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-rw-r--r--numpy/oldnumeric/__init__.py41
-rw-r--r--numpy/oldnumeric/alter_code1.py240
-rw-r--r--numpy/oldnumeric/alter_code2.py146
-rw-r--r--numpy/oldnumeric/array_printer.py16
-rw-r--r--numpy/oldnumeric/arrayfns.py96
-rw-r--r--numpy/oldnumeric/compat.py66
-rw-r--r--numpy/oldnumeric/fft.py21
-rw-r--r--numpy/oldnumeric/fix_default_axis.py291
-rw-r--r--numpy/oldnumeric/functions.py124
-rw-r--r--numpy/oldnumeric/linear_algebra.py83
-rw-r--r--numpy/oldnumeric/ma.py14
-rw-r--r--numpy/oldnumeric/matrix.py67
-rw-r--r--numpy/oldnumeric/misc.py42
-rw-r--r--numpy/oldnumeric/mlab.py122
-rw-r--r--numpy/oldnumeric/precision.py169
-rw-r--r--numpy/oldnumeric/random_array.py266
-rw-r--r--numpy/oldnumeric/rng.py135
-rw-r--r--numpy/oldnumeric/rng_stats.py35
-rw-r--r--numpy/oldnumeric/setup.py8
-rw-r--r--numpy/oldnumeric/tests/test_oldnumeric.py86
-rw-r--r--numpy/oldnumeric/typeconv.py60
-rw-r--r--numpy/oldnumeric/ufuncs.py19
-rw-r--r--numpy/oldnumeric/user_array.py9
23 files changed, 0 insertions, 2156 deletions
diff --git a/numpy/oldnumeric/__init__.py b/numpy/oldnumeric/__init__.py
deleted file mode 100644
index 83819ad04..000000000
--- a/numpy/oldnumeric/__init__.py
+++ /dev/null
@@ -1,41 +0,0 @@
-# Don't add these to the __all__ variable though
-from numpy import *
-
-def _move_axis_to_0(a, axis):
- if axis == 0:
- return a
- n = len(a.shape)
- if axis < 0:
- axis += n
- axes = range(1, axis+1) + [0,] + range(axis+1, n)
- return transpose(a, axes)
-
-# Add these
-from compat import *
-from functions import *
-from precision import *
-from ufuncs import *
-from misc import *
-
-import compat
-import precision
-import functions
-import misc
-import ufuncs
-
-import numpy
-__version__ = numpy.__version__
-del numpy
-
-__all__ = ['__version__']
-__all__ += compat.__all__
-__all__ += precision.__all__
-__all__ += functions.__all__
-__all__ += ufuncs.__all__
-__all__ += misc.__all__
-
-del compat
-del functions
-del precision
-del ufuncs
-del misc
diff --git a/numpy/oldnumeric/alter_code1.py b/numpy/oldnumeric/alter_code1.py
deleted file mode 100644
index 87538a855..000000000
--- a/numpy/oldnumeric/alter_code1.py
+++ /dev/null
@@ -1,240 +0,0 @@
-"""
-This module converts code written for Numeric to run with numpy
-
-Makes the following changes:
- * Changes import statements (warns of use of from Numeric import *)
- * Changes import statements (using numerix) ...
- * Makes search and replace changes to:
- - .typecode()
- - .iscontiguous()
- - .byteswapped()
- - .itemsize()
- - .toscalar()
- * Converts .flat to .ravel() except for .flat = xxx or .flat[xxx]
- * Replace xxx.spacesaver() with True
- * Convert xx.savespace(?) to pass + ## xx.savespace(?)
-
- * Converts uses of 'b' to 'B' in the typecode-position of
- functions:
- eye, tri (in position 4)
- ones, zeros, identity, empty, array, asarray, arange,
- fromstring, indices, array_constructor (in position 2)
-
- and methods:
- astype --- only argument
- -- converts uses of '1', 's', 'w', and 'u' to
- -- 'b', 'h', 'H', and 'I'
-
- * Converts uses of type(...) is <type>
- isinstance(..., <type>)
-"""
-__all__ = ['convertfile', 'convertall', 'converttree', 'convertsrc']
-
-import sys
-import os
-import re
-import glob
-
-
-_func4 = ['eye', 'tri']
-_meth1 = ['astype']
-_func2 = ['ones', 'zeros', 'identity', 'fromstring', 'indices',
- 'empty', 'array', 'asarray', 'arange', 'array_constructor']
-
-_chars = {'1':'b','s':'h','w':'H','u':'I'}
-
-func_re = {}
-meth_re = {}
-
-for name in _func2:
- _astr = r"""(%s\s*[(][^,]*?[,][^'"]*?['"])b(['"][^)]*?[)])"""%name
- func_re[name] = re.compile(_astr, re.DOTALL)
-
-for name in _func4:
- _astr = r"""(%s\s*[(][^,]*?[,][^,]*?[,][^,]*?[,][^'"]*?['"])b(['"][^)]*?[)])"""%name
- func_re[name] = re.compile(_astr, re.DOTALL)
-
-for name in _meth1:
- _astr = r"""(.%s\s*[(][^'"]*?['"])b(['"][^)]*?[)])"""%name
- func_re[name] = re.compile(_astr, re.DOTALL)
-
-for char in _chars.keys():
- _astr = r"""(.astype\s*[(][^'"]*?['"])%s(['"][^)]*?[)])"""%char
- meth_re[char] = re.compile(_astr, re.DOTALL)
-
-def fixtypechars(fstr):
- for name in _func2 + _func4 + _meth1:
- fstr = func_re[name].sub('\\1B\\2',fstr)
- for char in _chars.keys():
- fstr = meth_re[char].sub('\\1%s\\2'%_chars[char], fstr)
- return fstr
-
-flatindex_re = re.compile('([.]flat(\s*?[[=]))')
-
-def changeimports(fstr, name, newname):
- importstr = 'import %s' % name
- importasstr = 'import %s as ' % name
- fromstr = 'from %s import ' % name
- fromall=0
-
- fstr = re.sub(r'(import\s+[^,\n\r]+,\s*)(%s)' % name,
- "\\1%s as %s" % (newname, name), fstr)
- fstr = fstr.replace(importasstr, 'import %s as ' % newname)
- fstr = fstr.replace(importstr, 'import %s as %s' % (newname,name))
-
- ind = 0
- Nlen = len(fromstr)
- Nlen2 = len("from %s import " % newname)
- while 1:
- found = fstr.find(fromstr,ind)
- if (found < 0):
- break
- ind = found + Nlen
- if fstr[ind] == '*':
- continue
- fstr = "%sfrom %s import %s" % (fstr[:found], newname, fstr[ind:])
- ind += Nlen2 - Nlen
- return fstr, fromall
-
-istest_re = {}
-_types = ['float', 'int', 'complex', 'ArrayType', 'FloatType',
- 'IntType', 'ComplexType']
-for name in _types:
- _astr = r'type\s*[(]([^)]*)[)]\s+(?:is|==)\s+(.*?%s)'%name
- istest_re[name] = re.compile(_astr)
-def fixistesting(astr):
- for name in _types:
- astr = istest_re[name].sub('isinstance(\\1, \\2)', astr)
- return astr
-
-def replaceattr(astr):
- astr = astr.replace(".typecode()",".dtype.char")
- astr = astr.replace(".iscontiguous()",".flags.contiguous")
- astr = astr.replace(".byteswapped()",".byteswap()")
- astr = astr.replace(".toscalar()", ".item()")
- astr = astr.replace(".itemsize()",".itemsize")
- # preserve uses of flat that should be o.k.
- tmpstr = flatindex_re.sub(r"@@@@\2",astr)
- # replace other uses of flat
- tmpstr = tmpstr.replace(".flat",".ravel()")
- # put back .flat where it was valid
- astr = tmpstr.replace("@@@@", ".flat")
- return astr
-
-svspc2 = re.compile(r'([^,(\s]+[.]spacesaver[(][)])')
-svspc3 = re.compile(r'(\S+[.]savespace[(].*[)])')
-#shpe = re.compile(r'(\S+\s*)[.]shape\s*=[^=]\s*(.+)')
-def replaceother(astr):
- astr = svspc2.sub('True',astr)
- astr = svspc3.sub(r'pass ## \1', astr)
- #astr = shpe.sub('\\1=\\1.reshape(\\2)', astr)
- return astr
-
-import datetime
-def fromstr(filestr):
- savestr = filestr[:]
- filestr = fixtypechars(filestr)
- filestr = fixistesting(filestr)
- filestr, fromall1 = changeimports(filestr, 'Numeric', 'numpy.oldnumeric')
- filestr, fromall1 = changeimports(filestr, 'multiarray','numpy.oldnumeric')
- filestr, fromall1 = changeimports(filestr, 'umath', 'numpy.oldnumeric')
- filestr, fromall1 = changeimports(filestr, 'Precision', 'numpy.oldnumeric.precision')
- filestr, fromall1 = changeimports(filestr, 'UserArray', 'numpy.oldnumeric.user_array')
- filestr, fromall1 = changeimports(filestr, 'ArrayPrinter', 'numpy.oldnumeric.array_printer')
- filestr, fromall2 = changeimports(filestr, 'numerix', 'numpy.oldnumeric')
- filestr, fromall3 = changeimports(filestr, 'scipy_base', 'numpy.oldnumeric')
- filestr, fromall3 = changeimports(filestr, 'Matrix', 'numpy.oldnumeric.matrix')
- filestr, fromall3 = changeimports(filestr, 'MLab', 'numpy.oldnumeric.mlab')
- filestr, fromall3 = changeimports(filestr, 'LinearAlgebra', 'numpy.oldnumeric.linear_algebra')
- filestr, fromall3 = changeimports(filestr, 'RNG', 'numpy.oldnumeric.rng')
- filestr, fromall3 = changeimports(filestr, 'RNG.Statistics', 'numpy.oldnumeric.rng_stats')
- filestr, fromall3 = changeimports(filestr, 'RandomArray', 'numpy.oldnumeric.random_array')
- filestr, fromall3 = changeimports(filestr, 'FFT', 'numpy.oldnumeric.fft')
- filestr, fromall3 = changeimports(filestr, 'MA', 'numpy.oldnumeric.ma')
- fromall = fromall1 or fromall2 or fromall3
- filestr = replaceattr(filestr)
- filestr = replaceother(filestr)
- if savestr != filestr:
- today = datetime.date.today().strftime('%b %d, %Y')
- name = os.path.split(sys.argv[0])[-1]
- filestr = '## Automatically adapted for '\
- 'numpy.oldnumeric %s by %s\n\n%s' % (today, name, filestr)
- return filestr, 1
- return filestr, 0
-
-def makenewfile(name, filestr):
- fid = file(name, 'w')
- fid.write(filestr)
- fid.close()
-
-def convertfile(filename, orig=1):
- """Convert the filename given from using Numeric to using NumPy
-
- Copies the file to filename.orig and then over-writes the file
- with the updated code
- """
- fid = open(filename)
- filestr = fid.read()
- fid.close()
- filestr, changed = fromstr(filestr)
- if changed:
- if orig:
- base, ext = os.path.splitext(filename)
- os.rename(filename, base+".orig")
- else:
- os.remove(filename)
- makenewfile(filename, filestr)
-
-def fromargs(args):
- filename = args[1]
- converttree(filename)
-
-def convertall(direc=os.path.curdir, orig=1):
- """Convert all .py files to use numpy.oldnumeric (from Numeric) in the directory given
-
- For each changed file, a backup of <usesnumeric>.py is made as
- <usesnumeric>.py.orig. A new file named <usesnumeric>.py
- is then written with the updated code.
