00001 """
The image module supports basic image loading, rescaling and display
operations.
"""
from __future__ import division
import os, warnings
import numpy as np
from numpy import ma
from matplotlib import rcParams
from matplotlib import artist as martist
from matplotlib import colors as mcolors
from matplotlib import cm
from matplotlib import _image
from matplotlib import _png
from matplotlib._image import *
class AxesImage(martist.Artist, cm.ScalarMappable):
zorder = 1
_interpd = {
'nearest' : _image.NEAREST,
'bilinear' : _image.BILINEAR,
'bicubic' : _image.BICUBIC,
'spline16' : _image.SPLINE16,
'spline36' : _image.SPLINE36,
'hanning' : _image.HANNING,
'hamming' : _image.HAMMING,
'hermite' : _image.HERMITE,
'kaiser' : _image.KAISER,
'quadric' : _image.QUADRIC,
'catrom' : _image.CATROM,
'gaussian' : _image.GAUSSIAN,
'bessel' : _image.BESSEL,
'mitchell' : _image.MITCHELL,
'sinc' : _image.SINC,
'lanczos' : _image.LANCZOS,
'blackman' : _image.BLACKMAN,
}
_interpdr = dict([ (v,k) for k,v in _interpd.items()])
interpnames = _interpd.keys()
def __init__(self, ax,
cmap = None,
norm = None,
interpolation=None,
origin=None,
extent=None,
filternorm=1,
filterrad=4.0,
resample = False,
**kwargs
):
"""
interpolation and cmap default to their rc settings
cmap is a colors.Colormap instance
norm is a colors.Normalize instance to map luminance to 0-1
extent is data axes (left, right, bottom, top) for making image plots
registered with data plots. Default is to label the pixel
centers with the zero-based row and column indices.
Additional kwargs are matplotlib.artist properties
"""
martist.Artist.__init__(self)
cm.ScalarMappable.__init__(self, norm, cmap)
if origin is None: origin = rcParams['image.origin']
self.origin = origin
self._extent = extent
self.set_filternorm(filternorm)
self.set_filterrad(filterrad)
self._filterrad = filterrad
self.set_interpolation(interpolation)
self.set_resample(resample)
self.axes = ax
self._imcache = None
self.update(kwargs)
def get_size(self):
'Get the numrows, numcols of the input image'
if self._A is None:
raise RuntimeError('You must first set the image array')
return self._A.shape[:2]
def set_alpha(self, alpha):
"""
Set the alpha value used for blending - not supported on
all backends
ACCEPTS: float
"""
martist.Artist.set_alpha(self, alpha)
self._imcache = None
def changed(self):
"""
Call this whenever the mappable is changed so observers can
update state
"""
self._imcache = None
self._rgbacache = None
cm.ScalarMappable.changed(self)
def make_image(self, magnification=1.0):
if self._A is None:
raise RuntimeError('You must first set the image array or the image attribute')
xmin, xmax, ymin, ymax = self.get_extent()
dxintv = xmax-xmin
dyintv = ymax-ymin
sx = dxintv/self.axes.viewLim.width
sy = dyintv/self.axes.viewLim.height
numrows, numcols = self._A.shape[:2]
if sx > 2:
x0 = (self.axes.viewLim.x0-xmin)/dxintv * numcols
ix0 = max(0, int(x0 - self._filterrad))
x1 = (self.axes.viewLim.x1-xmin)/dxintv * numcols
ix1 = min(numcols, int(x1 + self._filterrad))
xslice = slice(ix0, ix1)
xmin_old = xmin
xmin = xmin_old + ix0*dxintv/numcols
xmax = xmin_old + ix1*dxintv/numcols
dxintv = xmax - xmin
sx = dxintv/self.axes.viewLim.width
else:
xslice = slice(0, numcols)
if sy > 2:
y0 = (self.axes.viewLim.y0-ymin)/dyintv * numrows
iy0 = max(0, int(y0 - self._filterrad))
y1 = (self.axes.viewLim.y1-ymin)/dyintv * numrows
iy1 = min(numrows, int(y1 + self._filterrad))
if self.origin == 'upper':
yslice = slice(numrows-iy1, numrows-iy0)
else:
yslice = slice(iy0, iy1)
ymin_old = ymin
