def print_label(self, linecontour, labelwidth):
"if contours are too short, don't plot a label"
lcsize = len(linecontour)
if lcsize > 10 * labelwidth:
return 1
xmax = amax(array(linecontour)[:, 0])
xmin = amin(array(linecontour)[:, 0])
ymax = amax(array(linecontour)[:, 1])
ymin = amin(array(linecontour)[:, 1])
lw = labelwidth
if (xmax - xmin) > 1.2 * lw or (ymax - ymin) > 1.2 * lw:
return 1
else:
return 0
def __call__(self, value):
vmin = self.vmin
vmax = self.vmax
if type(value) in [IntType, FloatType]:
vtype = "scalar"
val = array([value])
else:
vtype = "array"
val = asarray(value)
if vmin is None or vmax is None:
rval = ravel(val)
if vmin is None:
vmin = amin(rval)
if vmax is None:
vmax = amax(rval)
if vmin > vmax:
raise ValueError("minvalue must be less than or equal to maxvalue")
elif vmin == vmax:
return 0.0 * value
else:
val = where(val < vmin, vmin, val)
val = where(val > vmax, vmax, val)
result = (1.0 / (vmax - vmin)) * (val - vmin)
if vtype == "scalar":
result = result[0]
return result
def autoscale(self, A):
if not self.scaled():
rval = ravel(A)
if self.vmin is None:
self.vmin = amin(rval)
if self.vmax is None:
self.vmax = amax(rval)
def print_label(self, linecontour,labelwidth):
"if contours are too short, don't plot a label"
lcsize = len(linecontour)
if lcsize > 10 * labelwidth:
return 1
xmax = amax(array(linecontour)[:,0])
xmin = amin(array(linecontour)[:,0])
ymax = amax(array(linecontour)[:,1])
ymin = amin(array(linecontour)[:,1])
lw = labelwidth
if (xmax - xmin) > 1.2* lw or (ymax - ymin) > 1.2 * lw:
return 1
else:
return 0
def _process_colors(self):
"""
Color argument processing for contouring.
Note that we base the color mapping on the contour levels,
not on the actual range of the Z values. This means we
don't have to worry about bad values in Z, and we always have
the full dynamic range available for the selected levels.
The color is based on the midpoint of the layer, except for
the end layers when clip_ends is True.
"""
self.monochrome = self.cmap.monochrome
if self.colors is not None:
self.cvalues = range(len(self.layers))
self.set_norm(no_norm())
else:
self.cvalues = self.layers
if self.filled and len(self.layers) > 2 and self.clip_ends:
vmin = 2 * self.levels[1] - self.levels[2]
vmax = 2 * self.levels[-2] - self.levels[-3]
else:
vmin = amin(self.levels) # alternative would be self.layers
vmax = amax(self.levels)
self.set_clim(vmin, vmax)
self.set_array(self.layers)
self.tcolors = [ (tuple(rgba),) for rgba in self.to_rgba(self.cvalues)]
def __call__(self, value):
vmin = self.vmin
vmax = self.vmax
if type(value) in [IntType, FloatType]:
vtype = 'scalar'
val = array([value])
else:
vtype = 'array'
val = asarray(value)