- """
- files = glob.glob(os.path.join(direc,'*.py'))
- for afile in files:
- if afile[-8:] == 'setup.py': continue # skip these
- convertfile(afile, orig)
-
-header_re = re.compile(r'(Numeric/arrayobject.h)')
-
-def convertsrc(direc=os.path.curdir, ext=None, orig=1):
- """Replace Numeric/arrayobject.h with numpy/oldnumeric.h in all files in the
- directory with extension give by list ext (if ext is None, then all files are
- replaced)."""
- if ext is None:
- files = glob.glob(os.path.join(direc,'*'))
- else:
- files = []
- for aext in ext:
- files.extend(glob.glob(os.path.join(direc,"*.%s" % aext)))
- for afile in files:
- fid = open(afile)
- fstr = fid.read()
- fid.close()
- fstr, n = header_re.subn(r'numpy/oldnumeric.h',fstr)
- if n > 0:
- if orig:
- base, ext = os.path.splitext(afile)
- os.rename(afile, base+".orig")
- else:
- os.remove(afile)
- makenewfile(afile, fstr)
-
-def _func(arg, dirname, fnames):
- convertall(dirname, orig=0)
- convertsrc(dirname, ext=['h','c'], orig=0)
-
-def converttree(direc=os.path.curdir):
- """Convert all .py files and source code files in the tree given
- """
- os.path.walk(direc, _func, None)
-
-
-if __name__ == '__main__':
- fromargs(sys.argv)
diff --git a/numpy/oldnumeric/alter_code2.py b/numpy/oldnumeric/alter_code2.py
deleted file mode 100644
index baa6b9d26..000000000
--- a/numpy/oldnumeric/alter_code2.py
+++ /dev/null
@@ -1,146 +0,0 @@
-"""
-This module converts code written for numpy.oldnumeric to work
-with numpy
-
-FIXME: Flesh this out.
-
-Makes the following changes:
- * Converts typecharacters '1swu' to 'bhHI' respectively
- when used as typecodes
- * Changes import statements
- * Change typecode= to dtype=
- * Eliminates savespace=xxx keyword arguments
- * Removes it when keyword is not given as well
- * replaces matrixmultiply with dot
- * converts functions that don't give axis= keyword that have changed
- * converts functions that don't give typecode= keyword that have changed
- * converts use of capitalized type-names
- * converts old function names in oldnumeric.linear_algebra,
- oldnumeric.random_array, and oldnumeric.fft
-
-"""
-#__all__ = ['convertfile', 'convertall', 'converttree']
-__all__ = []
-
-import warnings
-warnings.warn("numpy.oldnumeric.alter_code2 is not working yet.")
-
-import sys
-import os
-import re
-import glob
-
-# To convert typecharacters we need to
-# Not very safe. Disabled for now..
-def replacetypechars(astr):
- astr = astr.replace("'s'","'h'")
- astr = astr.replace("'b'","'B'")
- astr = astr.replace("'1'","'b'")
- astr = astr.replace("'w'","'H'")
- astr = astr.replace("'u'","'I'")
- return astr
-
-def changeimports(fstr, name, newname):
- importstr = 'import %s' % name
- importasstr = 'import %s as ' % name
- fromstr = 'from %s import ' % name
- fromall=0
-
- fstr = fstr.replace(importasstr, 'import %s as ' % newname)
- fstr = fstr.replace(importstr, 'import %s as %s' % (newname,name))
-
- ind = 0
- Nlen = len(fromstr)
- Nlen2 = len("from %s import " % newname)
- while 1:
- found = fstr.find(fromstr,ind)
- if (found < 0):
- break
- ind = found + Nlen
- if fstr[ind] == '*':
- continue
- fstr = "%sfrom %s import %s" % (fstr[:found], newname, fstr[ind:])
- ind += Nlen2 - Nlen
- return fstr, fromall
-
-def replaceattr(astr):
- astr = astr.replace("matrixmultiply","dot")
- return astr
-
-def replaceother(astr):
- astr = re.sub(r'typecode\s*=', 'dtype=', astr)
- astr = astr.replace('ArrayType', 'ndarray')
- astr = astr.replace('NewAxis', 'newaxis')
- return astr
-
-import datetime
-def fromstr(filestr):
- #filestr = replacetypechars(filestr)
- filestr, fromall1 = changeimports(filestr, 'numpy.oldnumeric', 'numpy')
- filestr, fromall1 = changeimports(filestr, 'numpy.core.multiarray', 'numpy')
- filestr, fromall1 = changeimports(filestr, 'numpy.core.umath', 'numpy')
- filestr, fromall3 = changeimports(filestr, 'LinearAlgebra',
- 'numpy.linalg.old')
- filestr, fromall3 = changeimports(filestr, 'RNG', 'numpy.random.oldrng')
- filestr, fromall3 = changeimports(filestr, 'RNG.Statistics', 'numpy.random.oldrngstats')
- filestr, fromall3 = changeimports(filestr, 'RandomArray', 'numpy.random.oldrandomarray')
- filestr, fromall3 = changeimports(filestr, 'FFT', 'numpy.fft.old')
- filestr, fromall3 = changeimports(filestr, 'MA', 'numpy.core.ma')
- fromall = fromall1 or fromall2 or fromall3
- filestr = replaceattr(filestr)
- filestr = replaceother(filestr)
- today = datetime.date.today().strftime('%b %d, %Y')
- name = os.path.split(sys.argv[0])[-1]
- filestr = '## Automatically adapted for '\
- 'numpy %s by %s\n\n%s' % (today, name, filestr)
- return filestr
-
-def makenewfile(name, filestr):
- fid = file(name, 'w')
- fid.write(filestr)
- fid.close()
-
-def getandcopy(name):
- fid = file(name)
- filestr = fid.read()
- fid.close()
- base, ext = os.path.splitext(name)
- makenewfile(base+'.orig', filestr)
- return filestr
-
-def convertfile(filename):
- """Convert the filename given from using Numeric to using NumPy
-
- Copies the file to filename.orig and then over-writes the file
- with the updated code
- """
- filestr = getandcopy(filename)
- filestr = fromstr(filestr)
- makenewfile(filename, filestr)
-
-def fromargs(args):
- filename = args[1]
- convertfile(filename)
-
-def convertall(direc=os.path.curdir):
- """Convert all .py files to use NumPy (from Numeric) in the directory given
-
- For each file, a backup of <usesnumeric>.py is made as
- <usesnumeric>.py.orig. A new file named <usesnumeric>.py
- is then written with the updated code.
- """
- files = glob.glob(os.path.join(direc,'*.py'))
- for afile in files:
- convertfile(afile)
-
-def _func(arg, dirname, fnames):
- convertall(dirname)
-
-def converttree(direc=os.path.curdir):
- """Convert all .py files in the tree given
-
- """
- os.path.walk(direc, _func, None)
-
-if __name__ == '__main__':
- fromargs(sys.argv)
diff --git a/numpy/oldnumeric/array_printer.py b/numpy/oldnumeric/array_printer.py
deleted file mode 100644
index 95f3f42c7..000000000
--- a/numpy/oldnumeric/array_printer.py
+++ /dev/null
@@ -1,16 +0,0 @@
-
-__all__ = ['array2string']
-
-from numpy import array2string as _array2string
-
-def array2string(a, max_line_width=None, precision=None,
- suppress_small=None, separator=' ',
- array_output=0):
- if array_output:
- prefix="array("
- style=repr
- else:
- prefix = ""
- style=str
- return _array2string(a, max_line_width, precision,
- suppress_small, separator, prefix, style)
diff --git a/numpy/oldnumeric/arrayfns.py b/numpy/oldnumeric/arrayfns.py
deleted file mode 100644
index 4c31a6827..000000000
--- a/numpy/oldnumeric/arrayfns.py
+++ /dev/null
@@ -1,96 +0,0 @@
-"""Backward compatible with arrayfns from Numeric
-"""
-
-__all__ = ['array_set', 'construct3', 'digitize', 'error', 'find_mask', 'histogram', 'index_sort',
- 'interp', 'nz', 'reverse', 'span', 'to_corners', 'zmin_zmax']
-
-import numpy as nx
-from numpy import asarray
-
-class error(Exception):
- pass
-
-def array_set(vals1, indices, vals2):
- indices = asarray(indices)
- if indices.ndim != 1:
- raise ValueError, "index array must be 1-d"
- if not isinstance(vals1, ndarray):
- raise TypeError, "vals1 must be an ndarray"
- vals1 = asarray(vals1)
- vals2 = asarray(vals2)
- if vals1.ndim != vals2.ndim or vals1.ndim < 1:
- raise error, "vals1 and vals2 must have same number of dimensions (>=1)"
- vals1[indices] = vals2
-
-from numpy import digitize
-from numpy import bincount as histogram
-
-def index_sort(arr):
- return asarray(arr).argsort(kind='heap')
-
-def interp(y, x, z, typ=None):
- """y(z) interpolated by treating y(x) as piecewise function
- """
- res = numpy.interp(z, x, y)
- if typ is None or typ == 'd':
- return res
- if typ == 'f':
- return res.astype('f')
-
- raise error, "incompatible typecode"
-
-def nz(x):
- x = asarray(x,dtype=nx.ubyte)
- if x.ndim != 1:
- raise TypeError, "intput must have 1 dimension."
