diff options
| -rw-r--r-- | numpy/lib/format.py | 52 | ||||
| -rw-r--r-- | numpy/lib/function_base.py | 70 | ||||
| -rw-r--r-- | numpy/lib/npyio.py | 33 |
3 files changed, 91 insertions, 64 deletions
diff --git a/numpy/lib/format.py b/numpy/lib/format.py index 395460315..1e508f3e5 100644 --- a/numpy/lib/format.py +++ b/numpy/lib/format.py @@ -366,19 +366,19 @@ def write_array(fp, array, version=(1,0)): """ Write an array to an NPY file, including a header. - If the array is neither C-contiguous or Fortran-contiguous 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 C-contiguous nor Fortran-contiguous 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 @@ def write_array(fp, array, version=(1,0)): 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 @@ def read_array(fp): 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 @@ def open_memmap(filename, mode='r+', dtype=None, shape=None, Parameters ---------- filename : str - The name of the file on disk. This may not be a file-like object. + The name of the file on disk. This may *not* be a file-like + 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 : data-type, 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 data-type 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 Fortran-contiguous (True) or - C-contiguous (False) if we are creating a new file in "write" mode. + C-contiguous (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 memory-mapped array. Raises @@ -509,7 +513,7 @@ def open_memmap(filename, mode='r+', dtype=None, shape=None, See Also -------- - numpy.memmap + memmap """ if not isinstance(filename, basestring): diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 7610c2db3..a1c4cae4b 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -29,9 +29,31 @@ from arraysetops import setdiff1d 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 @@ def place(arr, mask, vals): """ 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 @@ def place(arr, mask, vals): 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 @@ def place(arr, mask, vals): 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 @@ def corrcoef(x, y=None, rowvar=1, bias=0, ddof=None): 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 @@ def blackman(M): """ 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 @@ def blackman(M): .. 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 @@ -2027,12 +2048,11 @@ def blackman(M): 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. Discrete-Time Signal Processing. - Upper Saddle River, NJ: Prentice-Hall, 1999, pp. 468-471. + Blackman, R.B. and Tukey, J.W., (1958) The measurement of power spectra, + Dover Publications, New York. + + Oppenheim, A.V., and R.W. Schafer. Discrete-Time Signal Processing. + Upper Saddle River, NJ: Prentice-Hall, 1999, pp. 468-471. Examples -------- diff --git a/numpy/lib/npyio.py b/numpy/lib/npyio.py index b70807f32..3881c8882 100644 --- a/numpy/lib/npyio.py +++ b/numpy/lib/npyio.py @@ -367,7 +367,7 @@ def save(file, arr): 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 @@ def savez(file, *args, **kwds): 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 dictionary-like object which can be queried for @@ -509,30 +510,32 @@ def loadtxt(fname, dtype=float, comments='#', delimiter=None, 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 data-type, - the resulting array will be 1-dimensional, 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 data-type. + dtype : data-type, optional + Data-type of the resulting array; default: float. If this is a record + data-type, the resulting array will be 1-dimensional, 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 + data-type. 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 @@ def loadtxt(fname, dtype=float, comments='#', delimiter=None, -------- 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. |