Adds live plot context manager and update events

RATapi/events.py

@@ -57,11 +57,26 @@ def register(event_type: EventTypes, callback: Callable[[Union[str, PlotEventDat
     __event_callbacks[event_type].add(callback)
 
 
-def clear() -> None:
-    """Clears all event callbacks."""
-    __event_impl.clear()
-    for key in __event_callbacks:
-        __event_callbacks[key] = set()
+def clear(key=None, callback=None) -> None:
+    """Clears all event callbacks or specific callback.
+
+    Parameters
+    ----------
+    callback : Callable[[Union[str, PlotEventData, ProgressEventData]], None]
+        The callback for when the event is triggered.
+
+    """
+    if key is None and callback is None:
+        for key in __event_callbacks:
+            __event_callbacks[key] = set()
+    elif key is not None and callback is not None:
+        __event_callbacks[key].remove(callback)
+
+    for value in __event_callbacks.values():
+        if value:
+            break
+    else:
+        __event_impl.clear()
 
 
 dir_path = os.path.dirname(os.path.realpath(__file__))

RATapi/examples/domains/alloy_domains.py

@@ -18,7 +18,7 @@ def alloy_domains(params, bulkIn, bulkOut, contrast, domain):
     gold = [goldThick, goldSLD, goldRough]
 
     # Make the model depending on which domain we are looking at
-    if domain == 1:
+    if domain == 0:
         output = [alloyUp, gold]
     else:
         output = [alloyDn, gold]

RATapi/examples/domains/domains_XY_model.py

@@ -33,7 +33,7 @@ def domains_XY_model(params, bulk_in, bulk_out, contrast, domain):
     oxSLD = vfOxide * 3.41e-6
 
     # Layer SLD depends on whether we are calculating the domain or not
-    if domain == 1:
+    if domain == 0:
         laySLD = vfLayer * layerSLD
     else:
         laySLD = vfLayer * domainSLD

RATapi/utils/plotting.py

@@ -2,6 +2,7 @@
 
 from typing import Optional, Union
 
+import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
 from matplotlib.axes._axes import Axes
@@ -12,45 +13,6 @@
 from RATapi.rat_core import PlotEventData, makeSLDProfileXY
 
 
-class Figure:
-    """Creates a plotting figure."""
-
-    def __init__(self, row: int = 1, col: int = 1):
-        """Initializes the figure and the subplots.
-
-        Parameters
-        ----------
-        row : int, default: 1
-              The number of rows in subplot
-        col : int, default: 1
-              The number of columns in subplot
-
-        """
-        self._fig, self._ax = plt.subplots(row, col, num="Reflectivity Algorithms Toolbox (RAT)")
-        plt.show(block=False)
-        self._esc_pressed = False
-        self._close_clicked = False
-        self._fig.canvas.mpl_connect("key_press_event", self._process_button_press)
-        self._fig.canvas.mpl_connect("close_event", self._close)
-
-    def wait_for_close(self):
-        """Waits for the user to close the figure
-        using the esc key.
-        """
-        while not (self._esc_pressed or self._close_clicked):
-            plt.waitforbuttonpress(timeout=0.005)
-        plt.close(self._fig)
-
-    def _process_button_press(self, event):
-        """Process the key_press_event."""
-        if event.key == "escape":
-            self._esc_pressed = True
-
-    def _close(self, _):
-        """Process the close_event."""
-        self._close_clicked = True
-
-
 def plot_errorbars(ax: Axes, x: np.ndarray, y: np.ndarray, err: np.ndarray, one_sided: bool, color: str):
     """Plots the error bars.
 
@@ -75,33 +37,38 @@ def plot_errorbars(ax: Axes, x: np.ndarray, y: np.ndarray, err: np.ndarray, one_
     ax.scatter(x=x, y=y, s=3, marker="o", color=color)
 
 
-def plot_ref_sld_helper(data: PlotEventData, fig: Optional[Figure] = None, delay: bool = True):
+def plot_ref_sld_helper(data: PlotEventData, fig: Optional[matplotlib.pyplot.figure] = None, delay: bool = True):
     """Clears the previous plots and updates the ref and SLD plots.
 
     Parameters
     ----------
     data : PlotEventData
            The plot event data that contains all the information
            to generate the ref and sld plots
-    fig : Figure, optional
+    fig : matplotlib.pyplot.figure, optional
           The figure class that has two subplots
     delay : bool, default: True
             Controls whether to delay 0.005s after plot is created
 
     Returns
     -------
-    fig : Figure
+    fig : matplotlib.pyplot.figure
           The figure class that has two subplots
 
     """
+    preserve_zoom = False
+
     if fig is None:
-        fig = Figure(1, 2)
-    elif fig._ax.shape != (2,):
-        fig._fig.clf()
-        fig._ax = fig._fig.subplots(1, 2)
+        fig = plt.subplots(1, 2)[0]
+    elif len(fig.axes) != 2:
+        fig.clf()
+        fig.subplots(1, 2)
 
-    ref_plot = fig._ax[0]
-    sld_plot = fig._ax[1]
+    ref_plot = fig.axes[0]
+    sld_plot = fig.axes[1]
+    if ref_plot.lines and fig.canvas.toolbar is not None:
+        preserve_zoom = True
+        fig.canvas.toolbar.push_current()
 
     # Clears the previous plots
     ref_plot.cla()
@@ -170,6 +137,8 @@ def plot_ref_sld_helper(data: PlotEventData, fig: Optional[Figure] = None, delay
     sld_plot.legend()
     sld_plot.grid()
 
+    if preserve_zoom:
+        fig.canvas.toolbar.back()
     if delay:
         plt.pause(0.005)
 