- indxs = nx.flatnonzero(x != 0)
- return indxs[-1].item()+1
-
-def reverse(x, n):
- x = asarray(x,dtype='d')
- if x.ndim != 2:
- raise ValueError, "input must be 2-d"
- y = nx.empty_like(x)
- if n == 0:
- y[...] = x[::-1,:]
- elif n == 1:
- y[...] = x[:,::-1]
- return y
-
-def span(lo, hi, num, d2=0):
- x = linspace(lo, hi, num)
- if d2 <= 0:
- return x
- else:
- ret = empty((d2,num),x.dtype)
- ret[...] = x
- return ret
-
-def zmin_zmax(z, ireg):
- z = asarray(z, dtype=float)
- ireg = asarray(ireg, dtype=int)
- if z.shape != ireg.shape or z.ndim != 2:
- raise ValueError, "z and ireg must be the same shape and 2-d"
- ix, iy = nx.nonzero(ireg)
- # Now, add more indices
- x1m = ix - 1
- y1m = iy-1
- i1 = x1m>=0
- i2 = y1m>=0
- i3 = i1 & i2
- nix = nx.r_[ix, x1m[i1], x1m[i1], ix[i2] ]
- niy = nx.r_[iy, iy[i1], y1m[i3], y1m[i2]]
- # remove any negative indices
- zres = z[nix,niy]
- return zres.min().item(), zres.max().item()
-
-
-def find_mask(fs, node_edges):
- raise NotImplementedError
-
-def to_corners(arr, nv, nvsum):
- raise NotImplementedError
-
-
-def construct3(mask, itype):
- raise NotImplementedError
diff --git a/numpy/oldnumeric/compat.py b/numpy/oldnumeric/compat.py
deleted file mode 100644
index 369fa5000..000000000
--- a/numpy/oldnumeric/compat.py
+++ /dev/null
@@ -1,66 +0,0 @@
-# Compatibility module containing deprecated names
-
-__all__ = ['NewAxis',
- 'UFuncType', 'UfuncType', 'ArrayType', 'arraytype',
- 'LittleEndian', 'arrayrange', 'matrixmultiply',
- 'array_constructor', 'pickle_array',
- 'DumpArray', 'LoadArray', 'multiarray',
- # from cPickle
- 'dump', 'dumps'
- ]
-
-import numpy.core.multiarray as multiarray
-import numpy.core.umath as um
-from numpy.core.numeric import array, correlate
-import functions
-import sys
-
-from cPickle import dump, dumps
-
-mu = multiarray
-
-#Use this to add a new axis to an array
-#compatibility only
-NewAxis = None
-
-#deprecated
-UFuncType = type(um.sin)
-UfuncType = type(um.sin)
-ArrayType = mu.ndarray
-arraytype = mu.ndarray
-
-LittleEndian = (sys.byteorder == 'little')
-
-from numpy import deprecate
-
-# backward compatibility
-arrayrange = deprecate(functions.arange, 'arrayrange', 'arange')
-
-# deprecated names
-matrixmultiply = deprecate(mu.dot, 'matrixmultiply', 'dot')
-
-def DumpArray(m, fp):
- m.dump(fp)
-
-def LoadArray(fp):
- import cPickle
- return cPickle.load(fp)
-
-def array_constructor(shape, typecode, thestr, Endian=LittleEndian):
- if typecode == "O":
- x = array(thestr, "O")
- else:
- x = mu.fromstring(thestr, typecode)
- x.shape = shape
- if LittleEndian != Endian:
- return x.byteswap(True)
- else:
- return x
-
-def pickle_array(a):
- if a.dtype.hasobject:
- return (array_constructor,
- a.shape, a.dtype.char, a.tolist(), LittleEndian)
- else:
- return (array_constructor,
- (a.shape, a.dtype.char, a.tostring(), LittleEndian))
diff --git a/numpy/oldnumeric/fft.py b/numpy/oldnumeric/fft.py
deleted file mode 100644
index 67f30c750..000000000
--- a/numpy/oldnumeric/fft.py
+++ /dev/null
@@ -1,21 +0,0 @@
-
-__all__ = ['fft', 'fft2d', 'fftnd', 'hermite_fft', 'inverse_fft',
- 'inverse_fft2d', 'inverse_fftnd',
- 'inverse_hermite_fft', 'inverse_real_fft',
- 'inverse_real_fft2d', 'inverse_real_fftnd',
- 'real_fft', 'real_fft2d', 'real_fftnd']
-
-from numpy.fft import fft
-from numpy.fft import fft2 as fft2d
-from numpy.fft import fftn as fftnd
-from numpy.fft import hfft as hermite_fft
-from numpy.fft import ifft as inverse_fft
-from numpy.fft import ifft2 as inverse_fft2d
-from numpy.fft import ifftn as inverse_fftnd
-from numpy.fft import ihfft as inverse_hermite_fft
-from numpy.fft import irfft as inverse_real_fft
-from numpy.fft import irfft2 as inverse_real_fft2d
-from numpy.fft import irfftn as inverse_real_fftnd
-from numpy.fft import rfft as real_fft
-from numpy.fft import rfft2 as real_fft2d
-from numpy.fft import rfftn as real_fftnd
diff --git a/numpy/oldnumeric/fix_default_axis.py b/numpy/oldnumeric/fix_default_axis.py
deleted file mode 100644
index 8483de85e..000000000
--- a/numpy/oldnumeric/fix_default_axis.py
+++ /dev/null
@@ -1,291 +0,0 @@
-"""
-This module adds the default axis argument to code which did not specify it
-for the functions where the default was changed in NumPy.
-
-The functions changed are
-
-add -1 ( all second argument)
-======
-nansum
-nanmax
-nanmin
-nanargmax
-nanargmin
-argmax
-argmin
-compress 3
-
-
-add 0
-======
-take 3
-repeat 3
-sum # might cause problems with builtin.
-product
-sometrue
-alltrue
-cumsum
-cumproduct
-average
-ptp
-cumprod
-prod
-std
-mean
-"""
-__all__ = ['convertfile', 'convertall', 'converttree']
-
-import sys
-import os
-import re
-import glob
-
-
-_args3 = ['compress', 'take', 'repeat']
-_funcm1 = ['nansum', 'nanmax', 'nanmin', 'nanargmax', 'nanargmin',
- 'argmax', 'argmin', 'compress']
-_func0 = ['take', 'repeat', 'sum', 'product', 'sometrue', 'alltrue',
- 'cumsum', 'cumproduct', 'average', 'ptp', 'cumprod', 'prod',
- 'std', 'mean']
-
-_all = _func0 + _funcm1
-func_re = {}
-
-for name in _all:
- _astr = r"""%s\s*[(]"""%name
- func_re[name] = re.compile(_astr)
-
-
-import string
-disallowed = '_' + string.uppercase + string.lowercase + string.digits
-
-def _add_axis(fstr, name, repl):
- alter = 0
- if name in _args3:
- allowed_comma = 1
- else:
- allowed_comma = 0
- newcode = ""
- last = 0
- for obj in func_re[name].finditer(fstr):
- nochange = 0
- start, end = obj.span()
- if fstr[start-1] in disallowed:
- continue
- if fstr[start-1] == '.' \
- and fstr[start-6:start-1] != 'numpy' \
- and fstr[start-2:start-1] != 'N' \
- and fstr[start-9:start-1] != 'numarray' \
- and fstr[start-8:start-1] != 'numerix' \
- and fstr[start-8:start-1] != 'Numeric':
- continue
- if fstr[start-1] in ['\t',' ']:
- k = start-2
- while fstr[k] in ['\t',' ']:
- k -= 1
- if fstr[k-2:k+1] == 'def' or \
- fstr[k-4:k+1] == 'class':
- continue
- k = end
- stack = 1
- ncommas = 0
- N = len(fstr)
- while stack:
- if k>=N:
- nochange =1
- break
- if fstr[k] == ')':
- stack -= 1
- elif fstr[k] == '(':
- stack += 1
- elif stack == 1 and fstr[k] == ',':
- ncommas += 1
- if ncommas > allowed_comma:
- nochange = 1
- break
- k += 1
- if nochange:
- continue
- alter += 1
- newcode = "%s%s,%s)" % (newcode, fstr[last:k-1], repl)
- last = k
- if not alter:
- newcode = fstr
- else:
- newcode = "%s%s" % (newcode, fstr[last:])
- return newcode, alter
-
-def _import_change(fstr, names):
- # Four possibilities
- # 1.) import numpy with subsequent use of numpy.<name>
- # change this to import numpy.oldnumeric as numpy
- # 2.) import numpy as XXXX with subsequent use of
- # XXXX.<name> ==> import numpy.oldnumeric as XXXX
- # 3.) from numpy import *
- # with subsequent use of one of the names
- # 4.) from numpy import ..., <name>, ... (could span multiple
- # lines. ==> remove all names from list and
- # add from numpy.oldnumeric import <name>
-
- num = 0
- # case 1
- importstr = "import numpy"
- ind = fstr.find(importstr)
- if (ind > 0):
- found = 0
- for name in names:
- ind2 = fstr.find("numpy.%s" % name, ind)
- if (ind2 > 0):
- found = 1
- break
- if found:
- fstr = "%s%s%s" % (fstr[:ind], "import numpy.oldnumeric as numpy",
- fstr[ind+len(importstr):])
- num += 1
-
- # case 2
- importre = re.compile("""import numpy as ([A-Za-z0-9_]+)""")
- modules = importre.findall(fstr)
- if len(modules) > 0:
- for module in modules:
- found = 0
- for name in names:
- ind2 = fstr.find("%s.%s" % (module, name))
- if (ind2 > 0):
- found = 1
- break
- if found:
- importstr = "import numpy as %s" % module
- ind = fstr.find(importstr)
- fstr = "%s%s%s" % (fstr[:ind],
- "import numpy.oldnumeric as %s" % module,
- fstr[ind+len(importstr):])
- num += 1
-
- # case 3
- importstr = "from numpy import *"
- ind = fstr.find(importstr)
- if (ind > 0):
- found = 0
- for name in names:
- ind2 = fstr.find(name, ind)
- if (ind2 > 0) and fstr[ind2-1] not in disallowed:
- found = 1
- break
- if found:
- fstr = "%s%s%s" % (fstr[:ind],
- "from numpy.oldnumeric import *",
- fstr[ind+len(importstr):])
- num += 1
-
- # case 4
- ind = 0
- importstr = "from numpy import"
- N = len(importstr)
- while 1:
- ind = fstr.find(importstr, ind)
- if (ind < 0):
- break
- ind += N
- ptr = ind+1
