From 02088bc2baea4ecfe323701ece565aa9961ceeee Mon Sep 17 00:00:00 2001
From: eruijsena <enricoruijsenaars@gmail.com>
Date: Thu, 28 Sep 2023 14:28:37 +0200
Subject: [PATCH 1/8] add plots to show the change in maxContrib state

---
 devtools/conda-envs/full_env.yaml             |  1 +
 reeds/function_libs/analysis/sampling.py      | 68 +++++++++++++++++
 .../visualization/sampling_plots.py           | 73 ++++++++++++++++++-
 3 files changed, 141 insertions(+), 1 deletion(-)

diff --git a/devtools/conda-envs/full_env.yaml b/devtools/conda-envs/full_env.yaml
index 5ad5c940..bbe807d6 100644
--- a/devtools/conda-envs/full_env.yaml
+++ b/devtools/conda-envs/full_env.yaml
@@ -19,6 +19,7 @@ dependencies:
   - pandas
   - pytables
   - matplotlib
+  - plotly
   - mpmath
 
     #Docs
diff --git a/reeds/function_libs/analysis/sampling.py b/reeds/function_libs/analysis/sampling.py
index 707e0c80..e22fc875 100644
--- a/reeds/function_libs/analysis/sampling.py
+++ b/reeds/function_libs/analysis/sampling.py
@@ -6,6 +6,7 @@
 import pandas as pd
 
 import reeds.function_libs.visualization.sampling_plots
+from pygromos.files.repdat import Repdat
 
 
 def undersampling_occurence_potential_threshold_densityClustering(ene_trajs: List[pd.DataFrame],
@@ -349,7 +350,74 @@ def sampling_analysis(ene_trajs: List[pd.DataFrame],
 
     return final_results, out_path
 
+def analyse_state_transitions(repdat: Repdat, normalize: bool = False, bidirectional: bool = False):
+    """
+    Count the number of times a transition occurs between pairs of states, based on the repdat info.
+
+    Parameters
+    ----------
+    repdat: Repdat
+        Redat object containing the information regarding the replica exchange trials in the 
+        RE-EDS simulation.
+    normalize: bool, optional
+        Normalize the transitions by the total number of outgoing transitions per state
+    bidirectional: bool, optional
+        Count the transitions symmetrically (state A to B together with state B to A)
 
+    Returns
+    -------
+    np.ndarray
+        number of transitions between all pairs of states
+    """
+    if normalize and bidirectional:
+        raise Exception("Transitions cannot be normalized w.r.t leaving state and bidirectional")
+    
+    num_replicas = len(repdat.system.s)
+    repdat_eoffs = repdat.system.state_eir
+    num_states = len(repdat_eoffs)
+    eoffs = [[repdat_eoffs[state][s] for state in repdat_eoffs] for s in range(len(repdat_eoffs[1]))]
+
+    # Add end-state potentials as individual columns (this is pretty slow)
+
+    Vi = repdat.DATA["state_potentials"].apply(pd.Series)
+    values_to_subtract = np.array([eoffs[int(s_val_index-1)] for s_val_index in repdat.DATA['ID'].values])
+
+    corrected_Vi_array = Vi.values - values_to_subtract
+    corrected_Vi = pd.DataFrame(corrected_Vi_array, columns=[f"Vr{i+1}" for i in range(5)])
+    max_contrib = corrected_Vi.idxmin(axis=1)
+    max_contrib.name = "Vmin"
+    enhanced_repdat = pd.concat([repdat.DATA, corrected_Vi, max_contrib], axis=1)
+
+    # Initialize transition counts to zero for all pairs of states
+    transition_counts = np.zeros((num_states, num_states))
+
+    for replica in range(1, num_replicas+1):
+        state_trajectory = enhanced_repdat.query(f"coord_ID == {replica}")[["Vmin", "run"]].reset_index(drop=True)
+
+        # Count the transitions between different states
+        for i in range(len(state_trajectory) - 1):
+            current_state = int(state_trajectory["Vmin"][i][-1]) # Take the i in Vri
+            next_state = int(state_trajectory["Vmin"][i + 1][-1])
+            current_run = state_trajectory["run"][i] # To check in case the trajectory is spliced
+            next_run = state_trajectory["run"][i+1]
+            if next_run == current_run +1 and current_state != next_state:
+                transition_counts[current_state-1][next_state-1] += 1
+
+    if normalize: 
+        # Normalize by total number of transitions per state
+        tot_trans = np.sum(transition_counts, axis=1)
+        transition_counts = transition_counts / tot_trans[:, np.newaxis]
+
+    elif bidirectional:
+        # Consider exchanges in both directions together
+        bidirectional_counts = np.zeros((num_states, num_states))
+        for state1 in range(len(transition_counts)):
+            for state2 in range(len(transition_counts[state1])):
+                bidirectional_counts[state1][state2] += transition_counts[state1][state2]
+                bidirectional_counts[state2][state1] += transition_counts[state1][state2]
+        transition_counts = bidirectional_counts
+
+    return transition_counts
 