@@ -204,8 +173,52 @@ def plot_ref_sld(
     data.subRoughs = results.contrastParams.subRoughs
     data.resample = RATapi.inputs.make_resample(project)
 
-    figure = Figure(1, 2)
+    figure = plt.subplots(1, 2)[0]
 
     plot_ref_sld_helper(data, figure)
-    if block:
-        figure.wait_for_close()
+
+    plt.show(block=block)
+
+
+class LivePlot:
+    """Creates a plot that gets updates from the plot event during a
+    calculation
+
+    Parameters
+    ----------
+    block : bool, default: False
+            Indicates the plot should block until it is closed
+
+    """
+
+    def __init__(self, block=False):
+        self.block = block
+        self.closed = False
+
+    def __enter__(self):
+        self.figure = plt.subplots(1, 2)[0]
+        self.figure.canvas.mpl_connect("close_event", self._setCloseState)
+        self.figure.show()
+        RATapi.events.register(RATapi.events.EventTypes.Plot, self.plotEvent)
+
+        return self.figure
+
+    def _setCloseState(self, _):
+        """Close event handler"""
+        self.closed = True
+
+    def plotEvent(self, event):
+        """Callback for the plot event.
+
+        Parameters
+        ----------
+        event: PlotEventData
+            The plot event data.
+        """
+        if not self.closed and self.figure.number in plt.get_fignums():
+            plot_ref_sld_helper(event, self.figure)
+
+    def __exit__(self, _exc_type, _exc_val, _traceback):
+        RATapi.events.clear(RATapi.events.EventTypes.Plot, self.plotEvent)
+        if not self.closed and self.figure.number in plt.get_fignums():
+            plt.show(block=self.block)

cpp/rat.cpp

@@ -192,27 +192,34 @@ class EventBridge
     };
 
     py::list unpackDataToCell(int rows, int cols, double* data, double* nData, 
-                              double* data2, double* nData2, int dataCol)   
+                              double* data2, double* nData2, bool isOutput2D=false)   
     {
         py::list allResults;
-        int dims[2] = {0, dataCol};
+        int dims[2] = {0, 0};
         int offset = 0;
         for (int i = 0; i < rows; i++){
-            py::list rowList;
-            dims[0] = (int)nData[i] / dataCol;
+            dims[0] = (int)nData[2*i];
+            dims[1] = (int)nData[2*i+1];
             auto result = py::array_t<double,  py::array::f_style>({dims[0], dims[1]});
             std::memcpy(result.request().ptr, data + offset, result.nbytes());
             offset += result.size();
-            rowList.append(result);
-            allResults.append(rowList);
+            if (isOutput2D){
+                py::list rowList;
+                rowList.append(result);
+                allResults.append(rowList);
+            }
+            else{
+                allResults.append(result);
+            }
         }
 
         if (data2 != NULL && nData2 != NULL)
         {
             // This is used to unpack the domains data into the second column 
             offset = 0;
             for ( int i = 0; i < rows; i++){
-                dims[0] = (int)nData2[i] / dataCol;
+                dims[0] = (int)nData2[2*i];
+                dims[1] = (int)nData2[2*i+1];
                 auto result = py::array_t<double,  py::array::f_style>({dims[0], dims[1]});
                 std::memcpy(result.request().ptr, data2 + offset, result.nbytes());
                 offset +=  result.size();
@@ -252,18 +259,18 @@ class EventBridge
             std::memcpy(eventData.dataPresent.request().ptr, pEvent->data->dataPresent, eventData.dataPresent.nbytes());
 
             eventData.reflectivity = unpackDataToCell(pEvent->data->nContrast, 1, 
-                                                      pEvent->data->reflect, pEvent->data->nReflect, NULL, NULL, 2);
+                                                      pEvent->data->reflect, pEvent->data->nReflect, NULL, NULL);
 
             eventData.shiftedData = unpackDataToCell(pEvent->data->nContrast, 1, 
-                                                     pEvent->data->shiftedData, pEvent->data->nShiftedData, NULL, NULL, 3);
+                                                     pEvent->data->shiftedData, pEvent->data->nShiftedData, NULL, NULL);
 
             eventData.sldProfiles = unpackDataToCell(pEvent->data->nContrast, (pEvent->data->nSldProfiles2 == NULL) ? 1 : 2,
                                                      pEvent->data->sldProfiles, pEvent->data->nSldProfiles, 
-                                                     pEvent->data->sldProfiles2, pEvent->data->nSldProfiles2, 2);
-
+                                                     pEvent->data->sldProfiles2, pEvent->data->nSldProfiles2, true);
+            
             eventData.resampledLayers = unpackDataToCell(pEvent->data->nContrast, (pEvent->data->nLayers2 == NULL) ? 1 : 2, 
-                                                   pEvent->data->layers, pEvent->data->nLayers, 
-                                                   pEvent->data->layers2, pEvent->data->nLayers, 2);
+                                                         pEvent->data->layers, pEvent->data->nLayers, 
+                                                         pEvent->data->layers2, pEvent->data->nLayers2, true);
             this->callback(event.type, eventData);
         }
     };

tests/test_events.py

@@ -25,6 +25,11 @@ def test_event_register() -> None:
         [first_callback, second_callback]
     )
 
+    RATapi.events.clear(RATapi.events.EventTypes.Message, second_callback)
+    result = RATapi.events.get_event_callback(RATapi.events.EventTypes.Message)
+    assert result == [first_callback]
+    result = RATapi.events.get_event_callback(RATapi.events.EventTypes.Plot)
+    assert result == [second_callback]
     RATapi.events.clear()
     assert RATapi.events.get_event_callback(RATapi.events.EventTypes.Plot) == []
     assert RATapi.events.get_event_callback(RATapi.events.EventTypes.Message) == []