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ran reindent

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commit c66da19ab8bd6ad7f035b77026bbd703eab199d4 1 parent 0b7800b
@jarrodmillman jarrodmillman authored
View
1  benchmarks/simpleindex.py
@@ -46,4 +46,3 @@
print "Numarray: ", numarray_timer.repeat(3,100)
print "Python: ", python_timer.repeat(3,100)
print "Optimized: ", numpy_timer3.repeat(3,100)
-
View
4 numpy/_import_tools.py
@@ -152,10 +152,10 @@ def __call__(self,*packages, **options):
Parameters
----------
- *packges : arg-tuple
+ *packges : arg-tuple
the names (one or more strings) of all the modules one
wishes to load into the top-level namespace.
- verbose= : integer
+ verbose= : integer
verbosity level [default: -1].
verbose=-1 will suspend also warnings.
force= : bool
View
10 numpy/add_newdocs.py
@@ -1,7 +1,7 @@
# This is only meant to add docs to
# objects defined in C-extension modules.
# The purpose is to allow easier editing of the
-# docstrings without requiring a re-compile.
+# docstrings without requiring a re-compile.
from lib import add_newdoc
add_newdoc('numpy.core','dtype',
@@ -238,7 +238,7 @@
open file object or string containing file name.
dtype : data-type
data type of the returned array
- count : int
+ count : int
number of items to read (-1 mean 'all')
sep : string
separater between items if file is a text file (default "")
@@ -1107,8 +1107,8 @@
is done if the array is not of float type and 'decimals' is >= 0.
The keyword 'out' may be used to specify a different array to hold the
- result rather than the default new array. If the type of the array
- specified by 'out' differs from that of 'a', the result is cast to the
+ result rather than the default new array. If the type of the array
+ specified by 'out' differs from that of 'a', the result is cast to the
new type, otherwise the original type is kept. Floats round to floats
by default.
@@ -1209,7 +1209,7 @@
|'heapsort' | 3 | O(n*log(n)) | 0 | no |
|------------------------------------------------------|
- All the sort algorithms make temporary copies of the data when the sort is
+ All the sort algorithms make temporary copies of the data when the sort is
not along the last axis. Consequently, sorts along the last axis are faster
and use less space than sorts along other axis.
"""))
View
2  numpy/core/code_generators/generate_ufunc_api.py
@@ -71,7 +71,7 @@
def generate_api(output_dir, force=False):
basename = 'ufunc_api'
-
+
h_file = os.path.join(output_dir, '__%s.h' % basename)
c_file = os.path.join(output_dir, '__%s.c' % basename)
d_file = os.path.join(output_dir, '%s.txt' % basename)
View
16 numpy/core/defmatrix.py
@@ -51,16 +51,16 @@ def asmatrix(data, dtype=None):
class matrix(N.ndarray):
"""mat = matrix(data, dtype=None, copy=True)
- Returns a matrix from an array-like object, or a string of
+ Returns a matrix from an array-like object, or a string of
data. A matrix is a specialized 2-d array that retains
it's 2-d nature through operations and where '*' means matrix
- multiplication and '**' means matrix power.
+ multiplication and '**' means matrix power.
Parameters
----------
data : array-like or string
- If data is a string, then interpret the string as a matrix
- with commas or spaces separating columns and semicolons
+ If data is a string, then interpret the string as a matrix
+ with commas or spaces separating columns and semicolons
separating rows.
If data is array-like than convert the array to a matrix.
dtype : data-type
@@ -273,7 +273,7 @@ def mean(self, axis=None, out=None):
the flattened array by default, otherwise over the specified axis.
Parameters
- ----------
+ ----------
axis : integer
Axis along which the means are computed. The default is
to compute the standard deviation of the flattened array.
@@ -289,7 +289,7 @@ def mean(self, axis=None, out=None):
cast if necessary.
Returns
- -------
+ -------
mean : The return type varies, see above.
A new array holding the result is returned unless out is
specified, in which case a reference to out is returned.
@@ -342,7 +342,7 @@ def std(self, axis=None, dtype=None, out=None):
mean : average
Notes
- -----
+ -----
The standard deviation is the square root of the
average of the squared deviations from the mean, i.e. var =
sqrt(mean((x - x.mean())**2)). The computed standard
@@ -362,7 +362,7 @@ def var(self, axis=None, dtype=None, out=None):
----------
axis : integer
Axis along which the variance is computed. The default is to
- compute the variance of the flattened array.
+ compute the variance of the flattened array.
dtype : data-type
Type to use in computing the variance. For arrays of integer
type the default is float32, for arrays of float types it is
View
8 numpy/core/numeric.py
@@ -149,7 +149,7 @@ def asfortranarray(a, dtype=None):
def require(a, dtype=None, requirements=None):
"""Return an ndarray of the provided type that satisfies requirements.
-
+
This function is useful to be sure that an array with the correct flags
is returned for passing to compiled code (perhaps through ctypes).
