pydiodon.coa¶

pydiodon.coa(X, k=- 1, meth='svd', transpose=False)[source]¶

Correspondance Analysis of an array

Parameters

Xa 2D numpy array, n x p

array to be analysed

kan integer

number of axis to compute

default is $k=-1$ (all components are cimputed)

metha string

method for numerical computing

one string among evd, svd, grp (see notes)

default value is $svd$

transposea boolean

if True, matrix $A$ is transposed (usually because n < p)

default is False

Returns

Notes

If $k=-1$, all axis are computed. If $k > 0$, only k first axis and components are computed.

methods for SVD

svd	SVD with numpy.linalg.svd()
grp	SVD with gaussian random projection

Example

This example should be run from the directory where diodon_companion has been cloned for the dataset example_coa to be found.

>>> import pydiodon as dio
>>> A, headers, rownames = dio.load("example_coa")
>>> L, Y_r, Y_c = dio.coa(A)

and, to plot the row and column components

>>> dio.plot_coa(Y_r,Y_c, rownames=rownames, colnames=headers)

note on the example

The dataset is in text format with tabs as delimiters. It contains headers and row names. These are default parameters for functions dio.load()

References:

Nenadic & Greenacre, Journal of Statistical Software, 20(3): 2-13, 2007

Lebart, Morineau & Fénelon, 1982, pp. 305-320

af, revised 21.02.21, 22.11.05, 23.06.13