ymin = ymin_old + iy0*dyintv/numrows
ymax = ymin_old + iy1*dyintv/numrows
dyintv = ymax - ymin
sy = dyintv/self.axes.viewLim.height
else:
yslice = slice(0, numrows)
if xslice != self._oldxslice or yslice != self._oldyslice:
self._imcache = None
self._oldxslice = xslice
self._oldyslice = yslice
if self._imcache is None:
if self._A.dtype == np.uint8 and len(self._A.shape) == 3:
im = _image.frombyte(self._A[yslice,xslice,:], 0)
im.is_grayscale = False
else:
if self._rgbacache is None:
x = self.to_rgba(self._A, self._alpha)
self._rgbacache = x
else:
x = self._rgbacache
im = _image.fromarray(x[yslice,xslice], 0)
if len(self._A.shape) == 2:
im.is_grayscale = self.cmap.is_gray()
else:
im.is_grayscale = False
self._imcache = im
if self.origin=='upper':
im.flipud_in()
else:
im = self._imcache
fc = self.axes.get_frame().get_facecolor()
bg = mcolors.colorConverter.to_rgba(fc, 0)
im.set_bg( *bg)
im.reset_matrix()
numrows, numcols = im.get_size()
im.set_interpolation(self._interpd[self._interpolation])
im.set_resample(self._resample)
tx = (xmin-self.axes.viewLim.x0)/dxintv * numcols
ty = (ymin-self.axes.viewLim.y0)/dyintv * numrows
l, b, r, t = self.axes.bbox.extents
widthDisplay = (round(r) + 0.5) - (round(l) - 0.5)
heightDisplay = (round(t) + 0.5) - (round(b) - 0.5)
widthDisplay *= magnification
heightDisplay *= magnification
im.apply_translation(tx, ty)
rx = widthDisplay / numcols
ry = heightDisplay / numrows
im.apply_scaling(rx*sx, ry*sy)
im.resize(int(widthDisplay+0.5), int(heightDisplay+0.5),
norm=self._filternorm, radius=self._filterrad)
return im
def draw(self, renderer, *args, **kwargs):
if not self.get_visible(): return
if (self.axes.get_xscale() != 'linear' or
self.axes.get_yscale() != 'linear'):
warnings.warn("Images are not supported on non-linear axes.")
im = self.make_image(renderer.get_image_magnification())
l, b, widthDisplay, heightDisplay = self.axes.bbox.bounds
renderer.draw_image(round(l), round(b), im, self.axes.bbox.frozen(),
*self.get_transformed_clip_path_and_affine())
def contains(self, mouseevent):
"""Test whether the mouse event occured within the image.
"""
if callable(self._contains): return self._contains(self,mouseevent)
xmin, xmax, ymin, ymax = self.get_extent()
xdata, ydata = mouseevent.xdata, mouseevent.ydata
if xdata is not None and ydata is not None:
inside = xdata>=xmin and xdata<=xmax and ydata>=ymin and ydata<=ymax
else:
inside = False
return inside,{}
def write_png(self, fname, noscale=False):
"""Write the image to png file with fname"""
im = self.make_image()
if noscale:
numrows, numcols = im.get_size()
im.reset_matrix()
im.set_interpolation(0)
im.resize(numcols, numrows)
im.flipud_out()
rows, cols, buffer = im.as_rgba_str()
_png.write_png(buffer, cols, rows, fname)
def set_data(self, A, shape=None):
"""
Set the image array
ACCEPTS: numpy/PIL Image A"""
if hasattr(A,'getpixel'):
X = pil_to_array(A)
else:
X = ma.asarray(A)
self._A = X
self._imcache =None
self._rgbacache = None
self._oldxslice = None
self._oldyslice = None
def set_array(self, A):
"""
retained for backwards compatibility - use set_data instead
ACCEPTS: numpy array A or PIL Image"""
self.set_data(A)
def set_extent(self, extent):
"""extent is data axes (left, right, bottom, top) for making image plots
"""
self._extent = extent
xmin, xmax, ymin, ymax = extent
corners = (xmin, ymin), (xmax, ymax)
self.axes.update_datalim(corners)
if self.axes._autoscaleon:
self.axes.set_xlim((xmin, xmax))
self.axes.set_ylim((ymin, ymax))
def get_interpolation(self):
"""
Return the interpolation method the image uses when resizing.
