I have some problems understanding how to control the flexbox of ipywidgets in jupyter notebook. According to the docs this should be possible, however my styling code (see below) does not result in the desired layout. I checked on stack and found a good resource that seemed to work for people there, however running the code still does not provide the desired the result.
The problem
I would like control to build somewhat more complex layouts. In this case particularly the goal is to have the sliders vertically next to the matpltolib plot:
from matplotlib.pyplot import subplots
from IPython.display import display
import ipywidgets as ipy
import numpy as np
# setup figure
n = 10
fig, ax = subplots(figsize = (5,5))
h = ax.imshow(np.random.rand(n, n))
# show random mesh
def update(idx):
h.set_data(np.random.rand(n, n))
fig.canvas.flush_events()
fig.canvas.draw()
slider = ipy.IntSlider(min = 0, max = 10, orientation = 'vertical')
widget = ipy.interactive(update, idx = slider)
layout = ipy.Layout(display = 'flex',\
flex_flow = 'row',\
justify_content = 'space-between',\
align_items = 'center',\
)
widgets = ipy.HBox(widget.children[::-1], layout = layout)
display(widgets)
However it results in
How can I force the layout to be horizontal columns using ipywidgets in jupyter notebook?
Try specifically creating an output widget to contain your chart, and then placing that as one of your children in a HBox:
from IPython.display import display, clear_output
import ipywidgets as ipy
import matplotlib.pyplot as plt
import numpy as np
# setup figure
n = 10
out = ipy.Output()
# show random mesh
def update(idx):
with out:
clear_output()
fig, ax = plt.subplots(figsize = (5,5))
h = ax.imshow(np.random.rand(n, n))
h.set_data(np.random.rand(n, n))
fig.canvas.flush_events()
fig.canvas.draw()
plt.show()
slider = ipy.IntSlider(min = 0, max = 10, orientation = 'vertical')
widget = ipy.interactive(update, idx = slider)
layout = ipy.Layout(
# display = 'flex',
# flex_flow = 'row',
# justify_content = 'space-between',
# align_items = 'center',
)
widgets = ipy.HBox(children=(slider, out), layout = layout)
display(widgets)
Related
I am trying to update the plot after a new file is selected, but the new plot that is generated it has the points that are of previous plot on both X and Y axis, I don't want to those previous points, please anyone explain why this happens so and how to get rid of this. Images are shown here, previous plot is
after this I choose to select second file with different data to plot it, next plot is this image
The code I am trying to build is
import matplotlib.pyplot as plt
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from PyQt5.QtWidgets import (QApplication, QWidget, QFileDialog, QPushButton, QLabel, QGridLayout, QVBoxLayout, QLineEdit)
from Bio import SeqIO
from collections import Counter
from Bio.SeqUtils import molecular_weight
from Bio.SeqUtils import GC
class MainWindow(QWidget):
def __init__(self):
super().__init__()
self.setWindowTitle("DNA Sequence Analysis - Prashik Lokhande")
self.setLayout(QVBoxLayout())
my_label = QLabel("DNA Sequence Analysis from the FASTA Database, (FASTA databse can be found on NCBI website). Build by Prashik Lokhande")
self.layout().addWidget(my_label)
self.visualize()
self.show()
def visualize(self):
container = QWidget()
container.setLayout(QGridLayout())
label_1 = QLabel("PLease Select FASTA file")
button_1 = QPushButton("Select file", clicked = lambda: self.get_plot())
gc_count_label = QLabel("GC Count = ")
self.gc_count_field = QLabel("0")
self.canvas = FigureCanvas(plt.Figure(figsize=(10, 4)))
container.layout().addWidget(label_1, 0,0)
container.layout().addWidget(button_1, 1,0)
container.layout().addWidget(gc_count_label, 2, 1)
container.layout().addWidget(self.gc_count_field, 3, 1)
container.layout().addWidget(self.canvas, 2, 0, 3, 1)
self.layout().addWidget(container)
def get_plot(self):
filepath, _ = QFileDialog.getOpenFileName(self, 'select FASTA file')
record = SeqIO.read(filepath,"fasta")
dna = record.seq
mrna = dna.transcribe()
protein = mrna.translate()
self.mol_weight = molecular_weight(dna)
gc = GC(dna)
self.gc_count_field.setText(str(gc))
pr_freq = Counter(protein)
self.ax = self.canvas.figure.subplots()
self.ax.bar(pr_freq.keys(), pr_freq.values())
self.ax.set_title("Amino Acid Contents in the sequence (X-axis Amino acids, Y-axis frequency)")
app = QApplication([])
mw = MainWindow()
app.exec_()
Every time you press the button, self.ax = self.canvas.figure.subplots() will create a new set of axes and add it at the (0,0) position in the grid of previously created subplots. Since all subplots are placed at the same position in the grid they all overlap. To get around this, you could just create one set of axes in MainWindow.__init__, and reuse this one in MainWidon.get_plot, i.e.
