def apply_along_axis(self, func1d, axis=-1, ylabel=None, yunit=None):
"""Apply a function to 1-D slices along the given axis.
Execute `func1d(a, x)` where `func1d` operates on 1-D arrays and `a`
is a 1-D slice of `w` along `axis`
"""
axis = self.getaxis(axis)
newy = np.apply_along_axis(func1d, axis, self._y, self.x[axis])
if newy.shape == self.shape:
return Waveform(self.x, newy, xlabels=self.xlabels,
xunits=self.xunits,
ylabel=ylabel, yunit=yunit)
else:
if len(newy.shape) == 0:
return newy
elif newy.shape == tuple(remove_index(self.shape, axis)):
return Waveform(remove_index(self.x, axis), newy,
xlabels=remove_index(self.xlabels, axis),
xunits=remove_index(self.xunits, axis),
ylabel=ylabel, yunit=yunit)
else:
print newy.shape, tuple(remove_index(self.shape, axis))
raise ValueError('Shape mismatch')
def apply_along_axis(self, func1d, axis=-1, ylabel=None, yunit=None):
"""Apply a function to 1-D slices along the given axis.
Execute `func1d(a, x)` where `func1d` operates on 1-D arrays and `a`
is a 1-D slice of `w` along `axis`
"""
axis = self.getaxis(axis)
newy = np.apply_along_axis(func1d, axis, self._y, self.x[axis])
if newy.shape == self.shape:
return Waveform(self.x,
newy,
xlabels=self.xlabels,
xunits=self.xunits,
ylabel=ylabel,
yunit=yunit)
else:
if len(newy.shape) == 0:
return newy
elif newy.shape == tuple(remove_index(self.shape, axis)):
return Waveform(remove_index(self.x, axis),
newy,
xlabels=remove_index(self.xlabels, axis),
xunits=remove_index(self.xunits, axis),
ylabel=ylabel,
yunit=yunit)
else:
raise ValueError('Shape mismatch')
def value(self, x, axis = -1):
"""Returns and interpolated at the given x-value
*x* can be a number or a waveform where the number of dimensions of x is
is one less than the waveform it is operating on
Examples:
1-d waveform
>>> w1=Waveform(array([1,2,3]),array([3,5,6]))
>>> w1.value(1.5)
4.0
2-d waveform
>>> w2=Waveform([[1,2],[2,3,4]], array([[3,5,6], [4,6,7]]))
>>> w2.value(2.5)
Waveform(array([1, 2]), array([ 4., 5.]))
`x` is a waveform
>>> w2=Waveform([[1,2],[2,3,4]], array([[3,5,6], [4,6,7]]))
>>> w2.value(Waveform([[1, 2]], array([2.5, 3.5])))
Waveform(array([1, 2]), array([ 4. , 6.5]))
"""
axis = self.getaxis(axis)
def findvalue(y):
if len(self._xlist[axis]) == 1 and axis == -1:
return y[-1]
res = sp.interpolate.interp1d(self._xlist[axis], y)(x)
try:
return np.asscalar(res)
except TypeError:
return res
def findvalue_mdimindex(y, i):
xindex = list(i)
del xindex[axis]
xindex = tuple(xindex)
res = sp.interpolate.interp1d(self._xlist[axis], y)(x._y[xindex])
try:
return np.asscalar(res)
except TypeError:
return res
if iswave(x):
newyshape = list(self._y.shape)
del newyshape[axis]
newyshape = tuple(newyshape)
newy = apply_along_axis_with_idx(findvalue_mdimindex,
axis,
self._y).reshape(newyshape)
return reducedim(self, newy, axis=axis)
outw = applyfunc_and_reducedim(findvalue, self, axis = axis)
if outw and not isscalar(outw):
outw.ylabel = self.ylabel
outw.yunit = self.yunit
outw.xunits = remove_index(self.xunits, axis)
outw.xlabels = remove_index(self.xlabels, axis)
return outw
