pcomp¶
-
class
pydl.
pcomp
(x, standardize=False, covariance=False)[source]¶ Bases:
object
Replicates the IDL
PCOMP()
function.The attributes of this class are all read-only properties, implemented with
lazyproperty
.- Parameters
x : array-like
A 2-D array with \(N\) rows and \(M\) columns.
standardize :
bool
, optionalIf set to
True
, the input data will have its mean subtracted off and will be scaled to unit variance.covariance :
bool
, optional.If set to
True
, the covariance matrix of the data will be used for the computation. Otherwise the correlation matrix will be used.
References
http://www.harrisgeospatial.com/docs/pcomp.html
Attributes Summary
(
ndarray
) The principal components.(
ndarray
) The derived variables.(
ndarray
) The eigenvalues.(
ndarray
) The variances of each derived variable.Attributes Documentation
-
coefficients
¶ (
ndarray
) The principal components. These are the coefficients ofderived
. Basically, they are a re-scaling of the eigenvectors.
-
derived
¶ (
ndarray
) The derived variables.
-
eigenvalues
¶ (
ndarray
) The eigenvalues. There is one eigenvalue for each principal component.
-
variance
¶ (
ndarray
) The variances of each derived variable.