def fix(x): """ Rounds towards zero. x_rounded = fix(x) rounds the elements of x to the nearest integers towards zero. For negative numbers is equivalent to ceil and for positive to floor. """ dim = numerix.shape(x) if MLab.rank(x)==2: y = numerix.reshape(x,(1,dim[0]*dim[1]))[0] y = y.tolist() elif MLab.rank(x)==1: y = x else: y = [x] for i in range(len(y)): if y[i]>0: y[i] = numerix.floor(y[i]) else: y[i] = numerix.ceil(y[i]) if MLab.rank(x)==2: x = numerix.reshape(y,dim) elif MLab.rank(x)==0: x = y[0] return x
def fix(x): """ Rounds towards zero. x_rounded = fix(x) rounds the elements of x to the nearest integers towards zero. For negative numbers is equivalent to ceil and for positive to floor. """ dim = numerix.shape(x) if numerix.mlab.rank(x)==2: y = reshape(x,(1,dim[0]*dim[1]))[0] y = y.tolist() elif numerix.mlab.rank(x)==1: y = x else: y = [x] for i in range(len(y)): if y[i]>0: y[i] = floor(y[i]) else: y[i] = ceil(y[i]) if numerix.mlab.rank(x)==2: x = reshape(y,dim) elif numerix.mlab.rank(x)==0: x = y[0] return x
def _process_linewidths(self): linewidths = self.linewidths Nlev = len(self.levels) if linewidths is None: tlinewidths = [rcParams['lines.linewidth']] *Nlev else: if iterable(linewidths) and len(linewidths) < Nlev: linewidths = list(linewidths) * int(ceil(Nlev/len(linewidths))) elif not iterable(linewidths) and type(linewidths) in [int, float]: linewidths = [linewidths] * Nlev tlinewidths = [(w,) for w in linewidths] return tlinewidths
def locate_label(self, linecontour, labelwidth): """find a good place to plot a label (relatively flat part of the contour) and the angle of rotation for the text object """ nsize = len(linecontour) if labelwidth > 1: xsize = int(ceil(nsize / labelwidth)) else: xsize = 1 if xsize == 1: ysize = nsize else: ysize = labelwidth XX = resize(asarray(linecontour)[:, 0], (xsize, ysize)) YY = resize(asarray(linecontour)[:, 1], (xsize, ysize)) yfirst = YY[:, 0] ylast = YY[:, -1] xfirst = XX[:, 0] xlast = XX[:, -1] s = ((reshape(yfirst, (xsize, 1)) - YY) * (reshape(xlast, (xsize, 1)) - reshape(xfirst, (xsize, 1))) - (reshape(xfirst, (xsize, 1)) - XX) * (reshape(ylast, (xsize, 1)) - reshape(yfirst, (xsize, 1)))) L = sqrt((xlast - xfirst)**2 + (ylast - yfirst)**2) dist = add.reduce(([(abs(s)[i] / L[i]) for i in range(xsize)]), -1) x, y, ind = self.get_label_coords(dist, XX, YY, ysize, labelwidth) #print 'ind, x, y', ind, x, y angle = arctan2(ylast - yfirst, xlast - xfirst) rotation = angle[ind] * 180 / pi if rotation > 90: rotation = rotation - 180 if rotation < -90: rotation = 180 + rotation # There must be a more efficient way... lc = [tuple(l) for l in linecontour] dind = lc.index((x, y)) #print 'dind', dind #dind = list(linecontour).index((x,y)) return x, y, rotation, dind
def locate_label(self, linecontour, labelwidth): """find a good place to plot a label (relatively flat part of the contour) and the angle of rotation for the text object """ nsize= len(linecontour) if labelwidth > 1: xsize = int(ceil(nsize/labelwidth)) else: xsize = 1 if xsize == 1: ysize = nsize else: ysize = labelwidth XX = resize(asarray(linecontour)[:,0],(xsize, ysize)) YY = resize(asarray(linecontour)[:,1],(xsize,ysize)) yfirst = YY[:,0] ylast = YY[:,-1] xfirst = XX[:,0] xlast = XX[:,-1] s = ( (reshape(yfirst, (xsize,1))-YY) * (reshape(xlast,(xsize,1)) - reshape(xfirst,(xsize,1))) - (reshape(xfirst,(xsize,1))-XX) * (reshape(ylast,(xsize,1)) - reshape(yfirst,(xsize,1))) ) L=sqrt((xlast-xfirst)**2+(ylast-yfirst)**2) dist = add.reduce(([(abs(s)[i]/L[i]) for i in range(xsize)]),-1) x,y,ind = self.get_label_coords(dist, XX, YY, ysize, labelwidth) #print 'ind, x, y', ind, x, y angle = arctan2(ylast - yfirst, xlast - xfirst) rotation = angle[ind]*180/pi if rotation > 90: rotation = rotation -180 if rotation < -90: rotation = 180 + rotation # There must be a more efficient way... lc = [tuple(l) for l in linecontour] dind = lc.index((x,y)) #print 'dind', dind #dind = list(linecontour).index((x,y)) return x,y, rotation, dind
