[Numpysvn] r8583  branches/1.5.x/numpy/lib
numpysvn@scip...
numpysvn@scip...
Sun Aug 1 06:21:38 CDT 2010
Author: rgommers
Date: 20100801 06:21:38 0500 (Sun, 01 Aug 2010)
New Revision: 8583
Modified:
branches/1.5.x/numpy/lib/format.py
branches/1.5.x/numpy/lib/function_base.py
branches/1.5.x/numpy/lib/npyio.py
Log:
DOC: wiki merge, npyio, format and function_base
Modified: branches/1.5.x/numpy/lib/format.py
===================================================================
 branches/1.5.x/numpy/lib/format.py 20100801 11:21:13 UTC (rev 8582)
+++ branches/1.5.x/numpy/lib/format.py 20100801 11:21:38 UTC (rev 8583)
@@ 366,19 +366,19 @@
"""
Write an array to an NPY file, including a header.
 If the array is neither Ccontiguous or Fortrancontiguous AND if the
 filelike object is not a real file object, then this function will have
 to copy data in memory.
+ If the array is neither Ccontiguous nor Fortrancontiguous AND the
+ file_like object is not a real file object, this function will have to
+ copy data in memory.
Parameters

 fp : filelike object
 An open, writable file object or similar object with a `.write()`
+ fp : file_like object
+ An open, writable file object, or similar object with a ``.write()``
method.
 array : numpy.ndarray
+ array : ndarray
The array to write to disk.
version : (int, int), optional
 The version number of the format.
+ The version number of the format. Default: (1, 0)
Raises

@@ 386,7 +386,7 @@
If the array cannot be persisted.
Various other errors
If the array contains Python objects as part of its dtype, the
 process of pickling them may raise arbitrary errors if the objects
+ process of pickling them may raise various errors if the objects
are not picklable.
"""
@@ 418,13 +418,13 @@
Parameters

 fp : filelike object
 If this is not a real file object, then this may take extra memory and
 time.
+ fp : file_like object
+ If this is not a real file object, then this may take extra memory
+ and time.
Returns

 array : numpy.ndarray
+ array : ndarray
The array from the data on disk.
Raises
@@ 477,27 +477,31 @@
Parameters

filename : str
 The name of the file on disk. This may not be a filelike object.
+ The name of the file on disk. This may *not* be a filelike
+ object.
mode : str, optional
 The mode to open the file with. In addition to the standard file modes,
 'c' is also accepted to mean "copy on write". See `numpy.memmap` for
 the available mode strings.
 dtype : dtype, optional
+ The mode in which to open the file; the default is 'r+'. In
+ addition to the standard file modes, 'c' is also accepted to
+ mean "copy on write." See `memmap` for the available mode strings.
+ dtype : datatype, optional
The data type of the array if we are creating a new file in "write"
 mode.
 shape : tuple of int, optional
+ mode, if not, `dtype` is ignored. The default value is None,
+ which results in a datatype of `float64`.
+ shape : tuple of int
The shape of the array if we are creating a new file in "write"
 mode.
+ mode, in which case this parameter is required. Otherwise, this
+ parameter is ignored and is thus optional.
fortran_order : bool, optional
Whether the array should be Fortrancontiguous (True) or
 Ccontiguous (False) if we are creating a new file in "write" mode.
+ Ccontiguous (False, the default) if we are creating a new file
+ in "write" mode.
version : tuple of int (major, minor)
If the mode is a "write" mode, then this is the version of the file
 format used to create the file.
+ format used to create the file. Default: (1,0)
Returns

 marray : numpy.memmap
+ marray : memmap
The memorymapped array.
Raises
@@ 509,7 +513,7 @@
See Also

