Merge pull request #278 from ISISComputingGroup/Ticket156_replot_scans

Document how to replay documents into new callbacks (e.g. how to replot a scan)

Author: rerpha

doc/callbacks/plotting.md

@@ -110,3 +110,7 @@ def plan():
     # Add a PNG saving callback
     png_callback = PlotPNGSaver(y="y_variable", x="x_variable", ax=ax, output_dir=Path("C://", "Some", "Custom", "Directory"), postfix="test123")
 ```
+
+## Replotting a previous scan
+
+See {doc}`/replotting_scans` for information about how to replay bluesky documents into an arbitrary set of callbacks, which can be used to replot a previous scan.

doc/conf.py

@@ -92,4 +92,5 @@
     "matplotlib": ("https://matplotlib.org", None),
     "lmfit": ("https://lmfit.github.io/lmfit-py/", None),
     "typing_extensions": ("https://typing-extensions.readthedocs.io/en/latest/", None),
+    "ibex_user_manual": ("https://isiscomputinggroup.github.io/ibex_user_manual/", None),
 }

doc/index.md

@@ -71,6 +71,7 @@ plan_stubs/*
 :caption: Reference
 
 _api
+replotting_scans
 architectural_decisions
 developer_information
 ```

doc/replotting_scans.md

@@ -0,0 +1,56 @@
+# Replaying documents
+
+All {external+bluesky:doc}`callbacks <callbacks>` in bluesky operate on a data structure called a {external+bluesky:doc}`document <documents>`. These documents represent the metadata and data emitted by a bluesky scan.
+
+```{tip}
+The schema of these documents is defined formally by the bluesky {external+event_model:doc}`event model <explanations/data-model>`. However, the implementation details of these documents are not important for simply replaying them.
+
+If instead you wish to write a tool to consume bluesky documents _without_ using the callbacks provided in this library or in bluesky, please {external+ibex_user_manual:ref}`get in touch with experiment controls <report_a_problem>` for advice.
+```
+
+All bluesky {external+bluesky:doc}`callbacks <callbacks>` consume {external+bluesky:doc}`documents <documents>` as their source of data or metadata. This means that historic documents can be replayed into one or more callbacks. This facilitates:
+- Replaying documents into plotting callbacks to 'replot' a scan
+- Replaying documents into (potentially different) fitting callbacks, to experiment with different fitting routines
+- Developing entirely new callbacks using data from historic scans
+
+## Document storage and replay from file
+
+The IBEX {py:obj}`RunEngine <ibex_bluesky_core.run_engine.get_run_engine>` instance is configured to automatically save the raw documents from any scan - these are saved into
+```
+c:\Instrument\var\logs\bluesky\raw_documents
+```
+They are subsequently moved to a backups area after 10 days; if you need access to old scans, please contact experiment controls for the exact path you will need.
+
+These files are organised as line-delimited JSON dictionaries. The filename is the unique identifier of the scan.
+
+Documents can be loaded from their save files and replayed into arbitrary callbacks - which can be a completely different set of callbacks than were used during the scan. The following example shows replay into a {py:obj}`LivePlot <ibex_bluesky_core.callbacks.LivePlot>` callback to regenerate a matplotlib plot, as well as re-running a Gaussian fit using the {py:obj}`LiveFit <ibex_bluesky_core.callbacks.LiveFit>` callback and displaying that on the plot using {external+bluesky:py:obj}`LiveFitPlot <bluesky.callbacks.mpl_plotting.LiveFitPlot>`.
+
+```python
+import json
+import matplotlib.pyplot as plt
+from ibex_bluesky_core.callbacks import LivePlot, LiveFit
+from ibex_bluesky_core.fitting import Gaussian
+from bluesky.callbacks import LiveFitPlot
+
+
+def replot_scan(path_to_save_file: str, y_name: str, x_name: str):
+    # Prepare a set of matplotlib axes to plot onto
+    plt.close("all")
+    plt.show()
+    _, ax = plt.subplots()
+
+    # Example callbacks for plotting and fitting - the exact callbacks
+    # to use when replotting a scan can be chosen freely.
+    live_plot = LivePlot(y_name, x_name, marker="x", linestyle="none", ax=ax)
+    live_fit = LiveFit(Gaussian.fit(), y=y_name, x=x_name)
+    live_fit_plot = LiveFitPlot(livefit=live_fit, ax=ax, num_points=10000)
+
+    # Open the relevant save-file
+    with open(path_to_save_file) as f:
+        for line in f:
+            # Load the JSON representation of this document.
+            document = json.loads(line)
+            # Pass the document to arbitrary callbacks.
+            live_plot(document["type"], document["document"])
+            live_fit_plot(document["type"], document["document"])
+```