class MainWindow(QWidget):
def __init__(self):
....
self.ax = self.canvas.figure.subplots()
def get_plot(self):
....
# clear previous plot
self.ax.clear()
self.ax.bar(pr_freq.keys(), pr_freq.values())
....
I am working on a GUI (developed with wxPython) where you can plot graphs on different panels. At the moment I have this:
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas
from matplotlib.backends.backend_wx import NavigationToolbar2Wx
from matplotlib import pyplot as plt
import numpy as np
import wx
class Frame(wx.Frame):
def __init__(self):
wx.Frame.__init__(self,None,-1,'Plot',size=(1000,800))
# Main Panel (It will contain other elements besides the plotting panel)
self.mainPanel = wx.Panel(self,-1,size=(1000,800))
self.mainPanel.SetBackgroundColour('gray')
# Plotting panel
self.plottingPanel = wx.Panel(self,-1,pos=(50,20),size=(500,400))
self.plottingPanel.SetBackgroundColour('white')
# Plot example
figure = plt.figure()
axes = figure.add_subplot(111)
t = np.arange(0.0, 3.0, 0.01); s = np.cos(2 * np.pi * t);axes.plot(t,s)
plt.title('Cosine')
plt.xlabel('x');plt.ylabel('y')
# Canvas
canvas = FigureCanvas(self.plottingPanel,-1,figure)
# Navegation toolbar
navToolbar = NavigationToolbar2Wx(canvas)
navToolbar.DeleteToolByPos(6);navToolbar.DeleteToolByPos(2);navToolbar.DeleteToolByPos(1)
sizer = wx.BoxSizer(wx.VERTICAL)
sizer.Add(canvas)
sizer.Add(navToolbar)
class App(wx.App):
def OnInit(self):
self.Frame = Frame()
self.Frame.Show()
self.SetTopWindow(self.Frame)
return True
def main():
app = App()
app.MainLoop()
if __name__ == '__main__':
main()
When I run the script get this:
I have colored the plotting panel white to highlight it. How can the plot size be adapted to the panel size?
I want to get something like this (this is a montage):
On the other hand, I managed to eliminate from the bar some buttons that are unnecessary for what I need but the bar does not work, that is, when pressing the buttons nothing happens :(
Thanks for your help
It is possible to set parameters when the container for the plot elements (matplotlib.figure.Figure) is created.
e.g. figsize sets the figure dimension in inches and tight_layout adjust the sub plots in tight layout.
figure = plt.figure(figsize = (4, 3), tight_layout=True)
Alternatively you can set the position of the matplotlib.axes.Axes object by .set_position:
figure = plt.figure()
axes = figure.add_subplot(111)
axes.set_position(pos = [0.15,0.3,0.55,0.55], which='both')
Any Linux or Mac OS equivalent libraries to Win32gui, or to this code ?