 def detect_undersampling(ene_trajs: List[pd.DataFrame],
                          state_potential_treshold: List[float],
diff --git a/reeds/function_libs/visualization/sampling_plots.py b/reeds/function_libs/visualization/sampling_plots.py
index 64a5a054..f98086ab 100644
--- a/reeds/function_libs/visualization/sampling_plots.py
+++ b/reeds/function_libs/visualization/sampling_plots.py
@@ -2,11 +2,15 @@
 
 import numpy as np
 from matplotlib import pyplot as plt
+from matplotlib.colors import to_rgba
+
+import plotly.graph_objects as go
+from plotly.colors import convert_to_RGB_255
 
 from reeds.function_libs.visualization import plots_style as ps
 from reeds.function_libs.visualization.utils import nice_s_vals
 
-import reeds.function_libs.visualization.plots_style as ps
+
 
 def plot_sampling_convergence(ene_trajs, opt_trajs, outfile, title = None, trim_beg = 0.1):
     """
@@ -377,3 +381,70 @@ def plot_stateOccurence_matrix(data: dict,
     if (not out_dir is None):
         fig.savefig(out_dir + '/sampling_maxContrib_matrix.png', bbox_inches='tight')
         plt.close()
+
+def plot_state_transitions(state_transitions: np.ndarray, title: str = None, colors: List[str] =  ps.active_qualitative_map, out_path: str = None):
+    """
+    Make a Sankey plot showing the flows between states.
+     
+    Parameters
+    ----------
+    state_transitions : np.ndarray
+        num_states * num_states 2D array containing the number of transitions between states
+    title: str, optional
+        printed title of the plot
+    colors: List[str], optional
+        if you don't like the default colors
+    out_path: str, optional
+        path to save the image to. if none, the image is returned as a plotly figure
+
+    Returns
+    -------
+    None or fig
+        plotly figure if if was not saved
+    """
+    num_states = len(state_transitions)
+
+    def v_distribute(total_transitions):
+        # Vertically distribute states in plot based on total number of transitions
+        box_sizes = total_transitions / total_transitions.sum()
+        box_vplace = [np.sum(box_sizes[:i]) + box_sizes[i]/2 for i in range(len(box_sizes))]
+        return box_vplace
+    
+    y_placements = v_distribute(np.sum(state_transitions, axis=1)) + v_distribute(np.sum(state_transitions, axis=0))
+    
+    # Convert colors to plotly format and make them transparent
+    rgba_colors = []
+    for color in colors:
+        rgba = to_rgba(color)
+        rgba_plotly = convert_to_RGB_255(rgba[:-1])
+        # Add opacity
+        rgba_plotly = rgba_plotly + (0.8,)
+        # Make string
+        rgba_colors.append("rgba" + str(rgba_plotly))
+    
+    # Indices 0..n-1 are the source and n..2n-1 are the target.
+    fig = go.Figure(data=[go.Sankey(
+        node = dict(
+          thickness = 20,
+          line = dict(color = "black", width = 2),
+          label = [f"state {i+1}" for i in range(num_states)]*2,
+          color = rgba_colors[:num_states]*2,
+          x = [0.1,0.1,0.1,0.1,0.1,1,1,1,1,1],
+          y = y_placements
+        ),
+        link = dict(
+          arrowlen = 30,
+          source = np.array([[i]*num_states for i in range(num_states)]).flatten(),
+          target = np.array([[i for i in range(num_states, 2*num_states)] for _ in range(num_states)]).flatten(),
+          value = state_transitions.flatten(),
+          color = np.array([[c]*num_states for c in rgba_colors[:num_states]]).flatten()
+      ),
+        arrangement="fixed",
+    )])
+
+    fig.update_layout(title_text=title, font_size=20, title_x=0.5)
+    
+    if out_path:
+        fig.write_image(out_path)
+    else:
+        return fig
\ No newline at end of file

