"""
The image module supports basic image loading, rescaling and display
operations.
"""
from __future__ import division
import os, warnings
import numpy as npy
import matplotlib.numerix.npyma as ma
from matplotlib import rcParams
from matplotlib import artist as martist
from matplotlib import colors as mcolors
from matplotlib import cm
# For clarity, names from _image are given explicitly in this module:
from matplotlib import _image
# For user convenience, the names from _image are also imported into
# the image namespace:
from matplotlib._image import *
class AxesImage(martist.Artist, cm.ScalarMappable):
zorder = 1
def __init__(self, ax,
cmap = None,
norm = None,
interpolation=None,
origin=None,
extent=None,
filternorm=1,
filterrad=4.0,
**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)
# map interpolation strings to module constants
self._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,
}
# reverse interp dict
self._interpdr = dict([ (v,k) for k,v in self._interpd.items()])
self.set_interpolation(interpolation)
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
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')
if self._imcache is None:
if self._A.dtype == npy.uint8 and len(self._A.shape) == 3:
im = _image.frombyte(self._A, 0)
im.is_grayscale = False
else:
x = self.to_rgba(self._A, self._alpha)
im = _image.fromarray(x, 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)
# image input dimensions
im.reset_matrix()
numrows, numcols = im.get_size()
im.set_interpolation(self._interpd[self._interpolation])
xmin, xmax, ymin, ymax = self.get_extent()
dxintv = xmax-xmin
dyintv = ymax-ymin
# the viewport scale factor
sx = dxintv/self.axes.viewLim.width
sy = dyintv/self.axes.viewLim.height
# the viewport translation
tx = (xmin-self.axes.viewLim.x0)/dxintv * numcols
ty = (ymin-self.axes.viewLim.y0)/dyintv * numrows
l, b, widthDisplay, heightDisplay = self.axes.bbox.bounds
widthDisplay *= magnification
heightDisplay *= magnification
im.apply_translation(tx, ty)
im.apply_scaling(sx, sy)
# resize viewport to display
rx = widthDisplay / numcols
ry = heightDisplay / numrows
im.apply_scaling(rx, ry)
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(l, 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)
# TODO: make sure this is consistent with patch and patch
# collection on nonlinear transformed coordinates.
# TODO: consider returning image coordinates (shouldn't
# be too difficult given that the image is rectilinear
xmin, xmax, ymin, ymax = self.get_extent()
xdata, ydata = mouseevent.xdata, mouseevent.ydata
#print xdata, ydata, xmin, xmax, ymin, ymax
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()
im.write_png(fname)
def set_data(self, A, shape=None):
"""
Set the image array
ACCEPTS: numpy/PIL Image A"""
# check if data is PIL Image without importing Image
if hasattr(A,'getpixel'):
X = pil_to_array(A)
else:
X = ma.asarray(A) # assume array
self._A = X
self._imcache =None
def set_array(self, A):
"""
retained for backwards compatibility - use set_data instead
ACCEPTS: numpy array A or PIL Image"""
# This also needs to be here to override the inherited
# cm.ScalarMappable.set_array method so it is not invoked
# by mistake.
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 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()
#print 'sz', sz
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'
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, width, height = self.axes.bbox.bounds
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 = npy.asarray(x,npy.float32)
y = npy.asarray(y,npy.float32)
A = npy.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 != npy.uint8:
A = (self.cmap(self.norm(A))*255).astype(npy.uint8)
else:
A = npy.repeat(A[:,:,npy.newaxis], 4, 2)
A[:,:,3] = 255
else:
if A.dtype != npy.uint8:
A = (255*A).astype(npy.uint8)
if A.shape[2] == 3:
B = zeros(tuple(list(A.shape[0:2]) + [4]), npy.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):
print 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)
class PcolorImage(martist.Artist, cm.ScalarMappable):
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 = (npy.array(bg)*255).astype(npy.uint8)
x0, y0, v_width, v_height = self.axes.viewLim.get_bounds()
l, b, width, height = self.axes.bbox.get_bounds()
width *= magnification
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
im = _image.pcolor2(self._Ax, self._Ay, A,
height, width,
(x0, x0+v_width, y0, y0+v_height),
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())
l, b, widthDisplay, heightDisplay = self.axes.bbox.get_bounds()
renderer.draw_image(l, b, im, self.axes.bbox)
def set_data(self, x, y, A):
A = ma.asarray(A)
if x is None:
x = npy.arange(0, A.shape[1]+1, dtype=npy.float64)
else:
x = npy.asarray(x, npy.float64).ravel()
if y is None:
y = npy.arange(0, A.shape[0]+1, dtype=npy.float64)
else:
y = npy.asarray(y, npy.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')
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
#print xdata, ydata, xmin, xmax, ymin, ymax
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):
# had to introduce argument magnification to satisfy the unit test
# figimage_demo.py. I have no idea, how magnification should be used
# within the function. It should be !=1.0 only for non-default DPI
# settings in the PS backend, as introduced by patch #1562394
# Probably Nicholas Young should look over this code and see, how
# magnification should be handled correctly.
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(self.ox, 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()
im.write_png(fname)
def imread(fname):
"""
return image file in fname as numpy array
Return value is a MxNx4 array of 0-1 normalized floats
"""
handlers = {'png' :_image.readpng,
}
basename, ext = os.path.splitext(fname)
ext = ext.lower()[1:]
if ext not in handlers.keys():
raise ValueError('Only know how to handled extensions: %s' % handlers.keys())
handler = handlers[ext]
return handler(fname)
def pil_to_array( pilImage ):
if pilImage.mode in ('RGBA', 'RGBX'):
im = pilImage # no need to convert images in rgba format
else: # try to convert to an rgba image
try:
im = pilImage.convert('RGBA')
except ValueError:
raise RuntimeError('Unknown image mode')
x_str = im.tostring('raw',im.mode,0,-1)
x = npy.fromstring(x_str,npy.uint8)
x.shape = im.size[1], im.size[0], 4
return x
