The exponential distribution didn't show up in the shell - shell

Here is a short code :
import numpy as np
from scipy.stats import expon
import matplotlib.pyplot as plt
x = np.arange(0, 10, 0.001)
plt.plot(x, expon.pdf(x))
When I type that in the shell in using ipython, that didn't show up anything while it is supposed to plot the exponential distribution for x between 0 and 10. Could anyone be able to tell me what is the problem here?
I got that, but the plot did show up
In [16]: plt.plot(x, norm.pdf(x))
Out[16]: [<matplotlib.lines.Line2D at 0x7fbfe6bc2890>]
Thanks in advance!
P.S. Be aware that I am using Ubuntu 16.10 (Linux distribution).

It seems you are using IPython. Depending on in which environment you use it, you can create inline plots or plot to a window.
Ipython in Jupyther QtConsole allows to set the inline backend, %matplotlib inline.
In IPython without graphical support, you need to invoke a plotting window using plt.show()

Related

Export PDF: font not found

I am trying to export my figure as a PDF. I run into the problem that when I want to edit it (in this case by Graphic on macOS) that the font appears not to be found by the editor. My question is, how do I solve this? Can I 'install' the fonts used by matplotlib?
Example
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([0,1], [0,1])
plt.savefig('test.pdf')
This PDF looks fine in Preview:
But in the editor, it gives gibberish:
Failing solution
Setting
matplotlib.rc("pdf", fonttype=42)
(see this answer).
Partly working solution
What works is to install all matplotlib's fonts. I have followed this answer to find all matplotlib's ttfs, and installed them. This works and solves the problem.
But... This does solve the issues when LaTeX is enabled, by
import matplotlib
matplotlib.rcParams['text.usetex'] = True
How do I install the fonts that matplotlib uses now?
A solution here is to export as SVG. However, for some reason this takes ages on my system (see this bug).
I have found a workaround. This is to convert all fonts to outlines before editing. One way to do this is with GhostScript with the option -dNoOutputFonts, as described in this answer:
gs -o file-with-outlines.pdf -dNoOutputFonts -sDEVICE=pdfwrite file.pdf
What pdf editor are you using? I don't know how to check whether an attempt to solve this is working... but I always use this code to save images in pdf or png:
plt.savefig('test.pdf', edgecolor='none', bbox_inches="tight")

Procedural PyQt4 generates extra windows after pyplot.show()

I have encountered a strange behaviour on Mac OSX 10.12 when using PyQt4 and matplotlib in a procedural python function.
The function pops up a dialogue which is used to select a directory. The files in this directory are read, and their data is plotted using matplotlib.pyplot.
The issue is that when matplotlib shows the plot window, additional blank windows are also generated behind the matplotlib window. These extra windows are only generated if I include the PyQt code in my function.
When I close the matplotlib window the script hangs, and if i close the additional blank windows the function exits without executing the remaining code in the function.
Does anyone else get these extra windows? I have the feeling that If I can somehow "quit the PyQt app loop" after I've used it to pick my directory then this would fix the problem. This is my intuition / speculation, and attempts to do this have failed.
Here is a screenshot showing the extra windows which pop up when plt.show() is called:
Here is my code:
import os
import sys
from PyQt4.QtGui import *
import numpy as np
import matplotlib.pyplot as plt
def qt_mpl_test():
home = os.path.expanduser('~')
print('Select data top directory...')
app = QApplication(sys.argv)
w = QWidget()
dat_dir = QFileDialog.getExistingDirectory(w, 'Select data top directory', home)
dat_dir = str(dat_dir)
## At this stage I load in my data files for processing / plotting
## For the sake of simplicity, generate some data below
x = np.array([1, 2, 3, 4, 5, 6, 7])
y = np.array([1, 2, 3, 4, 3, 2, 1])
fig, ax = plt.subplots(1, 1)
ax.plot(y, x)
plt.show()
qt_mpl_test()

Python 3.4: Where is the image library?

I am trying to display images with only builtin functions, and there are plenty of Tkinter examples online. However, none of the libraries work:
import Image # none of these exist.
import tkinter.Image
import _tkinter.Image
etc
However, tkinter does exist, a hellow-world with buttons worked fine.
I am on a MacBook pro 10.6.8 and using PyCharm.
Edit: The best way so far (a little slow but tolerable):
Get the pixel array as a 2D list (you can use a third-party .py to load your image).
Now you make a data array from the pixels like this (this is the weirdest format I have seen, why not a simple 2D array?). This may be sideways, so you may get an error for non-square images. I will have to check.
Imports:
from tkinter import *
import tkinter
data = list() # the image is x pixels by y pixels.
y = len(pixels)
x = len(pixels[0])
for i in range(y):
col_str.append('{')
for j in range(x):
data.append(pixels[i][j]+" ")
data.append("} ")
data = "".join(data)
Now you can create an image and use put:
# PhotoImage is builtin (tkinter).
# It does NOT need PIL, Pillow, or any other externals.
im = PhotoImage(width=x, height=y)
im.put(col_str)
Finally, attach it to the canvas:
canvas = tkinter.Canvas(width=x, height=y)
canvas.create_image(x/2, y/2, image=GLOBAL_IMAGE) # x/2 and y/2 are the center.
tK.mainloop() # enter the main loop and it will be drawn.
Image must be global or else it may not show up because the garbage collector gets greedy.
PIL hasn't been updated since 2009, with Python 3 support being terminally stuck at "later."
Instead, try pillow, which has forked PIL and provides Python 3 support.

Healpy Mollview function returned nothing

I am a new healpy user. I used healpy tutorial available at page http://healpy.readthedocs.org/en/latest/tutorial.html for creating a map but after execution of "healpy.mollview" command it returned nothing and no plot was visible. Need Help!
I have searched the problem already but unable to find the exact situation anywhere
Thanks,
Jibran
For using healpy plotting functions, the best is to use ipython, in particular:
ipython --pylab
You have to show the plot
import matplotlib.pyplot as plt
plt.show()
as you would do for any plot in matplotlib

adding contrast to an image in python

I am trying to work through a process where I take an astronomical fits file, subtract a masterflat file and then later the contrast on the resultant image.
The first part has been done successfully but my image lacks contrast. Here's my code
from astropy.io.fits import getdata
import numpy
import numpy as np
import scipy
import Image
import PIL
import os
os.chdir("/localdir/")
from scipy import misc
import ImageEnhance
image = getdata('23484748.fts')
flat = getdata('Masterflat.fit')
normalized_flat = flat / numpy.mean(flat)
calibrated_image = image / normalized_flat
pix=numpy.fliplr(calibrated_image)
# the problem starts about here. How do I alter the contrast of pix?
from matplotlib import pyplot as plt
misc.imsave('saved image.gif', pix) # uses the Image module (PIL)
plt.imshow(pix, interpolation='nearest')
plt.show()
Now before you tell me all about PIL functions and Matlib etc I have tried these without success.
I have tried to use image.fromarray to convert my numpy array into an image but the resultant image displays as pure white.
How can I take my numpy array (pix) and change its contrast?
For testing purposes I have put the two sample files at http://members.optusnet.com.au/berrettp/
Thanking you
Peter

Resources