working on an outside project and this windows code will help me grab the screen. Havent been able to find any libraries that are similar. Thank you
def grab_screen(region=None):
hwin = win32gui.GetDesktopWindow()
if region:
left,top,x2,y2 = region
width = x2 - left + 1
height = y2 - top + 1
else:
width = win32api.GetSystemMetrics(win32con.SM_CXVIRTUALSCREEN)
height = win32api.GetSystemMetrics(win32con.SM_CYVIRTUALSCREEN)
left = win32api.GetSystemMetrics(win32con.SM_XVIRTUALSCREEN)
top = win32api.GetSystemMetrics(win32con.SM_YVIRTUALSCREEN)
hwindc = win32gui.GetWindowDC(hwin)
srcdc = win32ui.CreateDCFromHandle(hwindc)
memdc = srcdc.CreateCompatibleDC()
bmp = win32ui.CreateBitmap()
bmp.CreateCompatibleBitmap(srcdc, width, height)
memdc.SelectObject(bmp)
memdc.BitBlt((0, 0), (width, height), srcdc, (left, top), win32con.SRCCOPY)
signedIntsArray = bmp.GetBitmapBits(True)
img = np.fromstring(signedIntsArray, dtype='uint8')
img.shape = (height,width,4)
srcdc.DeleteDC()
memdc.DeleteDC()
win32gui.ReleaseDC(hwin, hwindc)
win32gui.DeleteObject(bmp.GetHandle())
return cv2.cvtColor(img, cv2.COLOR_BGRA2RGB)
You can grab the screen with pyautogui:
import pyautogui
image = pyautogui.screenshot('filename.png')
You can do this :)
I think Mac OS can't use those WiIn32gui libraries.
instead you can use pillow for grabbing screen.
Screen size can be changed depends on the size you want.
import cv2
import numpy as np
import pyautogui
from PIL import ImageGrab
screen_w = 1920
screen_h = 1080
while True:
rgb = ImageGrab.grab(bbox=(0, 0, screen_w, screen_h))
rgb = np.array(rgb)
cv2.imshow('window_frame', rgb)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
I dont seem to be able to fully control the figure size on my embedded figure on a Tkinter canvas.
Heres what i want to do. Maybe you have another suggestion, than using the embedded figure.
Im trying to make a simple script to make some visual content. Right now its just a pixel mapping of falling squares in random colors.
My problem is that i need it to be fullscreen, and i can for my life not figure out how.
It is mainly about this piece of code, i think:
fig = plt.figure(figsize=(40,40))
im = plt.imshow(top.img) # later use a.set_data(new_data)
plt.tick_params(
axis='both', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
bottom='off', # ticks along the bottom edge are off
top='off', # ticks along the top edge are off
left='off',
right='off',
labelleft='off',
labelbottom='off') # labels along the bottom edge are off
# a tk.DrawingArea
canvas = FigureCanvasTkAgg(fig, master=top)
canvas.show()
canvas.get_tk_widget().pack(side=gui.TOP , fill=gui.BOTH, expand=1)
It seems that figsize has a limit to how big it goes.
