Re: [Matplotlib-users] windrose 0.5
Hi Derek, I forgot to mention: you can pass throught your problem by using a masked array instead of a simple array, and it should work fine, the 'default' parameter is here to fill missing value by -1.e20, then these directions will be dropped if your speed_classes not include that missing value (generally we compute on positives speeds). Le Jeudi 01 Février 2007 13:17, Derek Hohls a écrit : Lionel I have encountered a problem with windrose. In some cases, one or more of the wind direction values are null [''] - the program then fails on line 200: values = select( [greater_equal( direction, wind_classes[i] )],[speed], default=-1.e20 ) Is it possible for you to upgrade the program to perform error trapping and simply skip (i.e. not process) any values that are null (and handle the exceptional case that all of them might, in fact, be null). Thanks! Derek -- Lionel Roubeyrie - [EMAIL PROTECTED] LIMAIR http://www.limair.asso.fr - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier. Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
[Matplotlib-users] Wrong colorbar-ticks in imshow-colorbar with 10 colors
Hi all,
I want to use imshow to plot an array of floats using
interpolation='nearest' so that every gridbox has a distinct color. Also I
want to limit the number of colors to a rather small number, e.g. 10. The
problem is that the tick labels are not at the edge of each color in the
colorbar, but somewhere in between.
An example is the trunk/matplotlib/examples/poormans_contour.py which does
not work in my case.
from pylab import *
delta = 0.01
x = arange(-3.0, 3.0, delta)
y = arange(-3.0, 3.0, delta)
X,Y = meshgrid(x, y)
Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z = Z2 - Z1 # difference of Gaussians
cmap = cm.get_cmap('jet', 10)# 10 discrete colors
im = imshow(Z, cmap=cmap, interpolation='bilinear')
axis('off')
colorbar()
#savefig('test')
show()
Is there a solution?
Ciao Claas
-
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[Matplotlib-users] Bug: Image transparency varies periodically for imshow(img, aspect='auto') at high magnification
Hi! I believe I've found a bug in matplotlib which manifests after imshow(img, aspect='auto') when only a small portion of the image is displayed, e.g: when (xmax-xmin) img.shape[1]. The effect of the bug is that the transparency for the entire image seems to vary, seemingly as a periodic funtion of (xmax-xmin). Explicitly setting the alpha channel for each pixel has no effect. The attached script generates a random image of a certain size, and plots it in four different subplots. The only thing that differs between the subplots are slight variations in x_max. The four subplots are labeled: 1) The background image is visible. 2) The background image is not visible! 3) The background image is faded! 4) The background image is again visible! which reflects the actual result on my system. As the subplots are scaled (for example by resizing the window), the intensity then varies in a periodic manner in each of the subplots. The expected result is of course that the background should be fully visible in all subplots. Additional details: $ python test.py --verbose-helpful matplotlib data path /usr/lib/python2.4/site-packages/matplotlib/mpl-data $HOME=/home/bioinfo/yohell CONFIGDIR=/home/bioinfo/yohell/.matplotlib loaded rc file /usr/lib/python2.4/site-packages/matplotlib/mpl-data/matplotlibrc matplotlib version 0.87.7 verbose.level helpful interactive is False platform is linux2 numerix numpy 1.0 font search path ['/usr/lib/python2.4/site-packages/matplotlib/mpl-data'] loaded ttfcache file /home/bioinfo/yohell/.matplotlib/ttffont.cache backend WXAgg version 2.6.1.2pre In this example I used the WXAgg backend, but GTKAgg shows the same results. I've also reproduced this bug on a WinXP machine. Thanks for an excellent plotting package! /Joel Hedlund Linköping University import numpy, pylab image = numpy.random.randint(0, 255, 309 * 1230 * 3) image.shape = (309, 1230, 3) pylab.subplot(221) pylab.text(72.5, 200, 'The background image\nis visible.') pylab.imshow(image, aspect='auto') pylab.axis((72, 75, 0, 309)) pylab.subplot(222) pylab.imshow(image, aspect='auto') pylab.text(72.5, 200, 'The background image\nis not visible!') pylab.axis((72, 76, 0, 309)) pylab.subplot(223) pylab.imshow(image, aspect='auto') pylab.text(72.5, 200, 'The background image\nis faded!') pylab.axis((72, 77, 0, 309)) pylab.subplot(224) pylab.imshow(image, aspect='auto') pylab.text(72.5, 200, 'The background image\nis again visible!') pylab.axis((72, 78, 0, 309)) pylab.show() - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier. Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Bug: Image transparency varies periodically for imshow(img, aspect='auto') at high magnification
Hi Joel, On Thursday 01 February 2007 11:09:11 am Joel Hedlund wrote: I believe I've found a bug in matplotlib which manifests after imshow(img, aspect='auto') when only a small portion of the image is displayed, e.g: when (xmax-xmin) img.shape[1]. The effect of the bug is that the transparency for the entire image seems to vary, seemingly as a periodic funtion of (xmax-xmin). Explicitly setting the alpha channel for each pixel has no effect. The attached script generates a random image of a certain size, and plots it in four different subplots. The only thing that differs between the subplots are slight variations in x_max. The four subplots are labeled: 1) The background image is visible. 2) The background image is not visible! 3) The background image is faded! 4) The background image is again visible! which reflects the actual result on my system. As the subplots are scaled (for example by resizing the window), the intensity then varies in a periodic manner in each of the subplots. The expected result is of course that the background should be fully visible in all subplots. I can verify this behavior, more or less. I observe that the figure.dpi rc setting influences the results (I tried 86.23 and 200). - Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier. Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
[Matplotlib-users] Help needed: Rendering of multiple text labels is very slow.
Hi!
