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## Automatically adapted for scipy Oct 31, 2005 by
# $Id: yorick.py 1698 2006-03-14 23:12:10Z cookedm $
# Copyright (c) 1996, 1997, The Regents of the University of California.
# All rights reserved. See Legal.htm for full text and disclaimer.
from scipy import *
import os
import time
from shapetest import *
"""
The yorick module supplies Python versions of some common
yorick functions: zcen_, dif_, maxelt_, minelt_, rem_0_,
avg_, timer_, timer_print.
"""
_ZcenError = "ZcenError"
def zcen_ (x, i = 0) :
"""
zcen_(x, i) does the same thing as in Yorick: x(...,zcen,...)
where zcen is the ith subscript. (works for up to 5 dimensions).
Namely, the elements along the ith dimension of x are replaced
by the averages of adjacent pairs, and the dimension decreases
by one. Remember that Python sunscripts are counted from 0.
"""
if is_scalar (x) :
raise _ZcenError, "zcen_ must be called with an array."
dims = shape (x)
ndims = len (dims)
if i < 0 or i > ndims - 1 :
raise _ZcenError, "i <" + `i+1` + \
"> is out of the range of x's dimensions<" + `ndims` +"."
if i == 0 :
newx = (x [0:dims [0]-1] + x [1:dims [0]]) /2.0
elif i == 1 :
newx = (x [:, 0:dims [1]-1] + x[:, 1:dims [1]]) / 2.0
elif i == 2 :
newx = (x [:, :, 0:dims [2]-1] + x[:, :, 1:dims [2]]) / 2.0
elif i == 3 :
newx = (x [:, :, :, 0:dims [3]-1] + x[:, :, :, 1:dims [3]]) / 2.0
elif i == 4 :
newx = (x [:, :, :, :, 0:dims [4]-1] + \
x [:, :, :, :, 0:dims [4]]) / 2.0
return newx
_DifError = "DifError"
def dif_ (x, i = 0) :
"""
dif_(x, i) does the same thing as in Yorick: x(...,dif_,...)
where dif_ is the ith subscript. (works for up to 5 dimensions).
Namely, the elements along the ith dimension of x are replaced
by the differences of adjacent pairs, and the dimension decreases
by one. Remember that Python sunscripts are counted from 0.
"""
if is_scalar (x) :
raise _DifError, "dif_ must be called with an array."
dims = shape (x)
ndims = len (dims)
if i < 0 or i > ndims - 1 :
raise _DifError, "i <" + `i+1` + \
"> is out of the range of x's dimensions <" + `ndims` +">."
if i == 0 :
newx = x [1:dims [0]] - x [0:dims [0] - 1]
elif i == 1 :
newx = x [:, 1:dims [1]] - x[:, 0:dims [1] - 1]
elif i == 2 :
newx = x [:, :, 1:dims [2]] - x [:, :, 0:dims [2] - 1]
elif i == 3 :
newx = x [:, :, :, 1:dims [3]] - x [:, :, :, 0:dims [3] - 1]
elif i == 4 :
newx = x [:, :, :, :, 1:dims [4]] - x [:, :, :, :, 0:dims [4] - 1]
return newx
def maxelt_ (*x) :
"""
maxelt_ accepts a sequence of one or more possible multi-dimensional
objects and computes their maximum. In principle these can be of
arbitrary complexity, since the routine recurses.
"""
if len (x) == 0 :
return None
elif len (x) == 1 :
z = x [0]
if is_scalar (z) :
return z
if len (shape (z)) >= 1 :
zz = array (z)
return maximum.reduce (ravel (zz))
else :
maxelt = maxelt_ (x [0])
for i in range (1, len (x)) :
maxelt = max (maxelt, maxelt_ (x [i]))
return maxelt
def minelt_ (*x) :
"""
minelt_ accepts a sequence of one or more possible multi-dimensional
objects and computes their minimum. In principle these can be of
arbitrary complexity, since the routine recurses.
"""
if len (x) == 0 :
return None
elif len (x) == 1 :
z = x [0]
if is_scalar (z) :
return z
if len (shape (z)) >= 1 :
zz = array (z)
return minimum.reduce (ravel (zz))
else :
minelt = minelt_ (x [0])
for i in range (1, len (x)) :
minelt = min (minelt, minelt_ (x [i]))
return minelt
def rem_0_ (z) :
"""
rem_0_ (z) goes through array z and replaces any zero
elements with 1.e-35. Assumes z has one or two dimensions.
"""
if len (shape (z)) == 1 :
for i in range (len (z)) :
z [i] = z [i] + (z [i] == 0.0) * 1.e-35
elif len (shape (z)) == 2 :
(k, l) = shape (z)
for i in range (k) :
for j in range (l) :
z [i] [j] = z [i] [j] + (z [i] [j] == 0.0) * 1.e-35
def avg_ (z) :
"""
avg_ (z) returns the average of all elements of its array
argument.
"""
zz = array (z, copy = 1 )
return add.reduce (ravel (zz)) / len (ravel (zz))
def sign_ (x) :
if x >= 0 :
return (1)
else :
return (- 1)
def timer_ (elapsed, *split) :
"""
timer (elapsed) returns a triple consisting of the times
[cpu, system, wall].
timer (elapsed, split) returns a sequence whose first element
is [cpu, system, wall] and whose second element is the
sum of split and the difference between ththe new and old values
of 'elapsed.'
"""
stime = os.times ( )
wtime = time.time ( )
retval = array ( [stime [0], stime [1], wtime], Float )
if len (split) == 0 :
return retval
else :
return [retval, split [0] + retval - elapsed]
def timer_print (label, split, *other_args) :
"""
timer_print (label1, split1 [,label2, split2, ...]) prints
out a timing summary for splits accumulated by timer_.
"""
print label, split
i = 0
while i < len (other_args) :
print other_args [i], other_args [i + 1]
i = i + 2
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