One of
'bicubic', 'bilinear', 'blackman100', 'blackman256', 'blackman64',
'nearest', 'sinc144', 'sinc256', 'sinc64', 'spline16', 'spline36'
"""
return self._interpolation
def set_interpolation(self, s):
"""
Set the interpolation method the image uses when resizing.
ACCEPTS: ['bicubic' | 'bilinear' | 'blackman100' | 'blackman256' | 'blackman64', 'nearest' | 'sinc144' | 'sinc256' | 'sinc64' | 'spline16' | 'spline36']
"""
if s is None: s = rcParams['image.interpolation']
s = s.lower()
if not self._interpd.has_key(s):
raise ValueError('Illegal interpolation string')
self._interpolation = s
def set_resample(self, v):
if v is None: v = rcParams['image.resample']
self._resample = v
def get_interpolation(self):
return self._resample
def get_extent(self):
'get the image extent: left, right, bottom, top'
if self._extent is not None:
return self._extent
else:
sz = self.get_size()
numrows, numcols = sz
if self.origin == 'upper':
return (-0.5, numcols-0.5, numrows-0.5, -0.5)
else:
return (-0.5, numcols-0.5, -0.5, numrows-0.5)
def set_filternorm(self, filternorm):
"""Set whether the resize filter norms the weights -- see
help for imshow
ACCEPTS: 0 or 1
"""
if filternorm:
self._filternorm = 1
else:
self._filternorm = 0
def get_filternorm(self):
'return the filternorm setting'
return self._filternorm
def set_filterrad(self, filterrad):
"""Set the resize filter radius only applicable to some
interpolation schemes -- see help for imshow
ACCEPTS: positive float
"""
r = float(filterrad)
assert(r>0)
self._filterrad = r
def get_filterrad(self):
'return the filterrad setting'
return self._filterrad
class NonUniformImage(AxesImage):
def __init__(self, ax,
**kwargs
):
AxesImage.__init__(self, ax,
**kwargs)
def make_image(self, magnification=1.0):
if self._A is None:
raise RuntimeError('You must first set the image array')
x0, y0, v_width, v_height = self.axes.viewLim.bounds
l, b, r, t = self.axes.bbox.extents
width = (round(r) + 0.5) - (round(l) - 0.5)
height = (round(t) + 0.5) - (round(b) - 0.5)
width *= magnification
height *= magnification
im = _image.pcolor(self._Ax, self._Ay, self._A,
height, width,
(x0, x0+v_width, y0, y0+v_height))
fc = self.axes.get_frame().get_facecolor()
bg = mcolors.colorConverter.to_rgba(fc, 0)
im.set_bg(*bg)
return im
def set_data(self, x, y, A):
x = np.asarray(x,np.float32)
y = np.asarray(y,np.float32)
A = np.asarray(A)
if len(x.shape) != 1 or len(y.shape) != 1\
or A.shape[0:2] != (y.shape[0], x.shape[0]):
raise TypeError("Axes don't match array shape")
if len(A.shape) not in [2, 3]:
raise TypeError("Can only plot 2D or 3D data")
if len(A.shape) == 3 and A.shape[2] not in [1, 3, 4]:
raise TypeError("3D arrays must have three (RGB) or four (RGBA) color components")
if len(A.shape) == 3 and A.shape[2] == 1:
A.shape = A.shape[0:2]
if len(A.shape) == 2:
if A.dtype != np.uint8:
A = (self.cmap(self.norm(A))*255).astype(np.uint8)
else:
A = np.repeat(A[:,:,np.newaxis], 4, 2)
A[:,:,3] = 255
else:
if A.dtype != np.uint8:
A = (255*A).astype(np.uint8)
if A.shape[2] == 3:
B = zeros(tuple(list(A.shape[0:2]) + [4]), np.uint8)
B[:,:,0:3] = A
B[:,:,3] = 255
A = B
self._A = A
self._Ax = x
self._Ay = y
self._imcache = None
def set_array(self, *args):
raise NotImplementedError('Method not supported')
def set_interpolation(self, s):
if s != None and s != 'nearest':
raise NotImplementedError('Only nearest neighbor supported')
AxesImage.set_interpolation(self, s)
def get_extent(self):
if self._A is None:
raise RuntimeError('Must set data first')
return self._Ax[0], self._Ax[-1], self._Ay[0], self._Ay[-1]
def set_filternorm(self, s):
pass
def set_filterrad(self, s):
pass
def set_norm(self, norm):
if self._A is not None:
raise RuntimeError('Cannot change colors after loading data')
cm.ScalarMappable.set_norm(self, norm)
def set_cmap(self, cmap):
if self._A is not None:
raise RuntimeError('Cannot change colors after loading data')
cm.ScalarMappable.set_cmap(self, norm)
00469 class PcolorImage(martist.Artist, cm.ScalarMappable):
'''
Make a pcolor-style plot with an irregular rectangular grid.