- stack = 1
- while stack:
- if fstr[ptr] == '\\':
- stack += 1
- elif fstr[ptr] == '\n':
- stack -= 1
- ptr += 1
- substr = fstr[ind:ptr]
- found = 0
- substr = substr.replace('\n',' ')
- substr = substr.replace('\\','')
- importnames = [x.strip() for x in substr.split(',')]
- # determine if any of names are in importnames
- addnames = []
- for name in names:
- if name in importnames:
- importnames.remove(name)
- addnames.append(name)
- if len(addnames) > 0:
- fstr = "%s%s\n%s\n%s" % \
- (fstr[:ind],
- "from numpy import %s" % \
- ", ".join(importnames),
- "from numpy.oldnumeric import %s" % \
- ", ".join(addnames),
- fstr[ptr:])
- num += 1
-
- return fstr, num
-
-def add_axis(fstr, import_change=False):
- total = 0
- if not import_change:
- for name in _funcm1:
- fstr, num = _add_axis(fstr, name, 'axis=-1')
- total += num
- for name in _func0:
- fstr, num = _add_axis(fstr, name, 'axis=0')
- total += num
- return fstr, total
- else:
- fstr, num = _import_change(fstr, _funcm1+_func0)
- return fstr, num
-
-
-def makenewfile(name, filestr):
- fid = file(name, 'w')
- fid.write(filestr)
- fid.close()
-
-def getfile(name):
- fid = file(name)
- filestr = fid.read()
- fid.close()
- return filestr
-
-def copyfile(name, fstr):
- base, ext = os.path.splitext(name)
- makenewfile(base+'.orig', fstr)
- return
-
-def convertfile(filename, import_change=False):
- """Convert the filename given from using Numeric to using NumPy
-
- Copies the file to filename.orig and then over-writes the file
- with the updated code
- """
- filestr = getfile(filename)
- newstr, total = add_axis(filestr, import_change)
- if total > 0:
- print "Changing ", filename
- copyfile(filename, filestr)
- makenewfile(filename, newstr)
- sys.stdout.flush()
-
-def fromargs(args):
- filename = args[1]
- convertfile(filename)
-
-def convertall(direc=os.path.curdir, import_change=False):
- """Convert all .py files in the directory given
-
- For each file, a backup of <usesnumeric>.py is made as
- <usesnumeric>.py.orig. A new file named <usesnumeric>.py
- is then written with the updated code.
- """
- files = glob.glob(os.path.join(direc,'*.py'))
- for afile in files:
- convertfile(afile, import_change)
-
-def _func(arg, dirname, fnames):
- convertall(dirname, import_change=arg)
-
-def converttree(direc=os.path.curdir, import_change=False):
- """Convert all .py files in the tree given
-
- """
- os.path.walk(direc, _func, import_change)
-
-if __name__ == '__main__':
- fromargs(sys.argv)
diff --git a/numpy/oldnumeric/functions.py b/numpy/oldnumeric/functions.py
deleted file mode 100644
index 1f09d8f84..000000000
--- a/numpy/oldnumeric/functions.py
+++ /dev/null
@@ -1,124 +0,0 @@
-# Functions that should behave the same as Numeric and need changing
-
-import numpy as N
-import numpy.core.multiarray as mu
-import numpy.core.numeric as nn
-from typeconv import convtypecode, convtypecode2
-
-__all__ = ['take', 'repeat', 'sum', 'product', 'sometrue', 'alltrue',
- 'cumsum', 'cumproduct', 'compress', 'fromfunction',
- 'ones', 'empty', 'identity', 'zeros', 'array', 'asarray',
- 'nonzero', 'reshape', 'arange', 'fromstring', 'ravel', 'trace',
- 'indices', 'where','sarray','cross_product', 'argmax', 'argmin',
- 'average']
-
-def take(a, indicies, axis=0):
- return N.take(a, indicies, axis)
-
-def repeat(a, repeats, axis=0):
- return N.repeat(a, repeats, axis)
-
-def sum(x, axis=0):
- return N.sum(x, axis)
-
-def product(x, axis=0):
- return N.product(x, axis)
-
-def sometrue(x, axis=0):
- return N.sometrue(x, axis)
-
-def alltrue(x, axis=0):
- return N.alltrue(x, axis)
-
-def cumsum(x, axis=0):
- return N.cumsum(x, axis)
-
-def cumproduct(x, axis=0):
- return N.cumproduct(x, axis)
-
-def argmax(x, axis=-1):
- return N.argmax(x, axis)
-
-def argmin(x, axis=-1):
- return N.argmin(x, axis)
-
-def compress(condition, m, axis=-1):
- return N.compress(condition, m, axis)
-
-def fromfunction(args, dimensions):
- return N.fromfunction(args, dimensions, dtype=int)
-
-def ones(shape, typecode='l', savespace=0, dtype=None):
- """ones(shape, dtype=int) returns an array of the given
- dimensions which is initialized to all ones.
- """
- dtype = convtypecode(typecode,dtype)
- a = mu.empty(shape, dtype)
- a.fill(1)
- return a
-
-def zeros(shape, typecode='l', savespace=0, dtype=None):
- """zeros(shape, dtype=int) returns an array of the given
- dimensions which is initialized to all zeros
- """
- dtype = convtypecode(typecode,dtype)
- return mu.zeros(shape, dtype)
-
-def identity(n,typecode='l', dtype=None):
- """identity(n) returns the identity 2-d array of shape n x n.
- """
- dtype = convtypecode(typecode, dtype)
- return nn.identity(n, dtype)
-
-def empty(shape, typecode='l', dtype=None):
- dtype = convtypecode(typecode, dtype)
- return mu.empty(shape, dtype)
-
-def array(sequence, typecode=None, copy=1, savespace=0, dtype=None):
- dtype = convtypecode2(typecode, dtype)
- return mu.array(sequence, dtype, copy=copy)
-
-def sarray(a, typecode=None, copy=False, dtype=None):
- dtype = convtypecode2(typecode, dtype)
- return mu.array(a, dtype, copy)
-
-def asarray(a, typecode=None, dtype=None):
- dtype = convtypecode2(typecode, dtype)
- return mu.array(a, dtype, copy=0)
-
-def nonzero(a):
- res = N.nonzero(a)
- if len(res) == 1:
- return res[0]
- else:
- raise ValueError, "Input argument must be 1d"
-
-def reshape(a, shape):
- return N.reshape(a, shape)
-
-def arange(start, stop=None, step=1, typecode=None, dtype=None):
- dtype = convtypecode2(typecode, dtype)
- return mu.arange(start, stop, step, dtype)
-
-def fromstring(string, typecode='l', count=-1, dtype=None):
- dtype = convtypecode(typecode, dtype)
- return mu.fromstring(string, dtype, count=count)
-
-def ravel(m):
- return N.ravel(m)
-
-def trace(a, offset=0, axis1=0, axis2=1):
- return N.trace(a, offset=0, axis1=0, axis2=1)
-
-def indices(dimensions, typecode=None, dtype=None):
- dtype = convtypecode(typecode, dtype)
- return N.indices(dimensions, dtype)
-
-def where(condition, x, y):
- return N.where(condition, x, y)
-
-def cross_product(a, b, axis1=-1, axis2=-1):
- return N.cross(a, b, axis1, axis2)
-
-def average(a, axis=0, weights=None, returned=False):
- return N.average(a, axis, weights, returned)
diff --git a/numpy/oldnumeric/linear_algebra.py b/numpy/oldnumeric/linear_algebra.py
deleted file mode 100644
index 2e7a264fe..000000000
--- a/numpy/oldnumeric/linear_algebra.py
+++ /dev/null
@@ -1,83 +0,0 @@
-"""Backward compatible with LinearAlgebra from Numeric
-"""
-# This module is a lite version of the linalg.py module in SciPy which contains
-# high-level Python interface to the LAPACK library. The lite version
-# only accesses the following LAPACK functions: dgesv, zgesv, dgeev,
-# zgeev, dgesdd, zgesdd, dgelsd, zgelsd, dsyevd, zheevd, dgetrf, dpotrf.
-
-
-__all__ = ['LinAlgError', 'solve_linear_equations',
- 'inverse', 'cholesky_decomposition', 'eigenvalues',
- 'Heigenvalues', 'generalized_inverse',
- 'determinant', 'singular_value_decomposition',
- 'eigenvectors', 'Heigenvectors',
- 'linear_least_squares'
- ]
-
-from numpy.core import transpose
-import numpy.linalg as linalg
-
-# Linear equations
-
-LinAlgError = linalg.LinAlgError
-
-def solve_linear_equations(a, b):
- return linalg.solve(a,b)
-
-# Matrix inversion
-
-def inverse(a):
- return linalg.inv(a)
-
-# Cholesky decomposition
-
-def cholesky_decomposition(a):
- return linalg.cholesky(a)
-
-# Eigenvalues
-
-def eigenvalues(a):
- return linalg.eigvals(a)
-
-def Heigenvalues(a, UPLO='L'):
- return linalg.eigvalsh(a,UPLO)
-
-# Eigenvectors
-
-def eigenvectors(A):
- w, v = linalg.eig(A)
- return w, transpose(v)
-
-def Heigenvectors(A):
- w, v = linalg.eigh(A)
- return w, transpose(v)
-
-# Generalized inverse
-
-def generalized_inverse(a, rcond = 1.e-10):
- return linalg.pinv(a, rcond)
-
-# Determinant
-
-def determinant(a):
- return linalg.det(a)
-
-# Linear Least Squares
-
-def linear_least_squares(a, b, rcond=1.e-10):
- """returns x,resids,rank,s
-where x minimizes 2-norm(|b - Ax|)
- resids is the sum square residuals
- rank is the rank of A
- s is the rank of the singular values of A in descending order
-
-If b is a matrix then x is also a matrix with corresponding columns.
