def recache(self):
#if self.axes is None: print 'recache no axes'
#else: print 'recache units', self.axes.xaxis.units, self.axes.yaxis.units
x = ma.asarray(self.convert_xunits(self._xorig), float)
y = ma.asarray(self.convert_yunits(self._yorig), float)
x = ma.ravel(x)
y = ma.ravel(y)
if len(x)==1 and len(y)>1:
x = x * npy.ones(y.shape, float)
if len(y)==1 and len(x)>1:
y = y * npy.ones(x.shape, float)
if len(x) != len(y):
raise RuntimeError('xdata and ydata must be the same length')
mx = ma.getmask(x)
my = ma.getmask(y)
mask = ma.mask_or(mx, my)
if mask is not ma.nomask:
x = ma.masked_array(x, mask=mask).compressed()
y = ma.masked_array(y, mask=mask).compressed()
self._segments = unmasked_index_ranges(mask)
else:
self._segments = None
self._x = npy.asarray(x, float)
self._y = npy.asarray(y, float)
self._logcache = None
def _update_x_y_logcache(self):
# check cache
need_update = False
try:
for key, var_id in self._cache_inputs.iteritems():
if id(getattr(self, key)) != var_id:
need_update = True
break
except:
need_update = True
if not need_update:
return
# update cache
for key in self._cache_inputs.keys():
try:
self._cache_inputs[key] = id(getattr(self, key))
except:
pass
# make sure that result values exist and release
# previous values
self._cached__x = None
self._cached__y = None
self._cached__segments = None
self._cached__logcache = None
if self.is_unitsmgr_set():
unitsmgr = self.get_unitsmgr()
x, y = unitsmgr._convert_units((self._x_orig, self._xunits), (self._y_orig, self._yunits))
else:
x, y = (self._x_orig, self._y_orig)
x = ma.ravel(x)
y = ma.ravel(y)
if len(x) == 1 and len(y) > 1:
x = x * ones(y.shape, Float)
if len(y) == 1 and len(x) > 1:
y = y * ones(x.shape, Float)
if len(x) != len(y):
raise RuntimeError("xdata and ydata must be the same length")
mx = ma.getmask(x)
my = ma.getmask(y)
mask = ma.mask_or(mx, my)
if mask is not ma.nomask:
x = ma.masked_array(x, mask=mask).compressed()
y = ma.masked_array(y, mask=mask).compressed()
self._cached__segments = unmasked_index_ranges(mask)
else:
self._cached__segments = None
self._cached__x = asarray(x, Float)
self._cached__y = asarray(y, Float)
self._cached__logcache = None
def set_data(self, *args):
"""
Set the x and y data
ACCEPTS: (array xdata, array ydata)
"""
if len(args) == 1:
x, y = args[0]
else:
x, y = args
try:
del self._xc, self._yc
except AttributeError:
pass
self._masked_x = None
self._masked_y = None
mx = ma.getmask(x)
my = ma.getmask(y)
if mx is not None:
mx = ravel(mx)
self._masked_x = x
if my is not None:
my = ravel(my)
self._masked_y = y
mask = ma.mask_or(mx, my)
if mask is not None:
x = ma.masked_array(ma.ravel(x), mask=mask).compressed()
y = ma.masked_array(ma.ravel(y), mask=mask).compressed()
self._segments = unmasked_index_ranges(mask)
else:
self._segments = None
self._x = asarray(x, Float)
self._y = asarray(y, Float)
if len(self._x.shape) > 1:
self._x = ravel(self._x)
if len(self._y.shape) > 1:
self._y = ravel(self._y)
