diff options
Diffstat (limited to 'numpy/lib/scimath.py')
| -rw-r--r-- | numpy/lib/scimath.py | 83 |
1 files changed, 60 insertions, 23 deletions
diff --git a/numpy/lib/scimath.py b/numpy/lib/scimath.py index e07caf805..5ac790ce9 100644 --- a/numpy/lib/scimath.py +++ b/numpy/lib/scimath.py @@ -20,6 +20,7 @@ from __future__ import division, absolute_import, print_function import numpy.core.numeric as nx import numpy.core.numerictypes as nt from numpy.core.numeric import asarray, any +from numpy.core.overrides import array_function_dispatch from numpy.lib.type_check import isreal @@ -58,7 +59,7 @@ def _tocomplex(arr): >>> a = np.array([1,2,3],np.short) >>> ac = np.lib.scimath._tocomplex(a); ac - array([ 1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64) + array([1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64) >>> ac.dtype dtype('complex64') @@ -69,7 +70,7 @@ def _tocomplex(arr): >>> b = np.array([1,2,3],np.double) >>> bc = np.lib.scimath._tocomplex(b); bc - array([ 1.+0.j, 2.+0.j, 3.+0.j]) + array([1.+0.j, 2.+0.j, 3.+0.j]) >>> bc.dtype dtype('complex128') @@ -80,13 +81,13 @@ def _tocomplex(arr): >>> c = np.array([1,2,3],np.csingle) >>> cc = np.lib.scimath._tocomplex(c); cc - array([ 1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64) + array([1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64) >>> c *= 2; c - array([ 2.+0.j, 4.+0.j, 6.+0.j], dtype=complex64) + array([2.+0.j, 4.+0.j, 6.+0.j], dtype=complex64) >>> cc - array([ 1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64) + array([1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64) """ if issubclass(arr.dtype.type, (nt.single, nt.byte, nt.short, nt.ubyte, nt.ushort, nt.csingle)): @@ -94,6 +95,7 @@ def _tocomplex(arr): else: return arr.astype(nt.cdouble) + def _fix_real_lt_zero(x): """Convert `x` to complex if it has real, negative components. @@ -121,6 +123,7 @@ def _fix_real_lt_zero(x): x = _tocomplex(x) return x + def _fix_int_lt_zero(x): """Convert `x` to double if it has real, negative components. @@ -147,6 +150,7 @@ def _fix_int_lt_zero(x): x = x * 1.0 return x + def _fix_real_abs_gt_1(x): """Convert `x` to complex if it has real components x_i with abs(x_i)>1. @@ -166,13 +170,19 @@ def _fix_real_abs_gt_1(x): array([0, 1]) >>> np.lib.scimath._fix_real_abs_gt_1([0,2]) - array([ 0.+0.j, 2.+0.j]) + array([0.+0.j, 2.+0.j]) """ x = asarray(x) if any(isreal(x) & (abs(x) > 1)): x = _tocomplex(x) return x + +def _unary_dispatcher(x): + return (x,) + + +@array_function_dispatch(_unary_dispatcher) def sqrt(x): """ Compute the square root of x. @@ -202,19 +212,21 @@ def sqrt(x): >>> np.lib.scimath.sqrt(1) 1.0 >>> np.lib.scimath.sqrt([1, 4]) - array([ 1., 2.]) + array([1., 2.]) But it automatically handles negative inputs: >>> np.lib.scimath.sqrt(-1) - (0.0+1.0j) + 1j >>> np.lib.scimath.sqrt([-1,4]) - array([ 0.+1.j, 2.+0.j]) + array([0.+1.j, 2.