Fixes for plots popping up in RasCAL

Author: StephenNneji

ratapi/utils/plotting.py

@@ -94,7 +94,7 @@ def _extract_plot_data(event_data: PlotEventData, q4: bool, show_error_bar: bool
 
 def plot_ref_sld_helper(
     data: PlotEventData,
-    fig: Optional[matplotlib.pyplot.figure] = None,
+    fig: matplotlib.pyplot.figure,
     delay: bool = True,
     confidence_intervals: Union[dict, None] = None,
     linear_x: bool = False,
@@ -112,8 +112,8 @@ def plot_ref_sld_helper(
     data : PlotEventData
         The plot event data that contains all the information
         to generate the ref and sld plots
-    fig : matplotlib.pyplot.figure, optional
-        The figure class that has two subplots
+    fig : matplotlib.pyplot.figure
+        The figure object that has two subplots
     delay : bool, default: True
         Controls whether to delay 0.005s after plot is created
     confidence_intervals : dict or None, default None
@@ -134,19 +134,13 @@ def plot_ref_sld_helper(
     animated : bool, default: False
         Controls whether the animated property of foreground plot elements should be set.
 
-    Returns
-    -------
-    fig : matplotlib.pyplot.figure
-        The figure class that has two subplots
-
     """
     preserve_zoom = False
 
-    if fig is None:
-        fig = plt.subplots(1, 2)[0]
-    elif len(fig.axes) != 2:
+    if len(fig.axes) != 2:
         fig.clf()
         fig.subplots(1, 2)
+
     fig.subplots_adjust(wspace=0.3)
 
     ref_plot: plt.Axes = fig.axes[0]
@@ -233,13 +227,12 @@ def plot_ref_sld_helper(
     if delay:
         plt.pause(0.005)
 
-    return fig
-
 
 def plot_ref_sld(
     project: ratapi.Project,
     results: Union[ratapi.outputs.Results, ratapi.outputs.BayesResults],
     block: bool = False,
+    fig: Optional[matplotlib.pyplot.figure] = None,
     return_fig: bool = False,
     bayes: Literal[65, 95, None] = None,
     linear_x: bool = False,
@@ -259,6 +252,8 @@ def plot_ref_sld(
               The result from the calculation
     block : bool, default: False
             Indicates the plot should block until it is closed
+    fig : matplotlib.pyplot.figure, optional
+        The figure object that has two subplots
     return_fig : bool, default False
         If True, return the figure instead of displaying it.
     bayes : 65, 95 or None, default None
@@ -336,11 +331,15 @@ def plot_ref_sld(
     else:
         confidence_intervals = None
 
-    figure = plt.subplots(1, 2)[0]
+    if fig is None:
+        fig = plt.subplots(1, 2)[0]
+    elif len(fig.axes) != 2:
+        fig.clf()
+        fig.subplots(1, 2)
 
     plot_ref_sld_helper(
         data,
-        figure,
+        fig,
         confidence_intervals=confidence_intervals,
         linear_x=linear_x,
         q4=q4,
@@ -351,7 +350,7 @@ def plot_ref_sld(
     )
 
     if return_fig:
-        return figure
+        return fig
 
     plt.show(block=block)
 
@@ -486,7 +485,7 @@ def update_plot(self, data):
         """
         if self.figure is not None:
             self.figure.clf()
-        self.figure = ratapi.plotting.plot_ref_sld_helper(
+        plot_ref_sld_helper(
             data,
             self.figure,
             linear_x=self.linear_x,
@@ -520,7 +519,7 @@ def update_foreground(self, data):
         """
         self.set_animated(True)
         self.figure.canvas.restore_region(self.bg)
-        plot_data = ratapi.plotting._extract_plot_data(data, self.q4, self.show_error_bar, self.shift_value)
+        plot_data = _extract_plot_data(data, self.q4, self.show_error_bar, self.shift_value)
 
         offset = 2 if self.show_error_bar else 1
         for i in range(
@@ -649,6 +648,7 @@ def plot_corner(
     params: Union[list[Union[int, str]], None] = None,
     smooth: bool = True,
     block: bool = False,
+    fig: Optional[matplotlib.pyplot.figure] = None,
     return_fig: bool = False,
     hist_kwargs: Union[dict, None] = None,
     hist2d_kwargs: Union[dict, None] = None,
@@ -666,6 +666,8 @@ def plot_corner(
         Whether to apply Gaussian smoothing to the corner plot.
     block : bool, default False
         Whether Python should block until the plot is closed.
+    fig : matplotlib.pyplot.figure, optional
+        The figure object to use for plot.
     return_fig: bool, default False
         If True, return the figure as an object instead of showing it.
     hist_kwargs : dict
@@ -696,7 +698,12 @@ def plot_corner(
 
     num_params = len(params)
 
