Maths

Mathematics.

Binning

clusterking.maths.binning.bin_function(fct, binning: numpy.array, normalize=False) → numpy.array[source]

Bin function, i.e. calculate the integrals of a function for each bin.

Parameters:
  • fct – Function to be integrated per bin
  • binning – Array of bin edge points.
  • normalize – If true, we will normalize the distribution, i.e. divide by the sum of all bins in the end.
Returns:

Array of bin contents

Metric

clusterking.maths.metric.chi2(n1: numpy.ndarray, n2: numpy.ndarray, cov1: numpy.ndarray, cov2: numpy.ndarray, normalize=False) → numpy.ndarray[source]
Parameters:
  • n1 – n_obs x n_bins
  • n2 – Either n_obs x n_bins or just nbins if we’re testing against a constant histogram
  • cov1 – Either n_obs x n_bins x n_bins or n_bins x n_bins
  • cov2 – Either n_obs x n_bins x n_bins or n_bins x n_bins
  • normalize –
Returns:

n_obs vector of chi2 test results (degrees of freedom not yet divided out)
clusterking.maths.metric.chi2_metric(dwe: clusterking.data.dwe.DataWithErrors, output='condensed')[source]

Returns the chi2/ndf values of the comparison of a datasets.

Parameters:
  • dwe – clusterking.data.dwe.DataWithErrors object
  • output – ‘condensed’ (condensed distance matrix) or ‘full’ (full distance matrix)
Returns:

Condensed distance matrix or full distance matrix

Statistics

clusterking.maths.statistics.cov2err(cov)[source]

Convert covariance matrix (or array of covariance matrices of equal shape) to error array (or array thereof).

Parameters:cov – [n x ] nbins x nbins array
Returns
[n x ] nbins array
clusterking.maths.statistics.cov2corr(cov)[source]

Convert covariance matrix (or array of covariance matrices of equal shape) to correlation matrix (or array thereof).

Parameters:cov – [n x ] nbins x nbins array
Returns
[n x ] nbins x nbins array
clusterking.maths.statistics.corr2cov(corr, err)[source]

Convert correlation matrix (or array of covariance matrices of equal shape) together with error array (or array thereof) to covariance matrix (or array thereof).

Parameters:
  • corr – [n x ] nbins x nbins array
  • err – [n x ] nbins array
Returns
[n x ] nbins x nbins array
clusterking.maths.statistics.rel2abs_cov(cov, data)[source]

Convert relative covariance matrix to absolute covariance matrix

Parameters:
  • cov – n x nbins x nbins array
  • data – n x nbins array
Returns:

n x nbins x nbins array
clusterking.maths.statistics.abs2rel_cov(cov, data)[source]

Convert covariance matrix to relative covariance matrix

Parameters:
  • cov – n x nbins x nbins array
  • data – n x nbins array
Returns:

n x nbins x nbins array