From aa468457c7f7843973ad68066bf1139f295ed0b2 Mon Sep 17 00:00:00 2001
From: eruijsena <enricoruijsenaars@gmail.com>
Date: Fri, 29 Sep 2023 17:05:27 +0200
Subject: [PATCH 2/8] make it work for more than 5 states

---
 reeds/function_libs/analysis/sampling.py      | 16 +++++-----
 .../visualization/sampling_plots.py           | 29 +++++++++++--------
 2 files changed, 25 insertions(+), 20 deletions(-)

diff --git a/reeds/function_libs/analysis/sampling.py b/reeds/function_libs/analysis/sampling.py
index e22fc875..98910871 100644
--- a/reeds/function_libs/analysis/sampling.py
+++ b/reeds/function_libs/analysis/sampling.py
@@ -353,7 +353,6 @@ def sampling_analysis(ene_trajs: List[pd.DataFrame],
 def analyse_state_transitions(repdat: Repdat, normalize: bool = False, bidirectional: bool = False):
     """
     Count the number of times a transition occurs between pairs of states, based on the repdat info.
-
     Parameters
     ----------
     repdat: Repdat
@@ -363,7 +362,6 @@ def analyse_state_transitions(repdat: Repdat, normalize: bool = False, bidirecti
         Normalize the transitions by the total number of outgoing transitions per state
     bidirectional: bool, optional
         Count the transitions symmetrically (state A to B together with state B to A)
-
     Returns
     -------
     np.ndarray
@@ -371,7 +369,7 @@ def analyse_state_transitions(repdat: Repdat, normalize: bool = False, bidirecti
     """
     if normalize and bidirectional:
         raise Exception("Transitions cannot be normalized w.r.t leaving state and bidirectional")
-    
+        
     num_replicas = len(repdat.system.s)
     repdat_eoffs = repdat.system.state_eir
     num_states = len(repdat_eoffs)
@@ -383,7 +381,7 @@ def analyse_state_transitions(repdat: Repdat, normalize: bool = False, bidirecti
     values_to_subtract = np.array([eoffs[int(s_val_index-1)] for s_val_index in repdat.DATA['ID'].values])
 
     corrected_Vi_array = Vi.values - values_to_subtract
-    corrected_Vi = pd.DataFrame(corrected_Vi_array, columns=[f"Vr{i+1}" for i in range(5)])
+    corrected_Vi = pd.DataFrame(corrected_Vi_array, columns=[f"Vr{i+1}" for i in range(num_states)])
     max_contrib = corrected_Vi.idxmin(axis=1)
     max_contrib.name = "Vmin"
     enhanced_repdat = pd.concat([repdat.DATA, corrected_Vi, max_contrib], axis=1)
@@ -392,13 +390,15 @@ def analyse_state_transitions(repdat: Repdat, normalize: bool = False, bidirecti
     transition_counts = np.zeros((num_states, num_states))
 
     for replica in range(1, num_replicas+1):
-        state_trajectory = enhanced_repdat.query(f"coord_ID == {replica}")[["Vmin", "run"]].reset_index(drop=True)
+        state_repdat = enhanced_repdat.query(f"coord_ID == {replica}")
+            
+        state_trajectory = state_repdat[["Vmin", "run"]].reset_index(drop=True)
 
