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Rerun jupyternotebooks to check their functionality after relocating them to notebooks. OpenBis related python scripts still need to be tested.

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This commit is contained in:
florez_j
2024-11-24 10:45:40 +01:00
parent 02ded9c11a
commit c257ab6072
6 changed files with 7402 additions and 85 deletions
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3651
notebooks/demo_create_and_visualize_hdf5_file.ipynb
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3685
notebooks/demo_data_integration.ipynb
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21
notebooks/demo_h5_file_2_obis_props_mapping.py
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@ -1,9 +1,21 @@
import src.openbis_lib as openbis_lib
import hdf5_lib
import datetime
import os import os
from nbutils import add_project_path_to_sys_path
# Add project root to sys.path
add_project_path_to_sys_path()
import datetime
import logging import logging
try:
import src.openbis_lib as openbis_lib
import src.hdf5_ops as hdf5_ops
#import pipelines.metadata_revision as metadata_revision
print("Imports successful!")
except ImportError as e:
print(f"Import error: {e}")
def main(): def main():
#df_h5 = hdf5_lib.read_hdf5_as_dataframe_v2('BeamTimeMetaData.h5') #df_h5 = hdf5_lib.read_hdf5_as_dataframe_v2('BeamTimeMetaData.h5')
@ -20,7 +32,8 @@ def main():
print(sample.identifier) print(sample.identifier)
df_openbis = samples.df.copy(deep=True) df_openbis = samples.df.copy(deep=True)
h5_file_path = os.path.join(os.path.curdir,'input_files\\BeamTimeMetaData.h5') h5_file_path = os.path.join(os.path.curdir,'input_files\\BeamTimeMetaData.h5')
df_h5 = hdf5_lib.read_hdf5_as_dataframe(h5_file_path)
df_h5 = hdf5_ops.read_mtable_as_dataframe(h5_file_path)
# dataframe preprocessing steps # dataframe preprocessing steps
df_h5, df_openbis = openbis_lib.align_datetime_observation_windows(df_h5, df_openbis) df_h5, df_openbis = openbis_lib.align_datetime_observation_windows(df_h5, df_openbis)

62
notebooks/demo_hdf5_data_sharing_and_plotting.ipynb
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24
notebooks/demo_single_sample_update_to_openbis.py
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@ -1,12 +1,22 @@
import os, sys
sys.path.append(os.path.abspath('src'))
import src.openbis_lib as openbis_lib
import src.hdf5_lib as hdf5_lib
import datetime
import os import os
from nbutils import add_project_path_to_sys_path
# Add project root to sys.path
add_project_path_to_sys_path()
import datetime
import logging import logging
try:
import src.openbis_lib as openbis_lib
import src.hdf5_ops as hdf5_ops
#import pipelines.metadata_revision as metadata_revision
print("Imports successful!")
except ImportError as e:
print(f"Import error: {e}")
def main(): def main():
#df_h5 = hdf5_lib.read_hdf5_as_dataframe_v2('BeamTimeMetaData.h5') #df_h5 = hdf5_lib.read_hdf5_as_dataframe_v2('BeamTimeMetaData.h5')
@ -23,7 +33,7 @@ def main():
print(sample.identifier) print(sample.identifier)
df_openbis = samples.df.copy(deep=True) df_openbis = samples.df.copy(deep=True)
h5_file_path = os.path.join(os.path.curdir,'input_files\\BeamTimeMetaData.h5') h5_file_path = os.path.join(os.path.curdir,'input_files\\BeamTimeMetaData.h5')
df_h5 = hdf5_lib.read_mtable_as_dataframe(h5_file_path) df_h5 = hdf5_ops.read_mtable_as_dataframe(h5_file_path)
# dataframe preprocessing steps # dataframe preprocessing steps
df_h5, df_openbis = openbis_lib.align_datetime_observation_windows(df_h5, df_openbis) df_h5, df_openbis = openbis_lib.align_datetime_observation_windows(df_h5, df_openbis)

44
notebooks/example_workflow_metadata_annotation.ipynb
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@ -23,11 +23,29 @@
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Imports successful!\n"
]
}
],
"source": [ "source": [
"import src.metadata_review_lib as metadata_annotation\n", "import os\n",
"import src.hdf5_vis as hdf5_vis\n", "from nbutils import add_project_path_to_sys_path\n",
"import os" "\n",
"\n",
"# Add project root to sys.path\n",
"add_project_path_to_sys_path()\n",
"\n",
"try:\n",
" import src.hdf5_ops as hdf5_ops\n",
" import pipelines.metadata_revision as metadata_revision\n",
" print(\"Imports successful!\")\n",
"except ImportError as e:\n",
" print(f\"Import error: {e}\")"
] ]
}, },
{ {
@ -46,7 +64,7 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"hdf5_file_path = \"output_files/kinetic_flowtube_study_2023-06-29_LuciaI.h5\"" "hdf5_file_path = \"../output_files/collection_kinetic_flowtube_study_LuciaI_2022-01-31_2023-06-29/kinetic_flowtube_study_LuciaI_2023-06-29.h5\""
] ]
}, },
{ {
@ -62,11 +80,19 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The YAML file representation output_files/collection_kinetic_flowtube_study_LuciaI_2022-01-31_2023-06-29/kinetic_flowtube_study_LuciaI_2023-06-29.json of the HDF5 file output_files/collection_kinetic_flowtube_study_LuciaI_2022-01-31_2023-06-29/kinetic_flowtube_study_LuciaI_2023-06-29.h5 was created successfully.\n"
]
}
],
"source": [ "source": [
"yaml_file_path = hdf5_vis.take_yml_snapshot_of_hdf5_file(hdf5_file_path)\n", "yaml_file_path = hdf5_ops.serialize_metadata(hdf5_file_path,output_format='json')\n",
"\n", "\n",
"if os.path.exists(yaml_file_path):\n", "if os.path.exists(yaml_file_path):\n",
" print(f'The YAML file representation {yaml_file_path} of the HDF5 file {hdf5_file_path} was created successfully.')" " print(f'The YAML file representation {yaml_file_path} of the HDF5 file {hdf5_file_path} was created successfully.')"
@ -118,7 +144,7 @@
"outputs": [], "outputs": [],
"source": [ "source": [
"\n", "\n",
"metadata_annotation.update_hdf5_file_with_review(hdf5_file_path,yaml_file_path)" "metadata_revision.update_hdf5_file_with_review(hdf5_file_path,yaml_file_path)"
] ]
} }
], ],