00001 """ This module contains the instantiations of color mapping classes """ import colors from matplotlib import verbose from matplotlib import rcParams from matplotlib.numerix import asarray from numerix import nx import numerix.ma as ma from cbook import iterable from _cm import * 00016 def get_cmap(name=None, lut=None): """ Get a colormap instance, defaulting to rc values if name is None """ if name is None: name = rcParams['image.cmap'] if lut is None: lut = rcParams['image.lut'] assert(name in datad.keys()) return colors.LinearSegmentedColormap(name, datad[name], lut) 00026 class ScalarMappable: """ This is a mixin class to support scalar -> RGBA mapping. Handles normalization and colormapping """ 00032 def __init__(self, norm=None, cmap=None): """ norm is a colors.normalize instance to map luminance to 0-1 cmap is a cm colormap instance """ if cmap is None: cmap = get_cmap() if norm is None: norm = colors.Normalize() self._A = None self.norm = norm self.cmap = cmap self.observers = [] self.colorbar = None def set_colorbar(self, im, ax): 'set the colorbar image and axes associated with mappable' self.colorbar = im, ax 00051 def to_rgba(self, x, alpha=1.0): '''Return a normalized rgba array corresponding to x. If x is already an rgb or rgba array, return it unchanged. ''' if hasattr(x, 'shape') and len(x.shape)>2: return x x = ma.asarray(x) x = self.norm(x) x = self.cmap(x, alpha) return x def set_array(self, A): 'Set the image array from numeric/numarray A' self._A = A def get_array(self): 'Return the array' return self._A def get_clim(self): 'return the min, max of the color limits for image scaling' return self.norm.vmin, self.norm.vmax 00073 def set_clim(self, vmin=None, vmax=None): """ set the norm limits for image scaling; if vmin is a length2 sequence, interpret it as (vmin, vmax) which is used to support setp ACCEPTS: a length 2 sequence of floats """ if vmin is not None and vmax is None and iterable(vmin) and len(vmin)==2: vmin, vmax = vmin if vmin is not None: self.norm.vmin = vmin if vmax is not None: self.norm.vmax = vmax self.changed() 00088 def set_cmap(self, cmap): """ set the colormap for luminance data ACCEPTS: a colormap """ if cmap is None: cmap = get_cmap() self.cmap = cmap self.changed() def set_norm(self, norm): 'set the normalization instance' if norm is None: norm = colors.Normalize() self.norm = norm self.changed() 00104 def autoscale(self): """ Autoscale the scalar limits on the norm instance using the current array """ if self._A is None: raise TypeError('You must first set_array for mappable') self.norm.autoscale(self._A) self.changed() 00114 def autoscale_None(self): """ Autoscale the scalar limits on the norm instance using the current array, changing only limits that are None """ if self._A is None: raise TypeError('You must first set_array for mappable') self.norm.autoscale_None(self._A) self.changed() 00126 def add_observer(self, mappable): """ whenever the norm, clim or cmap is set, call the notify instance of the mappable observer with self. This is designed to allow one image to follow changes in the cmap of another image """ self.observers.append(mappable) try: self.add_callback(mappable.notify) except AttributeError: pass 00140 def notify(self, mappable): """ If this is called then we are pegged to another mappable. Update our cmap, norm, alpha from the other mappable. """ self.set_cmap(mappable.cmap) self.set_norm(mappable.norm) try: self.set_alpha(mappable.get_alpha()) except AttributeError: pass 00152 def changed(self): """ Call this whenever the mappable is changed so observers can update state """ for observer in self.observers: observer.notify(self)