         # Count the transitions between different states
         for i in range(len(state_trajectory) - 1):
-            current_state = int(state_trajectory["Vmin"][i][-1]) # Take the i in Vri
-            next_state = int(state_trajectory["Vmin"][i + 1][-1])
-            current_run = state_trajectory["run"][i] # To check in case the trajectory is spliced
+            current_state = int("".join([char for char in state_trajectory["Vmin"][i] if char.isdigit()])) # Take the i in Vri
+            next_state = int("".join([char for char in state_trajectory["Vmin"][i + 1] if char.isdigit()]))
+            current_run = state_trajectory["run"][i] # Check whether you are actually comparing consecutive exchanges
             next_run = state_trajectory["run"][i+1]
             if next_run == current_run +1 and current_state != next_state:
                 transition_counts[current_state-1][next_state-1] += 1
diff --git a/reeds/function_libs/visualization/sampling_plots.py b/reeds/function_libs/visualization/sampling_plots.py
index f98086ab..b99bb018 100644
--- a/reeds/function_libs/visualization/sampling_plots.py
+++ b/reeds/function_libs/visualization/sampling_plots.py
@@ -1,8 +1,8 @@
-from typing import List
+from typing import Union, List
 
 import numpy as np
 from matplotlib import pyplot as plt
-from matplotlib.colors import to_rgba
+from matplotlib.colors import Colormap, to_rgba
 
 import plotly.graph_objects as go
 from plotly.colors import convert_to_RGB_255
@@ -382,7 +382,7 @@ def plot_stateOccurence_matrix(data: dict,
         fig.savefig(out_dir + '/sampling_maxContrib_matrix.png', bbox_inches='tight')
         plt.close()
 
-def plot_state_transitions(state_transitions: np.ndarray, title: str = None, colors: List[str] =  ps.active_qualitative_map, out_path: str = None):
+def plot_state_transitions(state_transitions: np.ndarray, title: str = None, colors: Union[List[str], Colormap] =  ps.qualitative_tab_map, out_path: str = None):
     """
     Make a Sankey plot showing the flows between states.
      
@@ -392,26 +392,30 @@ def plot_state_transitions(state_transitions: np.ndarray, title: str = None, col
         num_states * num_states 2D array containing the number of transitions between states
     title: str, optional
         printed title of the plot
-    colors: List[str], optional
+    colors: Union[List[str], Colormap], optional
         if you don't like the default colors
     out_path: str, optional
         path to save the image to. if none, the image is returned as a plotly figure
-
     Returns
     -------
     None or fig
         plotly figure if if was not saved
     """
     num_states = len(state_transitions)
+    
+    if isinstance(colors, Colormap):
+        colors = [colors(i) for i in np.linspace(0, 1, num_states)]
+    elif len(colors) < num_states:
+        raise Exception("Insufficient colors to plot all states")
 