@@ -160,7 +160,7 @@ def require(a, dtype=None, requirements=None):
dtype : data-type
The required data-type (None is the default data-type -- float64)
requirements : list of strings
- The requirements list can be any of the
+ The requirements list can be any of the
'ENSUREARRAY' ('E') - ensure that a base-class ndarray
'F_CONTIGUOUS' ('F') - ensure a Fortran-contiguous array
'C_CONTIGUOUS' ('C') - ensure a C-contiguous array
@@ -169,7 +169,7 @@ def require(a, dtype=None, requirements=None):
'OWNDATA' ('O') - ensure an array that owns its own data
The returned array will be guaranteed to have the listed requirements
- by making a copy if needed.
+ by making a copy if needed.
"""
if requirements is None:
requirements = []
@@ -276,7 +276,7 @@ def vdot(a, b):
try:
# importing this changes the dot function for basic 4 types
# to blas-optimized versions.
- from _dotblas import dot, vdot, inner, alterdot, restoredot
+ from _dotblas import dot, vdot, inner, alterdot, restoredot
except ImportError:
def alterdot():
"Does Nothing"
View
18 numpy/core/records.py
@@ -45,9 +45,9 @@ def find_duplicate(list):
class format_parser:
"""Class to convert formats, names, titles description to a dtype
- After constructing the format_parser object, the dtype attribute is
+ After constructing the format_parser object, the dtype attribute is
the converted data-type.
-
+
dtype = format_parser(formats, names, titles).dtype
Parameters
@@ -59,18 +59,18 @@ class format_parser:
comma-separated field names --- 'col1, col2, col3'
list or tuple of field names
titles : sequence
- sequence of title strings or unicode
+ sequence of title strings or unicode
aligned : bool
align the fields by padding as the C-compiler would
- byteorder :
- If specified, all the fields will be changed to the
+ byteorder :
+ If specified, all the fields will be changed to the
provided byteorder. Otherwise, the default byteorder is
used.
Returns
-------
object
- A Python object whose dtype attribute is a data-type.
+ A Python object whose dtype attribute is a data-type.
"""
def __init__(self, formats, names, titles, aligned=False, byteorder=None):
self._parseFormats(formats, aligned)
@@ -227,9 +227,9 @@ class recarray(ndarray):
by the *formats*, *names*, *titles*, *aligned*, and *byteorder* keywords.
buf : [buffer] or None
If this is None, then a new array is created of the given shape and data-type
- If this is an object exposing the buffer interface, then the array will
- use the memory from an existing buffer. In this case, the *offset* and
- *strides* keywords can also be used.
+ If this is an object exposing the buffer interface, then the array will
+ use the memory from an existing buffer. In this case, the *offset* and
+ *strides* keywords can also be used.
See Also
--------
View
8 numpy/core/scons_support.py
@@ -30,12 +30,12 @@ def split_ext(string):
# Ufunc and multiarray API generators
#------------------------------------
def do_generate_array_api(target, source, env):
- nowrap_do_generate_array_api([str(i) for i in target],
+ nowrap_do_generate_array_api([str(i) for i in target],
[str(i) for i in source])
return 0
def do_generate_ufunc_api(target, source, env):
- nowrap_do_generate_ufunc_api([str(i) for i in target],
+ nowrap_do_generate_ufunc_api([str(i) for i in target],
[str(i) for i in source])
return 0
@@ -74,7 +74,7 @@ def generate_from_template_emitter(target, source, env):
base, ext = split_ext(pbasename(str(source[0])))
t = pjoin(pdirname(str(target[0])), base)
return ([t], source)
-
+
#----------------
# umath generator
#----------------
@@ -92,7 +92,7 @@ def generate_umath(target, source, env):
def generate_umath_emitter(target, source, env):
t = str(target[0]) + '.c'
return ([t], source)
-
+
#-----------------------------------------
# Other functions related to configuration
#-----------------------------------------
View
8 numpy/core/setup.py
@@ -175,7 +175,7 @@ def generate_numpyconfig_h(ext, build_dir):
" python-dev|python-devel." % (python_h)
config.numpy_include_dirs
- result = config_cmd.try_run(testcode,
+ result = config_cmd.try_run(testcode,
include_dirs = [python_include] + \
config.numpy_include_dirs,
library_dirs = default_lib_dirs)
@@ -190,7 +190,7 @@ def generate_numpyconfig_h(ext, build_dir):
target_f.close()
print 'EOF'
return target
-
+
def generate_api_func(module_name):
def generate_api(ext, build_dir):
script = join(codegen_dir, module_name + '.py')
@@ -405,9 +405,9 @@ def generate_numpyconfig_code(target):
#include "config.h"
int main()
-{
+{
FILE* f;
-
+
f = fopen("%s", "w");
if (f == NULL) {
return -1;
View
8 numpy/core/setupscons.py
@@ -25,10 +25,10 @@ def configuration(parent_package='',top_path=None):
join('code_generators', 'multiarray_api_order.txt'),
join('code_generators', 'ufunc_api_order.txt')]
core_src = [join('src', basename(i)) for i in glob.glob(join(local_dir,
- 'src',
+ 'src',
'*.c'))]
core_src += [join('src', basename(i)) for i in glob.glob(join(local_dir,
- 'src',
+ 'src',
'*.src'))]
source_files = dot_blas_src + api_definition + core_src + \
@@ -54,7 +54,7 @@ def add_numpyconfig_header():
incl_dir = os.path.dirname(target)
if incl_dir not in config.numpy_include_dirs:
config.numpy_include_dirs.append(incl_dir)
- config.add_data_files((header_dir, target))
+ config.add_data_files((header_dir, target))
def add_array_api():
scons_build_dir = get_scons_build_dir()
@@ -83,7 +83,7 @@ def add_generated_files():
add_ufunc_api()
config.add_configres()
- config.add_sconscript('SConstruct',
+ config.add_sconscript('SConstruct',
post_hook = add_generated_files,
source_files = source_files)
View
20 numpy/distutils/command/scons.py
@@ -14,21 +14,21 @@
def get_scons_build_dir():
"""Return the top path where everything produced by scons will be put.
