I'm trying to add a Matplotlib Basemap to a TkInter Canvas. It works fine not using a basemap, however, when I try to plot one Python crashes. Code block #1 is the code which works, Code block #2 makes my program crash. If I delete everything in #2 except the m=Basemap(...)part it crashes also. Calculating the Basemap(...) takes about 6 or 7 seconds and I guess that is the reason for TkInter to crash. Any ideas how I can tell TkInter to wait?
1:
def plot_route(self, geom1, root):
root1 = Tk()
x1, y1 = zip(*((geom1.GetX(i), geom1.GetY(i)) for i in range(geom1.GetPointCount())))
f = Figure(figsize=(5,4), dpi=100)
a = f.add_subplot(111)
a.plot(x1,y1)
a.set_title('Tk embedding')
a.set_xlabel('X axis label')
a.set_ylabel('Y label')
canvas = FigureCanvasTkAgg(f, master=root1)
canvas.show()
canvas.get_tk_widget().pack(side=TOP, fill=BOTH, expand=1)
canvas._tkcanvas.pack(side=TOP, fill=BOTH, expand=1)
root1.mainloop()
2:
def plot_route(self, geom1, root):
root1 = Tk()
m = Basemap(width=12000000,height=9000000,projection='lcc', resolution='c',lat_1=45.,lat_2=55,lat_0=50,lon_0=-107.)
m.drawcoastlines()
m.drawmapboundary(fill_color='aqua')
m.fillcontinents(color='coral',lake_color='aqua')
canvas = FigureCanvasTkAgg(m, master=root1)
canvas.show()
canvas.get_tk_widget().pack(side=TOP, fill=BOTH, expand=1)
canvas._tkcanvas.pack(side=TOP, fill=BOTH, expand=1)
root1.mainloop()
canvas = FigureCanvasTkAgg(m, master=root1)
I don't think you should use 'm' here.
You should create a figure, and add a subplot (ax), and pass that ax to basemap.
And use fig as the parameter to FigureCanvasTkAgg.
import matplotlib
matplotlib.use('TkAgg')
from mpl_toolkits.basemap import Basemap
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import sys
if sys.version_info[0] < 3:
import Tkinter as Tk
else:
import tkinter as Tk
root = Tk.Tk()
fig = Figure() ## here
ax1 = fig.add_subplot(111) ## here
m = Basemap(width=12000000,height=9000000,projection='lcc',
resolution='c',lat_1=45.,lat_2=55,lat_0=50,lon_0=-107.,
ax=ax1) ## here
m.drawcoastlines()
m.drawmapboundary(fill_color='aqua')
m.fillcontinents(color='coral',lake_color='aqua')
canvas = FigureCanvasTkAgg(fig, master=root) ## here
canvas.show()
canvas.get_tk_widget().pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
canvas._tkcanvas.pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
root.mainloop()
Related
This code displays a moving graph with two lines, and the data is saved to a CSV file with the code that makes the data. I have tried to create a canvas class using the pyqt5 imports, but I am struggling with where exactly to put the matplotlib code.
from itertools import count
import matplotlib.pyplot as plt
import pandas as pd
from matplotlib.animation import FuncAnimation
plt.style.use('fivethirtyeight')
x_vals = []
y_vals = []
index = count()
def animate(i):
data = pd.read_csv("C:/Users/Khata/PycharmProjects/LiveData1/venv/data.csv")
x = data['x_value']
y1 = data['total_1']
y2 = data['total_2']
plt.cla()
plt.plot(x, y1, label='Channel 1')
plt.plot(x, y2, label='Channel 2')
plt.legend(loc='upper left')
plt.tight_layout()
ani = FuncAnimation(plt.gcf(), animate, interval=1000)
plt.tight_layout()
plt.show()
I'm trying to get the RectangleSelector form matplotlib.widgets to work with PySimpleGUI.
I'm basing my test code on the RectangleSelector demo shown in the accepted answer on this question.