This uses a variation of the original irregular image code,
and it is used by pcolorfast for the corresponding grid type.
'''
00476 def __init__(self, ax,
x=None,
y=None,
A=None,
cmap = None,
norm = None,
**kwargs
):
"""
cmap defaults to its rc setting
cmap is a colors.Colormap instance
norm is a colors.Normalize instance to map luminance to 0-1
Additional kwargs are matplotlib.artist properties
"""
martist.Artist.__init__(self)
cm.ScalarMappable.__init__(self, norm, cmap)
self.axes = ax
self._rgbacache = None
self.update(kwargs)
self.set_data(x, y, A)
def make_image(self, magnification=1.0):
if self._A is None:
raise RuntimeError('You must first set the image array')
fc = self.axes.get_frame().get_facecolor()
bg = mcolors.colorConverter.to_rgba(fc, 0)
bg = (np.array(bg)*255).astype(np.uint8)
l, b, r, t = self.axes.bbox.extents
width = (round(r) + 0.5) - (round(l) - 0.5)
height = (round(t) + 0.5) - (round(b) - 0.5)
width = width * magnification
height = height * magnification
if self.check_update('array'):
A = self.to_rgba(self._A, alpha=self._alpha, bytes=True)
self._rgbacache = A
if self._A.ndim == 2:
self.is_grayscale = self.cmap.is_gray()
else:
A = self._rgbacache
vl = self.axes.viewLim
im = _image.pcolor2(self._Ax, self._Ay, A,
height,
width,
(vl.x0, vl.x1, vl.y0, vl.y1),
bg)
im.is_grayscale = self.is_grayscale
return im
def draw(self, renderer, *args, **kwargs):
if not self.get_visible(): return
im = self.make_image(renderer.get_image_magnification())
renderer.draw_image(round(self.axes.bbox.xmin),
round(self.axes.bbox.ymin),
im,
self.axes.bbox.frozen(),
*self.get_transformed_clip_path_and_affine())
def set_data(self, x, y, A):
A = ma.asarray(A)
if x is None:
x = np.arange(0, A.shape[1]+1, dtype=np.float64)
else:
x = np.asarray(x, np.float64).ravel()
if y is None:
y = np.arange(0, A.shape[0]+1, dtype=np.float64)
else:
y = np.asarray(y, np.float64).ravel()
if A.shape[:2] != (y.size-1, x.size-1):
print A.shape
print y.size
print x.size
raise ValueError("Axes don't match array shape")
if A.ndim not in [2, 3]:
raise ValueError("A must be 2D or 3D")
if A.ndim == 3 and A.shape[2] == 1:
A.shape = A.shape[:2]
self.is_grayscale = False
if A.ndim == 3:
if A.shape[2] in [3, 4]:
if (A[:,:,0] == A[:,:,1]).all() and (A[:,:,0] == A[:,:,2]).all():
self.is_grayscale = True
else:
raise ValueError("3D arrays must have RGB or RGBA as last dim")
self._A = A
self._Ax = x
self._Ay = y
self.update_dict['array'] = True
def set_array(self, *args):
raise NotImplementedError('Method not supported')
00572 def set_alpha(self, alpha):
"""
Set the alpha value used for blending - not supported on
all backends
ACCEPTS: float
"""
martist.Artist.set_alpha(self, alpha)
self.update_dict['array'] = True
class FigureImage(martist.Artist, cm.ScalarMappable):
zorder = 1
def __init__(self, fig,
cmap = None,
norm = None,
offsetx = 0,
offsety = 0,
origin=None,
**kwargs
):
"""
cmap is a colors.Colormap instance
norm is a colors.Normalize instance to map luminance to 0-1
kwargs are an optional list of Artist keyword args
"""
martist.Artist.__init__(self)
cm.ScalarMappable.__init__(self, norm, cmap)
if origin is None: origin = rcParams['image.origin']
self.origin = origin
self.figure = fig
self.ox = offsetx
self.oy = offsety
self.update(kwargs)
def contains(self, mouseevent):
"""Test whether the mouse event occured within the image.