-
+
The path is relative to the top setup.py"""
from numscons import get_scons_build_dir
return get_scons_build_dir()
def get_scons_configres_dir():
"""Return the top path where everything produced by scons will be put.
-
+
The path is relative to the top setup.py"""
from numscons import get_scons_configres_dir
return get_scons_configres_dir()
def get_scons_configres_filename():
"""Return the top path where everything produced by scons will be put.
-
+
The path is relative to the top setup.py"""
from numscons import get_scons_configres_filename
return get_scons_configres_filename()
@@ -101,7 +101,7 @@ def dist2sconscxx(compiler):
def get_compiler_executable(compiler):
"""For any give CCompiler instance, this gives us the name of C compiler
(the actual executable).
-
+
NOTE: does NOT work with FCompiler instances."""
# Geez, why does distutils has no common way to get the compiler name...
if compiler.compiler_type == 'msvc':
@@ -112,7 +112,7 @@ def get_compiler_executable(compiler):
# hardcoded string
#compiler.initialize()
#print compiler.cc
- return 'cl.exe'
+ return 'cl.exe'
else:
return compiler.compiler[0]
@@ -124,7 +124,7 @@ def get_f77_compiler_executable(compiler):
def get_cxxcompiler_executable(compiler):
"""For any give CCompiler instance, this gives us the name of CXX compiler
(the actual executable).
-
+
NOTE: does NOT work with FCompiler instances."""
# Geez, why does distutils has no common way to get the compiler name...
if compiler.compiler_type == 'msvc':
@@ -135,7 +135,7 @@ def get_cxxcompiler_executable(compiler):
# hardcoded string
#compiler.initialize()
#print compiler.cc
- return 'cl.exe'
+ return 'cl.exe'
else:
return compiler.compiler_cxx[0]
@@ -181,7 +181,7 @@ class scons(old_build_ext):
# XXX: add an option to the scons command for configuration (auto/force/cache).
description = "Scons builder"
user_options = old_build_ext.user_options + \
- [('jobs=', None,
+ [('jobs=', None,
"specify number of worker threads when executing scons"),
('scons-tool-path=', None, 'specify additional path '\
'(absolute) to look for scons tools'),
@@ -239,11 +239,11 @@ def finalize_options(self):
self.scons_compiler = dist2sconscc(distutils_compiler)
self.scons_compiler_path = protect_path(get_tool_path(distutils_compiler))
except DistutilsPlatformError, e:
- if not self._bypass_distutils_cc:
+ if not self._bypass_distutils_cc:
raise e
else:
self.scons_compiler = compiler_type
-
+
# We do the same for the fortran compiler ...
fcompiler_type = self.fcompiler
from numpy.distutils.fcompiler import new_fcompiler
View
10 numpy/distutils/misc_util.py
@@ -1192,8 +1192,8 @@ def add_sconscript(self, sconscript, subpackage_path=None,
full_source_files.extend([self.paths(i)[0] for i in source_files])
if dist is not None:
- dist.scons_data.append((fullsconsname,
- pre_hook,
+ dist.scons_data.append((fullsconsname,
+ pre_hook,
post_hook,
full_source_files,
parent_name))