I'm getting the plot to show in PySimpleGUI but it's not interactive. Is it even possible in PySimpleGUI to have interactive matplotlib widgets?
import PySimpleGUI as sg
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib.widgets import RectangleSelector
import matplotlib
matplotlib.use('TkAgg')
xdata = np.linspace(0,9*np.pi, num=301)
ydata = np.sin(xdata)
fig, ax = plt.subplots()
line, = ax.plot(xdata, ydata)
def draw_figure(canvas, figure):
figure_canvas_agg = FigureCanvasTkAgg(figure, canvas)
figure_canvas_agg.draw()
figure_canvas_agg.get_tk_widget().pack(side="top", fill="both", expand=1)
return figure_canvas_agg
def line_select_callback(eclick, erelease):
x1, y1 = eclick.xdata, eclick.ydata
x2, y2 = erelease.xdata, erelease.ydata
rect = plt.Rectangle( (min(x1,x2),min(y1,y2)), np.abs(x1-x2), np.abs(y1-y2) )
ax.add_patch(rect)
rs = RectangleSelector(ax, line_select_callback,
drawtype='box', useblit=False, button=[1],
minspanx=5, minspany=5, spancoords='pixels',
interactive=True)
layout = [[sg.Canvas(key="-CANVAS-")]]
window = sg.Window('test', layout, finalize=True, element_justification='center', font='Helvetica 16')
draw_figure(window["-CANVAS-"].TKCanvas, fig)
event, values = window.read()
Edit: Thanks to MikeyB for the pointer, I now have the following code, which shows an interactive plot, but it's still not possible to draw rectangles. The callback function doesn't seem to be firing. New code below:
import PySimpleGUI as sg
import numpy as np
from matplotlib.widgets import RectangleSelector
import matplotlib.figure as figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
# instantiate matplotlib figure
fig = figure.Figure()
ax = fig.add_subplot(111)
DPI = fig.get_dpi()
fig.set_size_inches(505 * 2 / float(DPI), 707 / float(DPI))
# ------------------------------- This is to include a matplotlib figure in a Tkinter canvas
def draw_figure_w_toolbar(canvas, fig, canvas_toolbar):
if canvas.children:
for child in canvas.winfo_children():
child.destroy()
if canvas_toolbar.children:
for child in canvas_toolbar.winfo_children():
child.destroy()
figure_canvas_agg = FigureCanvasTkAgg(fig, master=canvas)
figure_canvas_agg.draw()
toolbar = Toolbar(figure_canvas_agg, canvas_toolbar)
toolbar.update()
figure_canvas_agg.get_tk_widget().pack(side='right', fill='both', expand=1)
def line_select_callback(eclick, erelease):
x1, y1 = eclick.xdata, eclick.ydata
x2, y2 = erelease.xdata, erelease.ydata
rect = plt.Rectangle( (min(x1,x2),min(y1,y2)), np.abs(x1-x2), np.abs(y1-y2) )
print(rect)
ax.add_patch(rect)
class Toolbar(NavigationToolbar2Tk):
def __init__(self, *args, **kwargs):
super(Toolbar, self).__init__(*args, **kwargs)
# ------------------------------- PySimpleGUI CODE
layout = [
[sg.B('start', key='start')],
[sg.Canvas(key='controls_cv')],
[sg.Column(
layout=[
[sg.Canvas(key='fig_cv',
# it's important that you set this size
size=(500 * 2, 700)
)]
],
background_color='#DAE0E6',
pad=(0, 0)
)],
]
window = sg.Window('Test', layout)
while True:
event, values = window.read()
print(event, values)
if event == sg.WIN_CLOSED:
break
elif event == 'start':
x = np.linspace(0, 2 * np.pi)
y = np.sin(x)
line, = ax.plot(x, y)
rs = RectangleSelector(ax, line_select_callback,
drawtype='box', useblit=False, button=[1],
minspanx=5, minspany=5, spancoords='pixels',
interactive=True)
draw_figure_w_toolbar(window['fig_cv'].TKCanvas, fig, window['controls_cv'].TKCanvas)
window.close()
Is it even possible in PySimpleGUI to have interactive matplotlib widgets?
Yes.
