Maths
Contents
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
objectoutput – ‘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