def set_data(self, data):
if data is None:
self.inputdata = None
self.chartdata = None
return
data = array(data)
dim = len(shape(data))
if dim not in (1, 2, 3):
raise AttributeError, "Input data must be a 1, 2, or 3d matrix"
self.inputdata = data
# If the input data is a 1d matrix, then it describes a
# standard bar chart.
if dim == 1:
self.chartdata = array([[data]])
# If the input data is a 2d matrix, then it describes a bar
# chart with groups. The matrix being an array of groups of
# bars.
if dim == 2:
self.chartdata = transpose([data], axes=(2, 0, 1))
# If the input data is a 3d matrix, then it describes an array
# of groups of bars with each bar being an array of stacked
# values.
if dim == 3:
self.chartdata = transpose(data, axes=(1, 2, 0))
def set_data(self, data):
if data is None:
self.inputdata = None
self.chartdata = None
return
data = array(data)
dim = len(shape(data))
if dim not in (1, 2, 3):
raise AttributeError, "Input data must be a 1, 2, or 3d matrix"
self.inputdata = data
# If the input data is a 1d matrix, then it describes a
# standard bar chart.
if dim == 1:
self.chartdata = array([[data]])
# If the input data is a 2d matrix, then it describes a bar
# chart with groups. The matrix being an array of groups of
# bars.
if dim == 2:
self.chartdata = transpose([data], axes=(2, 0, 1))
# If the input data is a 3d matrix, then it describes an array
# of groups of bars with each bar being an array of stacked
# values.
if dim == 3:
self.chartdata = transpose(data, axes=(1, 2, 0))
def _outline(self, X, Y):
"""
Return x, y arrays of colorbar bounding polygon,
taking orientation into account.
"""
N = nx.shape(X)[0]
ii = [0, 1, N - 2, N - 1, 2 * N - 1, 2 * N - 2, N + 1, N, 0]
x = nx.take(nx.ravel(nx.transpose(X)), ii)
y = nx.take(nx.ravel(nx.transpose(Y)), ii)
if self.orientation == "horizontal":
return y, x
return x, y
def _outline(self, X, Y):
'''
Return x, y arrays of colorbar bounding polygon,
taking orientation into account.
'''
N = nx.shape(X)[0]
ii = [0, 1, N - 2, N - 1, 2 * N - 1, 2 * N - 2, N + 1, N, 0]
x = nx.take(nx.ravel(nx.transpose(X)), ii)
y = nx.take(nx.ravel(nx.transpose(Y)), ii)
if self.orientation == 'horizontal':
return y, x
return x, y
def _add_solids(self, X, Y, C):
"""
Draw the colors using pcolormesh; optionally add separators.
"""
if self.orientation == "vertical":
args = (X, Y, C)
else:
args = (nx.transpose(Y), nx.transpose(X), nx.transpose(C))
kw = {"cmap": self.cmap, "norm": self.norm, "shading": "flat"}
col = self.ax.pcolor(*args, **kw)
self.add_observer(col)
self.solids = col
if self.drawedges:
self.dividers = LineCollection(
self._edges(X, Y), colors=(rcParams["axes.edgecolor"],), linewidths=(0.5 * rcParams["axes.linewidth"],)
)
self.ax.add_collection(self.dividers)
def _add_solids(self, X, Y, C):
'''
Draw the colors using pcolormesh; optionally add separators.
'''
if self.orientation == 'vertical':
args = (X, Y, C)
else:
args = (nx.transpose(Y), nx.transpose(X), nx.transpose(C))
kw = {'cmap': self.cmap, 'norm': self.norm, 'shading': 'flat'}
col = self.ax.pcolor(*args, **kw)
self.add_observer(col)
self.solids = col
if self.drawedges:
self.dividers = LineCollection(
self._edges(X, Y),
colors=(rcParams['axes.edgecolor'], ),
linewidths=(0.5 * rcParams['axes.linewidth'], ))
self.ax.add_collection(self.dividers)
def init_plot_data(self):
# jdh you can add a subplot directly from the fig rather than
# the fig manager
a = self.fig.add_subplot(111)
self.x = numerix.arange(120.0) * 2 * numerix.pi / 120.0
self.x.resize((100, 120))
self.y = numerix.arange(100.0) * 2 * numerix.pi / 100.0
self.y.resize((120, 100))
self.y = numerix.transpose(self.y)
z = numerix.sin(self.x) + numerix.cos(self.y)
self.im = a.imshow(z, cmap=cm.jet) #, interpolation='nearest')
def init_plot_data(self):
# jdh you can add a subplot directly from the fig rather than
# the fig manager
a = self.fig.add_subplot(111)
self.x = numerix.arange(120.0)*2*numerix.pi/120.0
self.x.resize((100,120))
self.y = numerix.arange(100.0)*2*numerix.pi/100.0
self.y.resize((120,100))
self.y = numerix.transpose(self.y)
z = numerix.sin(self.x) + numerix.cos(self.y)
self.im = a.imshow( z, cmap=cm.jet)#, interpolation='nearest')
def set_err(self, err):
if err is None:
self.inputerr = None
self.charterr = None
return
err = array(err)
dim = len(shape(err))
if dim not in (1, 2, 3):
raise AttributeError, "Input err must be a 1, 2, or 3d matrix"
self.inputerr = err
if dim == 1:
self.charterr = array([[err]])
if dim == 2:
self.charterr = transpose([err], axes=(2, 0, 1))
if dim == 3:
self.charterr = transpose(err, axes=(1, 2, 0))
def set_err(self, err):
if err is None:
self.inputerr = None
self.charterr = None
return
err = array(err)
dim = len(shape(err))
if dim not in (1, 2, 3):
raise AttributeError, "Input err must be a 1, 2, or 3d matrix"
self.inputerr = err
if dim == 1:
self.charterr = array([[err]])
if dim == 2:
self.charterr = transpose([err], axes=(2, 0, 1))
if dim == 3:
self.charterr = transpose(err, axes=(1, 2, 0))
def init_plot_data(self):
# jdh you can add a subplot directly from the fig rather than
# the fig manager
a = self.fig.add_axes([0.075,0.1,0.75,0.85])
cax = self.fig.add_axes([0.85,0.1,0.075,0.85])
self.x = numerix.arange(120.0)*2*numerix.pi/120.0
self.x.resize((100,120))
self.y = numerix.arange(100.0)*2*numerix.pi/100.0
self.y.resize((120,100))
self.y = numerix.transpose(self.y)
z = numerix.sin(self.x) + numerix.cos(self.y)
self.im = a.imshow( z, cmap=cm.jet)#, interpolation='nearest')
self.fig.colorbar(self.im,cax=cax,orientation='vertical')
def init_plot_data(self):
# jdh you can add a subplot directly from the fig rather than
# the fig manager
a = self.fig.add_axes([0.075, 0.1, 0.75, 0.85])
cax = self.fig.add_axes([0.85, 0.1, 0.075, 0.85])
self.x = numerix.arange(120.0) * 2 * numerix.pi / 120.0
self.x.resize((100, 120))
self.y = numerix.arange(100.0) * 2 * numerix.pi / 100.0
self.y.resize((120, 100))
self.y = numerix.transpose(self.y)
z = numerix.sin(self.x) + numerix.cos(self.y)
self.im = a.imshow(z, cmap=cm.jet) #, interpolation='nearest')
self.fig.colorbar(self.im, cax=cax, orientation='vertical')
def func(x):
return transpose(fliplr(x))
def func(x):
return transpose(fliplr(x))
