import PySimpleGUI as sg import numpy as np from matplotlib.backends.backend_tkagg import FigureCanvasAgg import matplotlib.figure import matplotlib.pyplot as plt import io from matplotlib import cm from mpl_toolkits.mplot3d.axes3d import get_test_data from matplotlib.ticker import NullFormatter # useful for `logit` scale """ Demo - Matplotlib Non-interactive Embedded with Theme and Style selection This demo is based on the Matplotlib "TEMPLATE" demo that is a general purpose, display-only demo as only the image of the plot is shown. None of the buttons and interactive parts of the MAtplotlib interface are included. This demo adds the ability to change the Window's "Theme" and the Matplotlib's "Style". It gives you a way to quickly see how well a theme is going to match a particular Matplotlib Style. Copyright 2020 PySimpleGUI.org """ def create_axis_grid(): from mpl_toolkits.axes_grid1.axes_rgb import RGBAxes plt.close('all') def get_demo_image(): # prepare image delta = 0.5 extent = (-3, 4, -4, 3) x = np.arange(-3.0, 4.001, delta) y = np.arange(-4.0, 3.001, delta) X, Y = np.meshgrid(x, y) Z1 = np.exp(-X ** 2 - Y ** 2) Z2 = np.exp(-(X - 1) ** 2 - (Y - 1) ** 2) Z = (Z1 - Z2) * 2 return Z, extent def get_rgb(): Z, extent = get_demo_image() Z[Z < 0] = 0. Z = Z / Z.max() R = Z[:13, :13] G = Z[2:, 2:] B = Z[:13, 2:] return R, G, B fig = plt.figure(1) ax = RGBAxes(fig, [0.1, 0.1, 0.8, 0.8]) r, g, b = get_rgb() kwargs = dict(origin="lower", interpolation="nearest") ax.imshow_rgb(r, g, b, **kwargs) ax.RGB.set_xlim(0., 9.5) ax.RGB.set_ylim(0.9, 10.6) plt.draw() return plt.gcf() def create_figure(): # ------------------------------- START OF YOUR MATPLOTLIB CODE ------------------------------- fig = matplotlib.figure.Figure(figsize=(5, 4), dpi=100) t = np.arange(0, 3, .01) fig.add_subplot(111).plot(t, 2 * np.sin(2 * np.pi * t)) return fig def create_subplot_3d(): fig = plt.figure() ax = fig.add_subplot(1, 2, 1, projection='3d') X = np.arange(-5, 5, 0.25) Y = np.arange(-5, 5, 0.25) X, Y = np.meshgrid(X, Y) R = np.sqrt(X ** 2 + Y ** 2) Z = np.sin(R) surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet, linewidth=0, antialiased=False) ax.set_zlim3d(-1.01, 1.01) fig.colorbar(surf, shrink=0.5, aspect=5) ax = fig.add_subplot(1, 2, 2, projection='3d') X, Y, Z = get_test_data(0.05) ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10) return fig def create_pyplot_scales(): plt.close('all') # Fixing random state for reproducibility np.random.seed(19680801) # make up some data in the interval ]0, 1[ y = np.random.normal(loc=0.5, scale=0.4, size=1000) y = y[(y > 0) & (y < 1)] y.sort() x = np.arange(len(y)) # plot with various axes scales plt.figure(1) # linear plt.subplot(221) plt.plot(x, y) plt.yscale('linear') plt.title('linear') plt.grid(True) # log plt.subplot(222) plt.plot(x, y) plt.yscale('log') plt.title('log') plt.grid(True) # symmetric log plt.subplot(223) plt.plot(x, y - y.mean()) plt.yscale('symlog', linthreshy=0.01) plt.title('symlog') plt.grid(True) # logit plt.subplot(224) plt.plot(x, y) plt.yscale('logit') plt.title('logit') plt.grid(True) # Format the minor tick labels of the y-axis into empty strings with # `NullFormatter`, to avoid cumbering the axis with too many labels. plt.gca().yaxis.set_minor_formatter(NullFormatter()) # Adjust the subplot layout, because the logit one may take more space # than usual, due to y-tick labels like "1 - 10^{-3}" plt.subplots_adjust(top=0.92, bottom=0.08, left=0.10, right=0.95, hspace=0.25, wspace=0.35) return plt.gcf() # ----------------------------- The draw figure helpful function ----------------------------- def draw_figure(element, figure): """ Draws the previously created "figure" in the supplied Image Element :param element: an Image Element :param figure: a Matplotlib figure :return: The figure canvas """ plt.close('all') # erases previously drawn plots canv = FigureCanvasAgg(figure) buf = io.BytesIO() canv.print_figure(buf, format='png') if buf is None: return None buf.seek(0) element.update(data=buf.read()) return canv dictionary_of_figures = {'Axis Grid': create_axis_grid, 'Subplot 3D': create_subplot_3d, 'Scales': create_pyplot_scales, 'Basic Figure': create_figure} # ----------------------------- The GUI Section ----------------------------- def create_window(): """ Defines the window's layout and creates the window object. This function is used so that the window's theme can be changed and the window "re-started". :return: The Window object :rtype: sg.Window """ left_col = [[sg.T('Figures to Draw')], [sg.Listbox(list(dictionary_of_figures), default_values=[list(dictionary_of_figures)[0]], size=(15, 5), key='-LB-')], [sg.T('Matplotlib Styles')], [sg.Combo(plt.style.available, size=(15, 10), key='-STYLE-')], [sg.T('PySimpleGUI Themes')], [sg.Combo(sg.theme_list(), default_value=sg.theme(), size=(15, 10), key='-THEME-')]] layout = [[sg.T('Matplotlib Example', font='Any 20')], [sg.Col(left_col), sg.Image(key='-IMAGE-')], [sg.B('Draw'), sg.B('Exit')]] window = sg.Window('Matplotlib Embedded Template', layout, finalize=True) return window def main(): window = create_window() while True: event, values = window.read() print(event, values) if event == 'Exit' or event == sg.WIN_CLOSED: break if event == 'Draw': if values['-THEME-'] != sg.theme(): # if new theme chosen, create a new window window.close() sg.theme(values['-THEME-']) window = create_window() if values['-LB-']: # make sure something selected to draw func = dictionary_of_figures[values['-LB-'][0]] if values['-STYLE-']: plt.style.use(values['-STYLE-']) draw_figure(window['-IMAGE-'], func()) window.close() if __name__ == "__main__": main()