 numpy.memmap
+ memmap
"""
if not isinstance(filename, basestring):
Modified: branches/1.5.x/numpy/lib/function_base.py
===================================================================
 branches/1.5.x/numpy/lib/function_base.py 20100801 11:21:13 UTC (rev 8582)
+++ branches/1.5.x/numpy/lib/function_base.py 20100801 11:21:38 UTC (rev 8583)
@@ 29,9 +29,31 @@
from utils import deprecate
import numpy as np
#end Fernando's utilities
def iterable(y):
+ """
+ Check whether or not an object can be iterated over.
+
+ Parameters
+ 
+ y : object
+ Input object.
+
+ Returns
+ 
+ b : {0, 1}
+ Return 1 if the object has an iterator method or is a sequence,
+ and 0 otherwise.
+
+
+ Examples
+ 
+ >>> np.iterable([1, 2, 3])
+ 1
+ >>> np.iterable(2)
+ 0
+
+ """
try: iter(y)
except: return 0
return 1
@@ 1237,7 +1259,7 @@
"""
Change elements of an array based on conditional and input values.
 Similar to ``np.putmask(a, mask, vals)``, the difference is that `place`
+ Similar to ``np.putmask(arr, mask, vals)``, the difference is that `place`
uses the first N elements of `vals`, where N is the number of True values
in `mask`, while `putmask` uses the elements where `mask` is True.
@@ 1245,7 +1267,7 @@
Parameters

 a : array_like
+ arr : array_like
Array to put data into.
mask : array_like
Boolean mask array. Must have the same size as `a`.
@@ 1260,9 +1282,9 @@
Examples

 >>> x = np.arange(6).reshape(2, 3)
 >>> np.place(x, x>2, [44, 55])
 >>> x
+ >>> arr = np.arange(6).reshape(2, 3)
+ >>> np.place(arr, arr>2, [44, 55])
+ >>> arr
array([[ 0, 1, 2],
[44, 55, 44]])
@@ 1936,12 +1958,12 @@
Return correlation coefficients.
Please refer to the documentation for `cov` for more detail. The
 relationship between the correlation coefficient matrix, P, and the
 covariance matrix, C, is
+ relationship between the correlation coefficient matrix, `P`, and the
+ covariance matrix, `C`, is
.. math:: P_{ij} = \\frac{ C_{ij} } { \\sqrt{ C_{ii} * C_{jj} } }
 The values of P are between 1 and 1.
+ The values of `P` are between 1 and 1, inclusive.
Parameters

@@ 1989,22 +2011,22 @@
"""
Return the Blackman window.
 The Blackman window is a taper formed by using the the first
 three terms of a summation of cosines. It was designed to have close
 to the minimal leakage possible.
 It is close to optimal, only slightly worse than a Kaiser window.
+ The Blackman window is a taper formed by using the the first three
+ terms of a summation of cosines. It was designed to have close to the
+ minimal leakage possible. It is close to optimal, only slightly worse
+ than a Kaiser window.
Parameters

M : int
 Number of points in the output window. If zero or less, an
 empty array is returned.
+ Number of points in the output window. If zero or less, an empty
+ array is returned.
Returns

 out : array
 The window, normalized to one (the value one
 appears only if the number of samples is odd).
+ out : ndarray
+ The window, normalized to one (the value one appears only if the
+ number of samples is odd).
See Also

@@ 2016,7 +2038,6 @@
.. math:: w(n) = 0.42  0.5 \\cos(2\\pi n/M) + 0.08 \\cos(4\\pi n/M)

Most references to the Blackman window come from the signal processing
literature, where it is used as one of many windowing functions for
smoothing values. It is also known as an apodization (which means
@@ 2027,13 +2048,12 @@
References

