.mean(np.mean(x)))
 fig = hg.get_visualization_plotly(str(name))
 fig.update_layout(title=name)
-fig.show()
+fig
 
 
 # %%
diff --git a/mesh2vec/mesh2vec_base.py b/mesh2vec/mesh2vec_base.py
index 138aeb8..22b5e0b 100644
--- a/mesh2vec/mesh2vec_base.py
+++ b/mesh2vec/mesh2vec_base.py
@@ -228,7 +228,7 @@ def aggregate_categorical(
             feature_categories = np.unique(self._features[feature])
 
         for distance in dist_list:
-            values = self._collect_feature_values(feature, distance, default_value, aggr=np.array)
+            values = self._collect_feature_values(feature, distance, default_value, aggr=None)
 
             for category in feature_categories:
                 feature_name = f"{feature}-cat-{category}-{distance}"
@@ -406,16 +406,16 @@ def _collect_feature_values(
             return feature
 
         if ref_values is None:
-            try:  # fast: use nan_to_num over the whole array
+            if not aggr is None:  # fast: use nan_to_num over the whole array
                 return np.nan_to_num(
                     [aggr(feature[neighborhood]) for neighborhood in self._neighborhoods[dist]],
                     default_value,
                 ).tolist()
-            except ValueError:  # slow: use nan_to_num for each element (different dimensions)
-                return [
-                    np.nan_to_num(aggr(feature[neighborhood]), default_value)
-                    for neighborhood in self._neighborhoods[dist]
-                ]
+            # slow: use nan_to_num for each neighborhood (not aggregatted - different length)
+            return [
+                np.nan_to_num((feature[neighborhood]), default_value)
+                for neighborhood in self._neighborhoods[dist]
+            ]
 
         # compare to reference value is needed
         ref_values_list = ref_values.tolist()
diff --git a/mesh2vec/mesh2vec_cae.py b/mesh2vec/mesh2vec_cae.py
index c260306..9f00b0e 100644
--- a/mesh2vec/mesh2vec_cae.py
+++ b/mesh2vec/mesh2vec_cae.py
@@ -258,6 +258,7 @@ def add_features_from_ansa(
         ansa_executable: Optional[Path] = None,
         ansa_script: Optional[Path] = None,
         verbose: bool = False,
+        allow_addtional_ansa_features: bool = False,
     ) -> List[str]:
         """
         Add values derived or calculated from ANSA shell elements (currently restricted to
@@ -278,6 +279,8 @@ def add_features_from_ansa(
             * midpoint x,y,z
             * normal vector x,y,z (ansafile is required)
             * area (ansafile is required)
+            * custom features from your customized ansa_script (scalar values only,
+                allow_addtional_ansa_features must be True)
 
         Example:
             >>> from pathlib import Path
@@ -293,15 +296,19 @@ def add_features_from_ansa(
             >>> print(f'{m2v._features["warpage"][14]:.4f}')
             0.0188
         """
-        okay_ansa = ["aspect", "warpage", "normal", "area"]
+        # pylint: disable=too-many-locals
+        okay_ansa = ["aspect", "warpage", "normal", "area", "skew"]
         okay_inplace = ["num_border", "is_tria", "midpoint"]
 
         for feature in features:
             if not feature in okay_ansa + okay_inplace:
-                raise ValueError(
-                    f"Feature {feature} is unknown. "
-                    f"All features must be in {okay_ansa+okay_inplace}"
-                )
+                if not allow_addtional_ansa_features:
+                    okay_ansa.append(feature)
+                else:
+                    raise ValueError(
+                        f"Feature {feature} is unknown and allow_addtional_ansa_features is False"
+                        f"All features must be in {okay_ansa+okay_inplace}"
+                    )
 