I'm using matplotlib and pygtk to write a viewer for multiple sequence
alignments. (Big matrices (~100x1000) of characters, usually colored by
cell according to chemical properties). Now I've run into trouble since
the rendering of the actual characters is very slow. I have included a
small example that illustrates this. Set SHOW_LETTERS = False to see the
change in rendering speed. The difference is even greater when using
real data, so I would very much appreciate suggestions as to how I could
improve it.
My strategy:
I create an image with the same dimension as the msa, and where each
pixel is colored according to properties of the corresponding character
in the msa. I plot this in the background of the figure using imshow().
At each redraw (refresh, resize, zoom...) I determine the size that each
image pixel occupies at the current canvas size, and pick a font where
one letter will fit inside this square. Then I put the corresponding msa
letter into this square using text()/add_artist().
Would it be possible to use only one Text instance that would hold all
letters, and somehow stretch that to the desired size? If so, could I
expect better performance?
Does anyone have a better idea?
Thanks for an awesome plotting package!
/Joel Hedlund
# Change this to see change in rendering speed:
SHOW_LETTERS = False
import matplotlib
matplotlib.use('GTKAgg')
import pylab
from numpy import array, uint8
RED = array([229, 51, 25], uint8)
BLUE = array([25, 127, 229], uint8)
GREEN = array([25, 204, 25], uint8)
CYAN = array([25, 178, 178], uint8)
PINK = array([229, 127, 127], uint8)
MAGENTA = array([204, 76, 204], uint8)
YELLOW = array([204, 204, 0], uint8)
ORANGE = array([229, 153, 76], uint8)
WHITE = array([255, 255, 255], uint8)
colors = {'G': ORANGE,
'P': YELLOW,
'T': GREEN,
'S': GREEN,
'N': GREEN,
'Q': GREEN,
'W': BLUE,
'L': BLUE,
'V': BLUE,
'I': BLUE,
'M': BLUE,
'A': BLUE,
'F': BLUE,
'C': BLUE,
'H': CYAN,
'Y': CYAN,
'E': MAGENTA,
'D': MAGENTA,
'K': RED,
'R': RED}
msa = \
KYFALQ---
KYFALQPDDVYYCGIKYIKDDVILNEPSAD---APAALY--QTIEENIKIFVEFISVPVPE
KYFALQPDDVYYCGIKYIKDDVLLNEPSAD---APAARY--QTIEENIKIFEEDEVEFISVPVPE
KYFAFQPDDVYYCGIKYIKDDVVLNEPSAD---APASRY--QTIEENIKIFEEDEVEFISVPVPE
KYFAFQQDDVYYCGIKYIKDDLILNEPSAN---APAARF--QTIEENIKILEEDNVEFISVPVPE
KYFAMQ-RGVYFCGIRYLEDDAALTEPYAETPVRY--HSFRESIQILVELINVPVPE
KYFAMQ-RGVYFCGIRYLEDDAALTEPYAETPVRY--HSFKESIQILEEEDVELINVPVPE
KYFAMQ-RGVYFCGIRYLEDDAALTEPYAETPVRY--HSFKESIQILEEEDVELINVPVPE
KYFAFQ-GGVYFCGIKYIEDGLSLPESGAE---AQSARY--HTIEQNIQILEEEDVEFISVPVPE
KYFAFQQGGVYFCGIKYIEDGLSLPESGAQ---LKSARY--HTIEQNIQILEEEDVEFISVPVPE
RYYVLERDQVFICGLKYYEEDYELNEEVDP-EIGAPLRLIEENVSFFEDDEVELISVPVPE
HHYYNPEVSYQHHGGWED-EVELPNQFPLRQMEERIRVLEREQVELISVPVPE
RYYFIEEERMYFCGVNYREENYKMQDSQEDTDMDLPAAY--KRIEEKVRVLEDEGVELINIPVPK
.splitlines(False)
tmp = []
for s in msa:
tmp.extend(colors.get(t, WHITE) for t in s)
bg = array(tmp)
bg.shape = (len(msa), len(msa[0]), 3)
class CharSize(object):
def __init__(self, width=None, height=None, fontprops=None):
self.width = width
self.height = height
self.fontprops = fontprops
def __lt__(self, other):
if not isinstance(other, tuple):
raise TypeError(can only be compared to (x, y) tuple)
return (self.width other[0] * 0.5) and (self.height other[1] * 0.5)
class FontSelector(object):
def __init__(self, charsizes=None):
if charsizes is None:
charsizes = []
self.charsizes = charsizes
@classmethod
def from_sizes(cls, renderer, *fontsizes, **fontprops):
if not fontsizes:
raise TypeError(need a font size range)
o = cls()
for i in sorted(range(*fontsizes), reverse=True):
fontprops['size'] = i
oFontProps = matplotlib.font_manager.FontProperties(**fontprops)
nWidth, nHeight = renderer.get_text_width_height('M', oFontProps,
False)
o.charsizes.append(CharSize(nWidth, nHeight, oFontProps))
return o
def by_cell_size(self, width, height):
tnAvailableSize = (width, height)
for oCharSize in self.charsizes:
if oCharSize tnAvailableSize:
return oCharSize.fontprops
return None
figure = pylab.figure()
renderer = figure.canvas.get_renderer()
font_selector = FontSelector.from_sizes(renderer, 4, 18, family='monospace')
def replot(widget):
pylab.cla()
pylab.imshow(bg, origin='lower', interpolation='nearest', aspect='auto')
pylab.ylim(len(msa), 0)
iWidth, iHeight = figure.canvas.get_width_height()
nCharWidth = iWidth / float(len(msa[0]))
nCharHeight = iHeight / float(len(msa))
oFont =