@@ -1203,8 +1203,8 @@ def add_sconscript(self, sconscript, subpackage_path=None,
# options in distutils command.
dist.add_extension('', sources = [])
else:
- self.scons_data.append((fullsconsname,
- pre_hook,
+ self.scons_data.append((fullsconsname,
+ pre_hook,
post_hook,
full_source_files,
parent_name))
@@ -1214,7 +1214,7 @@ def add_sconscript(self, sconscript, subpackage_path=None,
def add_configres(self):
from numscons import get_scons_configres_dir, get_scons_configres_filename
- file = os.path.join(get_scons_configres_dir(), self.local_path,
+ file = os.path.join(get_scons_configres_dir(), self.local_path,
get_scons_configres_filename())
def add_scripts(self,*files):
View
2  numpy/doc/example.py
@@ -53,7 +53,7 @@ def foo(var1, var2, long_var_name='hi') :
Explanation
See Also
- --------
+ --------
otherfunc : relationship (optional)
newfunc : relationship (optional)
View
2  numpy/fft/setupscons.py
@@ -4,7 +4,7 @@ def configuration(parent_package = '', top_path = None):
config.add_data_dir('tests')
- config.add_sconscript('SConstruct',
+ config.add_sconscript('SConstruct',
source_files = ['fftpack_litemodule.c', 'fftpack.c',
'fftpack.h'])
View
2  numpy/lib/arraysetops.py
@@ -207,7 +207,7 @@ def setmember1d( ar1, ar2 ):
b1 = nm.zeros( ar1.shape, dtype = nm.int8 )
b2 = nm.ones( ar2.shape, dtype = nm.int8 )
tt = nm.concatenate( (b1, b2) )
-
+
# We need this to be a stable sort, so always use 'mergesort' here. The
# values from the first array should always come before the values from the
# second array.
View
5 numpy/lib/format.py
@@ -227,7 +227,7 @@ def read_array_header_1_0(fp):
raise ValueError("Header does not contain the correct keys: %r" % (keys,))
# Sanity-check the values.
- if (not isinstance(d['shape'], tuple) or
+ if (not isinstance(d['shape'], tuple) or
not numpy.all([isinstance(x, int) for x in d['shape']])):
raise ValueError("shape is not valid: %r" % (d['shape'],))
if not isinstance(d['fortran_order'], bool):
@@ -407,6 +407,3 @@ def open_memmap(filename, mode='r+', dtype=None, shape=None,
mode=mode, offset=offset)
return marray
-
-
-
View
50 numpy/lib/io.py
@@ -19,8 +19,8 @@
_file = file
class BagObj(object):
- """A simple class that converts attribute lookups to
- getitems on the class passed in.
+ """A simple class that converts attribute lookups to
+ getitems on the class passed in.
"""
def __init__(self, obj):
self._obj = obj
@@ -31,8 +31,8 @@ def __getattribute__(self, key):
raise AttributeError, key
class NpzFile(object):
- """A dictionary-like object with lazy-loading of files in the zipped
- archive provided on construction.
+ """A dictionary-like object with lazy-loading of files in the zipped
+ archive provided on construction.
The arrays and file strings are lazily loaded on either
getitem access using obj['key'] or attribute lookup using obj.f.key
@@ -54,13 +54,13 @@ def __init__(self, fid):
def __getitem__(self, key):
# FIXME: This seems like it will copy strings around
- # more than is strictly necessary. The zipfile
+ # more than is strictly necessary. The zipfile
# will read the string and then
# the format.read_array will copy the string
- # to another place in memory.
- # It would be better if the zipfile could read
+ # to another place in memory.
+ # It would be better if the zipfile could read
# (or at least uncompress) the data
- # directly into the array memory.
+ # directly into the array memory.
member = 0
if key in self._files:
member = 1
@@ -90,21 +90,21 @@ def load(file, memmap=False):
memmap : bool
If true, then memory-map the .npy file or unzip the .npz file into
a temporary directory and memory-map each component
- This has no effect for a pickle.
+ This has no effect for a pickle.
Returns
-------
result : array, tuple, dict, etc.
- data stored in the file.
+ data stored in the file.
If file contains pickle data, then whatever is stored in the pickle is
returned.
- If the file is .npy file, then an array is returned.
- If the file is .npz file, then a dictionary-like object is returned
+ If the file is .npy file, then an array is returned.
+ If the file is .npz file, then a dictionary-like object is returned
which has a filename:array key:value pair for every file in the zip.
Raises
------
- IOError
+ IOError
"""
if isinstance(file, type("")):
fid = _file(file,"rb")
@@ -124,7 +124,7 @@ def load(file, memmap=False):
elif magic == format.MAGIC_PREFIX: # .npy file
return format.read_array(fid)
else: # Try a pickle
- try:
+ try:
return _cload(fid)
except:
raise IOError, \
@@ -133,8 +133,8 @@ def load(file, memmap=False):
def save(file, arr):
"""Save an array to a binary file (a string or file-like object).
- If the file is a string, then if it does not have the .npy extension,
- it is appended and a file open.
+ If the file is a string, then if it does not have the .npy extension,
+ it is appended and a file open.
Data is saved to the open file in NumPy-array format
@@ -144,7 +144,7 @@ def save(file, arr):
...
np.save('myfile', a)
a = np.load('myfile.npy')
- """
+ """
if isinstance(file, str):
if not file.endswith('.npy'):
file = file + '.npy'
@@ -158,15 +158,15 @@ def save(file, arr):
def savez(file, *args, **kwds):
"""Save several arrays into an .npz file format which is a zipped-archive
of arrays
-
- If keyword arguments are given, then filenames are taken from the keywords.
- If arguments are passed in with no keywords, then stored file names are
- arr_0, arr_1, etc.
+
+ If keyword arguments are given, then filenames are taken from the keywords.