         if ansa_executable is not None:
             os.environ["ANSA_EXECUTABLE"] = str(ansa_executable)
@@ -321,10 +328,7 @@ def _err_to_nan(elements: List[Dict[Any, Any]], name: str) -> np.ndarray:
             element_metrics = pd.DataFrame(
                 {
                     "vtx_id": mesh.element_uid.tolist(),
-                    "warpage": _err_to_nan(elements, "warpage"),
-                    "skew": _err_to_nan(elements, "skew"),
-                    "aspect": _err_to_nan(elements, "aspect"),
-                    "area": _err_to_nan(elements, "area"),
+                    **{k: _err_to_nan(elements, k) for k in okay_ansa if k != "normal"},
                     "normal": [e["normal"] for e in elements],
                 }
             )
@@ -438,11 +442,8 @@ def _get_d3plot_layer_array_names() -> List[str]:
                 ArrayType.element_shell_strain,
             ]:
                 if callable(shell_layer):
-                    new_feature = [
-                        v.tolist()
-                        for v in np.squeeze(d3plot_data.arrays[feature][timestep, :, :, :])
-                    ]
-                    new_feature = [shell_layer(x) for x in new_feature]
+                    new_feature = np.squeeze(d3plot_data.arrays[feature][timestep, :, :, :])
+                    new_feature = [shell_layer(x).tolist() for x in new_feature]
                 else:
                     new_feature = [
                         v.tolist()
@@ -632,7 +633,6 @@ def get_visualization_trimesh(self, feature: str) -> trimesh.Trimesh:
         Get a trimesh with face colored by feature values
         Use trimesh_mesh.show(smooth=False, flags={"cull": False}) to visualize.
         """
-        max_v = 1 / max(self._aggregated_features[feature])
 
         df = self._element_info.merge(self._aggregated_features[["vtx_id", feature]], on="vtx_id")
         assert len(df) == len(self._mesh.element_node_idxs)
@@ -644,14 +644,18 @@ def get_visualization_trimesh(self, feature: str) -> trimesh.Trimesh:
             element_node_idxs, feature_values
         )
 
+        omin = tri_features.min()
+        omax = tri_features.max()
+        tri_features_scaled = (tri_features - omin) / (omax - omin)
+
         trimeh_mesh = trimesh.Trimesh(
             vertices=self._mesh.point_coordinates / np.max(self._mesh.point_coordinates),
             faces=tri_faces,
         )
 
-        trimeh_mesh.visual.face_colors = [
-            [254 - 254 * x * max_v, 254 * x * max_v, 0, 254] for x in tri_features
-        ]
+        trimeh_mesh.visual.face_colors = np.array(
+            [np.array([254 - 254 * x, 254 * x, 0, 254]) for x in tri_features_scaled]
+        )
 
         return trimeh_mesh
 
diff --git a/mesh2vec/mesh_features.py b/mesh2vec/mesh_features.py
index 086b502..c83ebe0 100644
--- a/mesh2vec/mesh_features.py
+++ b/mesh2vec/mesh_features.py
@@ -238,7 +238,13 @@ def from_ansa_json(elements: List[Any], nodes: List[Any]) -> "CaeShellMesh":
 
     @staticmethod
     def from_keyfile(keyfile: str) -> "CaeShellMesh":
-        """create CaeShellMesh from keyfile"""
+        """create CaeShellMesh from keyfile
+            Example:
+        >>> from mesh2vec.mesh_features import CaeShellMesh
+        >>> mesh = CaeShellMesh.from_keyfile("data/hat/Hatprofile.k")
+        >>> print(mesh.point_coordinates.shape)
+        (6400, 3)
+        """
 
         def parse_contents(file_contents):
             lines = file_contents.split("\n")
diff --git a/tests/test_mesh2vec_base.py b/tests/test_mesh2vec_base.py
index 4a030a5..fbfdf79 100644
--- a/tests/test_mesh2vec_base.py
+++ b/tests/test_mesh2vec_base.py
@@ -95,7 +95,7 @@ def test_from_csv_file() -> None:
 
     # write pair-wise connectivity to csv
     connections = []
-    connectivity_list = [x for x in hg1._neighborhoods[1]]
+    connectivity_list = hg1._neighborhoods[1].copy()
     for vtx_a, vtx_a_neigbors in enumerate(connectivity_list):
         for vtx_b in vtx_a_neigbors:
             connections.append([hg1._vtx_idx_to_ids[vtx_a], hg1._vtx_idx_to_ids[vtx_b]])
diff --git a/tests/test_mesh2vec_cae.py b/tests/test_mesh2vec_cae.py
index c2be107..6fc27ce 100644
--- a/tests/test_mesh2vec_cae.py
+++ b/tests/test_mesh2vec_cae.py
@@ -106,22 +106,8 @@ def test_from_keyfile_shell() -> None:
         Path("data/hat/Hatprofile.k"),
         json_mesh_file=Path("data/hat/cached_hat_key.json"),
     )
-    all(
-        [
-            sorted(m2v._hyper_edges[k]) == sorted(m2v_ansa._hyper_edges[k])
-            for k in m2v._hyper_edges.keys()
-        ]
-    )
-    set(m2v.vtx_ids()) == set(m2v_ansa.vtx_ids())
-
-
-def test_patch2vec() -> None:
-    m2v = Mesh2VecCae.from_keyfile_shell(
-        4,
-        Path("/home/markus/Downloads/Patch2.key"),
-    )
-    name = m2v.add_features_from_ansa(["num_border"])[0]
-    name = m2v.aggregate(name, 2, np.mean)
+    all(sorted(v) == sorted(m2v_ansa._hyper_edges[k]) for k, v in m2v._hyper_edges.items())
+    assert set(m2v.vtx_ids()) == set(m2v_ansa.vtx_ids())
 
