FigureCanvas is never shown even when draw is called

Question

I am trying to embed a matplotlib figure in my QT application, using which I want to show different plots upon different user actions.

I have created a custom figure canvas, in which I initialize a figure and a subplot. The code is as followed:

from matplotlib.backends.backend_qt5 import FigureCanvasQT, FigureManagerQT
from PyQt5 import QtWidgets
import matplotlib.pyplot as plt
import numpy as np

class CustomFigureCanvas(FigureCanvasQT):
    def __init__(self, parent=None, cmap_name="coolwarm"):
        fig = plt.Figure()
        self.color_map = plt.get_cmap(cmap_name)
        self.axes = fig.add_subplot(111)
        super().__init__(fig)
        self.setParent(parent)
        self.setBaseSize(300, 300)
        self.setMaximumSize(400, 400)
        self.setMinimumSize(250, 250)
        self.setSizePolicy(
            QtWidgets.QSizePolicy.MinimumExpanding,
            QtWidgets.QSizePolicy.MinimumExpanding,
        )

    def set_clf_2d(self, clf_2d):
        self.clf = clf_2d

    def plot_new_datapoints(self, x2D):
        self.add_datapoint(x2D)

    @staticmethod
    def _make_meshgrid(x, y, h=0.02):
        x_min, x_max = x.min() - 1, x.max() + 1
        y_min, y_max = y.min() - 1, y.max() + 1
        XX, YY = np.meshgrid(
            np.arange(x_min, x_max, h), np.arange(y_min, y_max, h)
        )
        return XX, YY

    def _plot_contours(self, xx, yy, **params):
        """Plot the decision boundaries for a classifier.

        Parameters
        ----------
        ax: matplotlib axes object
        clf: a classifier
        xx: meshgrid ndarray
        yy: meshgrid ndarray
        params: dictionary of params to pass to contourf, optional
        """
        Z = self.clf.predict(np.c_[xx.ravel(), yy.ravel()])
        Z = Z.reshape(xx.shape)
        self.axes.contourf(xx, yy, Z, **params)

    def plot_data(self, x2D, y):
        """plots the given array and the decision function bounday.

        Arguments:
            x2D {np.array} -- [2d array]
            y {np.array} -- [1d array]
        """

        x0, x1 = x2D[:, 0], x2D[:, 1]
        xx, yy = CustomFigureCanvas._make_meshgrid(x0, x1)
        labels = ["Cognitive", "Not Cognitive"]
        colors = ["r", "b"]
        self.axes.clear()
        self._plot_contours(xx, yy, cmap=self.color_map, alpha=0.8)
        target_ids = [0, 1]
        for i, c, label in zip(target_ids, colors, labels):
            print(i, label)
            self.axes.scatter(
                x0[y == i, 0],
                x1[y == i, 1],
                color=c,
                label=label,
                marker="o",
                s=(15, 15),
            )

        self.axes.set_xlim(xx.min(), xx.max())
        self.axes.set_ylim(yy.min(), yy.max())
        self.axes.set_title("2D Representation using PCA")
        self.axes.legend(fontsize=8)
        self.axes.plot()

    def add_datapoint(self, x2d):
        """Adds a new datapoint to the plot

        Arguments:
            x2d {a 2d single point, [x,y]} -- [np.array with shape (1,2)]
            axes {plt.axes} -- [description]

        """
        print(x2d, type(x2d))
        self.axes.scatter(
            x2d[:, 0],
            x2d[:, 1],
            color="k",
            label="Current Text",
            marker="o",
            s=(15, 15),
        )
        self.axes.legend(fontsize=8)

My problem is that whatever I do, my FigureCanvas will always be filled with black, and won't be changed on any circumstances.

By using the CustomFigureCanvas you can reproduce my problem.

FigureCanvas is never shown even when draw is called

Answers (1)

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