+ If arguments are passed in with no keywords, then stored file names are
+ arr_0, arr_1, etc.
"""
if isinstance(file, str):
if not file.endswith('.npz'):
- file = file + '.npz'
+ file = file + '.npz'
namedict = kwds
for i, val in enumerate(args):
@@ -190,7 +190,7 @@ def savez(file, *args, **kwds):
format.write_array(fid, np.asanyarray(val))
fid.close()
zip.write(filename, arcname=fname)
-
+
zip.close()
for name in todel:
os.remove(name)
@@ -359,7 +359,3 @@ def savetxt(fname, X, fmt='%.18e',delimiter=' '):
if origShape is not None:
X.shape = origShape
-
-
-
-
View
28 numpy/lib/scimath.py
@@ -93,7 +93,7 @@ def _fix_real_lt_zero(x):
"""Convert `x` to complex if it has real, negative components.
Otherwise, output is just the array version of the input (via asarray).
-
+
Parameters
----------
x : array_like
@@ -119,7 +119,7 @@ def _fix_int_lt_zero(x):
"""Convert `x` to double if it has real, negative components.
Otherwise, output is just the array version of the input (via asarray).
-
+
Parameters
----------
x : array_like
@@ -145,7 +145,7 @@ def _fix_real_abs_gt_1(x):
"""Convert `x` to complex if it has real components x_i with abs(x_i)>1.
Otherwise, output is just the array version of the input (via asarray).
-
+
Parameters
----------
x : array_like
@@ -203,7 +203,7 @@ def log(x):
If x contains negative inputs, the answer is computed and returned in the
complex domain.
-
+
Parameters
----------
x : array_like
@@ -221,7 +221,7 @@ def log(x):
Negative arguments are correctly handled (recall that for negative
arguments, the identity exp(log(z))==z does not hold anymore):
-
+
>>> log(-math.exp(1)) == (1+1j*math.pi)
True
"""
@@ -233,7 +233,7 @@ def log10(x):
If x contains negative inputs, the answer is computed and returned in the
complex domain.
-
+
Parameters
----------
x : array_like
@@ -263,7 +263,7 @@ def logn(n, x):
If x contains negative inputs, the answer is computed and returned in the
complex domain.
-
+
Parameters
----------
x : array_like
@@ -293,7 +293,7 @@ def log2(x):
If x contains negative inputs, the answer is computed and returned in the
complex domain.
-
+
Parameters
----------
x : array_like
@@ -307,7 +307,7 @@ def log2(x):
(We set the printing precision so the example can be auto-tested)
>>> import numpy as np; np.set_printoptions(precision=4)
-
+
>>> log2([4,8])
array([ 2., 3.])
@@ -323,7 +323,7 @@ def power(x, p):
If x contains negative values, it is converted to the complex domain.
If p contains negative values, it is converted to floating point.
-
+
Parameters
----------
x : array_like
@@ -332,7 +332,7 @@ def power(x, p):
Returns
-------
array_like
-
+
Examples
--------
(We set the printing precision so the example can be auto-tested)
@@ -357,7 +357,7 @@ def arccos(x):
For real x with abs(x)<=1, this returns the principal value.
If abs(x)>1, the complex arccos() is computed.
-
+
Parameters
----------
x : array_like
@@ -385,7 +385,7 @@ def arcsin(x):
For real x with abs(x)<=1, this returns the principal value.
If abs(x)>1, the complex arcsin() is computed.
-
+
Parameters
----------
x : array_like
@@ -414,7 +414,7 @@ def arctanh(x):
For real x with abs(x)<=1, this returns the principal value.
If abs(x)>1, the complex arctanh() is computed.
-
+
Parameters
----------
x : array_like
View
2  numpy/lib/setupscons.py
@@ -5,7 +5,7 @@ def configuration(parent_package='',top_path=None):
config = Configuration('lib',parent_package,top_path)
- config.add_sconscript('SConstruct',
+ config.add_sconscript('SConstruct',
source_files = [join('src', '_compiled_base.c')])
config.add_data_dir('tests')
View
28 numpy/lib/tests/test_format.py
@@ -21,9 +21,9 @@
... np.complex128,
... object,
... ]
- >>>
+ >>>
>>> basic_arrays = []
- >>>
+ >>>
>>> for scalar in scalars:
... for endian in '<>':
... dtype = np.dtype(scalar).newbyteorder(endian)
@@ -36,20 +36,20 @@
... basic.reshape((3,5)).T,
... basic.reshape((3,5))[::-1,::2],
... ])
- ...
- >>>
+ ...
