def _distSpearmanW_NU(x, y, w):
"""x,y,w must be Numeric
"""
x = Numeric.asarray(x)
y = Numeric.asarray(y)
w = Numeric.asarray(w)
assert Numeric.rank(x) == Numeric.rank(y) == Numeric.rank(w) == 1
rankx = Numeric.array(statc.rankdata(x.tolist()))
ranky = Numeric.array(statc.rankdata(y.tolist()))
return distPearsonW(rankx, ranky, w)
def mad(m,axis=0):
"""Returns Median Absolute Deviation of the given array along the given axis.
"""
m = Numeric.asarray(m)
mx = Numeric.asarray(median(m,axis),Numeric.Float)
xt = Numeric.transpose(m, [axis]+range(axis)+range(axis+1,Numeric.rank(m))) # do not use swapaxes: (0,1,2) -swap-> (2,1,0); (0,1,2) -transpose-> (2,0,1)
return MLab.median(Numeric.absolute(xt-mx))
def __init__ ( self, x=None, y=None, ireg=None, triangle=None ):
try:
self.x = array ( x, typecode=Float, copy=0 )
except:
raise TypeError( "Could not cast x to numpy array")
if not ( rank(self.x) == 2 and
shape(self.x)[0] >=2 and shape(self.x)[1] >= 2 ):
raise TypeError( "x must be 2D")
try:
self.y = array ( y, typecode=Float, copy=0 )
except:
raise TypeError( "Could not cast y to numpy array")
if not ( rank(self.y) == 2 and
shape(self.y)[0] >=2 and shape(self.y)[1] >= 2 ):
raise TypeError( "y must be 2D")
if ireg is None:
self.ireg = zeros ( shape(self.x), Int )
self.ireg[1:,1:] = 1
else:
try:
self.ireg = array ( ireg, typecode=Int, copy=0 )
except:
raise TypeError( "Could not cast ireg to numpy array")
if not ( rank(self.ireg) == 2 and
shape(self.ireg)[0] >=2 and shape(self.ireg)[1] >= 2 ):
raise TypeError( "ireg must be 2D")
if triangle is None:
self.triangle = zeros ( shape(self.x), Int16 )
else:
try:
self.triangle = array ( triangle, typecode=Int16, copy=0 )
except:
raise TypeError( "Could not cast triangle to numpy array")
if not ( rank(self.triangle) == 2 and
shape(self.triangle)[0] >=2 and shape(self.triangle)[1] >= 2 ):
raise TypeError( "triangle must be 2D")
self.shape = shape(self.x)
def rankData(n, inverse=False):
"""Returns ranks of 1D Numeric array in range 1...shape[0].
"""
n = Numeric.asarray(n)
assert Numeric.rank(n) == 1
r = Numeric.zeros(n.shape[0], Numeric.Float)
Numeric.put(r, Numeric.argsort(n), Numeric.arange(n.shape[0]))
if inverse:
return -1*r+n.shape[0]
else:
return r+1
def setReg ( self, ireg ):
try:
self.ireg = array ( ireg, typecode=Int, copy=0 )
except:
raise TypeError( "Could not cast ireg to numpy array")
if not ( rank(self.ireg) == 2 and
shape(self.ireg)[0] >=2 and shape(self.ireg)[1] >= 2 ):
raise TypeError( "ireg must be 2D")
if self.shape != shape ( self.ireg ):
raise InputError( "ireg has incompatible shape.")
def setTriangle ( self, triangle ):
try:
self.triangle = array ( triangle, typecode=Int16, copy=0 )
except:
raise TypeError( "Could not cast triangle to numpy array")
if not ( rank(self.triangle) == 2 and
shape(self.triangle)[0] >=2 and shape(self.triangle)[1] >= 2 ):
raise TypeError( "triangle must be 2D")
if self.shape != shape (self.triangle):
raise InputError( "triangle has incompatible shape.")