"""
if callable(self._contains): return self._contains(self,mouseevent)
xmin, xmax, ymin, ymax = self.get_extent()
xdata, ydata = mouseevent.x, mouseevent.y
if xdata is not None and ydata is not None:
inside = xdata>=xmin and xdata<=xmax and ydata>=ymin and ydata<=ymax
else:
inside = False
return inside,{}
def get_size(self):
'Get the numrows, numcols of the input image'
if self._A is None:
raise RuntimeError('You must first set the image array')
return self._A.shape[:2]
def get_extent(self):
'get the image extent: left, right, bottom, top'
numrows, numcols = self.get_size()
return (-0.5+self.ox, numcols-0.5+self.ox,
-0.5+self.oy, numrows-0.5+self.oy)
def make_image(self, magnification=1.0):
if self._A is None:
raise RuntimeError('You must first set the image array')
x = self.to_rgba(self._A, self._alpha)
im = _image.fromarray(x, 1)
fc = self.figure.get_facecolor()
im.set_bg( *mcolors.colorConverter.to_rgba(fc, 0) )
im.is_grayscale = (self.cmap.name == "gray" and
len(self._A.shape) == 2)
if self.origin=='upper':
im.flipud_out()
return im
def draw(self, renderer, *args, **kwargs):
if not self.get_visible(): return
im = self.make_image()
renderer.draw_image(round(self.ox), round(self.oy), im, self.figure.bbox,
*self.get_transformed_clip_path_and_affine())
def write_png(self, fname):
"""Write the image to png file with fname"""
im = self.make_image()
rows, cols, buffer = im.as_rgba_str()
_png.write_png(buffer, cols, rows, fname)
00671 def imread(fname):
"""
Return image file in *fname* as :class:`numpy.array`.
Return value is a :class:`numpy.array`. For grayscale images, the
return array is MxN. For RGB images, the return value is MxNx3.
For RGBA images the return value is MxNx4.
matplotlib can only read PNGs natively, but if `PIL
<http://www.pythonware.com/products/pil/>`_ is installed, it will
use it to load the image and return an array (if possible) which
can be used with :func:`~matplotlib.pyplot.imshow`.
TODO: support RGB and grayscale return values in _image.readpng
"""
def pilread():
'try to load the image with PIL or return None'
try: import Image
except ImportError: return None
image = Image.open( fname )
return pil_to_array(image)
handlers = {'png' :_png.read_png,
}
basename, ext = os.path.splitext(fname)
ext = ext.lower()[1:]
if ext not in handlers.keys():
im = pilread()
if im is None:
raise ValueError('Only know how to handle extensions: %s; with PIL installed matplotlib can handle more images' % handlers.keys())
return im
handler = handlers[ext]
return handler(fname)
00711 def pil_to_array( pilImage ):
"""
load a PIL image and return it as a numpy array of uint8. For
grayscale images, the return array is MxN. For RGB images, the
return value is MxNx3. For RGBA images the return value is MxNx4
"""
def toarray(im):
'return a 1D array of floats'
x_str = im.tostring('raw',im.mode,0,-1)
x = np.fromstring(x_str,np.uint8)
return x
if pilImage.mode in ('RGBA', 'RGBX'):
im = pilImage
elif pilImage.mode=='L':
im = pilImage
x = toarray(im)
x.shape = im.size[1], im.size[0]
return x
elif pilImage.mode=='RGB':
im = pilImage
x = toarray(im)
x.shape = im.size[1], im.size[0], 3
return x
else:
try:
im = pilImage.convert('RGBA')
except ValueError:
raise RuntimeError('Unknown image mode')
x = toarray(im)
x.shape = im.size[1], im.size[0], 4
return x