+ >>>
>>> Pdescr = [
... ('x', 'i4', (2,)),
... ('y', 'f8', (2, 2)),
... ('z', 'u1')]
- >>>
- >>>
+ >>>
+ >>>
>>> PbufferT = [
... ([3,2], [[6.,4.],[6.,4.]], 8),
... ([4,3], [[7.,5.],[7.,5.]], 9),
... ]
- >>>
- >>>
+ >>>
+ >>>
>>> Ndescr = [
... ('x', 'i4', (2,)),
... ('Info', [
@@ -68,14 +68,14 @@
... ('Value', 'c16')]),
... ('y', 'f8', (2, 2)),
... ('z', 'u1')]
- >>>
- >>>
+ >>>
+ >>>
>>> NbufferT = [
... ([3,2], (6j, 6., ('nn', [6j,4j], [6.,4.], [1,2]), 'NN', True), 'cc', ('NN', 6j), [[6.,4.],[6.,4.]], 8),
... ([4,3], (7j, 7., ('oo', [7j,5j], [7.,5.], [2,1]), 'OO', False), 'dd', ('OO', 7j), [[7.,5.],[7.,5.]], 9),
... ]
- >>>
- >>>
+ >>>
+ >>>
>>> record_arrays = [
... np.array(PbufferT, dtype=np.dtype(Pdescr).newbyteorder('<')),
... np.array(NbufferT, dtype=np.dtype(Ndescr).newbyteorder('<')),
@@ -111,7 +111,7 @@
... f = StringIO()
... format.write_array_header_1_0(f, arr)
... print repr(f.getvalue())
- ...
+ ...
"F\x00{'descr': '|u1', 'fortran_order': False, 'shape': (0,)} \n"
"F\x00{'descr': '|u1', 'fortran_order': False, 'shape': ()} \n"
"F\x00{'descr': '|u1', 'fortran_order': False, 'shape': (15,)} \n"
@@ -506,5 +506,3 @@ def test_read_version_1_0_bad_magic():
for magic in bad_version_magic + malformed_magic:
f = StringIO(magic)
yield raises(ValueError)(format.read_array), f
-
-
View
16 numpy/lib/utils.py
@@ -106,7 +106,7 @@ def deprecate(func, oldname=None, newname=None):
else:
str1 = "%s is deprecated, use %s" % (oldname, newname),
depdoc = '%s is DEPRECATED!! -- use %s instead' % (oldname, newname,)
-
+
def newfunc(*args,**kwds):
warnings.warn(str1, DeprecationWarning)
return func(*args, **kwds)
@@ -487,28 +487,28 @@ def source(object, output=sys.stdout):
# * raise SyntaxError instead of a custom exception.
class SafeEval(object):
-
+
def visit(self, node, **kw):
cls = node.__class__
meth = getattr(self,'visit'+cls.__name__,self.default)
return meth(node, **kw)
-
+
def default(self, node, **kw):
raise SyntaxError("Unsupported source construct: %s" % node.__class__)
-
+
def visitExpression(self, node, **kw):
for child in node.getChildNodes():
return self.visit(child, **kw)
-
+
def visitConst(self, node, **kw):
return node.value
def visitDict(self, node,**kw):
return dict([(self.visit(k),self.visit(v)) for k,v in node.items])
-
+
def visitTuple(self, node, **kw):
return tuple([self.visit(i) for i in node.nodes])
-
+
def visitList(self, node, **kw):
return [self.visit(i) for i in node.nodes]
@@ -578,5 +578,3 @@ def safe_eval(source):
raise
#-----------------------------------------------------------------------------
-
-
View
94 numpy/linalg/linalg.py
@@ -138,11 +138,11 @@ def _assertNonEmpty(*arrays):
def tensorsolve(a, b, axes=None):
"""Solve the tensor equation a x = b for x
-
+
It is assumed that all indices of x are summed over in the product,
together with the rightmost indices of a, similarly as in
tensordot(a, x, axes=len(b.shape)).
-
+
Parameters
----------
a : array, shape b.shape+Q
@@ -153,11 +153,11 @@ def tensorsolve(a, b, axes=None):
axes : tuple of integers
Axes in a to reorder to the right, before inversion.
If None (default), no reordering is done.
-
+
Returns
-------
x : array, shape Q
-
+
Examples
--------
>>> from numpy import *
@@ -169,7 +169,7 @@ def tensorsolve(a, b, axes=None):
(2, 3, 4)
>>> allclose(tensordot(a, x, axes=3), b)
True
-
+
"""
a = asarray(a)
b = asarray(b)
@@ -206,7 +206,7 @@ def solve(a, b):
x : array, shape (M,)
Raises LinAlgError if a is singular or not square
-
+
"""
one_eq = len(b.shape) == 1
if one_eq:
@@ -239,10 +239,10 @@ def tensorinv(a, ind=2):
The result is an inverse corresponding to the operation
tensordot(a, b, ind), ie.,
-
+
x == tensordot(tensordot(tensorinv(a), a, ind), x, ind)
== tensordot(tensordot(a, tensorinv(a), ind), x, ind)
-
+
for all x (up to floating-point accuracy).
Parameters
@@ -298,12 +298,12 @@ def tensorinv(a, ind=2):
def inv(a):
"""Compute the inverse of a matrix.
-
+
Parameters
----------
a : array-like, shape (M, M)
Matrix to be inverted
-
+
Returns
-------
ainv : array-like, shape (M, M)
@@ -330,20 +330,20 @@ def inv(a):
def cholesky(a):
"""Compute the Cholesky decomposition of a matrix.