 .. [1] Blackman, R.B. and Tukey, J.W., (1958) The measurement of power
 spectra, Dover Publications, New York.
 .. [2] Wikipedia, "Window function",
 http://en.wikipedia.org/wiki/Window_function
 .. [3] Oppenheim, A.V., and R.W. Schafer. DiscreteTime Signal Processing.
 Upper Saddle River, NJ: PrenticeHall, 1999, pp. 468471.
+ Blackman, R.B. and Tukey, J.W., (1958) The measurement of power spectra,
+ Dover Publications, New York.
+ Oppenheim, A.V., and R.W. Schafer. DiscreteTime Signal Processing.
+ Upper Saddle River, NJ: PrenticeHall, 1999, pp. 468471.
+
Examples

>>> from numpy import blackman
Modified: branches/1.5.x/numpy/lib/npyio.py
===================================================================
 branches/1.5.x/numpy/lib/npyio.py 20100801 11:21:13 UTC (rev 8582)
+++ branches/1.5.x/numpy/lib/npyio.py 20100801 11:21:38 UTC (rev 8583)
@@ 367,7 +367,7 @@
def savez(file, *args, **kwds):
"""
 Save several arrays into a single, compressed file in ``.npz`` format.
+ Save several arrays into a single, archive file in ``.npz`` format.
If arguments are passed in with no keywords, the corresponding variable
names, in the .npz file, are 'arr_0', 'arr_1', etc. If keyword arguments
@@ 401,8 +401,9 @@
Notes

The ``.npz`` file format is a zipped archive of files named after the
 variables they contain. Each file contains one variable in ``.npy``
 format. For a description of the ``.npy`` format, see `format`.
+ variables they contain. The archive is not compressed and each file
+ in the archive contains one variable in ``.npy`` format. For a
+ description of the ``.npy`` format, see `format`.
When opening the saved ``.npz`` file with `load` a `NpzFile` object is
returned. This is a dictionarylike object which can be queried for
@@ 509,30 +510,32 @@
fname : file or str
File or filename to read. If the filename extension is ``.gz`` or
``.bz2``, the file is first decompressed.
 dtype : dtype, optional
 Data type of the resulting array. If this is a record datatype,
 the resulting array will be 1dimensional, and each row will be
 interpreted as an element of the array. In this case, the number
 of columns used must match the number of fields in the datatype.
+ dtype : datatype, optional
+ Datatype of the resulting array; default: float. If this is a record
+ datatype, the resulting array will be 1dimensional, and each row
+ will be interpreted as an element of the array. In this case, the
+ number of columns used must match the number of fields in the
+ datatype.
comments : str, optional
 The character used to indicate the start of a comment.
+ The character used to indicate the start of a comment; default: '#'.
delimiter : str, optional
The string used to separate values. By default, this is any
whitespace.
converters : dict, optional
A dictionary mapping column number to a function that will convert
that column to a float. E.g., if column 0 is a date string:
 ``converters = {0: datestr2num}``. Converters can also be used to
+ ``converters = {0: datestr2num}``. Converters can also be used to
provide a default value for missing data:
 ``converters = {3: lambda s: float(s or 0)}``.
+ ``converters = {3: lambda s: float(s or 0)}``. Default: None.
skiprows : int, optional
 Skip the first `skiprows` lines.
+ Skip the first `skiprows` lines; default: 0.
usecols : sequence, optional
Which columns to read, with 0 being the first. For example,
``usecols = (1,4,5)`` will extract the 2nd, 5th and 6th columns.
+ The default, None, results in all columns being read.
unpack : bool, optional
If True, the returned array is transposed, so that arguments may be
 unpacked using ``x, y, z = loadtxt(...)``. Default is False.
+ unpacked using ``x, y, z = loadtxt(...)``. The default is False.
Returns

@@ 543,11 +546,11 @@

load, fromstring, fromregex
genfromtxt : Load data with missing values handled as specified.
 scipy.io.loadmat : reads Matlab(R) data files
+ scipy.io.loadmat : reads MATLAB data files
Notes

 This function aims to be a fast reader for simply formatted files. The
+ This function aims to be a fast reader for simply formatted files. The
`genfromtxt` function provides more sophisticated handling of, e.g.,
lines with missing values.
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