# What is the rationale for the following two lines?
# And why is there not a similar pair with _x and _y reversed?
if len(self._y) == 1 and len(self._x) > 1:
self._y = self._y * ones(self._x.shape, Float)
if len(self._x) != len(self._y):
raise RuntimeError("xdata and ydata must be the same length")
if self._useDataClipping:
self._xsorted = self._is_sorted(self._x)
self._logcache = None
def set_data(self, *args):
"""
Set the x and y data
ACCEPTS: (array xdata, array ydata)
"""
if len(args)==1:
x, y = args[0]
else:
x, y = args
self._x_orig = x
self._y_orig = y
if (self._xunits and hasattr(x, 'convert_to')):
x = x.convert_to(self._xunits).get_value()
if (hasattr(x, 'get_value')):
x = x.get_value()
if (self._yunits and hasattr(y, 'convert_to')):
y = y.convert_to(self._yunits).get_value()
if (hasattr(y, 'get_value')):
y = y.get_value()
x = ma.ravel(x)
y = ma.ravel(y)
if len(x)==1 and len(y)>1:
x = x * ones(y.shape, Float)
if len(y)==1 and len(x)>1:
y = y * ones(x.shape, Float)
if len(x) != len(y):
raise RuntimeError('xdata and ydata must be the same length')
mx = ma.getmask(x)
my = ma.getmask(y)
mask = ma.mask_or(mx, my)
if mask is not ma.nomask:
x = ma.masked_array(x, mask=mask).compressed()
y = ma.masked_array(y, mask=mask).compressed()
self._segments = unmasked_index_ranges(mask)
else:
self._segments = None
self._x = asarray(x, Float)
self._y = asarray(y, Float)
self._logcache = None
def set_data(self, *args):
"""
Set the x and y data
ACCEPTS: (array xdata, array ydata)
"""
if len(args) == 1:
x, y = args[0]
else:
x, y = args
try:
del self._xc, self._yc
except AttributeError:
pass
self._x_orig = x
self._y_orig = y
x = ma.ravel(x)
y = ma.ravel(y)
if len(x) == 1 and len(y) > 1:
x = x * ones(y.shape, Float)
if len(y) == 1 and len(x) > 1:
y = y * ones(x.shape, Float)
if len(x) != len(y):
raise RuntimeError("xdata and ydata must be the same length")
mx = ma.getmask(x)
my = ma.getmask(y)
mask = ma.mask_or(mx, my)
if mask is not None:
x = ma.masked_array(x, mask=mask).compressed()
y = ma.masked_array(y, mask=mask).compressed()
self._segments = unmasked_index_ranges(mask)
else:
self._segments = None
self._x = asarray(x, Float)
self._y = asarray(y, Float)
if self._useDataClipping:
self._xsorted = self._is_sorted(self._x)
self._logcache = None
def set_data(self, *args):
"""
Set the x and y data
ACCEPTS: (array xdata, array ydata)
"""
if len(args) == 1:
x, y = args[0]
else:
x, y = args
try:
del self._xc, self._yc
except AttributeError:
pass
self._x_orig = x
self._y_orig = y
x = ma.ravel(x)
y = ma.ravel(y)
if len(x) == 1 and len(y) > 1:
x = x * ones(y.shape, Float)
if len(y) == 1 and len(x) > 1:
y = y * ones(x.shape, Float)
if len(x) != len(y):
raise RuntimeError('xdata and ydata must be the same length')
mx = ma.getmask(x)
my = ma.getmask(y)
mask = ma.mask_or(mx, my)
if mask is not None:
x = ma.masked_array(x, mask=mask).compressed()
y = ma.masked_array(y, mask=mask).compressed()
self._segments = unmasked_index_ranges(mask)
else:
self._segments = None
self._x = asarray(x, Float)
self._y = asarray(y, Float)
if self._useDataClipping: self._xsorted = self._is_sorted(self._x)
self._logcache = None
def _autolev(self, z, N, filled, badmask):
'''
Select contour levels to span the data.
We need one more level for filled contours than for
line contours, because for the latter we need to specify
the lower and upper boundary of each range. For example,
a single contour boundary, say at z = 0, requires only
one contour line, but two filled regions, and therefore
two levels. These are taken as the lower boundaries of
the regions.
'''
rz = ma.masked_array(z, badmask)
zmax = ma.maximum(rz) # was: zmax = amax(rz)
zmin = ma.minimum(rz)
if filled:
lev = linspace(zmin, zmax, N + 2)[:-1]
else:
lev = linspace(zmin, zmax, N + 2)[1:-1]
return lev
def _autolev(self, z, N, filled, badmask):
'''
Select contour levels to span the data.
We need one more level for filled contours than for
line contours, because for the latter we need to specify
the lower and upper boundary of each range. For example,
a single contour boundary, say at z = 0, requires only
one contour line, but two filled regions, and therefore
two levels. These are taken as the lower boundaries of
the regions.
'''
rz = ma.masked_array(z, badmask)
zmax = ma.maximum(rz) # was: zmax = amax(rz)
zmin = ma.minimum(rz)
if filled:
lev = linspace(zmin, zmax, N+2)[:-1]
else:
lev = linspace(zmin, zmax, N+2)[1:-1]
return lev