     def v_distribute(total_transitions):
-        # Vertically distribute states in plot based on total number of transitions
+        # Vertically distribute nodes in plot based on total number of transitions per state
         box_sizes = total_transitions / total_transitions.sum()
         box_vplace = [np.sum(box_sizes[:i]) + box_sizes[i]/2 for i in range(len(box_sizes))]
         return box_vplace
-    
+
     y_placements = v_distribute(np.sum(state_transitions, axis=1)) + v_distribute(np.sum(state_transitions, axis=0))
-    
+
     # Convert colors to plotly format and make them transparent
     rgba_colors = []
     for color in colors:
@@ -421,15 +425,16 @@ def v_distribute(total_transitions):
         rgba_plotly = rgba_plotly + (0.8,)
         # Make string
         rgba_colors.append("rgba" + str(rgba_plotly))
-    
+
     # Indices 0..n-1 are the source and n..2n-1 are the target.
     fig = go.Figure(data=[go.Sankey(
         node = dict(
+          pad = 5,
           thickness = 20,
           line = dict(color = "black", width = 2),
           label = [f"state {i+1}" for i in range(num_states)]*2,
           color = rgba_colors[:num_states]*2,
-          x = [0.1,0.1,0.1,0.1,0.1,1,1,1,1,1],
+          x = [0.1]*num_states + [1]*num_states,
           y = y_placements
         ),
         link = dict(
@@ -441,10 +446,10 @@ def v_distribute(total_transitions):
       ),
         arrangement="fixed",
     )])
+    fig.update_layout(title_text=title, font_size=20, title_x=0.5, height=max(600, num_states*100))
 
-    fig.update_layout(title_text=title, font_size=20, title_x=0.5)
-    
     if out_path:
         fig.write_image(out_path)
+        return None
     else:
         return fig
\ No newline at end of file

From 3b0f1fa90eafb2ad475ad5db1dda467e0afa6b2c Mon Sep 17 00:00:00 2001
From: eruijsena <enricoruijsenaars@gmail.com>
Date: Fri, 29 Sep 2023 17:06:20 +0200
Subject: [PATCH 3/8] add option to consider only high s values

---
 reeds/function_libs/analysis/sampling.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/reeds/function_libs/analysis/sampling.py b/reeds/function_libs/analysis/sampling.py
index 98910871..059df169 100644
--- a/reeds/function_libs/analysis/sampling.py
+++ b/reeds/function_libs/analysis/sampling.py
@@ -350,7 +350,7 @@ def sampling_analysis(ene_trajs: List[pd.DataFrame],
 
     return final_results, out_path
 
-def analyse_state_transitions(repdat: Repdat, normalize: bool = False, bidirectional: bool = False):
+def analyse_state_transitions(repdat: Repdat, min_s: int = None, normalize: bool = False, bidirectional: bool = False):
     """
     Count the number of times a transition occurs between pairs of states, based on the repdat info.
     Parameters
@@ -358,6 +358,8 @@ def analyse_state_transitions(repdat: Repdat, normalize: bool = False, bidirecti
     repdat: Repdat
         Redat object containing the information regarding the replica exchange trials in the 
         RE-EDS simulation.
+    min_s: int, optional
+        Index of the lowest s_value to consider for the transitions. If None, consider all s values.
     normalize: bool, optional
         Normalize the transitions by the total number of outgoing transitions per state
     bidirectional: bool, optional
@@ -390,7 +392,10 @@ def analyse_state_transitions(repdat: Repdat, normalize: bool = False, bidirecti
     transition_counts = np.zeros((num_states, num_states))
 
     for replica in range(1, num_replicas+1):
-        state_repdat = enhanced_repdat.query(f"coord_ID == {replica}")
+        if min_s:
+            state_repdat = enhanced_repdat.query(f"coord_ID == {replica} & ID <= {min_s}")
+        else:
+            state_repdat = enhanced_repdat.query(f"coord_ID == {replica}")
             
         state_trajectory = state_repdat[["Vmin", "run"]].reset_index(drop=True)
 

From 3b8b5b88dbdee7fbc47d5243df0b0f4c3bd35392 Mon Sep 17 00:00:00 2001
From: eruijsena <enricoruijsenaars@gmail.com>
Date: Fri, 29 Sep 2023 17:08:14 +0200
Subject: [PATCH 4/8] add plotly to test-env

