diff options
| -rw-r--r-- | numpy/core/__init__.py | 2 | ||||
| -rw-r--r-- | numpy/core/function_base.py | 159 | ||||
| -rw-r--r-- | numpy/core/tests/test_function_base.py | 37 | ||||
| -rw-r--r-- | numpy/lib/function_base.py | 158 | ||||
| -rw-r--r-- | numpy/lib/tests/test_function_base.py | 36 | ||||
| -rw-r--r-- | numpy/lib/tests/test_index_tricks.py | 5 |
6 files changed, 205 insertions, 192 deletions
diff --git a/numpy/core/__init__.py b/numpy/core/__init__.py index b7f5f2cb9..39ce94ac4 100644 --- a/numpy/core/__init__.py +++ b/numpy/core/__init__.py @@ -16,6 +16,7 @@ from records import * from memmap import * from defchararray import * import scalarmath +from function_base import * del nt from fromnumeric import amax as max, amin as min, \ @@ -27,6 +28,7 @@ __all__ += numeric.__all__ __all__ += fromnumeric.__all__ __all__ += rec.__all__ __all__ += char.__all__ +__all__ += function_base.__all__ from numpy.testing import Tester diff --git a/numpy/core/function_base.py b/numpy/core/function_base.py new file mode 100644 index 000000000..33cf3a15b --- /dev/null +++ b/numpy/core/function_base.py @@ -0,0 +1,159 @@ +__all__ = ['logspace', 'linspace'] + +import numeric as _nx +from numeric import array + +def linspace(start, stop, num=50, endpoint=True, retstep=False): + """ + Return evenly spaced numbers over a specified interval. + + Returns `num` evenly spaced samples, calculated over the + interval [`start`, `stop` ]. + + The endpoint of the interval can optionally be excluded. + + Parameters + ---------- + start : scalar + The starting value of the sequence. + stop : scalar + The end value of the sequence, unless `endpoint` is set to False. + In that case, the sequence consists of all but the last of ``num + 1`` + evenly spaced samples, so that `stop` is excluded. Note that the step + size changes when `endpoint` is False. + num : int, optional + Number of samples to generate. Default is 50. + endpoint : bool, optional + If True, `stop` is the last sample. Otherwise, it is not included. + Default is True. + retstep : bool, optional + If True, return (`samples`, `step`), where `step` is the spacing + between samples. + + Returns + ------- + samples : ndarray + There are `num` equally spaced samples in the closed interval + ``[start, stop]`` or the half-open interval ``[start, stop)`` + (depending on whether `endpoint` is True or False). + step : float (only if `retstep` is True) + Size of spacing between samples. + + + See Also + -------- + arange : Similiar to `linspace`, but uses a step size (instead of the + number of samples). + logspace : Samples uniformly distributed in log space. + + Examples + -------- + >>> np.linspace(2.0, 3.0, num=5) + array([ 2. , 2.25, 2.5 , 2.75, 3. ]) + >>> np.linspace(2.0, 3.0, num=5, endpoint=False) + array([ 2. , 2.2, 2.4, 2.6, 2.8]) + >>> np.linspace(2.0, 3.0, num=5, retstep=True) + (array([ 2. , 2.25, 2.5 , 2.75, 3. ]), 0.25) + + Graphical illustration: + + >>> import matplotlib.pyplot as plt + >>> N = 8 + >>> y = np.zeros(N) + >>> x1 = np.linspace(0, 10, N, endpoint=True) + >>> x2 = np.linspace(0, 10, N, endpoint=False) + >>> plt.plot(x1, y, 'o') + >>> plt.plot(x2, y + 0.5, 'o') + >>> plt.ylim([-0.5, 1]) + >>> plt.show() + + """ + num = int(num) + if num <= 0: + return array([], float) + if endpoint: + if num == 1: + return array([float(start)]) + step = (stop-start)/float((num-1)) + y = _nx.arange(0, num) * step + start + y[-1] = stop + else: + step = (stop-start)/float(num) + y = _nx.arange(0, num) * step + start + if retstep: + return y, step + else: + return y + +def logspace(start,stop,num=50,endpoint=True,base=10.0): + """ + Return numbers spaced evenly on a log scale. + + In linear space, the sequence starts at ``base ** start`` + (`base` to the power of `start`) and ends with ``base ** stop`` + (see `endpoint` below). + + Parameters + ---------- + start : float + ``base ** start`` is the starting value of the sequence. + stop : float + ``base ** stop`` is the final value of the sequence, unless `endpoint` + is False. In that case, ``num + 1`` values are spaced over the + interval in log-space, of which all but the last (a sequence of + length ``num``) are returned. + num : integer, optional + Number of samples to generate. Default is 50. + endpoint : boolean, optional + If true, `stop` is the last sample. Otherwise, it is not included. + Default is True. + base : float, optional + 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. + + Returns + ------- + samples : ndarray + `num` samples, equally spaced on a log scale. + + See Also + -------- + arange : Similiar to linspace, with the step size specified instead of the + number of samples. Note that, when used with a float endpoint, the + endpoint may or may not be included. + linspace : Similar to logspace, but with the samples uniformly distributed + in linear space, instead of log space. + + Notes + ----- + Logspace is equivalent to the code + + >>> y = linspace(start, stop, num=num, endpoint=endpoint) + >>> power(base, y) + + Examples + -------- + >>> np.logspace(2.0, 3.0, num=4) + array([ 100. , 215.443469 , 464.15888336, 1000. ]) + >>> np.logspace(2.0, 3.0, num=4, endpoint=False) + array([ 100. , 177.827941 , 316.22776602, 562.34132519]) + >>> np.logspace(2.0, 3.0, num=4, base=2.0) + array([ 4. , 5.0396842 , 6.34960421, 8. ]) + + Graphical illustration: + + >>> import matplotlib.pyplot as plt + >>> N = 10 + >>> x1 = np.logspace(0.1, 1, N, endpoint=True) + >>> x2 = np.logspace(0.1, 1, N, endpoint=False) + >>> y = np.zeros(N) + >>> plt.plot(x1, y, 'o') + >>> plt.plot(x2, y + 0.5, 'o') + >>> plt.ylim([-0.5, 1]) + >>> plt.show() + + """ + y = linspace(start,stop,num=num,endpoint=endpoint) + return _nx.power(base,y) + diff --git a/numpy/core/tests/test_function_base.py b/numpy/core/tests/test_function_base.py new file mode 100644 index 000000000..67ce8953f --- /dev/null +++ b/numpy/core/tests/test_function_base.py @@ -0,0 +1,37 @@ + +from numpy.testing import * +from numpy import logspace, linspace + +class TestLogspace(TestCase): + def test_basic(self): + y = logspace(0,6) + assert(len(y)==50) + y = logspace(0,6,num=100) + assert(y[-1] == 10**6) + y = logspace(0,6,endpoint=0) + assert(y[-1] < 10**6) + y = logspace(0,6,num=7) + assert_array_equal(y,[1,10,100,1e3,1e4,1e5,1e6]) + +class TestLinspace(TestCase): + def test_basic(self): + y = linspace(0,10) + assert(len(y)==50) + y = linspace(2,10,num=100) + assert(y[-1] == 10) + y = linspace(2,10,endpoint=0) + assert(y[-1] < 10) + + def test_corner(self): + y = list(linspace(0,1,1)) + assert y == [0.0], y + y = list(linspace(0,1,2.5)) + assert y == [0.0, 1.0] + + def test_type(self): + t1 = linspace(0,1,0).dtype + t2 = linspace(0,1,1).dtype + t3 = linspace(0,1,2).dtype + assert_equal(t1, t2) + assert_equal(t2, t3) + diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 