-If the rank of A is less than the number of columns of A or greater than
-the number of rows, then residuals will be returned as an empty array
-otherwise resids = sum((b-dot(A,x)**2).
-Singular values less than s[0]*rcond are treated as zero.
-"""
- return linalg.lstsq(a,b,rcond)
-
-def singular_value_decomposition(A, full_matrices=0):
- return linalg.svd(A, full_matrices)
diff --git a/numpy/oldnumeric/ma.py b/numpy/oldnumeric/ma.py
deleted file mode 100644
index 601ff88af..000000000
--- a/numpy/oldnumeric/ma.py
+++ /dev/null
@@ -1,14 +0,0 @@
-# Incompatibility in that getmask and a.mask returns nomask
-# instead of None
-
-from numpy.core.ma import *
-import numpy.core.ma as nca
-
-def repeat(a, repeats, axis=0):
- return nca.repeat(a, repeats, axis)
-
-def average(a, axis=0, weights=None, returned=0):
- return nca.average(a, axis, weights, returned)
-
-def take(a, indices, axis=0):
- return nca.average(a, indices, axis=0)
diff --git a/numpy/oldnumeric/matrix.py b/numpy/oldnumeric/matrix.py
deleted file mode 100644
index 5f8c1ca5e..000000000
--- a/numpy/oldnumeric/matrix.py
+++ /dev/null
@@ -1,67 +0,0 @@
-# This module is for compatibility only.
-
-__all__ = ['UserArray', 'squeeze', 'Matrix', 'asarray', 'dot', 'k', 'Numeric', 'LinearAlgebra', 'identity', 'multiply', 'types', 'string']
-
-import types
-from user_array import UserArray, asarray
-import numpy.oldnumeric as Numeric
-from numpy.oldnumeric import dot, identity, multiply
-import numpy.oldnumeric.linear_algebra as LinearAlgebra
-from numpy import matrix as Matrix, squeeze
-
-# Hidden names that will be the same.
-
-_table = [None]*256
-for k in range(256):
- _table[k] = chr(k)
-_table = ''.join(_table)
-
-_numchars = '0123456789.-+jeEL'
-_todelete = []
-for k in _table:
- if k not in _numchars:
- _todelete.append(k)
-_todelete = ''.join(_todelete)
-
-
-def _eval(astr):
- return eval(astr.translate(_table,_todelete))
-
-def _convert_from_string(data):
- data.find
- rows = data.split(';')
- newdata = []
- count = 0
- for row in rows:
- trow = row.split(',')
- newrow = []
- for col in trow:
- temp = col.split()
- newrow.extend(map(_eval,temp))
- if count == 0:
- Ncols = len(newrow)
- elif len(newrow) != Ncols:
- raise ValueError, "Rows not the same size."
- count += 1
- newdata.append(newrow)
- return newdata
-
-
-_lkup = {'0':'000',
- '1':'001',
- '2':'010',
- '3':'011',
- '4':'100',
- '5':'101',
- '6':'110',
- '7':'111'}
-
-def _binary(num):
- ostr = oct(num)
- bin = ''
- for ch in ostr[1:]:
- bin += _lkup[ch]
- ind = 0
- while bin[ind] == '0':
- ind += 1
- return bin[ind:]
diff --git a/numpy/oldnumeric/misc.py b/numpy/oldnumeric/misc.py
deleted file mode 100644
index 4b43f3985..000000000
--- a/numpy/oldnumeric/misc.py
+++ /dev/null
@@ -1,42 +0,0 @@
-# Functions that already have the correct syntax or miscellaneous functions
-
-
-__all__ = ['load', 'sort', 'copy_reg', 'clip', 'Unpickler', 'rank',
- 'sign', 'shape', 'types', 'allclose', 'size',
- 'choose', 'swapaxes', 'array_str',
- 'pi', 'math', 'concatenate', 'putmask', 'put',
- 'around', 'vdot', 'transpose', 'array2string', 'diagonal',
- 'searchsorted', 'copy', 'resize',
- 'array_repr', 'e', 'StringIO', 'pickle',
- 'argsort', 'convolve', 'loads', 'cross_correlate',
- 'Pickler', 'dot', 'outerproduct', 'innerproduct', 'insert']
-
-import types
-import StringIO
-import pickle
-import math
-import copy
-import copy_reg
-from pickle import load, loads
-
-from numpy import sort, clip, rank, sign, shape, putmask, allclose, size,\
- choose, swapaxes, array_str, array_repr, e, pi, put, \
- resize, around, concatenate, vdot, transpose, \
- diagonal, searchsorted, argsort, convolve, dot, \
- outer as outerproduct, inner as innerproduct, correlate as cross_correlate, \
- place as insert
-
-from array_printer import array2string
-
-
-class Unpickler(pickle.Unpickler):
- def __init__(self, *args, **kwds):
- raise NotImplemented
- def load_array(self):
- raise NotImplemented
-
-class Pickler(pickle.Pickler):
- def __init__(self, *args, **kwds):
- raise NotImplemented
- def save_array(self, object):
- raise NotImplemented
diff --git a/numpy/oldnumeric/mlab.py b/numpy/oldnumeric/mlab.py
deleted file mode 100644
index 47be89e1b..000000000
--- a/numpy/oldnumeric/mlab.py
+++ /dev/null
@@ -1,122 +0,0 @@
-# This module is for compatibility only. All functions are defined elsewhere.
-
-__all__ = ['rand', 'tril', 'trapz', 'hanning', 'rot90', 'triu', 'diff', 'angle', 'roots', 'ptp', 'kaiser', 'randn', 'cumprod', 'diag', 'msort', 'LinearAlgebra', 'RandomArray', 'prod', 'std', 'hamming', 'flipud', 'max', 'blackman', 'corrcoef', 'bartlett', 'eye', 'squeeze', 'sinc', 'tri', 'cov', 'svd', 'min', 'median', 'fliplr', 'eig', 'mean']
-
-import numpy.oldnumeric.linear_algebra as LinearAlgebra
-import numpy.oldnumeric.random_array as RandomArray
-from numpy import tril, trapz as _Ntrapz, hanning, rot90, triu, diff, \
- angle, roots, ptp as _Nptp, kaiser, cumprod as _Ncumprod, \
- diag, msort, prod as _Nprod, std as _Nstd, hamming, flipud, \
- amax as _Nmax, amin as _Nmin, blackman, bartlett, \
- squeeze, sinc, median, fliplr, mean as _Nmean, transpose
-
-from numpy.linalg import eig, svd
-from numpy.random import rand, randn
-import numpy as nn
-
-from typeconv import convtypecode
-
-def eye(N, M=None, k=0, typecode=None, dtype=None):
- """ eye returns a N-by-M 2-d array where the k-th diagonal is all ones,
- and everything else is zeros.
- """
- dtype = convtypecode(typecode, dtype)
- if M is None: M = N
- m = nn.equal(nn.subtract.outer(nn.arange(N), nn.arange(M)),-k)
- if m.dtype != dtype:
- return m.astype(dtype)
-
-def tri(N, M=None, k=0, typecode=None, dtype=None):
- """ returns a N-by-M array where all the diagonals starting from
- lower left corner up to the k-th are all ones.
- """
- dtype = convtypecode(typecode, dtype)
- if M is None: M = N
- m = nn.greater_equal(nn.subtract.outer(nn.arange(N), nn.arange(M)),-k)
- if m.dtype != dtype:
- return m.astype(dtype)
-
-def trapz(y, x=None, axis=-1):
- return _Ntrapz(y, x, axis=axis)
-
-def ptp(x, axis=0):
- return _Nptp(x, axis)
-
-def cumprod(x, axis=0):
- return _Ncumprod(x, axis)
-
-def max(x, axis=0):
- return _Nmax(x, axis)
-
-def min(x, axis=0):
- return _Nmin(x, axis)
-
-def prod(x, axis=0):
- return _Nprod(x, axis)
-
-def std(x, axis=0):
- N = asarray(x).shape[axis]
- return _Nstd(x, axis)*sqrt(N/(N-1.))
-
-def mean(x, axis=0):
- return _Nmean(x, axis)
-
-# This is exactly the same cov function as in MLab
-def cov(m, y=None, rowvar=0, bias=0):
- if y is None:
- y = m
- else:
- y = y
- if rowvar:
- m = transpose(m)
- y = transpose(y)
- if (m.shape[0] == 1):
- m = transpose(m)
- if (y.shape[0] == 1):
- y = transpose(y)
- N = m.shape[0]
- if (y.shape[0] != N):
- raise ValueError, "x and y must have the same number "\
- "of observations"
- m = m - _Nmean(m,axis=0)
- y = y - _Nmean(y,axis=0)
- if bias:
- fact = N*1.0
- else:
- fact = N-1.0
- return squeeze(dot(transpose(m), conjugate(y)) / fact)
-
-from numpy import sqrt, multiply
-def corrcoef(x, y=None):
- c = cov(x,y)
- d = diag(c)
- return c/sqrt(multiply.outer(d,d))
-
-from compat import *
-from functions import *
-from precision import *
-from ufuncs import *
-from misc import *
-
-import compat
-import precision
-import functions
-import misc
-import ufuncs
-
-import numpy
-__version__ = numpy.__version__
-del numpy
-
-__all__ += ['__version__']
-__all__ += compat.__all__
-__all__ += precision.__all__
-__all__ += functions.__all__
-__all__ += ufuncs.__all__
-__all__ += misc.__all__
-
-del compat
-del functions
-del precision
-del ufuncs
-del misc
diff --git a/numpy/oldnumeric/precision.py b/numpy/oldnumeric/precision.py
deleted file mode 100644
index 51dd77454..000000000
--- a/numpy/oldnumeric/precision.py
+++ /dev/null
@@ -1,169 +0,0 @@
-# Lifted from Precision.py. This is for compatibility only.