---
 devtools/conda-envs/test_env.yaml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/devtools/conda-envs/test_env.yaml b/devtools/conda-envs/test_env.yaml
index 92c7e794..9aaef8c0 100644
--- a/devtools/conda-envs/test_env.yaml
+++ b/devtools/conda-envs/test_env.yaml
@@ -19,6 +19,7 @@ dependencies:
   - pandas
   - pytables
   - matplotlib
+  - plotlty
 
 
     # Pip-only installs

From 609f26ac632e8efdfcd395ca20e31c1b8ece9d52 Mon Sep 17 00:00:00 2001
From: eruijsena <enricoruijsenaars@gmail.com>
Date: Fri, 29 Sep 2023 17:08:42 +0200
Subject: [PATCH 5/8] spelling

---
 devtools/conda-envs/test_env.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/devtools/conda-envs/test_env.yaml b/devtools/conda-envs/test_env.yaml
index 9aaef8c0..88a08745 100644
--- a/devtools/conda-envs/test_env.yaml
+++ b/devtools/conda-envs/test_env.yaml
@@ -19,7 +19,7 @@ dependencies:
   - pandas
   - pytables
   - matplotlib
-  - plotlty
+  - plotly
 
 
     # Pip-only installs

From 6de0513e633f6eed016e7188acbe2218d3daac70 Mon Sep 17 00:00:00 2001
From: eruijsena <enricoruijsenaars@gmail.com>
Date: Mon, 2 Oct 2023 12:51:24 +0200
Subject: [PATCH 6/8] analyse transitions with expanded repdat

---
 reeds/function_libs/analysis/sampling.py | 35 ++++++++----------------
 reeds/submodules/pygromos                |  2 +-
 2 files changed, 12 insertions(+), 25 deletions(-)

diff --git a/reeds/function_libs/analysis/sampling.py b/reeds/function_libs/analysis/sampling.py
index 059df169..c095a197 100644
--- a/reeds/function_libs/analysis/sampling.py
+++ b/reeds/function_libs/analysis/sampling.py
@@ -6,7 +6,7 @@
 import pandas as pd
 
 import reeds.function_libs.visualization.sampling_plots
-from pygromos.files.repdat import Repdat
+from pygromos.files.repdat import ExpandedRepdat
 
 
 def undersampling_occurence_potential_threshold_densityClustering(ene_trajs: List[pd.DataFrame],
@@ -350,14 +350,14 @@ def sampling_analysis(ene_trajs: List[pd.DataFrame],
 
     return final_results, out_path
 
-def analyse_state_transitions(repdat: Repdat, min_s: int = None, normalize: bool = False, bidirectional: bool = False):
+def analyse_state_transitions(repdat: ExpandedRepdat, min_s: int = None, normalize: bool = False, bidirectional: bool = False):
     """
     Count the number of times a transition occurs between pairs of states, based on the repdat info.
     Parameters
     ----------
-    repdat: Repdat
-        Redat object containing the information regarding the replica exchange trials in the 
-        RE-EDS simulation.
+    repdat: ExpandedRepdat
+        ExpandedRepdat object (created from a Repdat) which contains all the exchange information of a 
+        RE-EDS simulation plus the potential energies of the end-states
     min_s: int, optional
         Index of the lowest s_value to consider for the transitions. If None, consider all s values.
     normalize: bool, optional
@@ -373,37 +373,24 @@ def analyse_state_transitions(repdat: Repdat, min_s: int = None, normalize: bool
         raise Exception("Transitions cannot be normalized w.r.t leaving state and bidirectional")
         
     num_replicas = len(repdat.system.s)
-    repdat_eoffs = repdat.system.state_eir
-    num_states = len(repdat_eoffs)
-    eoffs = [[repdat_eoffs[state][s] for state in repdat_eoffs] for s in range(len(repdat_eoffs[1]))]
-
-    # Add end-state potentials as individual columns (this is pretty slow)
-
-    Vi = repdat.DATA["state_potentials"].apply(pd.Series)
-    values_to_subtract = np.array([eoffs[int(s_val_index-1)] for s_val_index in repdat.DATA['ID'].values])
-
-    corrected_Vi_array = Vi.values - values_to_subtract
-    corrected_Vi = pd.DataFrame(corrected_Vi_array, columns=[f"Vr{i+1}" for i in range(num_states)])
-    max_contrib = corrected_Vi.idxmin(axis=1)
-    max_contrib.name = "Vmin"
-    enhanced_repdat = pd.concat([repdat.DATA, corrected_Vi, max_contrib], axis=1)
+    num_states = len(repdat.system.state_eir)
 
