8000 ENH: Add dtype parameter to linspace and logspace functions. by jjhelmus · Pull Request #3482 · numpy/numpy · GitHub
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ENH: Add dtype parameter to linspace and logspace functions. #3482

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Merged
merged 1 commit into from
Sep 16, 2013
Merged

ENH: Add dtype parameter to linspace and logspace functions. #3482

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5 changes: 5 additions & 0 deletions doc/release/1.9.0-notes.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,10 @@ functions (ufuncs), ``numpy.core._dotblas.dot``, and
``numpy.core.multiarray.dot`` (the numpy.dot functions). By defining a
``__numpy_ufunc__`` method.

Dtype parameter added to `np.linspace` and `np.logspace`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The returned data type from the `linspace` and `logspace` functions
can now be specificed using the dtype parameter.

Improvements
============
Expand All @@ -39,6 +43,7 @@ Improvements
Changes
=======


C-API
~~~~~

Expand Down
36 changes: 25 additions & 11 deletions numpy/core/function_base.py
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Expand Up @@ -3,9 +3,10 @@
__all__ = ['logspace', 'linspace']

from . import numeric as _nx
from .numeric import array
from .numeric import array, result_type

def linspace(start, stop, num=50, endpoint=True, retstep=False):

def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None):
"""
Return evenly spaced numbers over a specified interval.

Expand All @@ -31,6 +32,9 @@ def linspace(start, stop, num=50, endpoint=True, retstep=False):
retstep : bool, optional
If True, return (`samples`, `step`), where `step` is the spacing
between samples.
dtype : dtype
The type of the output array. If `dtype` is not given, infer the data
type from the other input arguments.

Returns
-------
Expand Down Expand Up @@ -74,23 +78,28 @@ def linspace(start, stop, num=50, endpoint=True, retstep=False):

"""
num = int(num)

if dtype is None:
dtype = result_type(start, stop, float(num))

if num <= 0:
return array([], float)
return array([], dtype)
if endpoint:
if num == 1:
return array([float(start)])
return array([start], dtype=dtype)
step = (stop-start)/float((num-1))
y = _nx.arange(0, num) * step + start
y = _nx.arange(0, num, dtype=dtype) * step + start
y[-1] = stop
else:
step = (stop-start)/float(num)
y = _nx.arange(0, num) * step + start
y = _nx.arange(0, num, dtype=dtype) * step + start
if retstep:
return y, step
return y.astype(dtype), step
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After double checking, this seems not quite right. dtype(None) == np.float64 in other words, this casts to float no matter what the input is if None is given, which disagrees with the documentation.

else:
return y
return y.astype(dtype)


def logspace(start,stop,num=50,endpoint=True,base=10.0):
def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None):
"""
Return numbers spaced evenly on a log scale.

Expand All @@ -116,6 +125,9 @@ def logspace(start,stop,num=50,endpoint=True,base=10.0):
The base of the log space. The step size between the elements in
``ln(samples) / ln(base)`` (or ``log_base(samples)``) is uniform.
Default is 10.0.
dtype : dtype
The type of the output array. If `dtype` is not given, infer the data
type from the other input arguments.

Returns
-------
Expand All @@ -136,7 +148,7 @@ def logspace(start,stop,num=50,endpoint=True,base=10.0):

>>> y = np.linspace(start, stop, num=num, endpoint=endpoint)
... # doctest: +SKIP
>>> power(base, y)
>>> power(base, y).astype(dtype)
... # doctest: +SKIP

Examples
Expand Down Expand Up @@ -165,4 +177,6 @@ def logspace(start,stop,num=50,endpoint=True,base=10.0):

"""
y = linspace(start, stop, num=num, endpoint=endpoint)
return _nx.power(base, y)
if dtype is None:
return _nx.power(base, y)
return _nx.power(base, y).astype(dtype)
30 changes: 25 additions & 5 deletions numpy/core/tests/test_function_base.py
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@@ -1,23 +1,35 @@
from __future__ import division, absolute_import, print_function

from numpy.testing import *
from numpy import logspace, linspace
from numpy import logspace, linspace, dtype


class TestLogspace(TestCase):

def test_basic(self):
y = logspace(0, 6)
assert_(len(y)==50)
assert_(len(y) == 50)
y = logspace(0, 6, num=100)
assert_(y[-1] == 10**6)
assert_(y[-1] == 10 ** 6)
y = logspace(0, 6, endpoint=0)
assert_(y[-1] < 10**6)
assert_(y[-1] < 10 ** 6)
y = logspace(0, 6, num=7)
assert_array_equal(y, [1, 10, 100, 1e3, 1e4, 1e5, 1e6])

def test_dtype(self):
y = logspace(0, 6, dtype='float32')
assert_equal(y.dtype, dtype('float32'))
y = logspace(0, 6, dtype='float64')
assert_equal(y.dtype, dtype('float64'))
y = logspace(0, 6, dtype='int32')
assert_equal(y.dtype, dtype('int32'))


class TestLinspace(TestCase):

def test_basic(self):
y = linspace(0, 10)
assert_(len(y)==50)
assert_(len(y) == 50)
y = linspace(2, 10, num=100)
assert_(y[-1] == 10)
y = linspace(2, 10, endpoint=0)
Expand All @@ -35,3 +47,11 @@ def test_type(self):
t3 = linspace(0, 1, 2).dtype
assert_equal(t1, t2)
assert_equal(t2, t3)

def test_dtype(self):
y = linspace(0, 6, dtype='float32')
assert_equal(y.dtype, dtype('float32'))
y = linspace(0, 6, dtype='float64')
assert_equal(y.dtype, dtype('float64'))
y = linspace(0, 6, dtype='int32')
assert_equal(y.dtype, dtype('int32'))
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