Heres all the code:
import matplotlib
import numpy as np
matplotlib.use('TkAgg')
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib import figure
import matplotlib.pyplot as plt
import tkinter as gui
from math import floor
import time
class FullScreenApp(object):
def __init__(self, master, **kwargs):
self.master=master
pad=3
self._geom='200x200+0+0'
master.geometry("{0}x{1}+0+0".format(
master.winfo_screenwidth()-pad, master.winfo_screenheight()-pad))
master.bind('<Escape>',self.toggle_geom)
def toggle_geom(self,event):
geom=self.master.winfo_geometry()
print(geom,self._geom)
self.master.geometry(self._geom)
self._geom=geom
def flashBox(color,oy,ox):
global j1, j2
top.img[0+oy:j2+oy,0+ox:j1+ox] = color
im.set_data(top.img)
canvas.draw();
time.sleep(t)
top.img[0+oy:j2+oy,0+ox:j1+ox] = [0,0,0]
im.set_data(top.img)
canvas.draw();
return top.img
def drawBox(color,oy,ox):
global j1, j2
top.img[0+oy:j2+oy,0+ox:j1+ox] = color
im.set_data(top.img)
canvas.draw();
time.sleep(t)
return top.img
def resetBox(oy,ox):
global j1, j2
top.img[0+oy:j2+oy,0+ox:j1+ox] = [0,0,0]
im.set_data(top.img)
canvas.draw();
return top.img
def drawColumn(color,u):
global gridsize, j1, j2
for l in range(gridsize):
im.set_data(flashBox(color,j2*l,j1*u))
time.sleep(t2)
top = gui.Tk()
t = 0.1
t2 = 0.00001
x = 40
y = 40
gridsize = 10
j1 = floor(x // gridsize)
j2 = floor(y // gridsize)
top.img = np.zeros([y,x,3],dtype=np.uint8)
top.img.fill(0) # or img[:] = 255
fig = plt.figure(figsize=(40,40))
im = plt.imshow(top.img) # later use a.set_data(new_data)
plt.tick_params(
axis='both', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
bottom='off', # ticks along the bottom edge are off
top='off', # ticks along the top edge are off
left='off',
right='off',
labelleft='off',
labelbottom='off') # labels along the bottom edge are off
# a tk.DrawingArea
canvas = FigureCanvasTkAgg(fig, master=top)
canvas.show()
canvas.get_tk_widget().pack(side=gui.TOP , fill=gui.BOTH, expand=1)
#app=FullScreenApp(top)
while True:
for n in range(gridsize):
top.update()
p = np.random.randint(0,99)
#drawColumn([np.random.random_integers(0,255),np.random.random_integers(0,255),np.random.random_integers(0,255)],np.random.random_integers(0,gridsize-1))
if p > 10:
flashBox([np.random.random_integers(0,255),np.random.random_integers(0,255),np.random.random_integers(0,255)],j1*np.random.random_integers(0,gridsize-1),j2*np.random.random_integers(0,gridsize-1))
else:
flashBox([0,0,0],0,0)
I writing a code in Python 3 to plot some markers over a DICOM image. for this, I wrote a very short program:
In the main program, I read the DICOM filename from the terminal and plot the image.
main_prog.py:
import sys
import dicom as dcm
import numpy as np
from matplotlib import pyplot as plt
from dicomplot import dicomplot as dcmplot
filename = sys.argv[1]
dicomfile = dcm.read_file(filename)
dicomimg = dicomfile.pixel_array
fig = plt.figure(dpi = 300)
ax = fig.add_subplot(1, 1, 1)
plt.set_cmap(plt.gray())
plt.pcolormesh(np.flipud(dicomimg))
dcm = dcmplot(ax)
plt.show()
Then, I define a class to store the coordinates clicked by the user and plot each of them at a time over the image:
dicomplot.py
from matplotlib import pyplot as plt
class dicomplot():
def __init__(self, img):
self.img = img
self.fig = plt.figure(dpi = 300)
self.xcoord = list()
self.ycoord = list()
self.cid = img.figure.canvas.mpl_connect('button_press_event', self)
def __call__(self, event):
if event.button == 1:
self.xcoord.append(event.x)
self.ycoord.append(event.y)
self.img.plot(self.ycoord, self.xcoord, 'r*')
self.img.figure.canvas.draw()
elif event.button == 2:
self.img.figure.canvas.mpl_disconnect(self.cid)
elif event.button == 3:
self.xcoord.append(-1)
self.ycoord.append(-1)
The problem is that when I click over the image, the markers appear in a different scale, and not over the image as they are supposed to.
How can I modify my code so when I click on the image, all the mouse clicks are stored and ploted in the desired position?
The MouseEvent objects carry both a x/y andxdata/ydata attributes (docs). The first set is in screen coordinates (ex pixels from the lower left) and the second set (*data) are in the data coordinates.
You might also be interested in mpldatacursor.