The demo program on the project's GitHub shows how to make an interactive Matplotlib drawing.
https://github.com/PySimpleGUI/PySimpleGUI/blob/master/DemoPrograms/Demo_Matplotlib_Embedded_Toolbar.py
You need to embed the controls into the window.
you need to add
fig.canvas.draw()
to your callback-function if you want the plot to be updated after the callback has triggered!
here's an updated version of your code that works just fine:
import PySimpleGUI as sg
import numpy as np
from matplotlib.widgets import RectangleSelector
import matplotlib.figure as figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
import matplotlib.pyplot as plt
# instantiate matplotlib figure
fig = figure.Figure()
ax = fig.add_subplot(111)
DPI = fig.get_dpi()
fig.set_size_inches(505 * 2 / float(DPI), 707 / float(DPI))
# ------------------------------- This is to include a matplotlib figure in a Tkinter canvas
def draw_figure_w_toolbar(canvas, fig, canvas_toolbar):
if canvas.children:
for child in canvas.winfo_children():
child.destroy()
if canvas_toolbar.children:
for child in canvas_toolbar.winfo_children():
child.destroy()
figure_canvas_agg = FigureCanvasTkAgg(fig, master=canvas)
figure_canvas_agg.draw()
toolbar = Toolbar(figure_canvas_agg, canvas_toolbar)
toolbar.update()
figure_canvas_agg.get_tk_widget().pack(side='right', fill='both', expand=1)
def line_select_callback(eclick, erelease):
x1, y1 = eclick.xdata, eclick.ydata
x2, y2 = erelease.xdata, erelease.ydata
rect = plt.Rectangle( (min(x1,x2),min(y1,y2)), np.abs(x1-x2), np.abs(y1-y2) )
print(rect)
ax.add_patch(rect)
fig.canvas.draw()
class Toolbar(NavigationToolbar2Tk):
def __init__(self, *args, **kwargs):
super(Toolbar, self).__init__(*args, **kwargs)
# ------------------------------- PySimpleGUI CODE
layout = [
[sg.B('start', key='start')],
[sg.Canvas(key='controls_cv')],
[sg.Column(
layout=[
[sg.Canvas(key='fig_cv',
# it's important that you set this size
size=(500 * 2, 700)
)]
],
background_color='#DAE0E6',
pad=(0, 0)
)],
]
window = sg.Window('Test', layout)
while True:
event, values = window.read()
print(event, values)
if event == sg.WIN_CLOSED:
break
elif event == 'start':
x = np.linspace(0, 2 * np.pi)
y = np.sin(x)
line, = ax.plot(x, y)
rs = RectangleSelector(ax, line_select_callback,
drawtype='box', useblit=False, button=[1],
minspanx=5, minspany=5, spancoords='pixels',
interactive=True)
draw_figure_w_toolbar(window['fig_cv'].TKCanvas, fig, window['controls_cv'].TKCanvas)
window.close()
I've been having some trouble getting the following animation of DFS to run.
I believe it might be because there is no background canvas, but I'm not sure exactly how to fix this, as all other similar implementations online use plt.plot rather than nx.draw in saving images to be displayed.
Can someone offer any guidance?
import networkx as nx
import matplotlib.pyplot as plt
from matplotlib.animation import ArtistAnimation
fig = plt.figure()
ax = plt.gca()
colors = [0]*len(g)
cmap = plt.get_cmap("autumn")
g = nx.random_tree(20)
pos = nx.fruchterman_reingold_layout(g, k=0.1)
ims = [[nx.draw_networkx(g, pos, node_color = colors, cmap = cmap, ax = ax, vmin=0.0, vmax=1.0)]]
artists = [(nx.draw_networkx(g, pos, node_color = colors, cmap = cmap, ax = ax, vmin=0.0, vmax=1.0),)]
stack = [0]
while stack:
node = stack.pop()
if colors[node]:
continue
colors[node] = 0.8
stack += list(g[node].keys())
img = nx.draw_networkx(g, pos, node_color=colors, cmap=cmap, ax=ax, vmin=0.0, vmax=1.0)
ims += [img]
anim = ArtistAnimation(fig, ims, blit = True)
# plt.show()
The problem with your code is that nx.draw_networkx() doesn't return anything and it's always easier to use FuncAnimation method instead. At first, you need to create a color generator to make the animation function switch to the next color set by each call. Then using the FuncAnimation you can animate your frames (plots):
import networkx as nx
import matplotlib.pyplot as plt
import matplotlib
import matplotlib.animation as animation
matplotlib.use('TkAgg')
plt.ion()
g = nx.random_tree(20)
colors = [0] * len(g)
cmap = plt.get_cmap('autumn')
pos = nx.fruchterman_reingold_layout(g, k=0.1)
# here you make the generator
def change_colors():
stack = [0]
yield colors
while stack:
node = stack.pop()
if colors[node]:
continue
colors[node] = 0.8
stack += list(g[node].keys())
yield colors
# instantiate your generator
color_gen = change_colors()
def update_frame(n):
# clear the plot
plt.cla()
# here switch to the next colors
colors = next(color_gen)
# then draw
nx.draw(g, pos, with_labels=True, node_color=colors, cmap=cmap, vmin=0.0, vmax=1.0)
ani = animation.FuncAnimation(plt.gcf(), update_frame, repeat=False, interval=1000)
plt.ioff()
plt.show()
which will give you:
you can save it as a gif file by replacing plt.show() with ani.save('anim.gif', writer='imagemagick').
