Merge pull request #78 from kushalbakshi/main

Fixed Equipment table import & minor issues in .ipynb files

notebooks/01-configure.ipynb

@@ -17,17 +17,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
     "import os\n",
-    "os.chdir('..')"
+    "if os.path.basename(os.getcwd()) == \"notebooks\": os.chdir(\"..\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -54,7 +54,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -73,7 +73,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -92,16 +92,17 @@
     "\n",
     "+ Giving a prefix to schema could help on the configuration of privilege settings. For example, if we set prefix `neuro_`, every schema created with the current workflow will start with `neuro_`, e.g. `neuro_lab`, `neuro_subject`, `neuro_imaging` etc.\n",
     "\n",
-    "+ The prefix could be configurated as follows in `dj.config`:"
+    "+ The prefix could be configurated in `dj.config` as follows. CodeBook users should keep their username as the prefix for schema for declaration permissions."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
-    "dj.config['custom'] = {'database.prefix': 'neuro_'}"
+    "username_as_prefix = dj.config[\"database.user\"] + \"_\"\n",
+    "dj.config[\"custom\"] = {\"database.prefix\": username_as_prefix}"
    ]
   },
   {
@@ -130,7 +131,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -142,7 +143,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -160,7 +161,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -169,7 +170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -206,8 +207,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.7.9 64-bit ('workflow-calcium-imaging': conda)",
-   "name": "python379jvsc74a57bd01a512f474e195e32ad84236879d3bb44800a92b431919ef0b10d543f5012a23c"
+   "display_name": "Python 3.9.12 ('elementsPractice')",
+   "language": "python",
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -219,7 +221,12 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.9"
+   "version": "3.9.12"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "28657e2c4c8fc87d9c51bab987cae00550904d22e795ba7dc84df7e29d09653b"
+   }
   }
  },
  "nbformat": 4,

notebooks/04-automate-optional.ipynb

@@ -28,7 +28,7 @@
    ],
    "source": [
     "import os\n",
-    "os.chdir('..')\n",
+    "if os.path.basename(os.getcwd()) == \"notebooks\": os.chdir(\"..\")\n",
     "import numpy as np\n",
     "from workflow_calcium_imaging.pipeline import lab, subject, session, scan, imaging"
    ]

notebooks/06-drop-optional.ipynb

@@ -25,7 +25,7 @@
    "outputs": [],
    "source": [
     "import os\n",
-    "os.chdir('..')"
+    "if os.path.basename(os.getcwd()) == \"notebooks\": os.chdir(\"..\")"
    ]
   },
   {

notebooks/py_scripts/00-data-download-optional.py

@@ -5,7 +5,7 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.5'
-#       jupytext_version: 1.13.7
+#       jupytext_version: 1.14.1
 #   kernelspec:
 #     display_name: 'Python 3.7.9 64-bit (''workflow-calcium-imaging'': conda)'
 #     name: python379jvsc74a57bd01a512f474e195e32ad84236879d3bb44800a92b431919ef0b10d543f5012a23c

notebooks/py_scripts/01-configure.py

@@ -5,10 +5,11 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.5'
-#       jupytext_version: 1.13.7
+#       jupytext_version: 1.14.1
 #   kernelspec:
-#     display_name: 'Python 3.7.9 64-bit (''workflow-calcium-imaging'': conda)'
-#     name: python379jvsc74a57bd01a512f474e195e32ad84236879d3bb44800a92b431919ef0b10d543f5012a23c
+#     display_name: Python 3.9.12 ('elementsPractice')
+#     language: python
+#     name: python3
 # ---
 
 # # Configure DataJoint connection to the database
@@ -22,8 +23,7 @@
 # + As a convention, we set the configuration up in the root directory of the `workflow-calcium-imaging` package and always start importing DataJoint and pipeline modules from there.
 
 import os
-if os.path.basename(os.getcwd()) == 'notebooks':
-    os.chdir('..')
+if os.path.basename(os.getcwd()) == "notebooks": os.chdir("..")
 
 pwd
 
@@ -50,9 +50,10 @@
 #
 # + Giving a prefix to schema could help on the configuration of privilege settings. For example, if we set prefix `neuro_`, every schema created with the current workflow will start with `neuro_`, e.g. `neuro_lab`, `neuro_subject`, `neuro_imaging` etc.
 #
-# + The prefix could be configurated as follows in `dj.config`:
+# + The prefix could be configurated in `dj.config` as follows. CodeBook users should keep their username as the prefix for schema for declaration permissions.
 
