def bin_size(self, bs):
if self.histogram.dim != 1:
raise GeneralError('Currently only 1D histograms can be binned')
if isinstance(bs, int):
# You can only bin further the histogram, there is no
# way back (load original data again)
if bs > self._bin_size:
self._bin_size = bs
self.histogram = self.histogram.rebin1d(bs)
elif bs <= self._bin_size:
pass
else:
raise GeneralError('Attempt to set bin size to {}'.\
format(bs))
else:
raise GeneralError('Attempt to set bin size to {}'.\
format(bs))
def _add_errors(self, error1, error2):
"""Add two error arrays
\sigma = \sqrt{\sigma_1^2 + \sigma_2^2}
"""
if error1.shape != error2.shape:
raise GeneralError('Shape of array mismatches')
errors = numpy.zeros(error1.shape)
for index, d in numpy.ndenumerate(error1):
errors[index] = math.sqrt(error1[index]**2 + error2[index]**2)
return errors
def mode(self, mode):
"""Deactivate all plots that have different mode (dimension)"""
if mode not in [1, 2]:
raise GeneralError('Only 1D and 2D plotting modes are possible')
# if mode == 2:
# self.plotter.ylin()
Experiment._mode = mode
for p in self.plots:
if p.histogram.dim != mode:
p.active = False
def norm(self, n):
if self.histogram.dim != 1:
raise GeneralError('Currently only 1D histograms can be normalized')
self.histogram = self.histogram.normalize1d(n, self.bin_size)