|
Imported modules
|
|
import LinearAlgebra
import Numeric
import Scientific.Statistics
import pyclimate.mctest
import pyclimate.mvarstatools
import pyclimate.pyclimateexcpt
import pyclimate.tools
import sys
import whrandom
|
|
Functions
|
|
|
|
|
|
CSCF
|
CSCF ( sigmas )
Cumulative squared covariance fraction
Argument:
-
sigmas
- Covariances returned by svd()
Returns a Numeric Array with the Cumulative squared covariance fraction
|
|
|
SCF
|
SCF ( sigmas )
Get the squared covariance fraction of the modes
Argument:
-
sigmas
- Covariances returned by svd()
Returns a Numeric array with the Squared covariance fraction
|
|
|
getcoefcorrelations
|
getcoefcorrelations ( scoefs, zcoefs )
Correlation between the temporal expansion coefficients
|
|
|
getcoefs
|
getcoefs ( data, svectors )
Temporal expansion coefficients
Arguments:
-
data
- Data to project onto the singular vectors, usually
the same NumPy used to get the vectors.
-
svectors
- Singular vectors (left or right) as returned by
svd()
|
|
|
getvector
|
getvector ( svectors, ivect )
Get the ivect-eth singular vector.
Arguments:
-
svectors
- Matrix of eigenvectors returned by svd (P or Q)
-
ivect
- The order of the eigenvector that must be returned
Returns the ivect-ieth spatial pattern
|
|
|
heterogeneousmaps
|
heterogeneousmaps ( xdata, ycoefs )
Heterogeneous correlation maps
Arguments:
-
xdata
- Data to be represented as heterogeneous correlation
-
ycoefs
- Temporal expansion coefs to correlate with
xdata. To get
an heterogeneous map they must be left-xdata and right-ycoefs
or right-xdata and left-ycoefs.
|
|
|
homogeneousmaps
|
homogeneousmaps ( data, svectors )
Homogeneus correlation maps
Arguments:
-
data
- Data to be represented as homogeneous correlation
-
svectors
- Correspondent singular vectors as returned by
svd()
|
|
|
makemctest
|
makemctest (
Umaster,
Vmaster,
ldata,
rdata,
itimes,
ielems,
)
Monte Carlo test on the congruence of the singular vectors
Arguments:
-
Umaster
- Left singular vectors as returned by
svd()
-
Vmaster
- Right singular vectors as returned by
svd()
-
ldata
- Left data field
-
rdata
- Right data field
-
itimes
- Number of Monte Carlo runs
-
ielems
- Number of records in each Monte Carlo subsample
|
Exceptions
|
|
excpt.SVDSubsetLengthException(vectors, len(Vmaster [ 0 ] ) )
|
|
|
|
numberofvectors
|
numberofvectors ( svectors )
Number of eigenvectors according to our storage rules.
Arguments:
-
svectors
- Matrix of eigenvectors returned by svd() (P or Q)
|
|
|
svd
|
svd ( sfield, zfield )
Given two fields, get the SVD of their covariance matrix.
Arguments:
-
sfield
- Input left field
-
zfield
- Input right field
Returns a tuple (P,S,Q) with:
-
P
- The left singular vectors.
-
S
- The covariance of each of the modes.
-
Q
- The right singular vectors
|
Exceptions
|
|
excpt.SVDLengthException(len( sfield ), len( zfield ) )
|
|