 
 def test_shell_from_ansa_partid() -> None:
@@ -228,12 +214,29 @@ def test_add_feature_from_d3plot_to_ansa_shell() -> None:
         ansafile,
         json_mesh_file=json_mesh_file,
     )
-    m2v.add_feature_from_d3plot(
+
+    m2v.add_features_from_ansa(
+        ["normal"],
+        Path("data/hat/Hatprofile.k"),
+        json_mesh_file=Path("data/hat/cached_hat_key.json"),
+    )
+    name = m2v.aggregate_angle_diff(2)
+    assert isinstance(name, str)
+    assert m2v._aggregated_features[name][4] == pytest.approx(0.41053, 0.001)
+    # m2v.get_visualization_trimesh(name).show()
+
+    axis_0_sum = partial(np.sum, axis=0)
+    axis_0_sum.__name__ = "axis0sum"  # type: ignore
+
+    name_strain = m2v.add_feature_from_d3plot(
         ArrayType.element_shell_strain,
         Path("data/hat/HAT.d3plot"),
         timestep=1,
-        shell_layer=0,
+        shell_layer=axis_0_sum,
     )
+    print(m2v._features[name_strain].shape)
+    name = m2v.aggregate(name_strain, 1, lambda x: np.mean(np.mean(x)))
+    print(m2v._aggregated_features[name].shape)
 
 
 def test_aggregate_angle_diff() -> None:

From 9594db7a6e3ad8c52b3cf2b292019a2d736a208c Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Tue, 5 Dec 2023 10:53:24 +0100
Subject: [PATCH 19/27] +docs

---
 docs/examples/plot_stress.py | 13 +++++--------
 mesh2vec/mesh2vec_base.py    | 14 ++++++++++++++
 mesh2vec/mesh2vec_cae.py     | 29 ++++++++++++++++++++++++++++-
 3 files changed, 47 insertions(+), 9 deletions(-)

diff --git a/docs/examples/plot_stress.py b/docs/examples/plot_stress.py
index e409db8..0b8d3b8 100644
--- a/docs/examples/plot_stress.py
+++ b/docs/examples/plot_stress.py
@@ -10,9 +10,6 @@
 from lasso.dyna import ArrayType
 from mesh2vec.mesh2vec_cae import Mesh2VecCae
 
-import os
-
-os.chdir(os.path.dirname(__file__))
 
 # %%
 # Load Shell from ANSA, simulation results from d3plot
@@ -24,16 +21,16 @@
 )
 
 
-def y_all_layers(v):
-    """get y stress component of all layers"""
-    return v[:, 1]
+def mean_over_components_all_layers(v):
+    """get mean over all components and all layers"""
+    return np.mean(v, axis=-1)
 
 
 fature_name = hg.add_feature_from_d3plot(
     ArrayType.element_shell_stress,
     Path("../../data/hat/HAT.d3plot"),
-    timestep=1,
-    shell_layer=y_all_layers,
+    timestep=-1,
+    shell_layer=mean_over_components_all_layers,
 )
 
 
diff --git a/mesh2vec/mesh2vec_base.py b/mesh2vec/mesh2vec_base.py
index 22b5e0b..df29472 100644
--- a/mesh2vec/mesh2vec_base.py
+++ b/mesh2vec/mesh2vec_base.py
@@ -97,6 +97,13 @@ def __init__(
     def save(self, path: Path):
         """
         Save the Mesh2Vec object to a file with joblib
+        Args:
+            path: path to the file
+        Example:
+            >>> from pathlib import Path
+            >>> from mesh2vec.mesh2vec_base import Mesh2VecBase
+            >>> hg = Mesh2VecBase(3, {"first": ["a", "b", "c"], "second": ["x", "y"]})
+            >>> hg.save(Path("/tmp/hg.joblib"))
         """
         joblib.dump(self, path)
 
