diff --git a/CHANGELOG.md b/CHANGELOG.md
index cb86904..6442f62 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -5,9 +5,11 @@ Log of changes in the versions
## v1.6.0
- `rootgroup` as alias for `rootparent`
- `ZenodoRecord` has new property `env_name_for_token` to define the environment variable name to be used for the Zenodo token
+- bugfix downloading zenodo files
+- allowing higher versions of `pymongo`
## v1.5.2
-- bugix dumping json-ld
+- bugfix dumping json-ld
## v1.5.1
- a json-ld string can be assigned to a rdf object (see https://h5rdmtoolbox.readthedocs.io/en/latest/userguide/wrapper/FAIRAttributes.html)
@@ -134,7 +136,7 @@ major changes:
## v0.13.0
-- scale and offset is now implemented in the package is should not longer be defined in a convention.
+- scale and offset is now implemented in the package. it should no longer be defined in a convention.
- bugfix normalization extension
- bugfix exporting xr.DataArray built with the toolbox to netCDF
- support usage of IRI to describe metadata
@@ -154,7 +156,7 @@ major changes:
## v0.12.0
- 0D data is written to MongoDB
-- new utils like computing filesize
+- new utils like computing file size
- update to new zenodo_search package due to change in backend at Zenodo.org
- `find`, `find_one` and `distinct` can be called on HDF files
- small bugfixes
diff --git a/codemeta.json b/codemeta.json
index 8c8f6b7..1c612bb 100644
--- a/codemeta.json
+++ b/codemeta.json
@@ -4,7 +4,7 @@
"license": "https://spdx.org/licenses/MIT",
"codeRepository": "git+https://github.com/matthiasprobst/h5RDMtoolbox.git",
"name": "h5RDMtoolbox",
- "version": "1.5.3",
+ "version": "1.6.0",
"description": "Supporting a FAIR Research Data lifecycle using Python and HDF5.",
"applicationCategory": "Engineering",
"programmingLanguage": [
diff --git a/docs/colab/quickstart.ipynb b/docs/colab/quickstart.ipynb
index 61c9a6c..78e887a 100644
--- a/docs/colab/quickstart.ipynb
+++ b/docs/colab/quickstart.ipynb
@@ -8,7 +8,7 @@
},
"outputs": [],
"source": [
- "# !pip install h5rdmtoolbox==1.5.3"
+ "# !pip install h5rdmtoolbox==1.6.0"
]
},
{
diff --git a/docs/userguide/database/mongoDB.ipynb b/docs/userguide/database/mongoDB.ipynb
index a3ed49a..a21d4f2 100644
--- a/docs/userguide/database/mongoDB.ipynb
+++ b/docs/userguide/database/mongoDB.ipynb
@@ -26,21 +26,10 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"id": "1e3c96fc-62ac-4462-8e87-d131aeb52c53",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "using(\"h5py\")"
- ]
- },
- "execution_count": 2,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"import pymongo\n",
"# from pymongo import MongoClient\n",
@@ -66,21 +55,10 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"id": "b40e8640-b166-4792-913b-6ce39765eef4",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "mongomock.MongoClient('localhost', 27017)"
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"client = MongoClient()\n",
"client"
@@ -96,7 +74,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"id": "a8f3cb21-e1e3-4969-9103-a48ac49547b9",
"metadata": {},
"outputs": [],
@@ -119,7 +97,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": null,
"id": "111e3c0d-6d5d-4931-9aac-e4f9e6575088",
"metadata": {},
"outputs": [],
@@ -139,291 +117,10 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": null,
"id": "3c7f5e27-c173-4a14-941c-2614466219a5",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "
\n",
- "\n",
- "\n",
- "
\n",
- " - \n",
- " \n",
- " \n",
- " \n",
- "\n",
- "\n",
- " \n",
- "\n",
- " \n",
- "\n",
- " \n",
- "\n",
- " \n",
- "\n",
- " \n",
- "
\n",
- "
\n",
- "
"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"from skimage.feature import graycomatrix, graycoprops\n",
"\n",
@@ -475,7 +172,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": null,
"id": "16c8fddc-d3f2-4987-925f-db07a1337b8b",
"metadata": {},
"outputs": [],
@@ -485,7 +182,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": null,
"id": "1f5d4d82-78ce-49fc-8883-bb89bb1a6666",
"metadata": {},
"outputs": [],
@@ -518,7 +215,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": null,
"id": "afcd3f7d-754e-4f55-9fd3-d8cfef7c4a66",
"metadata": {},
"outputs": [],
@@ -537,21 +234,10 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": null,
"id": "6d8e16c7-cd04-4b25-bb18-382bb98b2ee0",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "1"
- ]
- },
- "execution_count": 10,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"collection.count_documents({}) # or mdb.collection.count_documents({})"
]
@@ -566,7 +252,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": null,
"id": "df71d034-ebcf-4c2d-811f-24dff3ae59fc",
"metadata": {},
"outputs": [],
@@ -584,21 +270,10 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": null,
"id": "615cea84-62d8-416c-ba3d-8609663f7dd8",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "(1797, 8, 8)"
- ]
- },
- "execution_count": 12,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"res[()].shape"
]
@@ -623,7 +298,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": null,
"id": "34e31813-62f1-4af6-bb1d-b4dac415a5b1",
"metadata": {},
"outputs": [],
@@ -633,7 +308,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": null,
"id": "40d84010-8add-4b34-b090-64340880bcf9",
"metadata": {},
"outputs": [],
@@ -652,21 +327,10 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": null,
"id": "951f2bec-1e21-4f17-8932-6cb6a2d1edc1",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "1797"
- ]
- },
- "execution_count": 15,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"collection.count_documents({}) # or mdb.collection.count_documents({})"
]
@@ -681,21 +345,10 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": null,
"id": "5e95ad39-9b21-417f-8c09-e2bc6b135e62",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "(1, 8, 8)"
- ]
- },
- "execution_count": 16,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"one_res = mdb.find_one({'digit': {'$eq': 3}})\n",
"one_res[()].shape"
@@ -711,92 +364,20 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": null,
"id": "80f1e871-f048-434b-9372-8fec5a85fbc8",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 17,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
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