-#
-# The character strings are still for "new" NumPy
-# which is the only Incompatibility with Numeric
-
-__all__ = ['Character', 'Complex', 'Float',
- 'PrecisionError', 'PyObject', 'Int', 'UInt',
- 'UnsignedInteger', 'string', 'typecodes', 'zeros']
-
-from functions import zeros
-import string # for backwards compatibility
-
-typecodes = {'Character':'c', 'Integer':'bhil', 'UnsignedInteger':'BHI', 'Float':'fd', 'Complex':'FD'}
-
-def _get_precisions(typecodes):
- lst = []
- for t in typecodes:
- lst.append( (zeros( (1,), t ).itemsize*8, t) )
- return lst
-
-def _fill_table(typecodes, table={}):
- for key, value in typecodes.items():
- table[key] = _get_precisions(value)
- return table
-
-_code_table = _fill_table(typecodes)
-
-class PrecisionError(Exception):
- pass
-
-def _lookup(table, key, required_bits):
- lst = table[key]
- for bits, typecode in lst:
- if bits >= required_bits:
- return typecode
- raise PrecisionError, key+" of "+str(required_bits)+" bits not available on this system"
-
-Character = 'c'
-
-try:
- UnsignedInt8 = _lookup(_code_table, "UnsignedInteger", 8)
- UInt8 = UnsignedInt8
- __all__.extend(['UnsignedInt8', 'UInt8'])
-except(PrecisionError):
- pass
-try:
- UnsignedInt16 = _lookup(_code_table, "UnsignedInteger", 16)
- UInt16 = UnsignedInt16
- __all__.extend(['UnsignedInt16', 'UInt16'])
-except(PrecisionError):
- pass
-try:
- UnsignedInt32 = _lookup(_code_table, "UnsignedInteger", 32)
- UInt32 = UnsignedInt32
- __all__.extend(['UnsignedInt32', 'UInt32'])
-except(PrecisionError):
- pass
-try:
- UnsignedInt64 = _lookup(_code_table, "UnsignedInteger", 64)
- UInt64 = UnsignedInt64
- __all__.extend(['UnsignedInt64', 'UInt64'])
-except(PrecisionError):
- pass
-try:
- UnsignedInt128 = _lookup(_code_table, "UnsignedInteger", 128)
- UInt128 = UnsignedInt128
- __all__.extend(['UnsignedInt128', 'UInt128'])
-except(PrecisionError):
- pass
-UnsignedInteger = 'u'
-UInt = UnsignedInteger
-
-try:
- Int0 = _lookup(_code_table, 'Integer', 0)
- __all__.append('Int0')
-except(PrecisionError):
- pass
-try:
- Int8 = _lookup(_code_table, 'Integer', 8)
- __all__.append('Int8')
-except(PrecisionError):
- pass
-try:
- Int16 = _lookup(_code_table, 'Integer', 16)
- __all__.append('Int16')
-except(PrecisionError):
- pass
-try:
- Int32 = _lookup(_code_table, 'Integer', 32)
- __all__.append('Int32')
-except(PrecisionError):
- pass
-try:
- Int64 = _lookup(_code_table, 'Integer', 64)
- __all__.append('Int64')
-except(PrecisionError):
- pass
-try:
- Int128 = _lookup(_code_table, 'Integer', 128)
- __all__.append('Int128')
-except(PrecisionError):
- pass
-Int = 'l'
-
-try:
- Float0 = _lookup(_code_table, 'Float', 0)
- __all__.append('Float0')
-except(PrecisionError):
- pass
-try:
- Float8 = _lookup(_code_table, 'Float', 8)
- __all__.append('Float8')
-except(PrecisionError):
- pass
-try:
- Float16 = _lookup(_code_table, 'Float', 16)
- __all__.append('Float16')
-except(PrecisionError):
- pass
-try:
- Float32 = _lookup(_code_table, 'Float', 32)
- __all__.append('Float32')
-except(PrecisionError):
- pass
-try:
- Float64 = _lookup(_code_table, 'Float', 64)
- __all__.append('Float64')
-except(PrecisionError):
- pass
-try:
- Float128 = _lookup(_code_table, 'Float', 128)
- __all__.append('Float128')
-except(PrecisionError):
- pass
-Float = 'd'
-
-try:
- Complex0 = _lookup(_code_table, 'Complex', 0)
- __all__.append('Complex0')
-except(PrecisionError):
- pass
-try:
- Complex8 = _lookup(_code_table, 'Complex', 16)
- __all__.append('Complex8')
-except(PrecisionError):
- pass
-try:
- Complex16 = _lookup(_code_table, 'Complex', 32)
- __all__.append('Complex16')
-except(PrecisionError):
- pass
-try:
- Complex32 = _lookup(_code_table, 'Complex', 64)
- __all__.append('Complex32')
-except(PrecisionError):
- pass
-try:
- Complex64 = _lookup(_code_table, 'Complex', 128)
- __all__.append('Complex64')
-except(PrecisionError):
- pass
-try:
- Complex128 = _lookup(_code_table, 'Complex', 256)
- __all__.append('Complex128')
-except(PrecisionError):
- pass
-Complex = 'D'
-
-PyObject = 'O'
diff --git a/numpy/oldnumeric/random_array.py b/numpy/oldnumeric/random_array.py
deleted file mode 100644
index 73564811d..000000000
--- a/numpy/oldnumeric/random_array.py
+++ /dev/null
@@ -1,266 +0,0 @@
-# Backward compatible module for RandomArray
-
-__all__ = ['ArgumentError','F','beta','binomial','chi_square', 'exponential',
- 'gamma', 'get_seed', 'mean_var_test', 'multinomial',
- 'multivariate_normal', 'negative_binomial', 'noncentral_F',
- 'noncentral_chi_square', 'normal', 'permutation', 'poisson',
- 'randint', 'random', 'random_integers', 'seed', 'standard_normal',
- 'uniform']
-
-ArgumentError = ValueError
-
-import numpy.random.mtrand as mt
-import numpy as Numeric
-
-def seed(x=0, y=0):
- if (x == 0 or y == 0):
- mt.seed()
- else:
- mt.seed((x,y))
-
-def get_seed():
- raise NotImplementedError, \
- "If you want to save the state of the random number generator.\n"\
- "Then you should use obj = numpy.random.get_state() followed by.\n"\
- "numpy.random.set_state(obj)."
-
-def random(shape=[]):
- "random(n) or random([n, m, ...]) returns array of random numbers"
- if shape == []:
- shape = None
- return mt.random_sample(shape)
-
-def uniform(minimum, maximum, shape=[]):
- """uniform(minimum, maximum, shape=[]) returns array of given shape of random reals
- in given range"""
- if shape == []:
- shape = None
- return mt.uniform(minimum, maximum, shape)
-
-def randint(minimum, maximum=None, shape=[]):
- """randint(min, max, shape=[]) = random integers >=min, < max
- If max not given, random integers >= 0, <min"""
- if not isinstance(minimum, int):
- raise ArgumentError, "randint requires first argument integer"
- if maximum is None:
- maximum = minimum
- minimum = 0
- if not isinstance(maximum, int):
- raise ArgumentError, "randint requires second argument integer"
- a = ((maximum-minimum)* random(shape))
- if isinstance(a, Numeric.ndarray):
- return minimum + a.astype(Numeric.int)
- else:
- return minimum + int(a)
-
-def random_integers(maximum, minimum=1, shape=[]):
- """random_integers(max, min=1, shape=[]) = random integers in range min-max inclusive"""
- return randint(minimum, maximum+1, shape)
-
-def permutation(n):
- "permutation(n) = a permutation of indices range(n)"
- return mt.permutation(n)
-
-def standard_normal(shape=[]):
- """standard_normal(n) or standard_normal([n, m, ...]) returns array of
- random numbers normally distributed with mean 0 and standard
- deviation 1"""
- if shape == []:
- shape = None
- return mt.standard_normal(shape)
-
-def normal(mean, std, shape=[]):
- """normal(mean, std, n) or normal(mean, std, [n, m, ...]) returns
- array of random numbers randomly distributed with specified mean and
- standard deviation"""
- if shape == []:
- shape = None
- return mt.normal(mean, std, shape)
-
-def multivariate_normal(mean, cov, shape=[]):
- """multivariate_normal(mean, cov) or multivariate_normal(mean, cov, [m, n, ...])
- returns an array containing multivariate normally distributed random numbers
- with specified mean and covariance.
-
- mean must be a 1 dimensional array. cov must be a square two dimensional
- array with the same number of rows and columns as mean has elements.
-
- The first form returns a single 1-D array containing a multivariate
- normal.
-
- The second form returns an array of shape (m, n, ..., cov.shape[0]).
- In this case, output[i,j,...,:] is a 1-D array containing a multivariate
- normal."""
- if shape == []:
- shape = None
- return mt.multivariate_normal(mean, cov, shape)
-
-def exponential(mean, shape=[]):
- """exponential(mean, n) or exponential(mean, [n, m, ...]) returns array
- of random numbers exponentially distributed with specified mean"""
- if shape == []:
- shape = None
- return mt.exponential(mean, shape)
-
-def beta(a, b, shape=[]):
- """beta(a, b) or beta(a, b, [n, m, ...]) returns array of beta distributed random numbers."""
- if shape == []:
- shape = None
- return mt.beta(a, b, shape)
-
-def gamma(a, r, shape=[]):
- """gamma(a, r) or gamma(a, r, [n, m, ...]) returns array of gamma distributed random numbers."""
- if shape == []:
- shape = None
- return mt.gamma(a, r, shape)
-
-def F(dfn, dfd, shape=[]):
- """F(dfn, dfd) or F(dfn, dfd, [n, m, ...]) returns array of F distributed random numbers with dfn degrees of freedom in the numerator and dfd degrees of freedom in the denominator."""
- if shape == []:
- shape = None
- return mt.f(dfn, dfd, shape)
-
-def noncentral_F(dfn, dfd, nconc, shape=[]):
- """noncentral_F(dfn, dfd, nonc) or noncentral_F(dfn, dfd, nonc, [n, m, ...]) returns array of noncentral F distributed random numbers with dfn degrees of freedom in the numerator and dfd degrees of freedom in the denominator, and noncentrality parameter nconc."""
- if shape == []:
- shape = None
- return mt.noncentral_f(dfn, dfd, nconc, shape)
-
-def chi_square(df, shape=[]):
- """chi_square(df) or chi_square(df, [n, m, ...]) returns array of chi squared distributed random numbers with df degrees of freedom."""