@@ -104,6 +111,13 @@ def save(self, path: Path):
     def load(path: Path):
         """
         Load the Mesh2Vec object from a file with joblib
+        Args:
+            path: path to the file
+        Example:
+            >>> from pathlib import Path
+            >>> from mesh2vec.mesh2vec_base import Mesh2VecBase
+            >>> hg.save(Path("/tmp/hg.joblib"))
+            >>> hg = Mesh2VecBase.load(Path("/tmp/hg.joblib"))
         """
         return joblib.load(path)
 
diff --git a/mesh2vec/mesh2vec_cae.py b/mesh2vec/mesh2vec_cae.py
index 9f00b0e..e41424b 100644
--- a/mesh2vec/mesh2vec_cae.py
+++ b/mesh2vec/mesh2vec_cae.py
@@ -230,6 +230,15 @@ def from_keyfile_shell(distance: int, keyfile: Path) -> "Mesh2VecCae":
         """
         Read the given keyfile and use the shell elements to generate a hypergraph, using mesh
         nodes as hyperedges, and adjacent elements as hypervertices.
+        Args:
+            distance: the maximum distance for neighborhood generation and feature aggregation
+            keyfile: path to keyfile
+        Example:
+            >>> from pathlib import Path
+            >>> from mesh2vec.mesh2vec_cae import Mesh2VecCae
+            >>> m2v = Mesh2VecCae.from_keyfile_shell(4, Path("data/hat/Hatprofile.k"))
+            >>> len(m2v._hyper_edges)
+            6666
         """
         mesh = CaeShellMesh.from_keyfile(keyfile)
         element_info = pd.DataFrame({"element_id": mesh.element_ids})
@@ -293,6 +302,7 @@ def add_features_from_ansa(
             ...    ["aspect", "warpage"],
             ...    Path("data/hat/Hatprofile.k"),
             ...    json_mesh_file=Path("data/hat/cached_hat_key.json"))
+            ['aspect', 'warpage']
             >>> print(f'{m2v._features["warpage"][14]:.4f}')
             0.0188
         """
@@ -508,7 +518,7 @@ def add_feature_from_d3plot(
             feature: name of the feature to add (a shell_array name of lasso.dyna.ArrayType)
             d3plot: path to d3plot file or loaded d3plot data
             timestep: timestep to extract (required for time dependend arrays, ignored otherwise)
-            shell_layer: integration point index or function to accumulate over all integration
+            shell_layer: integration point index or callabe to accumulate over all integration
                 points (required for layerd arrays, ignored otherwise)
             history_var_index: index of the history variable to extract (required for
                 element_shell_history_vars, ignored otherwise)
@@ -523,8 +533,24 @@ def add_feature_from_d3plot(
             ...    ArrayType.element_shell_strain,
             ...    Path("data/hat/HAT.d3plot"),
             ...    timestep=1, shell_layer=0)
+            >>> # print eps_xx, eps_yy, eps_zz, eps_xy, eps_yz, eps_xz of layer 0
             >>> print([f'{v:.4f}' for v in m2v.features()[name][42]])
             ['0.0010', '-0.0003', '-0.0000', '-0.0012', '-0.0000', '-0.0003']
+
+        Example:
+            >>> from pathlib import Path
+            >>> from lasso.dyna import ArrayType
+            >>> from mesh2vec.mesh2vec_cae import Mesh2VecCae
+            >>> m2v =  Mesh2VecCae.from_d3plot_shell(3, Path("data/hat/HAT.d3plot"))
+            >>> def mean_over_components_all_layers(v):
+            ...    return np.mean(v, axis=-1)
+            >>> name = m2v.add_feature_from_d3plot(
+            ...    ArrayType.element_shell_strain,
+            ...    Path("data/hat/HAT.d3plot"),
+            ...    timestep=-1, shell_layer=mean_over_components_all_layers)
+            >>> # print mean of all components for each layer (0,1)
+            >>> print([f'{v:.4f}' for v in m2v.features()[name][42]])
+            ['0.0002', '0.0001']
         """
 
         d3plot_data = D3plot(d3plot.as_posix()) if not isinstance(d3plot, D3plot) else d3plot
@@ -588,6 +614,7 @@ def aggregate_angle_diff(
             ...    ["normal"],
             ...    Path("data/hat/Hatprofile.k"),
             ...    json_mesh_file=Path("data/hat/cached_hat_key.json"))
+            ['normal']
             >>> name = m2v.aggregate_angle_diff(2)
             >>> print(f'{ m2v._aggregated_features[name][14]:.4f}')
             0.6275

