I really like the 'spy' and 'pcolor' functions, which are useful in viewing matrices. 'spy' prints colored blocks for values that are above a threshold, and 'pcolor' prints out each element in a continuous range of colors. The attached is a little Python/PIL script that does these functions for Numpy arrays.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 | def spy_matrix_pil(A,fname='tmp.png',cutoff=0.1,do_outline=0,
height=300,width=300):
"""\
Use a matlab-like 'spy' function to display the large elements
of a matrix using the Python Imaging Library.
Arguments:
A Input Numpy matrix
fname Output filename to which to dump the graphics (default 'tmp.png')
cutoff Threshold value for printing an element (default 0.1)
do_outline Whether or not to print an outline around the block (default 0)
height The height of the image (default 300)
width The width of the image (default 300)
Example:
>>> from Numeric import identity,Float
>>> a = identity(10,Float)
>>> spy_matrix_pil(a)
"""
import Image,ImageDraw
img = Image.new("RGB",(width,height),(255,255,255))
draw = ImageDraw.Draw(img)
n,m = A.shape
if n>width or m>height:
raise "Rectangle too big %d %d %d %d" % (n,m,width,height)
for i in range(n):
xmin = width*i/float(n)
xmax = width*(i+1)/float(n)
for j in range(m):
ymin = height*j/float(m)
ymax = height*(j+1)/float(m)
if abs(A[i,j]) > cutoff:
if do_outline:
draw.rectangle((xmin,ymin,xmax,ymax),fill=(0,0,255),
outline=(0,0,0))
else:
draw.rectangle((xmin,ymin,xmax,ymax),fill=(0,0,255))
img.save(fname)
return
def pcolor_matrix_pil(A,fname='tmp.png',do_outline=0,
height=300,width=300):
"""\
Use a matlab-like 'pcolor' function to display the large elements
of a matrix using the Python Imaging Library.
Arguments:
A Input Numpy matrix
fname Output filename to which to dump the graphics (default 'tmp.png')
do_outline Whether or not to print an outline around the block (default 0)
height The height of the image (default 300)
width The width of the image (default 300)
Example:
>>> from Numeric import identity,Float
>>> a = identity(10,Float)
>>> pcolor_matrix_pil(a)
"""
import Image,ImageDraw
img = Image.new("RGB",(width,height),(255,255,255))
draw = ImageDraw.Draw(img)
mina = min(min(A))
maxa = max(max(A))
n,m = A.shape
if n>width or m>height:
raise "Rectangle too big %d %d %d %d" % (n,m,width,height)
for i in range(n):
xmin = width*i/float(n)
xmax = width*(i+1)/float(n)
for j in range(m):
ymin = height*j/float(m)
ymax = height*(j+1)/float(m)
color = get_color(A[i,j],mina,maxa)
if do_outline:
draw.rectangle((xmin,ymin,xmax,ymax),fill=color,
outline=(0,0,0))
else:
draw.rectangle((xmin,ymin,xmax,ymax),fill=color)
img.save(fname)
return
def get_color(a,cmin,cmax):
"""\
Convert a float value to one of a continuous range of colors.
Rewritten to use recipe 9.10 from the Python Cookbook.
"""
import math
try: a = float(a-cmin)/(cmax-cmin)
except ZeroDivisionError: a=0.5 # cmax == cmin
blue = min((max((4*(0.75-a),0.)),1.))
red = min((max((4*(a-0.25),0.)),1.))
green = min((max((4*math.fabs(a-0.5)-1.,0)),1.))
return '#%1x%1x%1x' % (int(15*red),int(15*green),int(15*blue))
from Numeric import identity,Float
a = identity(10,Float)
spy_matrix_pil(a)
pcolor_matrix_pil(a,'tmp2.png')
|
I often want to use Matlab's wonderful matrix viewing capabilities, especially the 'spy' and 'pcolor' functions, but the hassles of dumping a numpy matrix and reading it into Matlab normally keep me from doing this. Here's a little toy that I wrote to do this using the PIL.
There are some idiocies in this script, particularly the way that elements are converted to pixels. But this function does 99% of what I need out of a code.
Tweak for Numarray. I had to make a small tweak to pcolor_matrix_pil() to get it to work with Numarray:
Otherwise, it seems to work nicely. I am using your recipe to visualize coefficients of inbreeding and relationship in pedigrees. Thanks for the cool recipe -- it took me about fifteen minutes to drop it into my app and get it working.
Check out matplotlib. Take a look at the matplotlib package:
http://matplotlib.sourceforge.net/
It's a recreation (ongoing) of the matlab plotting system in python using a variety of rendering packages (backends) and non-GUI and GUI front ends. I believe that it implements pcolor and spy (as well as most 2-D matlab plotting)