- if shape == []:
- shape = None
- return mt.chisquare(df, shape)
-
-def noncentral_chi_square(df, nconc, shape=[]):
- """noncentral_chi_square(df, nconc) or chi_square(df, nconc, [n, m, ...]) returns array of noncentral chi squared distributed random numbers with df degrees of freedom and noncentrality parameter."""
- if shape == []:
- shape = None
- return mt.noncentral_chisquare(df, nconc, shape)
-
-def binomial(trials, p, shape=[]):
- """binomial(trials, p) or binomial(trials, p, [n, m, ...]) returns array of binomially distributed random integers.
-
- trials is the number of trials in the binomial distribution.
- p is the probability of an event in each trial of the binomial distribution."""
- if shape == []:
- shape = None
- return mt.binomial(trials, p, shape)
-
-def negative_binomial(trials, p, shape=[]):
- """negative_binomial(trials, p) or negative_binomial(trials, p, [n, m, ...]) returns
- array of negative binomially distributed random integers.
-
- trials is the number of trials in the negative binomial distribution.
- p is the probability of an event in each trial of the negative binomial distribution."""
- if shape == []:
- shape = None
- return mt.negative_binomial(trials, p, shape)
-
-def multinomial(trials, probs, shape=[]):
- """multinomial(trials, probs) or multinomial(trials, probs, [n, m, ...]) returns
- array of multinomial distributed integer vectors.
-
- trials is the number of trials in each multinomial distribution.
- probs is a one dimensional array. There are len(prob)+1 events.
- prob[i] is the probability of the i-th event, 0<=i<len(prob).
- The probability of event len(prob) is 1.-Numeric.sum(prob).
-
- The first form returns a single 1-D array containing one multinomially
- distributed vector.
-
- The second form returns an array of shape (m, n, ..., len(probs)).
- In this case, output[i,j,...,:] is a 1-D array containing a multinomially
- distributed integer 1-D array."""
- if shape == []:
- shape = None
- return mt.multinomial(trials, probs, shape)
-
-def poisson(mean, shape=[]):
- """poisson(mean) or poisson(mean, [n, m, ...]) returns array of poisson
- distributed random integers with specified mean."""
- if shape == []:
- shape = None
- return mt.poisson(mean, shape)
-
-
-def mean_var_test(x, type, mean, var, skew=[]):
- n = len(x) * 1.0
- x_mean = Numeric.sum(x,axis=0)/n
- x_minus_mean = x - x_mean
- x_var = Numeric.sum(x_minus_mean*x_minus_mean,axis=0)/(n-1.0)
- print "\nAverage of ", len(x), type
- print "(should be about ", mean, "):", x_mean
- print "Variance of those random numbers (should be about ", var, "):", x_var
- if skew != []:
- x_skew = (Numeric.sum(x_minus_mean*x_minus_mean*x_minus_mean,axis=0)/9998.)/x_var**(3./2.)
- print "Skewness of those random numbers (should be about ", skew, "):", x_skew
-
-def test():
- obj = mt.get_state()
- mt.set_state(obj)
- obj2 = mt.get_state()
- if (obj2[1] - obj[1]).any():
- raise SystemExit, "Failed seed test."
- print "First random number is", random()
- print "Average of 10000 random numbers is", Numeric.sum(random(10000),axis=0)/10000.
- x = random([10,1000])
- if len(x.shape) != 2 or x.shape[0] != 10 or x.shape[1] != 1000:
- raise SystemExit, "random returned wrong shape"
- x.shape = (10000,)
- print "Average of 100 by 100 random numbers is", Numeric.sum(x,axis=0)/10000.
- y = uniform(0.5,0.6, (1000,10))
- if len(y.shape) !=2 or y.shape[0] != 1000 or y.shape[1] != 10:
- raise SystemExit, "uniform returned wrong shape"
- y.shape = (10000,)
- if Numeric.minimum.reduce(y) <= 0.5 or Numeric.maximum.reduce(y) >= 0.6:
- raise SystemExit, "uniform returned out of desired range"
- print "randint(1, 10, shape=[50])"
- print randint(1, 10, shape=[50])
- print "permutation(10)", permutation(10)
- print "randint(3,9)", randint(3,9)
- print "random_integers(10, shape=[20])"
- print random_integers(10, shape=[20])
- s = 3.0
- x = normal(2.0, s, [10, 1000])
- if len(x.shape) != 2 or x.shape[0] != 10 or x.shape[1] != 1000:
- raise SystemExit, "standard_normal returned wrong shape"
- x.shape = (10000,)
- mean_var_test(x, "normally distributed numbers with mean 2 and variance %f"%(s**2,), 2, s**2, 0)
- x = exponential(3, 10000)
- mean_var_test(x, "random numbers exponentially distributed with mean %f"%(s,), s, s**2, 2)
- x = multivariate_normal(Numeric.array([10,20]), Numeric.array(([1,2],[2,4])))
- print "\nA multivariate normal", x
- if x.shape != (2,): raise SystemExit, "multivariate_normal returned wrong shape"
- x = multivariate_normal(Numeric.array([10,20]), Numeric.array([[1,2],[2,4]]), [4,3])
- print "A 4x3x2 array containing multivariate normals"
- print x
- if x.shape != (4,3,2): raise SystemExit, "multivariate_normal returned wrong shape"
- x = multivariate_normal(Numeric.array([-100,0,100]), Numeric.array([[3,2,1],[2,2,1],[1,1,1]]), 10000)
- x_mean = Numeric.sum(x,axis=0)/10000.
- print "Average of 10000 multivariate normals with mean [-100,0,100]"
- print x_mean
- x_minus_mean = x - x_mean
- print "Estimated covariance of 10000 multivariate normals with covariance [[3,2,1],[2,2,1],[1,1,1]]"
- print Numeric.dot(Numeric.transpose(x_minus_mean),x_minus_mean)/9999.
- x = beta(5.0, 10.0, 10000)
- mean_var_test(x, "beta(5.,10.) random numbers", 0.333, 0.014)
- x = gamma(.01, 2., 10000)
- mean_var_test(x, "gamma(.01,2.) random numbers", 2*100, 2*100*100)
- x = chi_square(11., 10000)
- mean_var_test(x, "chi squared random numbers with 11 degrees of freedom", 11, 22, 2*Numeric.sqrt(2./11.))
- x = F(5., 10., 10000)
- mean_var_test(x, "F random numbers with 5 and 10 degrees of freedom", 1.25, 1.35)
- x = poisson(50., 10000)
- mean_var_test(x, "poisson random numbers with mean 50", 50, 50, 0.14)
- print "\nEach element is the result of 16 binomial trials with probability 0.5:"
- print binomial(16, 0.5, 16)
- print "\nEach element is the result of 16 negative binomial trials with probability 0.5:"
- print negative_binomial(16, 0.5, [16,])
- print "\nEach row is the result of 16 multinomial trials with probabilities [0.1, 0.5, 0.1 0.3]:"
- x = multinomial(16, [0.1, 0.5, 0.1], 8)
- print x
- print "Mean = ", Numeric.sum(x,axis=0)/8.
-
-if __name__ == '__main__':
- test()
diff --git a/numpy/oldnumeric/rng.py b/numpy/oldnumeric/rng.py
deleted file mode 100644
index fcf08bb37..000000000
--- a/numpy/oldnumeric/rng.py
+++ /dev/null
@@ -1,135 +0,0 @@
-# This module re-creates the RNG interface from Numeric
-# Replace import RNG with import numpy.oldnumeric.rng as RNG
-#
-# It is for backwards compatibility only.
-
-
-__all__ = ['CreateGenerator','ExponentialDistribution','LogNormalDistribution','NormalDistribution',
- 'UniformDistribution', 'error', 'default_distribution', 'random_sample', 'ranf',
- 'standard_generator']
-
-import numpy.random.mtrand as mt
-import math
-
-class error(Exception):
- pass
-
-class Distribution(object):
- def __init__(self, meth, *args):
- self._meth = meth
- self._args = args
-
- def density(self,x):
- raise NotImplementedError
-
- def __call__(self, x):
- return self.density(x)
-
- def _onesample(self, rng):
- return getattr(rng, self._meth)(*self._args)
-
- def _sample(self, rng, n):
- kwds = {'size' : n}
- return getattr(rng, self._meth)(*self._args, **kwds)
-
-
-class ExponentialDistribution(Distribution):
- def __init__(self, lambda_):
- if (lambda_ <= 0):
- raise error, "parameter must be positive"
- Distribution.__init__(self, 'exponential', lambda_)
-
- def density(x):
- if x < 0:
- return 0.0
- else:
- lambda_ = self._args[0]
- return lambda_*exp(-lambda_*x)
-
-class LogNormalDistribution(Distribution):
- def __init__(self, m, s):
- m = float(m)
- s = float(s)
- if (s <= 0):
- raise error, "standard deviation must be positive"
- Distribution.__init__(self, 'lognormal', m, s)
- sn = math.log(1.0+s*s/(m*m));
- self._mn = math.log(m)-0.5*sn
- self._sn = math.sqrt(sn)
- self._fac = 1.0/math.sqrt(2*math.pi)/self._sn
-
- def density(x):
- m,s = self._args
- y = (math.log(x)-self._mn)/self._sn
- return self._fac*exp(-0.5*y*y)/x
-
-
-class NormalDistribution(Distribution):
- def __init__(self, m, s):
- m = float(m)
- s = float(s)
- if (s <= 0):
- raise error, "standard deviation must be positive"
- Distribution.__init__(self, 'normal', m, s)
- self._fac = 1.0/math.sqrt(2*math.pi)/s
-
- def density(x):
- m,s = self._args
- y = (x-m)/s
- return self._fac*exp(-0.5*y*y)
-
-class UniformDistribution(Distribution):
- def __init__(self, a, b):
- a = float(a)
- b = float(b)
- width = b-a
- if (width <=0):
- raise error, "width of uniform distribution must be > 0"
- Distribution.__init__(self, 'uniform', a, b)
- self._fac = 1.0/width
-
- def density(x):
- a, b = self._args
- if (x < a) or (x >= b):
- return 0.0
- else:
- return self._fac
-
-default_distribution = UniformDistribution(0.0,1.0)
-
-class CreateGenerator(object):
- def __init__(self, seed, dist=None):
- if seed <= 0:
- self._rng = mt.RandomState()
- elif seed > 0:
- self._rng = mt.RandomState(seed)
- if dist is None:
- dist = default_distribution
- if not isinstance(dist, Distribution):
- raise error, "Not a distribution object"
- self._dist = dist
-
- def ranf(self):
- return self._dist._onesample(self._rng)
-
- def sample(self, n):
- return self._dist._sample(self._rng, n)
-
-
-standard_generator = CreateGenerator(-1)
-
-def ranf():
- "ranf() = a random number from the standard generator."
