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
Related
I generate a PIL image from a NumPy array. The image showed by show function differs from what is saved by the save function directly called after show. Why might that be the case? How can I solve this issue? I use TIFF file format. Viewing both images in Windows Photos App.
from PIL import Image
import numpy as np
orig_img = Image.open('img.tif'))
dent = Image.open('mask.tif')
img_np = np.asarray(orig_img)
dent_np = np.asarray(dent)
dented = img_np*0.5 + dent_np*0.5
im = Image.fromarray(dented)
im.show('dented')
im.save("dented_2.tif", "TIFF")
Edit: I figured out that the save function saves correctly if the values for pixel in the NumPy array called 'dented' are normalized to 0,1 range. However then show function shows the image completely black.
I suspect the problem is related to the dtype of your variable dented. Try:
print(img_np.dtype, dented.dtype)
As a possible solution, you could use:
im = Image.fromarray(dented.astype(np.uint8))
You don't actually need to go to Numpy to do the maths and then convert back if you want the mean of two images, because you can do that with PIL.
from PIL import ImageChops
mean = ImageChops.add(imA, imB, scale=2.0)
I am attempting to take a screenshot of a correlation table made with pandas in Jupyter Notebooks but since it is very wide I must scroll to the right in order to view the whole table. On a mac it is not possible to scroll left or right while taking a screenshot so I am unable to capture the entire table. Is there anyway to get the entire table (doesn't have to be a screenshot an export of some type would work as well)?
Is the table already shown in markdown? If not, you can try df.to_html(). From there, you can convert it to pdf, see (https://www.npmjs.com/package/markdown-pdf)
Otherwise you can plot the pandas table with matplotlib and remove the axis etc.
import matplotlib.pyplot as plt
import pandas as pd
from pandas.table.plotting import table
ax = plt.subplot(111, frame_on=False) # no visible frame
ax.xaxis.set_visible(False) # hide the x axis
ax.yaxis.set_visible(False) # hide the y axis
table(ax, df) # where df is your data frame
plt.savefig('table.png')
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()
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.
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