Addition of Jupyter notebook

.gitignore

@@ -81,3 +81,4 @@ lib/
 # Output files
 data/*
 !data/.placeholder
+src/tomoscan/.ipynb_checkpoints/setup-checkpoint.ipynb

docker-compose.yml

@@ -102,7 +102,7 @@ services:
       - --pv-prefix
       - "EPAC-DEV:PULSE:"
       - --period
-      - "5"
+      - "2"
       - --epics-time-offset
       - "-0.05"
       - --enable-gate

docs/user/how-to/run-scan.rst

@@ -1,5 +1,9 @@
 Running a scan
 ==================
+Scans can either be run within an IPython terminal or a Jupyter notebook.
+
+IPython terminal
+----------------
 
 * Start the interactive bluesky environment. It is important to mount the output directory and run the container within the same network as the docker-compose environment. This can be achieved by running:
 
@@ -11,6 +15,21 @@ Running a scan
 
 There are two scan modes which are explained below. Outputs from the scan are saved to the data directory.
 
+Jupyter notebook
+-----------------
+
+* Start the Jupyter notebook container, mounting the output directory and the directory containing the example Jupyter notebook. The container must also be run within the same network as the docker-compose environment. Do this by running:
+
+.. code-block:: bash
+
+    docker run -p 8888:8888 -v `pwd`/src/tomoscan:/home/jovyan/work -v `pwd`/data:/home/jovyan/data --net tomoscan_default tomoscan_jupyter
+
+* Copy and paste the URL starting :code:`http://127.0.0.1:8888` that appears in the terminal into a browser to launch the Jupyter server
+* Launch the setup notebook which is found in the work folder
+* Start the phoebus screen to monitor the scan's progress. Navigate to the display folder and run :code:`./startOverview.sh`
+* Follow the steps in the Jupyter notebook
+
+
 Synced scan
 -------------
 In the default setup the pulse generator triggers the laser IOC and then when running the synced scan the motor moves to its next position, waits for the laser PV to

sim/build.sh

@@ -2,7 +2,7 @@
 
 set -e
 
-BUILD_DIRECTORIES="areaDetectorDock motorDock pmac pulsedLaser"
+BUILD_DIRECTORIES="areaDetectorDock motorDock pmac pulsedLaser jupyter"
 
 for DIR in $BUILD_DIRECTORIES; do
 	echo "+--------------------------"

sim/jupyter/Dockerfile

@@ -0,0 +1,7 @@
+#Due to copying a top level file this must be run from the top level directory
+FROM jupyter/base-notebook
+
+#Long term this list should somehow be synced with the bluesky pip install list
+RUN set -ex && pip install h5py bluesky ophyd ipython matplotlib databroker pyepics area-detector-handlers
+RUN mkdir -p ~/.config/databroker
+COPY ./mongo.yml /home/jovyan/.config/databroker/mongo.yml

sim/jupyter/build.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+DIR=$(pwd)
+cd ../..
+docker build -t tomoscan_jupyter -f sim/jupyter/Dockerfile .
+cd $DIR

src/tomoscan/setup.ipynb

@@ -0,0 +1,96 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First the detector, laser and motor are setup along with the bluesky environment from the ophyd_inter_setup file.\n",
+    "Due to the different file structure of the Jupyter notebook the read path must be updated.\n",
+    "An error related to caRepeater will likely appear, this is not a concern."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from ophyd_inter_setup import *\n",
+    "det.hdf1.read_path_template =  \"/home/jovyan/data/%Y/%m/%d/\"  "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The synced scan can then be run. This example scans in 11 steps between -10 and +10."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "uids = RE(pulse_sync([det], motor1, laser1, -10, 10, 11))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To access the data stored in the databroker catalog run the following:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "run = catalog[uids[0]] #Accesses the run based on its uid, the most recent run can also be accessed as catalog[-1]\n",
+    "data = run.primary.read()\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The image data is accessed as shown below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "image = data[\"det_image\"]\n",
+    "frame = image[0][0]  # Index 1 refers to the time of the image and the second index refers to the frame number\n",
+    "frame.plot.pcolormesh()"
+   ]
+  }
+ ],
+ "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": 4
+}