- return standard_generator.ranf()
-
-def random_sample(*n):
- """random_sample(n) = array of n random numbers;
-
- random_sample(n1, n2, ...)= random array of shape (n1, n2, ..)"""
-
- if not n:
- return standard_generator.ranf()
- m = 1
- for i in n:
- m = m * i
- return standard_generator.sample(m).reshape(*n)
diff --git a/numpy/oldnumeric/rng_stats.py b/numpy/oldnumeric/rng_stats.py
deleted file mode 100644
index 8c7fec433..000000000
--- a/numpy/oldnumeric/rng_stats.py
+++ /dev/null
@@ -1,35 +0,0 @@
-
-__all__ = ['average', 'histogram', 'standardDeviation', 'variance']
-
-import numpy.oldnumeric as Numeric
-
-def average(data):
- data = Numeric.array(data)
- return Numeric.add.reduce(data)/len(data)
-
-def variance(data):
- data = Numeric.array(data)
- return Numeric.add.reduce((data-average(data,axis=0))**2)/(len(data)-1)
-
-def standardDeviation(data):
- data = Numeric.array(data)
- return Numeric.sqrt(variance(data))
-
-def histogram(data, nbins, range = None):
- data = Numeric.array(data, Numeric.Float)
- if range is None:
- min = Numeric.minimum.reduce(data)
- max = Numeric.maximum.reduce(data)
- else:
- min, max = range
- data = Numeric.repeat(data,
- Numeric.logical_and(Numeric.less_equal(data, max),
- Numeric.greater_equal(data,
- min)),axis=0)
- bin_width = (max-min)/nbins
- data = Numeric.floor((data - min)/bin_width).astype(Numeric.Int)
- histo = Numeric.add.reduce(Numeric.equal(
- Numeric.arange(nbins)[:,Numeric.NewAxis], data), -1)
- histo[-1] = histo[-1] + Numeric.add.reduce(Numeric.equal(nbins, data))
- bins = min + bin_width*(Numeric.arange(nbins)+0.5)
- return Numeric.transpose(Numeric.array([bins, histo]))
diff --git a/numpy/oldnumeric/setup.py b/numpy/oldnumeric/setup.py
deleted file mode 100644
index 82e8a6201..000000000
--- a/numpy/oldnumeric/setup.py
+++ /dev/null
@@ -1,8 +0,0 @@
-
-def configuration(parent_package='',top_path=None):
- from numpy.distutils.misc_util import Configuration
- return Configuration('oldnumeric',parent_package,top_path)
-
-if __name__ == '__main__':
- from numpy.distutils.core import setup
- setup(configuration=configuration)
diff --git a/numpy/oldnumeric/tests/test_oldnumeric.py b/numpy/oldnumeric/tests/test_oldnumeric.py
deleted file mode 100644
index 628ec231f..000000000
--- a/numpy/oldnumeric/tests/test_oldnumeric.py
+++ /dev/null
@@ -1,86 +0,0 @@
-from numpy.testing import *
-
-from numpy import array
-from numpy.oldnumeric import *
-from numpy.core.numeric import float32, float64, complex64, complex128, int8, \
- int16, int32, int64, uint, uint8, uint16, uint32, uint64
-
-class test_oldtypes(NumPyTestCase):
- def check_oldtypes(self, level=1):
- a1 = array([0,1,0], Float)
- a2 = array([0,1,0], float)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Float8)
- a2 = array([0,1,0], float)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Float16)
- a2 = array([0,1,0], float)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Float32)
- a2 = array([0,1,0], float32)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Float64)
- a2 = array([0,1,0], float64)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Complex)
- a2 = array([0,1,0], complex)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Complex8)
- a2 = array([0,1,0], complex)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Complex16)
- a2 = array([0,1,0], complex)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Complex32)
- a2 = array([0,1,0], complex64)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Complex64)
- a2 = array([0,1,0], complex128)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Int)
- a2 = array([0,1,0], int)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Int8)
- a2 = array([0,1,0], int8)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Int16)
- a2 = array([0,1,0], int16)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Int32)
- a2 = array([0,1,0], int32)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], Int64)
- a2 = array([0,1,0], int64)
- assert_array_equal(a1, a2)
- a1 = array([0,1,0], UnsignedInt)
- a2 = array([0,1,0], UnsignedInteger)
- a3 = array([0,1,0], uint)
- assert_array_equal(a1, a3)
- assert_array_equal(a2, a3)
- a1 = array([0,1,0], UInt8)
- a2 = array([0,1,0], UnsignedInt8)
- a3 = array([0,1,0], uint8)
- assert_array_equal(a1, a3)
- assert_array_equal(a2, a3)
- a1 = array([0,1,0], UInt16)
- a2 = array([0,1,0], UnsignedInt16)
- a3 = array([0,1,0], uint16)
- assert_array_equal(a1, a3)
- assert_array_equal(a2, a3)
- a1 = array([0,1,0], UInt32)
- a2 = array([0,1,0], UnsignedInt32)
- a3 = array([0,1,0], uint32)
- assert_array_equal(a1, a3)
- assert_array_equal(a2, a3)
- a1 = array([0,1,0], UInt64)
- a2 = array([0,1,0], UnsignedInt64)
- a3 = array([0,1,0], uint64)
- assert_array_equal(a1, a3)
- assert_array_equal(a2, a3)
- a1 = array([0,1,0], Bool)
- a2 = array([0,1,0], bool)
- assert_array_equal(a1, a2)
-
-
-if __name__ == "__main__":
- NumPyTest().run()
diff --git a/numpy/oldnumeric/typeconv.py b/numpy/oldnumeric/typeconv.py
deleted file mode 100644
index 1fbf1e072..000000000
--- a/numpy/oldnumeric/typeconv.py
+++ /dev/null
@@ -1,60 +0,0 @@
-__all__ = ['oldtype2dtype', 'convtypecode', 'convtypecode2', 'oldtypecodes']
-
-import numpy as N
-
-oldtype2dtype = {'1': N.dtype(N.byte),
- 's': N.dtype(N.short),
-# 'i': N.dtype(N.intc),
-# 'l': N.dtype(int),
-# 'b': N.dtype(N.ubyte),
- 'w': N.dtype(N.ushort),
- 'u': N.dtype(N.uintc),
-# 'f': N.dtype(N.single),
-# 'd': N.dtype(float),
-# 'F': N.dtype(N.csingle),
-# 'D': N.dtype(complex),
-# 'O': N.dtype(object),
-# 'c': N.dtype('c'),
- None:N.dtype(int)
- }
-
-# converts typecode=None to int
-def convtypecode(typecode, dtype=None):
- if dtype is None:
- try:
- return oldtype2dtype[typecode]
- except:
- return N.dtype(typecode)
- else:
- return dtype
-
-#if both typecode and dtype are None
-# return None
-def convtypecode2(typecode, dtype=None):
- if dtype is None:
- if typecode is None:
- return None
- else:
- try:
- return oldtype2dtype[typecode]
- except:
- return N.dtype(typecode)
- else:
- return dtype
-
-_changedtypes = {'B': 'b',
- 'b': '1',
- 'h': 's',
- 'H': 'w',
- 'I': 'u'}
-
-class _oldtypecodes(dict):
- def __getitem__(self, obj):
- char = N.dtype(obj).char
- try:
- return _changedtypes[char]
- except KeyError:
- return char
-
-
-oldtypecodes = _oldtypecodes()
diff --git a/numpy/oldnumeric/ufuncs.py b/numpy/oldnumeric/ufuncs.py
deleted file mode 100644
index c26050f55..000000000
--- a/numpy/oldnumeric/ufuncs.py
+++ /dev/null
@@ -1,19 +0,0 @@
-__all__ = ['less', 'cosh', 'arcsinh', 'add', 'ceil', 'arctan2', 'floor_divide',
- 'fmod', 'hypot', 'logical_and', 'power', 'sinh', 'remainder', 'cos',
- 'equal', 'arccos', 'less_equal', 'divide', 'bitwise_or',
- 'bitwise_and', 'logical_xor', 'log', 'subtract', 'invert',
- 'negative', 'log10', 'arcsin', 'arctanh', 'logical_not',
- 'not_equal', 'tanh', 'true_divide', 'maximum', 'arccosh',
- 'logical_or', 'minimum', 'conjugate', 'tan', 'greater',
- 'bitwise_xor', 'fabs', 'floor', 'sqrt', 'arctan', 'right_shift',
- 'absolute', 'sin', 'multiply', 'greater_equal', 'left_shift',
- 'exp', 'divide_safe']
-
-from numpy import less, cosh, arcsinh, add, ceil, arctan2, floor_divide, \
- fmod, hypot, logical_and, power, sinh, remainder, cos, \
- equal, arccos, less_equal, divide, bitwise_or, bitwise_and, \
- logical_xor, log, subtract, invert, negative, log10, arcsin, \
- arctanh, logical_not, not_equal, tanh, true_divide, maximum, \
- arccosh, logical_or, minimum, conjugate, tan, greater, bitwise_xor, \
- fabs, floor, sqrt, arctan, right_shift, absolute, sin, \
- multiply, greater_equal, left_shift, exp, divide as divide_safe
diff --git a/numpy/oldnumeric/user_array.py b/numpy/oldnumeric/user_array.py
deleted file mode 100644
index 375c4013b..000000000
--- a/numpy/oldnumeric/user_array.py
+++ /dev/null
@@ -1,9 +0,0 @@
-
-
-from numpy.oldnumeric import *
-from numpy.lib.user_array import container as UserArray
-
-import numpy.oldnumeric as nold
-__all__ = nold.__all__[:]
-__all__ += ['UserArray']
-del nold
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