def sanity_matrix2doutputExample(self):
"""
Sanity of matrix2doutput.
"""
from PyAstronomy import pyaC as PC
import numpy as np
m = np.zeros((4, 3))
colNames = ["first", "second", "third"]
rowNames = ["1", "2", "3", "4"]
for j in range(4):
for i in range(3):
m[j, i] = (i + 1) * 10**(j + 1) * np.sin(i * j)
PC.matrix2doutput(m, colNames=colNames, rowNames=rowNames)
print()
PC.matrix2doutput(m, rowNames=rowNames)
print()
PC.matrix2doutput(m, colsep=" ")
print()
PC.matrix2doutput(m,
oformat="% 12.5f",
colNames=colNames,
rowNames=rowNames)
print()
PC.matrix2doutput(m,
oformat=["% 12.5f", "% 6.3f", "% e"],
colNames=colNames)
def correlationMatrix(self, toScreen=True, method="pearson", parList=None, covariance=False):
"""
Calculates the correlation or covariance matrix.
Parameters
----------
parList : list of strings, optional
The list of parameters used in the calculation.
If not given, all available parameters will be
used.
toScreen : boolean, optional
If True, the result will be printed to stdout
method : string, {"pearson", "spearman"}
The correlation coefficient to be used.
covariance : boolean, optional
If True, the covariance will be returned instead
of the correlation. The default is False.
Returns
-------
Parlist : list
Parameter names in the order used in the calculation.
Correlation matrix : 2d array
The correlation matrix
lines : list of strings
Formatted version of the correlation matrix in the form
of a list of strings.
"""
if parList is None:
parList = self.availableParameters()
corFunc = None
if method == "pearson": corFunc = self.pearsonr
if method == "spearman": corFunc = self.spearmanr
if corFunc is None:
raise(PE.PyAValError("The method "+str(method)+" is currently not supported.", \
solution="Change method argument e.g. to 'pearson'."))
for p in parList:
self._parmCheck(p)
if covariance:
# The covariance is requested. In this case, the
# correlation coefficient has to be multiplied by the
# standard deviation(s).
stds = {}
for p in parList:
stds[p] = self.std(p)
# Calculate the matrix
n = len(parList)
matrix = np.zeros( (n, n) )
for i in xrange(n):
for j in xrange(n):
matrix[i, j] = corFunc(parList[i], parList[j])[0]
if covariance:
matrix[i, j] *= (stds[parList[i]] * stds[parList[j]])
# Format the output
lines = PC.matrix2doutput(matrix, colNames=parList, rowNames=parList, toScreen=toScreen)
return parList, matrix, lines
def correlationMatrix(self, toScreen=True, method="pearson", parList=None, covariance=False):
"""
Calculates the correlation or covariance matrix.
Parameters
----------
parList : list of strings, optional
The list of parameters used in the calculation.
If not given, all available parameters will be
used.
toScreen : boolean, optional
If True, the result will be printed to stdout
method : string, {"pearson", "spearman"}
The correlation coefficient to be used.
covariance : boolean, optional
If True, the covariance will be returned instead
of the correlation. The default is False.
Returns
-------
Parlist : list
Parameter names in the order used in the calculation.
Correlation matrix : 2d array
The correlation matrix
lines : list of strings
Formatted version of the correlation matrix in the form
of a list of strings.
"""
if parList is None:
parList = self.availableParameters()
corFunc = None
if method == "pearson": corFunc = self.pearsonr
if method == "spearman": corFunc = self.spearmanr
if corFunc is None:
raise(PE.PyAValError("The method "+str(method)+" is currently not supported.", \
solution="Change method argument e.g. to 'pearson'."))
for p in parList:
self._parmCheck(p)
if covariance:
# The covariance is requested. In this case, the
# correlation coefficient has to be multiplied by the
# standard deviation(s).
stds = {}
for p in parList:
stds[p] = self.std(p)
# Calculate the matrix
n = len(parList)
matrix = np.zeros( (n, n) )
for i in smo.range(n):
for j in smo.range(n):
matrix[i, j] = corFunc(parList[i], parList[j])[0]
if covariance:
matrix[i, j] *= (stds[parList[i]] * stds[parList[j]])
# Format the output
lines = PC.matrix2doutput(matrix, colNames=parList, rowNames=parList, toScreen=toScreen)
return parList, matrix, lines
def sanity_matrix2doutputExample(self):
"""
Sanity of matrix2doutput.
"""
from PyAstronomy import pyaC as PC
import numpy as np
m = np.zeros((4,3))
colNames = ["first", "second", "third"]
rowNames = ["1", "2", "3", "4"]
for j in range(4):
for i in range(3):
m[j,i] = (i+1) * 10**(j+1) * np.sin(i*j)
PC.matrix2doutput(m, colNames=colNames, rowNames=rowNames)
print()
PC.matrix2doutput(m, rowNames=rowNames)
print()
PC.matrix2doutput(m, colsep=" ")
print()
PC.matrix2doutput(m, oformat="% 12.5f", colNames=colNames, rowNames=rowNames)
print()
PC.matrix2doutput(m, oformat=["% 12.5f", "% 6.3f", "% e"], colNames=colNames)