I want to plot a figure by pyqt5 as below codes, and I want to see all the data in one figure and zoom in to see some detals; I hope when Izoom in a part of this figure, x axes and y axes fit the detail auto together;
import sys
from PyQt5 import QtWidgets
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt5 import NavigationToolbar2QT as NavigationToolbar
import matplotlib.pyplot as plt
import matplotlib.finance as mpf
class Window(QtWidgets.QDialog):
def __init__(self,Data,parent=None):
super().__init__(parent)
self.candleData=Data[0]
self.plots=len(Data)
if self.plots>1:
self.lineData=Data[1]
self.figure = plt.figure(figsize=(30,18))
self.axes = self.figure.add_subplot(111)
self.axes.hold(True)
self.canvas = FigureCanvas(self.figure)
self.toolbar = NavigationToolbar(self.canvas, self)
self.toolbar.hide()
self.button2 = QtWidgets.QPushButton('Zoom')
self.button2.clicked.connect(self.zoom)
self.button3 = QtWidgets.QPushButton('Pan')
self.button3.clicked.connect(self.pan)
self.button4 = QtWidgets.QPushButton('Home')
self.button4.clicked.connect(self.home)
layout = QtWidgets.QVBoxLayout()
layout.addWidget(self.toolbar)
layout.addWidget(self.canvas)
btnlayout = QtWidgets.QHBoxLayout()
btnlayout.addWidget(self.button2)
btnlayout.addWidget(self.button3)
btnlayout.addWidget(self.button4)
qw = QtWidgets.QWidget(self)
qw.setLayout(btnlayout)
layout.addWidget(qw)
self.setLayout(layout)
def home(self):
self.toolbar.home()
def zoom(self):
self.toolbar.zoom()
def pan(self):
self.toolbar.pan()
def plot(self):
[obj.insert(0,i) for i,obj in enumerate(self.candleData)]
mpf.candlestick_ohlc(self.axes,self.candleData,width=0.8,colorup='r',colordown='g')
self.axes.grid()
print(self.plots)
if self.plots>1:
for i in range(len(self.lineData)):
self.axes.plot(self.lineData[i][0],self.lineData[i][1],color=self.lineData[i][2])
self.canvas.draw()
Now I plot a figure and zoom in for some small part as blow:
Screenshot:
but I should use "pan" to see all of it; shall I see all of it auto when I zoom in?
If you want to insert a small plot inside a bigger one you can use Axes, like here.
The problem is that I don't know how to do the same inside a subplot.
I have several subplots and I would like to plot a small plot inside each subplot.
The example code would be something like this:
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure()
for i in range(4):
ax = fig.add_subplot(2,2,i)
ax.plot(np.arange(11),np.arange(11),'b')
#b = ax.axes([0.7,0.7,0.2,0.2])
#it gives an error, AxesSubplot is not callable
#b = plt.axes([0.7,0.7,0.2,0.2])
#plt.plot(np.arange(3),np.arange(3)+11,'g')
#it plots the small plot in the selected position of the whole figure, not inside the subplot
Any ideas?