-
+
Returns the Cholesky decomposition, :lm:`A = L L^*` of a Hermitian
positive-definite matrix :lm:`A`.
-
+
Parameters
----------
a : array, shape (M, M)
Matrix to be decomposed
-
+
Returns
-------
L : array, shape (M, M)
Lower-triangular Cholesky factor of A
-
+
Raises LinAlgError if decomposition fails
Examples
@@ -357,7 +357,7 @@ def cholesky(a):
>>> dot(L, L.T.conj())
array([[ 1.+0.j, 0.-2.j],
[ 0.+2.j, 5.+0.j]])
-
+
"""
_assertRank2(a)
_assertSquareness(a)
@@ -400,7 +400,7 @@ def qr(a, mode='full'):
Q : double or complex array, shape (M, K)
R : double or complex array, shape (K, N)
Size K = min(M, N)
-
+
mode = 'r'
R : double or complex array, shape (K, N)
@@ -429,7 +429,7 @@ def qr(a, mode='full'):
True
>>> allclose(r, triu(r3[:6,:6], k=0))
True
-
+
"""
_assertRank2(a)
m, n = a.shape
@@ -507,7 +507,7 @@ def qr(a, mode='full'):
def eigvals(a):
"""Compute the eigenvalues of a general matrix.
-
+
Parameters
----------
a : array, shape (M, M)
@@ -520,7 +520,7 @@ def eigvals(a):
The eigenvalues, each repeated according to its multiplicity.
They are not necessarily ordered, nor are they necessarily
real for real matrices.
-
+
Raises LinAlgError if eigenvalue computation does not converge
See Also
@@ -534,7 +534,7 @@ def eigvals(a):
This is a simple interface to the LAPACK routines dgeev and zgeev
that sets the flags to return only the eigenvalues of general real
and complex arrays respectively.
-
+
The number w is an eigenvalue of a if there exists a vector v
satisfying the equation dot(a,v) = w*v. Alternately, if w is a root of
the characteristic equation det(a - w[i]*I) = 0, where det is the
@@ -586,7 +586,7 @@ def eigvals(a):
def eigvalsh(a, UPLO='L'):
"""Compute the eigenvalues of a Hermitean or real symmetric matrix.
-
+
Parameters
----------
a : array, shape (M, M)
@@ -596,7 +596,7 @@ def eigvalsh(a, UPLO='L'):
Specifies whether the pertinent array data is taken from the upper
or lower triangular part of a. Possible values are 'L', and 'U' for
upper and lower respectively. Default is 'L'.
-
+
Returns
-------
w : double array, shape (M,)
@@ -616,7 +616,7 @@ def eigvalsh(a, UPLO='L'):
This is a simple interface to the LAPACK routines dsyevd and
zheevd that sets the flags to return only the eigenvalues of real
symmetric and complex Hermetian arrays respectively.
-
+
The number w is an eigenvalue of a if there exists a vector v
satisfying the equation dot(a,v) = w*v. Alternately, if w is a root of
the characteristic equation det(a - w[i]*I) = 0, where det is the
@@ -714,10 +714,10 @@ def eig(a):
that fact. If the eigenvalues are all different, then theoretically the
eigenvectors are independent. Likewise, the matrix of eigenvectors is
unitary if the matrix a is normal, i.e., if dot(a, a.H) = dot(a.H, a).
-
+
The left and right eigenvectors are not necessarily the (Hermitian)
transposes of each other.
-
+
"""
a, wrap = _makearray(a)
_assertRank2(a)
@@ -775,7 +775,7 @@ def eig(a):
def eigh(a, UPLO='L'):
"""Compute eigenvalues for a Hermitian or real symmetric matrix.
-
+
Parameters
----------
a : array, shape (M, M)
@@ -785,7 +785,7 @@ def eigh(a, UPLO='L'):
Specifies whether the pertinent array date is taken from the upper
or lower triangular part of a. Possible values are 'L', and 'U'.
Default is 'L'.
-
+
Returns
-------
w : double array, shape (M,)
@@ -793,7 +793,7 @@ def eigh(a, UPLO='L'):
v : double or complex double array, shape (M, M)
The normalized eigenvector corresponding to the eigenvalue w[i] is
the column v[:,i].
-
+
Raises LinAlgError if eigenvalue computation does not converge
See Also
@@ -801,13 +801,13 @@ def eigh(a, UPLO='L'):
eigvalsh : eigenvalues of symmetric or Hemitiean arrays.
eig : eigenvalues and right eigenvectors for non-symmetric arrays
eigvals : eigenvalues of non-symmetric array.
-
+
Notes
-----
A simple interface to the LAPACK routines dsyevd and zheevd that compute
the eigenvalues and eigenvectors of real symmetric and complex Hermitian
arrays respectively.