-dj.config['custom'] = {'database.prefix': 'neuro_'}
+username_as_prefix = dj.config["database.user"] + "_"
+dj.config["custom"] = {"database.prefix": username_as_prefix}
 
 # ### Root directories for raw calcium imaging data and processed results
 #

notebooks/py_scripts/02-workflow-structure-optional.py

@@ -6,10 +6,11 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.5'
-#       jupytext_version: 1.13.7
+#       jupytext_version: 1.14.1
 #   kernelspec:
-#     display_name: 'Python 3.7.9 64-bit (''workflow-calcium-imaging'': conda)'
-#     name: python379jvsc74a57bd01a512f474e195e32ad84236879d3bb44800a92b431919ef0b10d543f5012a23c
+#     display_name: Python 3.9.12 ('elementsPractice')
+#     language: python
+#     name: python3
 # ---
 
 # # Introduction to the workflow structure
@@ -25,7 +26,7 @@
 # To load the local configuration, we will change the directory to the package root.
 
 import os
-os.chdir('..')
+if os.path.basename(os.getcwd()) == "notebooks": os.chdir("..")
 
 # ## Schemas and tables
 #

notebooks/py_scripts/03-process.py

@@ -5,10 +5,11 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.5'
-#       jupytext_version: 1.13.7
+#       jupytext_version: 1.14.1
 #   kernelspec:
-#     display_name: 'Python 3.7.9 64-bit (''workflow-calcium-imaging'': conda)'
-#     name: python379jvsc74a57bd01a512f474e195e32ad84236879d3bb44800a92b431919ef0b10d543f5012a23c
+#     display_name: Python 3.9.12 ('elementsPractice')
+#     language: python
+#     name: python3
 # ---
 
 # # Interactively run workflow calcium imaging
@@ -26,13 +27,14 @@
 # Let's change the directory to the package root directory to load the local configuration (`dj_local_conf.json`).
 
 import os
-os.chdir('..')
+if os.path.basename(os.getcwd()) == "notebooks": os.chdir("..")
 import numpy as np
 
 # ## `Pipeline.py`
 #
 # + This script `activates` the DataJoint `elements` and declares other required tables.
 
+import datajoint as dj
 from workflow_calcium_imaging.pipeline import *
 
 # ## Schema diagrams

notebooks/py_scripts/04-automate-optional.py

@@ -5,7 +5,7 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.5'
-#       jupytext_version: 1.13.7
+#       jupytext_version: 1.14.1
 #   kernelspec:
 #     display_name: 'Python 3.7.9 64-bit (''workflow-calcium-imaging'': conda)'
 #     name: python379jvsc74a57bd01a512f474e195e32ad84236879d3bb44800a92b431919ef0b10d543f5012a23c
@@ -18,7 +18,7 @@
 # -
 
 import os
-os.chdir('..')
+if os.path.basename(os.getcwd()) == "notebooks": os.chdir("..")
 import numpy as np
 from workflow_calcium_imaging.pipeline import lab, subject, session, scan, imaging
 

notebooks/py_scripts/05-explore.py

@@ -5,18 +5,19 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.5'
-#       jupytext_version: 1.13.7
+#       jupytext_version: 1.14.1
 #   kernelspec:
-#     display_name: 'Python 3.7.9 64-bit (''workflow-calcium-imaging'': conda)'
-#     name: python379jvsc74a57bd01a512f474e195e32ad84236879d3bb44800a92b431919ef0b10d543f5012a23c
+#     display_name: Python 3.9.12 ('elementsPractice')
+#     language: python
+#     name: python3
 # ---
 
 # # DataJoint Workflow Calcium Imaging
 #
 # + This notebook will describe the steps for interacting with the data ingested into `workflow-calcium-imaging`.  
 
 import os
-os.chdir('..')
+if os.path.basename(os.getcwd()) == "notebooks": os.chdir("..")
 
 # +
 import datajoint as dj

notebooks/py_scripts/06-drop-optional.py

@@ -5,7 +5,7 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.5'
-#       jupytext_version: 1.13.7
+#       jupytext_version: 1.14.1
 #   kernelspec:
 #     display_name: 'Python 3.7.9 64-bit (''workflow-calcium-imaging'': conda)'
 #     name: python379jvsc74a57bd01a512f474e195e32ad84236879d3bb44800a92b431919ef0b10d543f5012a23c
@@ -20,7 +20,7 @@
 # Change into the parent directory to find the `dj_local_conf.json` file. 
 
 import os
-os.chdir('..')
+if os.path.basename(os.getcwd()) == "notebooks": os.chdir("..")
 
 from workflow_calcium_imaging.pipeline import *
 

notebooks/py_scripts/07-downstream-analysis-optional.py

@@ -5,7 +5,7 @@
 #       extension: .py
 #       format_name: light
 #       format_version: '1.5'
-#       jupytext_version: 1.13.7
+#       jupytext_version: 1.14.1
 #   kernelspec:
 #     display_name: venv-nwb
 #     language: python

workflow_calcium_imaging/pipeline.py

@@ -23,6 +23,7 @@
     "subject",
     "lab",
     "session",
+    "Equipment",
     "trial",
     "event",
     "scan",