# if both vmin is None and vmax is None, we'll automatically
# norm the data to vmin/vmax of the actual data, so the
# clipping step won't be needed.
if vmin is None and vmax is None:
needs_clipping = False
else:
needs_clipping = True
if vmin is None or vmax is None:
rval = ravel(val)
if vmin is None: vmin = amin(rval)
if vmax is None: vmax = amax(rval)
if vmin > vmax:
raise ValueError("minvalue must be less than or equal to maxvalue")
elif vmin == vmax:
return 0. * value
else:
if needs_clipping:
val = clip(val, vmin, vmax)
result = (1.0 / (vmax - vmin)) * (val - vmin)
if vtype == 'scalar':
result = result[0]
return result
def __call__(self, value):
vmin = self.vmin
vmax = self.vmax
if type(value) in [IntType, FloatType]:
vtype = 'scalar'
val = array([value])
else:
vtype = 'array'
val = asarray(value)
if vmin is None or vmax is None:
rval = ravel(val)
if vmin is None: vmin = amin(rval)
if vmax is None: vmax = amax(rval)
if vmin > vmax:
raise ValueError("minvalue must be less than or equal to maxvalue")
elif vmin == vmax:
return 0. * value
else:
val = where(val < vmin, vmin, val)
val = where(val > vmax, vmax, val)
result = (1.0 / (vmax - vmin)) * (val - vmin)
if vtype == 'scalar':
result = result[0]
return result
def _process_colors(self):
"""
Color argument processing for contouring.
Note that we base the color mapping on the contour levels,
not on the actual range of the Z values. This means we
don't have to worry about bad values in Z, and we always have
the full dynamic range available for the selected levels.
The color is based on the midpoint of the layer, except for
the end layers when clip_ends is True.
"""
self.monochrome = self.cmap.monochrome
if self.colors is not None:
self.cvalues = range(len(self.layers))
self.set_norm(no_norm())
else:
self.cvalues = self.layers
if self.filled and len(self.layers) > 2 and self.clip_ends:
vmin = 2 * self.levels[1] - self.levels[2]
vmax = 2 * self.levels[-2] - self.levels[-3]
else:
vmin = amin(self.levels) # alternative would be self.layers
vmax = amax(self.levels)
self.set_clim(vmin, vmax)
self.set_array(self.layers)
self.tcolors = [ (tuple(rgba),) for rgba in self.to_rgba(self.cvalues)]
def __call__(self, value):
vmin = self.vmin
vmax = self.vmax
if type(value) in [IntType, FloatType]:
vtype = 'scalar'
val = array([value])
else:
vtype = 'array'
val = asarray(value)
# if both vmin is None and vmax is None, we'll automatically
# norm the data to vmin/vmax of the actual data, so the
# clipping step won't be needed.
if vmin is None and vmax is None:
needs_clipping = False
else:
needs_clipping = True
if vmin is None or vmax is None:
rval = ravel(val)
if vmin is None: vmin = amin(rval)
if vmax is None: vmax = amax(rval)
if vmin > vmax:
raise ValueError("minvalue must be less than or equal to maxvalue")
elif vmin==vmax:
return 0.*value
else:
if needs_clipping:
val = clip(val,vmin, vmax)
result = (1.0/(vmax-vmin))*(val-vmin)
if vtype == 'scalar':
result = result[0]
return result
def _contour_args(self, *args):
if self.filled: fn = 'contourf'
else: fn = 'contour'
Nargs = len(args)
if Nargs <= 2:
z = args[0]
x, y = self._initialize_x_y(z)
elif Nargs <=4:
x,y,z = self._check_xyz(args[:3])
else:
raise TypeError("Too many arguments to %s; see help(%s)" % (fn,fn))
z = ma.asarray(z) # Convert to native masked array format if necessary.
self.zmax = ma.maximum(z)
self.zmin = ma.minimum(z)
self._auto = False
if self.levels is None:
if Nargs == 1 or Nargs == 3:
lev = self._autolev(z, 7)
else: # 2 or 4 args
level_arg = args[-1]
if type(level_arg) == int:
lev = self._autolev(z, level_arg)
elif iterable(level_arg) and len(shape(level_arg)) == 1:
lev = array([float(fl) for fl in level_arg])
else:
raise TypeError("Last %s arg must give levels; see help(%s)" % (fn,fn))
if self.filled and len(lev) < 2:
raise ValueError("Filled contours require at least 2 levels.")
