UniformSampleFromScaleVector¶
- class sherpa.sim.sample.UniformSampleFromScaleVector[source] [edit on github]¶
Bases:
sherpa.sim.sample.UniformParameterSampleFromScaleVector
Use a uniform distribution to sample statistic and parameters.
The parameters are drawn from a uniform distribution which is set to factor times the parameter error (the lower bound is included but the upper bound is not).
Methods Summary
clip
(fit, samples[, clip])Clip the samples if out of bounds.
get_sample
(fit[, num, factor, numcores])Return the statistic and parameter samples.
Methods Documentation
- clip(fit, samples, clip='none') [edit on github]¶
Clip the samples if out of bounds.
- Parameters
fit (sherpa.fit.Fit instance) – Contains the thawed parameters used to generate the samples.
samples (2D numpy array) – The samples array, stored as a n by npar matrix. This array is changed in place.
clip ({'none', 'hard', 'soft'} optional) – How should the values be clipped? The default (‘none’) has no clipping. The other methods restrict the values to lie within the hard or soft limits of the parameters.
- Returns
clipped – The clipped samples (may be unchanged) and a 1D boolean array indicating whether any sample in a row was clipped.
- Return type
1D numpy array
- get_sample(fit, num=1, factor=4, numcores=None)[source] [edit on github]¶
Return the statistic and parameter samples.
- Parameters
fit (sherpa.fit.Fit instance) – This defines the thawed parameters that are used to generate the samples, along with any possible error analysis.
num (int, optional) – The number of samples to return.
factor (number, optional) – The half-width of the uniform distribution is factor times the one-sigma error.
numcores (int or None, optional) – Should the calculation be done on multiple CPUs? The default (None) is to rely on the parallel.numcores setting of the configuration file.
- Returns
samples – The array is num by (npar + 1) size, where npar is the number of free parameters in the fit argument. The first element in each row is the statistic value, and the remaining are the parameter values.
- Return type
2D numpy array