def contour(self, *args, **kwargs): """ contour(self, *args, **kwargs) Function signatures contour(Z) - make a contour plot of an array Z. The level values are chosen automatically. contour(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface contour(Z,N) and contour(X,Y,Z,N) - draw N contour lines overriding the automatic value contour(Z,V) and contour(X,Y,Z,V) - draw len(V) contour lines, at the values specified in V (array, list, tuple) contour(Z, **kwargs) - Use keyword args to control colors, linewidth, origin, cmap ... see below [L,C] = contour(...) returns a list of levels and a silent_list of LineCollections Optional keywork args are shown with their defaults below (you must use kwargs for these): * colors = None: one of these: - a tuple of matplotlib color args (string, float, rgb, etc), different levels will be plotted in different colors in the order specified - one string color, e.g. colors = 'r' or colors = 'red', all levels will be plotted in this color - if colors == None, the default colormap will be used * alpha=1.0 : the alpha blending value * cmap = None: a cm Colormap instance from matplotlib.cm. * origin = None: 'upper'|'lower'|'image'|None. If 'image', the rc value for image.origin will be used. If None (default), the first value of Z will correspond to the lower left corner, location (0,0). This keyword is active only if contourf is called with one or two arguments, that is, without explicitly specifying X and Y. * extent = None: (x0,x1,y0,y1); also active only if X and Y are not specified. * badmask = None: array with dimensions of Z, and with values of zero at locations corresponding to valid data, and one at locations where the value of Z should be ignored. This is experimental. It presently works for edge regions for line and filled contours, but for interior regions it works correctly only for line contours. The badmask kwarg may go away in the future, to be replaced by the use of NaN value in Z and/or the use of a masked array in Z. * linewidths = None: or one of these: - a number - all levels will be plotted with this linewidth, e.g. linewidths = 0.6 - a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different levels will be plotted with different linewidths in the order specified - if linewidths == None, the default width in lines.linewidth in .matplotlibrc is used * fmt = '1.3f': a format string for adding a label to each collection. Useful for auto-legending. """ alpha = kwargs.get('alpha', 1.0) linewidths = kwargs.get('linewidths', None) fmt = kwargs.get('fmt', '%1.3f') origin = kwargs.get('origin', None) extent = kwargs.get('extent', None) cmap = kwargs.get('cmap', None) colors = kwargs.get('colors', None) badmask = kwargs.get('badmask', None) if cmap is not None: assert (isinstance(cmap, Colormap)) if origin is not None: assert (origin in ['lower', 'upper', 'image']) if extent is not None: assert (len(extent) == 4) if colors is not None and cmap is not None: raise RuntimeError('Either colors or cmap must be None') # todo: shouldn't this use the current image rather than the rc param? if origin == 'image': origin = rcParams['image.origin'] x, y, z, lev = self._contour_args(False, badmask, origin, extent, *args) # Manipulate the plot *after* checking the input arguments. if not self.ax.ishold(): self.ax.cla() Nlev = len(lev) if cmap is None: if colors is None: Ncolors = Nlev else: Ncolors = len(colors) else: Ncolors = Nlev reg, triangle = self._initialize_reg_tri(z, badmask) tcolors, mappable, collections = self._process_colors( z, colors, alpha, lev, cmap) if linewidths == None: tlinewidths = [rcParams['lines.linewidth']] * Nlev else: if iterable(linewidths) and len(linewidths) < Nlev: linewidths = list(linewidths) * int( ceil(Nlev / len(linewidths))) elif not iterable(linewidths) and type(linewidths) in [int, float]: linewidths = [linewidths] * Nlev tlinewidths = [(w, ) for w in linewidths] region = 0 for level, color, width in zip(lev, tcolors, tlinewidths): ntotal, nparts = _contour.GcInit1(x, y, reg, triangle, region, z, level) np = zeros((nparts, ), typecode='l') xp = zeros((ntotal, ), Float64) yp = zeros((ntotal, ), Float64) nlist = _contour.GcTrace(np, xp, yp) col = LineCollection(nlist) col.set_color(color) col.set_linewidth(width) if level < 0.0 and Ncolors == 1: col.set_linestyle((0, (6., 6.)), ) #print "setting dashed" col.set_label(fmt % level) self.ax.add_collection(col) collections.append(col) collections = silent_list('LineCollection', collections) # the mappable attr is for the pylab interface functions, # which maintain the current image collections.mappable = mappable return lev, collections