# Workaround for cntr.c bug wrt masked interior regions:
#if filled:
# z = ma.masked_array(z.filled(-1e38))
# It's not clear this is any better than the original bug.
self.levels = lev
#if self._auto and self.extend in ('both', 'min', 'max'):
# raise TypeError("Auto level selection is inconsistent "
# + "with use of 'extend' kwarg")
self._levels = list(self.levels)
if self.extend in ('both', 'min'):
self._levels.insert(0, self.zmin - 1)
if self.extend in ('both', 'max'):
self._levels.append(self.zmax + 1)
self._levels = asarray(self._levels)
self.vmin = amin(self.levels) # alternative would be self.layers
self.vmax = amax(self.levels)
if self.extend in ('both', 'min') or self.clip_ends:
self.vmin = 2 * self.levels[0] - self.levels[1]
if self.extend in ('both', 'max') or self.clip_ends:
self.vmax = 2 * self.levels[-1] - self.levels[-2]
self.layers = self._levels # contour: a line is a thin layer
if self.filled:
self.layers = 0.5 * (self._levels[:-1] + self._levels[1:])
if self.extend in ('both', 'min') or self.clip_ends:
self.layers[0] = 0.5 * (self.vmin + self._levels[1])
if self.extend in ('both', 'max') or self.clip_ends:
self.layers[-1] = 0.5 * (self.vmax + self._levels[-2])
return (x, y, z)
def autoscale(self, A):
if not self.scaled():
rval = ravel(A)
if self.vmin is None: self.vmin = amin(rval)
if self.vmax is None: self.vmax = amax(rval)
def _contour_args(self, *args):
if self.filled: fn = 'contourf'
else: fn = 'contour'
Nargs = len(args)
if Nargs <= 2:
z = args[0]
x, y = self._initialize_x_y(z)
elif Nargs <= 4:
x, y, z = self._check_xyz(args[:3])
else:
raise TypeError("Too many arguments to %s; see help(%s)" %
(fn, fn))
z = ma.asarray(
z) # Convert to native masked array format if necessary.
self.zmax = ma.maximum(z)
self.zmin = ma.minimum(z)
self._auto = False
if self.levels is None:
if Nargs == 1 or Nargs == 3:
lev = self._autolev(z, 7)
else: # 2 or 4 args
level_arg = args[-1]
if type(level_arg) == int:
lev = self._autolev(z, level_arg)
elif iterable(level_arg) and len(shape(level_arg)) == 1:
lev = array([float(fl) for fl in level_arg])
else:
raise TypeError(
"Last %s arg must give levels; see help(%s)" %
(fn, fn))
if self.filled and len(lev) < 2:
raise ValueError("Filled contours require at least 2 levels.")
# Workaround for cntr.c bug wrt masked interior regions:
#if filled:
# z = ma.masked_array(z.filled(-1e38))
# It's not clear this is any better than the original bug.
self.levels = lev
#if self._auto and self.extend in ('both', 'min', 'max'):
# raise TypeError("Auto level selection is inconsistent "
# + "with use of 'extend' kwarg")
self._levels = list(self.levels)
if self.extend in ('both', 'min'):
self._levels.insert(0, self.zmin - 1)
if self.extend in ('both', 'max'):
self._levels.append(self.zmax + 1)
self._levels = asarray(self._levels)
self.vmin = amin(self.levels) # alternative would be self.layers
self.vmax = amax(self.levels)
if self.extend in ('both', 'min') or self.clip_ends:
self.vmin = 2 * self.levels[0] - self.levels[1]
if self.extend in ('both', 'max') or self.clip_ends:
self.vmax = 2 * self.levels[-1] - self.levels[-2]
self.layers = self._levels # contour: a line is a thin layer
if self.filled:
self.layers = 0.5 * (self._levels[:-1] + self._levels[1:])
if self.extend in ('both', 'min') or self.clip_ends:
self.layers[0] = 0.5 * (self.vmin + self._levels[1])
if self.extend in ('both', 'max') or self.clip_ends:
self.layers[-1] = 0.5 * (self.vmax + self._levels[-2])
return (x, y, z)