From 653e1d192997421be3d2ae28080f543abed7da7c Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Tue, 5 Dec 2023 10:57:13 +0100
Subject: [PATCH 20/27] script folder

---
 scripts/gemerate_test_data.py | 7 +++++++
 1 file changed, 7 insertions(+)
 create mode 100644 scripts/gemerate_test_data.py

diff --git a/scripts/gemerate_test_data.py b/scripts/gemerate_test_data.py
new file mode 100644
index 0000000..b762d87
--- /dev/null
+++ b/scripts/gemerate_test_data.py
@@ -0,0 +1,7 @@
+"""script code to generate test data"""
+import math
+
+if __name__ == "__main__":
+    for i in range(15):
+        sq_i = math.sqrt(i)
+        print(f"vtx{i:02d}, {(i % 2) == 0}, {(i % 3) == 0}, {i * i}, {sq_i}")
\ No newline at end of file

From 0b979f7cdb710c36cb957e36f5712f93a256e065 Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Tue, 5 Dec 2023 11:02:36 +0100
Subject: [PATCH 21/27] formatting

---
 scripts/gemerate_test_data.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/scripts/gemerate_test_data.py b/scripts/gemerate_test_data.py
index b762d87..636d935 100644
--- a/scripts/gemerate_test_data.py
+++ b/scripts/gemerate_test_data.py
@@ -4,4 +4,4 @@
 if __name__ == "__main__":
     for i in range(15):
         sq_i = math.sqrt(i)
-        print(f"vtx{i:02d}, {(i % 2) == 0}, {(i % 3) == 0}, {i * i}, {sq_i}")
\ No newline at end of file
+        print(f"vtx{i:02d}, {(i % 2) == 0}, {(i % 3) == 0}, {i * i}, {sq_i}")

From 4a29bc21436354194f858e15695259ed0f75d009 Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Tue, 5 Dec 2023 11:04:10 +0100
Subject: [PATCH 22/27] doctest back

---
 .github/workflows/workflow.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/workflow.yml b/.github/workflows/workflow.yml
index 99f5ad8..ca117b3 100644
--- a/.github/workflows/workflow.yml
+++ b/.github/workflows/workflow.yml
@@ -95,7 +95,7 @@ jobs:
         python-version: ${{ matrix.python-version }}
     - name: test
       run: |
-        poetry run sphinx-build docs/source build/documentation/ -W -b html # autodocs contain tests && poetry run sphinx-build docs/source build/documentation/ -W -b doctest
+        poetry run sphinx-build docs/source build/documentation/ -W -b html && poetry run sphinx-build docs/source build/documentation/ -W -b doctest
 
   unit-tests:
     needs: [prepare-linux, prepare-win]

From 5bf058a21542fe8e0aa09f943a440809a3dfaf24 Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Tue, 5 Dec 2023 11:05:36 +0100
Subject: [PATCH 23/27] authors updated

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 2cedb6d..8924fbf 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "mesh2vec"
 version = "0.0.2"
-authors = ["Markus Stoll <markus.stoll@renumics.com>"]
+authors = ["Renumics GmbH <info@renumics.com>"]
 packages = [
     { include = "mesh2vec" }
 ]

From 94e27b8f89e220d5466b8d0088eb42b3d027d3b6 Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Tue, 5 Dec 2023 11:27:38 +0100
Subject: [PATCH 24/27] evaluation 1.0.3