def contour(self, *args, **kwargs): """ contour(self, *args, **kwargs) Function signatures contour(Z) - make a contour plot of an array Z. The level values are chosen automatically. contour(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface contour(Z,N) and contour(X,Y,Z,N) - draw N contour lines overriding the automatic value contour(Z,V) and contour(X,Y,Z,V) - draw len(V) contour lines, at the values specified in V (array, list, tuple) contour(Z, **kwargs) - Use keyword args to control colors, linewidth, origin, cmap ... see below [L,C] = contour(...) returns a list of levels and a silent_list of LineCollections Z may be a masked array. Optional keywork args are shown with their defaults below (you must use kwargs for these): * colors = None; or one of the following: - a tuple of matplotlib color args (string, float, rgb, etc), different levels will be plotted in different colors in the order specified - one string color, e.g. colors = 'r' or colors = 'red', all levels will be plotted in this color - if colors == None, the default colormap will be used * alpha=1.0 : the alpha blending value * cmap = None: a cm Colormap instance from matplotlib.cm. * origin = None: 'upper'|'lower'|'image'|None. If 'image', the rc value for image.origin will be used. If None (default), the first value of Z will correspond to the lower left corner, location (0,0). This keyword is active only if contourf is called with one or two arguments, that is, without explicitly specifying X and Y. * extent = None: (x0,x1,y0,y1); also active only if X and Y are not specified. * linewidths = None: or one of these: - a number - all levels will be plotted with this linewidth, e.g. linewidths = 0.6 - a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different levels will be plotted with different linewidths in the order specified - if linewidths == None, the default width in lines.linewidth in .matplotlibrc is used * fmt = '1.3f': a format string for adding a label to each collection. Useful for auto-legending. """ alpha = kwargs.get('alpha', 1.0) linewidths = kwargs.get('linewidths', None) fmt = kwargs.get('fmt', '%1.3f') origin = kwargs.get('origin', None) extent = kwargs.get('extent', None) cmap = kwargs.get('cmap', None) colors = kwargs.get('colors', None) if cmap is not None: assert(isinstance(cmap, Colormap)) if origin is not None: assert(origin in ['lower', 'upper', 'image']) if extent is not None: assert(len(extent) == 4) if colors is not None and cmap is not None: raise ValueError('Either colors or cmap must be None') if origin == 'image': origin = rcParams['image.origin'] x, y, z, lev = self._contour_args(False, origin, extent, *args) # Manipulate the plot *after* checking the input arguments. if not self.ax.ishold(): self.ax.cla() Nlev = len(lev) if cmap is None: if colors is None: Ncolors = Nlev else: Ncolors = len(colors) else: Ncolors = Nlev tcolors, mappable, collections = self._process_colors(colors, alpha, lev, cmap) if linewidths == None: tlinewidths = [rcParams['lines.linewidth']] *Nlev else: if iterable(linewidths) and len(linewidths) < Nlev: linewidths = list(linewidths) * int(ceil(Nlev/len(linewidths))) elif not iterable(linewidths) and type(linewidths) in [int, float]: linewidths = [linewidths] * Nlev tlinewidths = [(w,) for w in linewidths] C = _contour.Cntr(x, y, z.filled(), z.mask()) for level, color, width in zip(lev, tcolors, tlinewidths): nlist = C.trace(level, points = 1) col = LineCollection(nlist) col.set_color(color) col.set_linewidth(width) if level < 0.0 and Ncolors == 1: col.set_linestyle((0, (6.,6.)),) #print "setting dashed" col.set_label(fmt%level) self.ax.add_collection(col) collections.append(col) collections = silent_list('LineCollection', collections) # the mappable attr is for the pylab interface functions, # which maintain the current image collections.mappable = mappable return lev, collections