-    fig, axes = plt.subplots(num_params, num_params, figsize=(11, 10))
+    if fig is None:
+        fig, axes = plt.subplots(num_params, num_params, figsize=(11, 10))
+    else:
+        fig.clf()
+        axes = fig.subplots(num_params, num_params)
+
     # i is row, j is column
     for i, row_param in enumerate(params):
         for j, col_param in enumerate(params):
@@ -956,7 +963,9 @@ def plot_contour(
         plt.show(block=block)
 
 
-def panel_plot_helper(plot_func: Callable, indices: list[int]) -> matplotlib.figure.Figure:
+def panel_plot_helper(
+    plot_func: Callable, indices: list[int], fig: Optional[matplotlib.pyplot.figure] = None
+) -> matplotlib.figure.Figure:
     """Generate a panel-based plot from a single plot function.
 
     Parameters
@@ -965,6 +974,8 @@ def panel_plot_helper(plot_func: Callable, indices: list[int]) -> matplotlib.fig
         A function which plots one parameter on an Axes object, given its index.
     indices : list[int]
         The list of indices to pass into ``plot_func``.
+    fig : matplotlib.pyplot.figure, optional
+        The figure object to use for plot.
 
     Returns
     -------
@@ -974,10 +985,18 @@ def panel_plot_helper(plot_func: Callable, indices: list[int]) -> matplotlib.fig
     """
     nplots = len(indices)
     nrows, ncols = ceil(sqrt(nplots)), round(sqrt(nplots))
-    fig = plt.subplots(nrows, ncols, figsize=(11, 10))[0]
+
+    if fig is None:
+        fig = plt.subplots(nrows, ncols, figsize=(11, 10))[0]
+    else:
+        fig.clf()
+        fig.subplots(nrows, ncols)
     axs = fig.get_axes()
 
     for plot_num, index in enumerate(indices):
+        axs[plot_num].tick_params(which="both", labelsize="medium")
+        axs[plot_num].xaxis.offsetText.set_fontsize("small")
+        axs[plot_num].yaxis.offsetText.set_fontsize("small")
         plot_func(axs[plot_num], index)
 
     # blank unused plots
@@ -998,6 +1017,7 @@ def plot_hists(
         dict[Literal["normal", "lognor", "kernel", None]], Literal["normal", "lognor", "kernel", None]
     ] = None,
     block: bool = False,
+    fig: Optional[matplotlib.pyplot.figure] = None,
     return_fig: bool = False,
     **hist_settings,
 ):
@@ -1031,6 +1051,8 @@ def plot_hists(
         e.g. to apply 'normal' to all unset parameters, set `estimated_density = {'default': 'normal'}`.
     block : bool, default False
         Whether Python should block until the plot is closed.
+    fig : matplotlib.pyplot.figure, optional
+        The figure object to use for plot.
     return_fig: bool, default False
         If True, return the figure as an object instead of showing it.
     hist_settings :
@@ -1090,6 +1112,7 @@ def validate_dens_type(dens_type: Union[str, None], param: str):
             **hist_settings,
         ),
         params,
+        fig,
     )
     if return_fig:
         return fig
@@ -1102,6 +1125,7 @@ def plot_chain(
     params: Union[list[Union[int, str]], None] = None,
     maxpoints: int = 15000,
     block: bool = False,
+    fig: Optional[matplotlib.pyplot.figure] = None,
     return_fig: bool = False,
 ):
     """Plot the MCMC chain for each parameter of a Bayesian analysis.
@@ -1117,6 +1141,8 @@ def plot_chain(
         The maximum number of points to plot for each parameter.
     block : bool, default False
         Whether Python should block until the plot is closed.
+    fig : matplotlib.pyplot.figure, optional
+        The figure object to use for plot.
     return_fig: bool, default False
         If True, return the figure as an object instead of showing it.
 
