diff options
| -rw-r--r-- | numpy/add_newdocs.py | 14 | ||||
| -rw-r--r-- | numpy/lib/arrayterator.py | 29 | ||||
| -rw-r--r-- | numpy/lib/function_base.py | 2 | ||||
| -rw-r--r-- | numpy/lib/polynomial.py | 22 | ||||
| -rw-r--r-- | numpy/ma/core.py | 12 |
5 files changed, 61 insertions, 18 deletions
diff --git a/numpy/add_newdocs.py b/numpy/add_newdocs.py index 5b65d9ce1..62e656346 100644 --- a/numpy/add_newdocs.py +++ b/numpy/add_newdocs.py @@ -2605,9 +2605,15 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('astype', Parameters ---------- - t : string or dtype + t : str or dtype Typecode or data-type to which the array is cast. + Raises + ------ + ComplexWarning : + When casting from complex to float or int. To avoid this, + one should use ``a.real.astype(t)``. + Examples -------- >>> x = np.array([1, 2, 2.5]) @@ -4297,8 +4303,9 @@ add_newdoc('numpy.lib._compiled_base', 'bincount', Input array. weights : array_like, optional Weights, array of the same shape as `x`. - minlength : integer, optional + minlength : int, optional .. versionadded:: 1.6.0 + A minimum number of bins for the output array. Returns @@ -4330,6 +4337,9 @@ add_newdoc('numpy.lib._compiled_base', 'bincount', >>> np.bincount(x).size == np.amax(x)+1 True + The input array needs to be of integer dtype, otherwise a + TypeError is raised: + >>> np.bincount(np.arange(5, dtype=np.float)) Traceback (most recent call last): File "<stdin>", line 1, in <module> diff --git a/numpy/lib/arrayterator.py b/numpy/lib/arrayterator.py index 3f07cd263..2df05e514 100644 --- a/numpy/lib/arrayterator.py +++ b/numpy/lib/arrayterator.py @@ -141,12 +141,41 @@ class Arrayterator(object): @property def flat(self): + """ + A 1-D flat iterator for Arrayterator objects. + + This iterator returns elements of the array to be iterated over in + `Arrayterator` one by one. It is similar to `flatiter`. + + See Also + -------- + `Arrayterator` + flatiter + + Examples + -------- + >>> a = np.arange(3 * 4 * 5 * 6).reshape(3, 4, 5, 6) + >>> a_itor = np.lib.arrayterator.Arrayterator(a, 2) + + >>> for subarr in a_itor.flat: + ... if not subarr: + ... print subarr, type(subarr) + ... + 0 <type 'numpy.int32'> + + """ for block in self: for value in block.flat: yield value @property def shape(self): + """ + The shape of the array to be iterated over. + + For an example, see `Arrayterator`. + + """ return tuple(((stop-start-1)//step+1) for start, stop, step in zip(self.start, self.stop, self.step)) diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 292dbe41d..033e18f8e 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -99,7 +99,7 @@ def histogram(a, bins=10, range=None, normed=False, weights=None): See Also -------- - histogramdd, bincount, searchsorted + histogramdd, bincount, searchsorted, digitize Notes ----- diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py index 603655ec2..f3146d691 100644 --- a/numpy/lib/polynomial.py +++ b/numpy/lib/polynomial.py @@ -151,13 +151,14 @@ def roots(p): Return the roots of a polynomial with coefficients given in p. The values in the rank-1 array `p` are coefficients of a polynomial. - If the length of `p` is n+1 then the polynomial is described by - p[0] * x**n + p[1] * x**(n-1) + ... + p[n-1]*x + p[n] + If the length of `p` is n+1 then the polynomial is described by:: + + p[0] * x**n + p[1] * x**(n-1) + ... + p[n-1]*x + p[n] Parameters ---------- - p : array_like of shape(M,) - Rank-1 array of polynomial co-efficients. + p : array_like + Rank-1 array of polynomial coefficients. Returns ------- @@ -166,32 +167,29 @@ def roots(p): Raises ------ - ValueError: + ValueError : When `p` cannot be converted to a rank-1 array. See also -------- - - poly : Find the coefficients of a polynomial with - a given sequence of roots. + poly : Find the coefficients of a polynomial with a given sequence + of roots. polyval : Evaluate a polynomial at a point. polyfit : Least squares polynomial fit. poly1d : A one-dimensional polynomial class. Notes ----- - The algorithm relies on computing the eigenvalues of the companion matrix [1]_. References ---------- - .. [1] Wikipedia, "Companion matrix", - http://en.wikipedia.org/wiki/Companion_matrix + .. [1] R. A. Horn & C. R. Johnson, *Matrix Analysis*. Cambridge, UK: + Cambridge University Press, 1999, pp. 146-7. Examples -------- - >>> coeff = [3.2, 2, 1] >>> np.roots(coeff) array([-0.3125+0.46351241j, -0.3125-0.46351241j]) diff --git a/numpy/ma/core.py b/numpy/ma/core.py index 673cfb1ab..48ed424ff 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -2580,9 +2580,9 @@ class MaskedArray(ndarray): Construction:: - x = MaskedArray(data, mask=nomask, dtype=None, copy=True, - fill_value=None, keep_mask=True, hard_mask=False, - shrink=True) + x = MaskedArray(data, mask=nomask, dtype=None, + copy=False, subok=True, ndmin=0, fill_value=None, + keep_mask=True, hard_mask=None, flag=None, shrink=True) Parameters ---------- @@ -3373,6 +3373,12 @@ class MaskedArray(ndarray): The value to use for invalid entries (None by default). If None, the `fill_value` attribute of the array is used instead. + Returns + ------- + filled_array : ndarray + A copy of ``self`` with invalid entries replaced by *fill_value* + (be it the function argument or the attribute of ``self``. + Notes ----- The result is **not** a MaskedArray! |