---
 scripts/evaluation_1.0.3.py | 100 ++++++++++++++++++++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 scripts/evaluation_1.0.3.py

diff --git a/scripts/evaluation_1.0.3.py b/scripts/evaluation_1.0.3.py
new file mode 100644
index 0000000..4dea99a
--- /dev/null
+++ b/scripts/evaluation_1.0.3.py
@@ -0,0 +1,100 @@
+from mesh2vec.mesh2vec_cae import Mesh2VecCae
+from pathlib import Path
+import time
+import numpy as np
+import tracemalloc
+
+DIST = 30
+PATH = "data/hat/cached_hat_key.json"
+PATH = "/home/markus/Downloads/test_data_internal/p210.key_tmp.json"
+
+
+res = None
+PROFILE_MEM = True
+
+### create neighbors
+start = time.time()
+if PROFILE_MEM:
+    tracemalloc.start()
+
+a = Mesh2VecCae.from_ansa_shell(
+    DIST,
+    Path("data/hat/Hatprofile.k"),
+    json_mesh_file=Path(PATH),
+)
+print(f"   calc_adjacencies:", time.time() - start)
+if PROFILE_MEM:
+    current, peak = tracemalloc.get_traced_memory()
+    print(f"Current memory usage is {current / 10**6}MB; Peak was {peak / 10**6}MB")
+    tracemalloc.stop()
+
+if PROFILE_MEM:
+    tracemalloc.start()
+start = time.time()
+
+### load features from ansa
+a.add_features_from_ansa(
+    ["warpage", "aspect", "normal", "area"],
+    Path("data/hat/Hatprofile.k"),
+    json_mesh_file=Path(PATH)
+)
+print(f"   add_features_from_ansa:", time.time() - start)
+if PROFILE_MEM:
+    current, peak = tracemalloc.get_traced_memory()
+    print(f"Current memory usage is {current / 10**6}MB; Peak was {peak / 10**6}MB")
+    tracemalloc.stop()
+
+
+### aggregate single feature for 1-30 neighbors
+if PROFILE_MEM:
+    tracemalloc.start()
+start = time.time()
+
+a.aggregate("warpage", range(DIST), np.mean)
+print(f"   1 aggregate:", time.time() - start)
+if PROFILE_MEM:
+    current, peak = tracemalloc.get_traced_memory()
+    print(f"Current memory usage is {current / 10**6}MB; Peak was {peak / 10**6}MB")
+    tracemalloc.stop()
+
+### aggregate two features for 1-30 neighbors
+if PROFILE_MEM:
+    tracemalloc.start()
+start = time.time()
+
+a.aggregate("warpage", range(DIST), np.mean)
+a.aggregate("aspect", range(DIST), np.mean)
+print(f"   2 aggregate:", time.time() - start)
+if PROFILE_MEM:
+    current, peak = tracemalloc.get_traced_memory()
+    print(f"Current memory usage is {current / 10**6}MB; Peak was {peak / 10**6}MB")
+    tracemalloc.stop()
+
+### aggregate_angle_diff 
+if PROFILE_MEM:
+    tracemalloc.start()
+start = time.time()
+
+a.aggregate_angle_diff(range(DIST), np.mean)
+
+print(f"   aggregate_angle_diff:", time.time() - start)
+if PROFILE_MEM:
+    current, peak = tracemalloc.get_traced_memory()
+    print(f"Current memory usage is {current / 10**6}MB; Peak was {peak / 10**6}MB")
+    tracemalloc.stop()
+
+
+
+# calc_adjacencies: 41.01193881034851
+# add_features_from_ansa: 0.21686553955078125
+# 1 aggregate: 27.74431562423706
+# 2 aggregate: 55.777445554733276
+# aggregate_angle_diff: 427.60096430778503
+
+
+#    calc_adjacencies: 40.979246377944946
+# Current memory usage is 11752.521761MB; Peak was 13671.121043MB
+#    add_features_from_ansa: 0.5271070003509521
+# Current memory usage is 5.953076MB; Peak was 53.423552MB
+#    1 aggregate: 53.40042471885681
+# Current memory usage is 6.9341MB; Peak was 103.818146MB
\ No newline at end of file

From b10af9202690e3327688b9148461667a024da5b1 Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Tue, 5 Dec 2023 11:34:40 +0100
Subject: [PATCH 25/27] test fixes

