import PySimpleGUI as g

import matplotlib

matplotlib.use('TkAgg')

from matplotlib.backends.backend_tkagg import FigureCanvasAgg

import matplotlib.backends.tkagg as tkagg

import tkinter as Tk

"""

Demonstrates one way of embedding Matplotlib figures into a PySimpleGUI window.

Basic steps are:

* Create a Canvas Element

* Layout form

* Display form (NON BLOCKING)

* Draw plots onto convas

* Display form (BLOCKING)

"""

def draw_figure(canvas, figure, loc=(0, 0)):

""" Draw a matplotlib figure onto a Tk canvas

loc: location of top-left corner of figure on canvas in pixels.

Inspired by matplotlib source: lib/matplotlib/backends/backend_tkagg.py

"""

figure_canvas_agg = FigureCanvasAgg(figure)

figure_canvas_agg.draw()

figure_x, figure_y, figure_w, figure_h = figure.bbox.bounds

figure_w, figure_h = int(figure_w), int(figure_h)

photo = Tk.PhotoImage(master=canvas, width=figure_w, height=figure_h)

# Position: convert from top-left anchor to center anchor

canvas.create_image(loc[0] + figure_w/2, loc[1] + figure_h/2, image=photo)

# Unfortunately, there's no accessor for the pointer to the native renderer

tkagg.blit(photo, figure_canvas_agg.get_renderer()._renderer, colormode=2)

# Return a handle which contains a reference to the photo object

# which must be kept live or else the picture disappears

return photo

#------------------------------- PASTE YOUR MATPLOTLIB CODE HERE -------------------------------

import numpy as np

import matplotlib.pyplot as plt

from matplotlib.ticker import NullFormatter # useful for `logit` scale

# 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)

#------------------------------- END OF YOUR MATPLOTLIB CODE -------------------------------

# ****** Comment out this line if not using Pyplot ******

fig = plt.gcf() # if using Pyplot then get the figure from the plot

# -------------------------------- GUI Starts Here -------------------------------#

# fig = your figure you want to display. Assumption is that 'fig' holds the #

# information to display. #

# --------------------------------------------------------------------------------#

figure_x, figure_y, figure_w, figure_h = fig.bbox.bounds

canvas_elem = g.Canvas(size=(figure_w, figure_h)) # get the canvas we'll be drawing on

# define the form layout

layout = [[g.Text('Plot test')],

[canvas_elem],

[g.OK(pad=((figure_w/2,0), 3), size=(4,2))]]

# create the form and show it without the plot

form = g.FlexForm('Demo Application - Embedding Matplotlib In PySimpleGUI')

form.Layout(layout)

form.ReadNonBlocking()

# add the plot to the window

fig_photo = draw_figure(canvas_elem.TKCanvas, fig)

# show it all again and get buttons

button, values = form.Read()