autowisp.browser_interface.diagnostics.image_diagnostics_views module

Class Inheritance Diagram

Views for displaying per-image diagnostics.

autowisp.browser_interface.diagnostics.image_diagnostics_views.create_figure(num_plots, plot_height_frac, aspect_ratio, num_columns)

Create the figure for the diagnostics plot per given configuration.

autowisp.browser_interface.diagnostics.image_diagnostics_views.create_image_diagnostics_figure(series_list, *, diagnostic_name, db_session, figure_config=None)

Create a multi-panel figure for the selected image diagnostic series.

Parameters:

• series_list (list) – Series entries (as produced by get_available_diagnostic_series()) to plot. Only entries whose marker is non-empty are plotted.

• diagnostic_name (str) – The diagnostic type name, or "quantiles".

• db_session – An active SQLAlchemy database session.

• figure_config (dict) –

  Configuration for the layout of the figure. Should define:

  plot_height_frac(float): Height of each subplot row as a

  fraction of the available screen area.

  num_columns(int): Number of columns in the subplot grid.

  aspect_ratio(float): Width / height of the available screen

  area.

  By default, height fraction is 1/3, number of columns is 1, and aspect ratio is 5.0.

Returns:

The completed figure.

Return type:

matplotlib.figure.Figure

autowisp.browser_interface.diagnostics.image_diagnostics_views.display_image_diagnostics(request, diagnostic_name)

View displaying the table of available series for an image diagnostic.

autowisp.browser_interface.diagnostics.image_diagnostics_views.download_plot_view(request, figure_factory, session_key, **url_kwargs)

Return the last-plotted figure as a PDF download.

Reads the plot configuration stored in the session by a previous call to update_plot_view() and regenerates the figure in PDF format.

Parameters:

• request – Django HTTP request.

• figure_factory – Same factory used by the corresponding update view.

• session_key – Session key where update_plot_view() stored the last POST data.

Returns:

HttpResponse with PDF content.

autowisp.browser_interface.diagnostics.image_diagnostics_views.get_available_diagnostic_series(diagnostic_name, db_session)

Return the observing sessions and channels with data for a diagnostic.

Queries for distinct (observing_session, channel) pairs that have at least one value for the given diagnostic name.

Parameters:

• diagnostic_name (str) – The name of the diagnostic to query (must match a DiagnosticType row).

• db_session – An active SQLAlchemy database session.

Returns:

A dictionary with two keys:

diagnostics_fields:

A list of column header strings for the extra table columns in the diagnostics_app.html template.

diagnostics_list:

A list of dicts, one per (observing session, channel) pair, each containing the keys id, color, marker, scale, label, and info (a list of values matching diagnostics_fields).

Return type:

dict

autowisp.browser_interface.diagnostics.image_diagnostics_views.get_available_diagnostics(db_session)

Return the list of diagnostic names that have at least one value.

autowisp.browser_interface.diagnostics.image_diagnostics_views.get_diagnostic_series_data(series, diagnostic_name, db_session)

Query the JD and diagnostic values for a single series.

Parameters:

• series (dict) – A series entry as produced by get_available_diagnostic_series().

• diagnostic_name (str) – The diagnostic type name to query, or "quantiles" (in which case the quantile name is extracted from the series id).

• db_session – An active SQLAlchemy database session.

Returns:

(jd_values, diag_values, image_ids) as tuples of

floats/ints, ordered by JD. Empty tuples if no data is found.

Return type:

tuple

autowisp.browser_interface.diagnostics.image_diagnostics_views.group_series_by_jd_overlap(series_data)

Group diagnostic series into sets that share overlapping JD ranges.

Series with the same diagnostic whose JD ranges overlap are grouped together (to be plotted on the same axes). Series with non-overlapping ranges end up in separate groups.

Parameters:

series_data (list) – A list of (series, jd_values, diag_values, image_ids) tuples, where jd_values are ordered sequences of Julian dates.

Returns:

A list of lists, each inner list containing

(series, jd_values, diag_values) tuples that should be plotted on the same axes.

Return type:

list

autowisp.browser_interface.diagnostics.image_diagnostics_views.plot_image_diagnostic_series(axes, time_values, diag_values, image_ids, config)

Plot a single image diagnostic series on the given axes.

Parameters:

• axes – A matplotlib Axes to plot on.

• time_values – Sequence of Julian date x-coordinates.

• diag_values – Sequence of diagnostic y-coordinates.

• config (dict) – Configuration for the plotting usually produce by get_available_diagnostic_series(). Should contain keys channel, color, marker, scale, and label.

autowisp.browser_interface.diagnostics.image_diagnostics_views.update_plot_view(request, figure_factory, session_key=None, **url_kwargs)

Common handler for diagnostics AJAX plot-update views.

Parses the JSON POST body, calls figure_factory to produce the figure, and returns an SVG JsonResponse.

Parameters:

• request – Django HTTP request whose body is a JSON object with a datasets dict (keyed by series id) and an optional figure_config dict.

• figure_factory – Callable accepting series_list, db_session, figure_config, plus any URL kwargs as keyword arguments.

• session_key – If given, the raw POST data is stored in the session under this key so a download view can retrieve it.

Returns:

JsonResponse with plot_data containing the SVG string.