+0.j]) """ x = _fix_real_lt_zero(x) return nx.sqrt(x) + +@array_function_dispatch(_unary_dispatcher) def log(x): """ Compute the natural logarithm of `x`. @@ -261,6 +273,8 @@ def log(x): x = _fix_real_lt_zero(x) return nx.log(x) + +@array_function_dispatch(_unary_dispatcher) def log10(x): """ Compute the logarithm base 10 of `x`. @@ -303,12 +317,18 @@ def log10(x): 1.0 >>> np.emath.log10([-10**1, -10**2, 10**2]) - array([ 1.+1.3644j, 2.+1.3644j, 2.+0.j ]) + array([1.+1.3644j, 2.+1.3644j, 2.+0.j ]) """ x = _fix_real_lt_zero(x) return nx.log10(x) + +def _logn_dispatcher(n, x): + return (n, x,) + + +@array_function_dispatch(_logn_dispatcher) def logn(n, x): """ Take log base n of x. @@ -318,8 +338,8 @@ def logn(n, x): Parameters ---------- - n : int - The base in which the log is taken. + n : array_like + The integer base(s) in which the log is taken. x : array_like The value(s) whose log base `n` is (are) required. @@ -334,15 +354,17 @@ def logn(n, x): >>> np.set_printoptions(precision=4) >>> np.lib.scimath.logn(2, [4, 8]) - array([ 2., 3.]) + array([2., 3.]) >>> np.lib.scimath.logn(2, [-4, -8, 8]) - array([ 2.+4.5324j, 3.+4.5324j, 3.+0.j ]) + array([2.+4.5324j, 3.+4.5324j, 3.+0.j ]) """ x = _fix_real_lt_zero(x) n = _fix_real_lt_zero(n) return nx.log(x)/nx.log(n) + +@array_function_dispatch(_unary_dispatcher) def log2(x): """ Compute the logarithm base 2 of `x`. @@ -383,12 +405,18 @@ def log2(x): >>> np.emath.log2(8) 3.0 >>> np.emath.log2([-4, -8, 8]) - array([ 2.+4.5324j, 3.+4.5324j, 3.+0.j ]) + array([2.+4.5324j, 3.+4.5324j, 3.+0.j ]) """ x = _fix_real_lt_zero(x) return nx.log2(x) + +def _power_dispatcher(x, p): + return (x, p) + + +@array_function_dispatch(_power_dispatcher) def power(x, p): """ Return x to the power p, (x**p). @@ -423,15 +451,17 @@ def power(x, p): >>> np.lib.scimath.power([2, 4], 2) array([ 4, 16]) >>> np.lib.scimath.power([2, 4], -2) - array([ 0.25 , 0.0625]) + array([0.25 , 0.0625]) >>> np.lib.scimath.power([-2, 4], 2) - array([ 4.+0.j, 16.+0.j]) + array([ 4.-0.j, 16.+0.j]) """ x = _fix_real_lt_zero(x) p = _fix_int_lt_zero(p) return nx.power(x, p) + +@array_function_dispatch(_unary_dispatcher) def arccos(x): """ Compute the inverse cosine of x. @@ -469,12 +499,14 @@ def arccos(x): 0.0 >>> np.emath.arccos([1,2]) - array([ 0.-0.j , 0.+1.317j]) + array([0.-0.j , 0.-1.317j]) """ x = _fix_real_abs_gt_1(x) return nx.arccos(x) + +@array_function_dispatch(_unary_dispatcher) def arcsin(x): """ Compute the inverse sine of x. @@ -513,12 +545,14 @@ def arcsin(x): 0.0 >>> np.emath.arcsin([0,1]) - array([ 0. , 1.5708]) + array([0. , 1.5708]) """ x = _fix_real_abs_gt_1(x) return nx.arcsin(x) + +@array_function_dispatch(_unary_dispatcher) def arctanh(x): """ Compute the inverse hyperbolic tangent of `x`. @@ -555,11 +589,14 @@ def arctanh(x): -------- >>> np.set_printoptions(precision=4) - >>> np.emath.arctanh(np.matrix(np.eye(2))) - array([[ Inf, 0.], - [ 0., Inf]]) + >>> from numpy.testing import suppress_warnings + >>> with suppress_warnings() as sup: + ... sup.filter(RuntimeWarning) + ... np.emath.arctanh(np.eye(2)) + array([[inf, 0.], + [ 0., inf]]) >>> np.emath.arctanh([1j]) - array([ 0.+0.7854j]) + array([0.+0.7854j]) """ x = _fix_real_abs_gt_1(x) |