I wrote a function very similar to plt.axes. You could use it for plotting yours sub-subplots. There is an example...
import matplotlib.pyplot as plt
import numpy as np
#def add_subplot_axes(ax,rect,facecolor='w'): # matplotlib 2.0+
def add_subplot_axes(ax,rect,axisbg='w'):
fig = plt.gcf()
box = ax.get_position()
width = box.width
height = box.height
inax_position = ax.transAxes.transform(rect[0:2])
transFigure = fig.transFigure.inverted()
infig_position = transFigure.transform(inax_position)
x = infig_position[0]
y = infig_position[1]
width *= rect[2]
height *= rect[3] # <= Typo was here
#subax = fig.add_axes([x,y,width,height],facecolor=facecolor) # matplotlib 2.0+
subax = fig.add_axes([x,y,width,height],axisbg=axisbg)
x_labelsize = subax.get_xticklabels()[0].get_size()
y_labelsize = subax.get_yticklabels()[0].get_size()
x_labelsize *= rect[2]**0.5
y_labelsize *= rect[3]**0.5
subax.xaxis.set_tick_params(labelsize=x_labelsize)
subax.yaxis.set_tick_params(labelsize=y_labelsize)
return subax
def example1():
fig = plt.figure(figsize=(10,10))
ax = fig.add_subplot(111)
rect = [0.2,0.2,0.7,0.7]
ax1 = add_subplot_axes(ax,rect)
ax2 = add_subplot_axes(ax1,rect)
ax3 = add_subplot_axes(ax2,rect)
plt.show()
def example2():
fig = plt.figure(figsize=(10,10))
axes = []
subpos = [0.2,0.6,0.3,0.3]
x = np.linspace(-np.pi,np.pi)
for i in range(4):
axes.append(fig.add_subplot(2,2,i))
for axis in axes:
axis.set_xlim(-np.pi,np.pi)
axis.set_ylim(-1,3)
axis.plot(x,np.sin(x))
subax1 = add_subplot_axes(axis,subpos)
subax2 = add_subplot_axes(subax1,subpos)
subax1.plot(x,np.sin(x))
subax2.plot(x,np.sin(x))
if __name__ == '__main__':
example2()
plt.show()
You can now do this with matplotlibs inset_axes method (see docs):
from mpl_toolkits.axes_grid.inset_locator import inset_axes
inset_axes = inset_axes(parent_axes,
width="30%", # width = 30% of parent_bbox
height=1., # height : 1 inch
loc=3)
Update: As Kuti pointed out, for matplotlib version 2.1 or above, you should change the import statement to:
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
There is now also a full example showing all different options available.
From matplotlib 3.0 on, you can use matplotlib.axes.Axes.inset_axes:
import numpy as np
import matplotlib.pyplot as plt
fig, axes = plt.subplots(2,2)
for ax in axes.flat:
ax.plot(np.arange(11),np.arange(11))
ins = ax.inset_axes([0.7,0.7,0.2,0.2])
plt.show()
The difference to mpl_toolkits.axes_grid.inset_locator.inset_axes mentionned in #jrieke's answer is that this is a lot easier to use (no extra imports etc.), but has the drawback of being slightly less flexible (no argument for padding or corner locations).
source: https://matplotlib.org/examples/pylab_examples/axes_demo.html
from mpl_toolkits.axes_grid.inset_locator import inset_axes
import matplotlib.pyplot as plt
import numpy as np
# create some data to use for the plot
dt = 0.001
t = np.arange(0.0, 10.0, dt)
r = np.exp(-t[:1000]/0.05) # impulse response
x = np.random.randn(len(t))
s = np.convolve(x, r)[:len(x)]*dt # colored noise
fig = plt.figure(figsize=(9, 4),facecolor='white')
ax = fig.add_subplot(121)
# the main axes is subplot(111) by default
plt.plot(t, s)
plt.axis([0, 1, 1.1*np.amin(s), 2*np.amax(s)])
plt.xlabel('time (s)')
plt.ylabel('current (nA)')
plt.title('Subplot 1: \n Gaussian colored noise')
# this is an inset axes over the main axes
inset_axes = inset_axes(ax,
width="50%", # width = 30% of parent_bbox
height=1.0, # height : 1 inch
loc=1)
n, bins, patches = plt.hist(s, 400, normed=1)
#plt.title('Probability')
plt.xticks([])
plt.yticks([])
ax = fig.add_subplot(122)
# the main axes is subplot(111) by default
plt.plot(t, s)
plt.axis([0, 1, 1.1*np.amin(s), 2*np.amax(s)])
plt.xlabel('time (s)')
plt.ylabel('current (nA)')
plt.title('Subplot 2: \n Gaussian colored noise')
plt.tight_layout()
plt.show()