@@ -1142,9 +1168,9 @@ def plot_chain(
 
     def plot_one_chain(axes: Axes, i: int):
         axes.plot(range(0, nsimulations, skip), chain[:, i][0:nsimulations:skip])
-        axes.set_title(results.fitNames[i])
+        axes.set_title(results.fitNames[i], fontsize="small")
 
-    fig = panel_plot_helper(plot_one_chain, params)
+    fig = panel_plot_helper(plot_one_chain, params, fig=fig)
     if return_fig:
         return fig
     plt.show(block=block)

tests/test_controls.py

@@ -2,8 +2,8 @@
 
 import contextlib
 import os
-from pathlib import Path
 import tempfile
+from pathlib import Path
 from typing import Any, Union
 
 import pydantic
@@ -45,14 +45,15 @@ def test_extra_property_error() -> None:
     with pytest.raises(pydantic.ValidationError, match="Object has no attribute 'test'"):
         controls.test = 1
 
+
 @pytest.mark.parametrize(
     "inputs",
     [
-        {"parallel": Parallel.Contrasts, "resampleMinAngle":  0.66},
-        {"procedure": 'simplex'},
-        {"procedure": 'dream', "nSamples": 504, "nChains": 1200},
-        {"procedure": 'de', "crossoverProbability": 0.45, "strategy": Strategies.RandomEitherOrAlgorithm},
-        {"procedure": 'ns', "nMCMC": 4, "propScale": 0.6},
+        {"parallel": Parallel.Contrasts, "resampleMinAngle": 0.66},
+        {"procedure": "simplex"},
+        {"procedure": "dream", "nSamples": 504, "nChains": 1200},
+        {"procedure": "de", "crossoverProbability": 0.45, "strategy": Strategies.RandomEitherOrAlgorithm},
+        {"procedure": "ns", "nMCMC": 4, "propScale": 0.6},
     ],
 )
 def test_save_load(inputs):
@@ -68,6 +69,7 @@ def test_save_load(inputs):
     for field in Controls.model_fields:
         assert getattr(converted_controls, field) == getattr(original_controls, field)
 
+
 class TestCalculate:
     """Tests the Calculate class."""
 

tests/test_plotting.py

@@ -50,7 +50,8 @@ def fig(request) -> plt.figure:
     """Creates the fixture for the tests."""
     plt.close("all")
     figure = plt.subplots(1, 2)[0]
-    return RATplot.plot_ref_sld_helper(fig=figure, data=domains_data() if request.param else data())
+    RATplot.plot_ref_sld_helper(fig=figure, data=domains_data() if request.param else data())
+    return figure
 
 
 @pytest.fixture
@@ -68,7 +69,8 @@ def bayes_fig(request) -> plt.figure:
             for sld in dat.sldProfiles
         ],
     }
-    return RATplot.plot_ref_sld_helper(data=dat, fig=figure, confidence_intervals=confidence_intervals)
+    RATplot.plot_ref_sld_helper(data=dat, fig=figure, confidence_intervals=confidence_intervals)
+    return figure
 
 
 @pytest.mark.parametrize("fig", [False, True], indirect=True)
@@ -120,8 +122,7 @@ def test_ref_sld_color_formatting(fig: plt.figure) -> None:
         assert sld_plot.get_lines()[i].get_color() == sld_plot.get_lines()[i + 1].get_color()
 
 
-@pytest.mark.parametrize("bayes", [65, 95])
-def test_ref_sld_bayes(fig, bayes_fig, bayes):
+def test_ref_sld_bayes(fig, bayes_fig):
     """Test that shading is correctly added to the figure when confidence intervals are supplied."""
     # the shading is of type PolyCollection
     for axes in fig.axes:
@@ -137,7 +138,7 @@ def test_sld_profile_function_call(mock: MagicMock) -> None:
     """Tests the makeSLDProfile function called with
     correct args.
     """
-    RATplot.plot_ref_sld_helper(data())
+    RATplot.plot_ref_sld_helper(data(), plt.subplots(1, 2)[0])
 
     assert mock.call_count == 3
     assert mock.call_args_list[0].args[0] == 2.07e-06
@@ -211,9 +212,9 @@ def test_plot_ref_sld(mock: MagicMock, input_project, reflectivity_calculation_r
 def test_ref_sld_subplot_correction():
     """Test that if an incorrect number of subplots is corrected in the figure helper."""
     fig = plt.subplots(1, 3)[0]
-    ref_sld_fig = RATplot.plot_ref_sld_helper(data=data(), fig=fig)
-    assert ref_sld_fig.axes[0].get_subplotspec().get_gridspec().get_geometry() == (1, 2)
-    assert len(ref_sld_fig.axes) == 2
+    RATplot.plot_ref_sld_helper(data=data(), fig=fig)
+    assert fig.axes[0].get_subplotspec().get_gridspec().get_geometry() == (1, 2)
+    assert len(fig.axes) == 2
 
 
 @patch("ratapi.utils.plotting.plot_ref_sld_helper")