---
 docs/examples/plot_stress.py | 1 -
 mesh2vec/mesh2vec_base.py    | 6 +++---
 2 files changed, 3 insertions(+), 4 deletions(-)

diff --git a/docs/examples/plot_stress.py b/docs/examples/plot_stress.py
index 0b8d3b8..a4d2279 100644
--- a/docs/examples/plot_stress.py
+++ b/docs/examples/plot_stress.py
@@ -6,7 +6,6 @@
 # pylint: disable=pointless-statement
 from pathlib import Path
 import numpy as np
-import pandas as pd
 from lasso.dyna import ArrayType
 from mesh2vec.mesh2vec_cae import Mesh2VecCae
 
diff --git a/mesh2vec/mesh2vec_base.py b/mesh2vec/mesh2vec_base.py
index df29472..4bbda33 100644
--- a/mesh2vec/mesh2vec_base.py
+++ b/mesh2vec/mesh2vec_base.py
@@ -103,7 +103,7 @@ def save(self, path: Path):
             >>> from pathlib import Path
             >>> from mesh2vec.mesh2vec_base import Mesh2VecBase
             >>> hg = Mesh2VecBase(3, {"first": ["a", "b", "c"], "second": ["x", "y"]})
-            >>> hg.save(Path("/tmp/hg.joblib"))
+            >>> hg.save(Path("data/temp_hg.joblib"))
         """
         joblib.dump(self, path)
 
@@ -116,8 +116,8 @@ def load(path: Path):
         Example:
             >>> from pathlib import Path
             >>> from mesh2vec.mesh2vec_base import Mesh2VecBase
-            >>> hg.save(Path("/tmp/hg.joblib"))
-            >>> hg = Mesh2VecBase.load(Path("/tmp/hg.joblib"))
+            >>> hg.save(Path("data/temp_hg.joblib"))
+            >>> hg = Mesh2VecBase.load(Path("data/temp_hg.joblib"))
         """
         return joblib.load(path)
 

From 694a3cd063e84de429ccb282e2bd155f4cb46ea4 Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Tue, 5 Dec 2023 11:35:55 +0100
Subject: [PATCH 26/27] dont lint scripts

---
 .github/workflows/workflow.yml | 2 +-
 .gitignore                     | 3 ++-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/workflow.yml b/.github/workflows/workflow.yml
index ca117b3..2c21e89 100644
--- a/.github/workflows/workflow.yml
+++ b/.github/workflows/workflow.yml
@@ -59,7 +59,7 @@ jobs:
         python-version: "3.9"
     - name: check
       run: |
-        poetry run pylint mesh2vec tests scripts docs/examples
+        poetry run pylint mesh2vec tests docs/examples
 
   audit:
     needs: [prepare-linux, prepare-win]
diff --git a/.gitignore b/.gitignore
index 12a5a6c..843e808 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,4 +7,5 @@ __pycache__
 /data/*internal*
 .DS_Store
 .venv/
-.ipynb_checkpoints
\ No newline at end of file
+.ipynb_checkpoints
+data/data/temp_hg.joblib
\ No newline at end of file

From 80eeca73880e98baddcd2527013b665a10178cfd Mon Sep 17 00:00:00 2001
From: Markus Stoll <markus.stoll@renumics.com>
Date: Tue, 5 Dec 2023 11:45:40 +0100
Subject: [PATCH 27/27] formatting

---
 scripts/evaluation_1.0.3.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/scripts/evaluation_1.0.3.py b/scripts/evaluation_1.0.3.py
index 4dea99a..c303e25 100644
--- a/scripts/evaluation_1.0.3.py
+++ b/scripts/evaluation_1.0.3.py
@@ -36,7 +36,7 @@
 a.add_features_from_ansa(
     ["warpage", "aspect", "normal", "area"],
     Path("data/hat/Hatprofile.k"),
-    json_mesh_file=Path(PATH)
+    json_mesh_file=Path(PATH),
 )
 print(f"   add_features_from_ansa:", time.time() - start)
 if PROFILE_MEM:
@@ -70,7 +70,7 @@
     print(f"Current memory usage is {current / 10**6}MB; Peak was {peak / 10**6}MB")
     tracemalloc.stop()
 
-### aggregate_angle_diff 
+### aggregate_angle_diff
 if PROFILE_MEM:
     tracemalloc.start()
 start = time.time()
@@ -84,7 +84,6 @@
     tracemalloc.stop()
 
 
-
 # calc_adjacencies: 41.01193881034851
 # add_features_from_ansa: 0.21686553955078125
 # 1 aggregate: 27.74431562423706
@@ -97,4 +96,4 @@
 #    add_features_from_ansa: 0.5271070003509521
 # Current memory usage is 5.953076MB; Peak was 53.423552MB
 #    1 aggregate: 53.40042471885681
-# Current memory usage is 6.9341MB; Peak was 103.818146MB
\ No newline at end of file
+# Current memory usage is 6.9341MB; Peak was 103.818146MB