     # Initialize transition counts to zero for all pairs of states
     transition_counts = np.zeros((num_states, num_states))
 
     for replica in range(1, num_replicas+1):
+        # Get exchange data per state
         if min_s:
-            state_repdat = enhanced_repdat.query(f"coord_ID == {replica} & ID <= {min_s}")
+            state_repdat = repdat.DATA.query(f"coord_ID == {replica} & ID <= {min_s}")
         else:
-            state_repdat = enhanced_repdat.query(f"coord_ID == {replica}")
-            
-        state_trajectory = state_repdat[["Vmin", "run"]].reset_index(drop=True)
+            state_repdat = repdat.DATA.query(f"coord_ID == {replica}")
+        state_trajectory = state_repdat[["Vmin", "run"]].reset_index(drop=True).copy()
 
         # Count the transitions between different states
         for i in range(len(state_trajectory) - 1):
             current_state = int("".join([char for char in state_trajectory["Vmin"][i] if char.isdigit()])) # Take the i in Vri
             next_state = int("".join([char for char in state_trajectory["Vmin"][i + 1] if char.isdigit()]))
-            current_run = state_trajectory["run"][i] # Check whether you are actually comparing consecutive exchanges
+            current_run = state_trajectory["run"][i] # Check that you are actually comparing consecutive exchanges
             next_run = state_trajectory["run"][i+1]
             if next_run == current_run +1 and current_state != next_state:
                 transition_counts[current_state-1][next_state-1] += 1
diff --git a/reeds/submodules/pygromos b/reeds/submodules/pygromos
index 47837858..ad25a499 160000
--- a/reeds/submodules/pygromos
+++ b/reeds/submodules/pygromos
@@ -1 +1 @@
-Subproject commit 4783785811265b169f26d16e881e662a9d58316d
+Subproject commit ad25a49907d5a09caa8b3b40b709da50d015ab64

From 170fd1b30f139b4711cb48d626678fda51b05315 Mon Sep 17 00:00:00 2001
From: eruijsena <enricoruijsenaars@gmail.com>
Date: Mon, 2 Oct 2023 15:49:11 +0200
Subject: [PATCH 7/8] update link to pygromos

---
 reeds/submodules/pygromos | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/reeds/submodules/pygromos b/reeds/submodules/pygromos
index ad25a499..d9c692ac 160000
--- a/reeds/submodules/pygromos
+++ b/reeds/submodules/pygromos
@@ -1 +1 @@
-Subproject commit ad25a49907d5a09caa8b3b40b709da50d015ab64
+Subproject commit d9c692acbfa77c27c6366acd87ae5f6dbff1fe7f

From 1060309592ef4bc7d46bf15661c1c1f9c08b6ccb Mon Sep 17 00:00:00 2001
From: eruijsena <enricoruijsenaars@gmail.com>
Date: Tue, 3 Oct 2023 14:53:37 +0200
Subject: [PATCH 8/8] updated submodule

---
 reeds/submodules/pygromos | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/reeds/submodules/pygromos b/reeds/submodules/pygromos
index d9c692ac..37b32f2b 160000
--- a/reeds/submodules/pygromos
+++ b/reeds/submodules/pygromos
@@ -1 +1 @@
-Subproject commit d9c692acbfa77c27c6366acd87ae5f6dbff1fe7f
+Subproject commit 37b32f2bb897cb1b3b0a0224b010fbf03da7c7b6