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# py/pyext - python script objects for PD and MaxMSP
#
# Copyright (c) 2002-2012 Thomas Grill (gr@grrrr.org)
# For information on usage and redistribution, and for a DISCLAIMER OF ALL
# WARRANTIES, see the file, "license.txt," in this distribution.
#
"""This is an example script for the py/pyext object's buffer support.
Pd/Max buffers can be mapped to Python arrays.
Currently, there are three implementations:
Numeric, numarray and numpy (for all of them see http://numeric.scipy.org)
"""
import sys
try:
import pyext
except:
print "ERROR: This script must be loaded by the PD/Max py/pyext external"
try:
# numpy is assumed here... numeric and numarray are considered deprecated
import numpy as N
except:
print "Failed importing numpy module:",sys.exc_value
def mul(*args):
# create buffer objects
# as long as these variables live the underlying buffers are locked
c = pyext.Buffer(args[0])
a = pyext.Buffer(args[1])
b = pyext.Buffer(args[2])
commonlen = min(len(a),len(b),len(c))
# slicing causes Python arrays (mapped to buffers) to be created
# note the c[:] - to assign contents you must assign to a slice of the buffer
c[:commonlen] = a[:commonlen]*b[:commonlen]
def add(*args):
c = pyext.Buffer(args[0])
a = pyext.Buffer(args[1])
b = pyext.Buffer(args[2])
commonlen = min(len(a),len(b),len(c))
# explicit casting to arrays is also possible
c[:commonlen] = N.array(a[:commonlen],dtype=N.float32) + N.array(b[:commonlen],dtype=N.float32)
def fadein(target):
a = pyext.Buffer(target)
# in place operations are ok
a *= N.arange(len(a),dtype=N.float32)/len(a)
def neg(target):
a = pyext.Buffer(target)
# in place transformation (see Python array ufuncs)
N.negative(a[:],a[:])
# must mark buffer content as dirty to update graph
# (no explicit assignment occurred)
a.dirty()
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