-
+
The number w is an eigenvalue of a if there exists a vector v
satisfying the equation dot(a,v) = w*v. Alternately, if w is a root of
the characteristic equation det(a - w[i]*I) = 0, where det is the
@@ -866,7 +866,7 @@ def svd(a, full_matrices=1, compute_uv=1):
an 1d-array s of singular values (real, non-negative) such that
a == U S Vh if S is an suitably shaped matrix of zeros whose
main diagonal is s.
-
+
Parameters
----------
a : array, shape (M, N)
@@ -876,7 +876,7 @@ def svd(a, full_matrices=1, compute_uv=1):
If false, the shapes are (M,K), (K,N) where K = min(M,N)
compute_uv : boolean
Whether to compute also U, Vh in addition to s
-
+
Returns
-------
U: array, shape (M,M) or (M,K) depending on full_matrices
@@ -884,7 +884,7 @@ def svd(a, full_matrices=1, compute_uv=1):
The singular values, sorted so that s[i] >= s[i+1]
K = min(M, N)
Vh: array, shape (N,N) or (K,N) depending on full_matrices
-
+
For compute_uv = False, only s is returned.
Raises LinAlgError if SVD computation does not converge
@@ -895,14 +895,14 @@ def svd(a, full_matrices=1, compute_uv=1):
>>> U, s, Vh = linalg.svd(a)
>>> U.shape, Vh.shape, s.shape
((9, 9), (6, 6), (6,))
-
+
>>> U, s, Vh = linalg.svd(a, full_matrices=False)
>>> U.shape, Vh.shape, s.shape
((9, 6), (6, 6), (6,))
>>> S = diag(s)
>>> allclose(a, dot(U, dot(S, Vh)))
True
-
+
>>> s2 = linalg.svd(a, compute_uv=False)
>>> allclose(s, s2)
True
@@ -969,11 +969,11 @@ def svd(a, full_matrices=1, compute_uv=1):
def pinv(a, rcond=1e-15 ):
"""Compute the (Moore-Penrose) pseudo-inverse of a matrix.
-
+
Calculate a generalized inverse of a matrix using its
singular-value decomposition and including all 'large' singular
values.
-
+
Parameters
----------
a : array, shape (M, N)
@@ -982,11 +982,11 @@ def pinv(a, rcond=1e-15 ):
Cutoff for 'small' singular values.
Singular values smaller than rcond*largest_singular_value are
considered zero.
-
+
Returns
-------
B : array, shape (N, M)
-
+
Raises LinAlgError if SVD computation does not converge
Examples
@@ -998,7 +998,7 @@ def pinv(a, rcond=1e-15 ):
True
>>> allclose(B, dot(B, dot(a, B)))
True
-
+
"""
a, wrap = _makearray(a)
_assertNonEmpty(a)
@@ -1028,7 +1028,7 @@ def det(a):
-------
det : float or complex
Determinant of a
-
+
Notes
-----
The determinant is computed via LU factorization, LAPACK routine z/dgetrf.
@@ -1057,9 +1057,9 @@ def det(a):
def lstsq(a, b, rcond=-1):
"""Compute least-squares solution to equation :m:`a x = b`
-
+
Compute a vector x such that the 2-norm :m:`|b - a x|` is minimised.
-
+
Parameters
----------
a : array, shape (M, N)
@@ -1068,9 +1068,9 @@ def lstsq(a, b, rcond=-1):
Cutoff for 'small' singular values.
Singular values smaller than rcond*largest_singular_value are
considered zero.
-
+
Raises LinAlgError if computation does not converge
-
+
Returns
-------
x : array, shape (N,) or (N, K) depending on shape of b
@@ -1169,7 +1169,7 @@ def norm(x, ord=None):
-2 smallest singular value as below
other - sum(abs(x)**ord)**(1./ord)
===== ============================ ==========================
-
+
Returns
-------
n : float
@@ -1180,7 +1180,7 @@ def norm(x, ord=None):
For values ord < 0, the result is, strictly speaking, not a
mathematical 'norm', but it may still be useful for numerical
purposes.
-
+
"""
x = asarray(x)
nd = len(x.shape)
View
2  numpy/linalg/setupscons.py
@@ -6,7 +6,7 @@ def configuration(parent_package='',top_path=None):
config.add_data_dir('tests')
- config.add_sconscript('SConstruct',
+ config.add_sconscript('SConstruct',
source_files = ['lapack_litemodule.c',
'zlapack_lite.c', 'dlapack_lite.c',
'blas_lite.c', 'dlamch.c',
View
8 numpy/random/setupscons.py
@@ -5,12 +5,12 @@ def configuration(parent_package='',top_path=None):
from numpy.distutils.misc_util import Configuration, get_mathlibs
config = Configuration('random',parent_package,top_path)
- source_files = [join('mtrand', i) for i in ['mtrand.c',
+ source_files = [join('mtrand', i) for i in ['mtrand.c',
'mtrand.pyx',
'numpy.pxi',
- 'randomkit.c',
- 'randomkit.h',
- 'Python.pxi',
+ 'randomkit.c',
+ 'randomkit.h',
+ 'Python.pxi',
'initarray.c',
'initarray.h',
'distributions.c',
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