663c3d2ef..2459ffc23 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -1,6 +1,5 @@ __docformat__ = "restructuredtext en" -__all__ = ['logspace', 'linspace', - 'select', 'piecewise', 'trim_zeros', +__all__ = ['select', 'piecewise', 'trim_zeros', 'copy', 'iterable', 'diff', 'gradient', 'angle', 'unwrap', 'sort_complex', 'disp', 'extract', 'place', 'nansum', 'nanmax', 'nanargmax', @@ -15,6 +14,7 @@ import warnings import types import numpy.core.numeric as _nx +from numpy.core import linspace from numpy.core.numeric import ones, zeros, arange, concatenate, array, \ asarray, asanyarray, empty, empty_like, ndarray, around from numpy.core.numeric import ScalarType, dot, where, newaxis, intp, \ @@ -33,160 +33,6 @@ import numpy as np #end Fernando's utilities -def linspace(start, stop, num=50, endpoint=True, retstep=False): - """ - Return evenly spaced numbers over a specified interval. - - Returns `num` evenly spaced samples, calculated over the - interval [`start`, `stop` ]. - - The endpoint of the interval can optionally be excluded. - - Parameters - ---------- - start : scalar - The starting value of the sequence. - stop : scalar - The end value of the sequence, unless `endpoint` is set to False. - In that case, the sequence consists of all but the last of ``num + 1`` - evenly spaced samples, so that `stop` is excluded. Note that the step - size changes when `endpoint` is False. - num : int, optional - Number of samples to generate. Default is 50. - endpoint : bool, optional - If True, `stop` is the last sample. Otherwise, it is not included. - Default is True. - retstep : bool, optional - If True, return (`samples`, `step`), where `step` is the spacing - between samples. - - Returns - ------- - samples : ndarray - There are `num` equally spaced samples in the closed interval - ``[start, stop]`` or the half-open interval ``[start, stop)`` - (depending on whether `endpoint` is True or False). - step : float (only if `retstep` is True) - Size of spacing between samples. - - - See Also - -------- - arange : Similiar to `linspace`, but uses a step size (instead of the - number of samples). - logspace : Samples uniformly distributed in log space. - - Examples - -------- - >>> np.linspace(2.0, 3.0, num=5) - array([ 2. , 2.25, 2.5 , 2.75, 3. ]) - >>> np.linspace(2.0, 3.0, num=5, endpoint=False) - array([ 2. , 2.2, 2.4, 2.6, 2.8]) - >>> np.linspace(2.0, 3.0, num=5, retstep=True) - (array([ 2. , 2.25, 2.5 , 2.75, 3. ]), 0.25) - - Graphical illustration: - - >>> import matplotlib.pyplot as plt - >>> N = 8 - >>> y = np.zeros(N) - >>> x1 = np.linspace(0, 10, N, endpoint=True) - >>> x2 = np.linspace(0, 10, N, endpoint=False) - >>> plt.plot(x1, y, 'o') - >>> plt.plot(x2, y + 0.5, 'o') - >>> plt.ylim([-0.5, 1]) - >>> plt.show() - - """ - num = int(num) - if num <= 0: - return array([], float) - if endpoint: - if num == 1: - return array([float(start)]) - step = (stop-start)/float((num-1)) - y = _nx.arange(0, num) * step + start - y[-1] = stop - else: - step = (stop-start)/float(num) - y = _nx.arange(0, num) * step + start - if retstep: - return y, step - else: - return y - -def logspace(start,stop,num=50,endpoint=True,base=10.0): - """ - Return numbers spaced evenly on a log scale. - - In linear space, the sequence starts at ``base ** start`` - (`base` to the power of `start`) and ends with ``base ** stop`` - (see `endpoint` below). - - Parameters - ---------- - start : float - ``base ** start`` is the starting value of the sequence. - stop : float - ``base ** stop`` is the final value of the sequence, unless `endpoint` - is False. In that case, ``num + 1`` values are spaced over the - interval in log-space, of which all but the last (a sequence of - length ``num``) are returned. - num : integer, optional - Number of samples to generate. Default is 50. - endpoint : boolean, optional - If true, `stop` is the last sample. Otherwise, it is not included. - Default is True. - base : float, optional - 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. - - Returns - ------- - samples : ndarray - `num` samples, equally spaced on a log scale. - - See Also - -------- - arange : Similiar to linspace, with the step size specified instead of the - number of samples. Note that, when used with a float endpoint, the - endpoint may or may not be included. - linspace : Similar to logspace, but with the samples uniformly distributed - in linear space, instead of log space. - - Notes - ----- - Logspace is equivalent to the code - - >>> y = linspace(start, stop, num=num, endpoint=endpoint) - >>> power(base, y) - - Examples - -------- - >>> np.logspace(2.0, 3.0, num=4) - array([ 100. , 215.443469 , 464.15888336, 1000. ]) - >>> np.logspace(2.0, 3.0, num=4, endpoint=False) - array([ 100. , 177.827941 , 316.22776602, 562.34132519]) - >>> np.logspace(2.0, 3.0, num=4, base=2.0) - array([ 4. , 5.0396842 , 6.34960421, 8. ]) - - Graphical illustration: - - >>> import matplotlib.pyplot as plt - >>> N = 10 - >>> x1 = np.logspace(0.1, 1, N, endpoint=True) - >>> x2 = np.logspace(0.1, 1, N, endpoint=False) - >>> y = np.zeros(N) - >>> plt.plot(x1, y, 'o') - >>> plt.plot(x2, y + 0.5, 'o') - >>> plt.ylim([-0.5, 1]) - >>> plt.show() - - """ - y = linspace(start,stop,num=num,endpoint=endpoint) - return _nx.power(base,y) - def iterable(y): try: iter(y) except: return 0 diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index cfb316074..8595c6b5c 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -134,42 +134,6 @@ class TestSelect(TestCase): assert_equal(len(choices),3) assert_equal(len(conditions),3) -class TestLogspace(TestCase): - def test_basic(self): - y = logspace(0,6) - assert(len(y)==50) - y = logspace(0,6,num=100) - assert(y[-1] == 10**6) - y = logspace(0,6,endpoint=0) - assert(y[-1] < 10**6) - y = logspace(0,6,num=7) - assert_array_equal(y,[1,10,100,1e3,1e4,1e5,1e6]) - -class TestLinspace(TestCase): - def test_basic(self): - y = linspace(0,10) - assert(len(y)==50) - y = linspace(2,10,num=100) - assert(y[-1] == 10) - y = linspace(2,10,endpoint=0) - assert(y[-1] < 10) - y,st = linspace(2,10,retstep=1) - assert_almost_equal(st,8/49.0) - assert_array_almost_equal(y,mgrid[2:10:50j],13) - - def test_corner(self): - y = list(linspace(0,1,1)) - assert y == [0.0], y - y = list(linspace(0,1,2.5)) - assert y == [0.0, 1.0] - - def test_type(self): - t1 = linspace(0,1,0).dtype - t2 = linspace(0,1,1).dtype - t3 = linspace(0,1,2).dtype - assert_equal(t1, t2) - assert_equal(t2, t3) - class TestInsert(TestCase): def test_basic(self): a = [1,2,3] diff --git a/numpy/lib/tests/test_index_tricks.py b/numpy/lib/tests/test_index_tricks.py index d7e61799a..3307cef3e 100644 --- a/numpy/lib/tests/test_index_tricks.py +++ b/numpy/lib/tests/test_index_tricks.py @@ -24,6 +24,11 @@ class TestGrid(TestCase): assert_almost_equal(b[-1],b[0]+19*0.1,11) assert_almost_equal(a[1]-a[0],2.0/9.0,11) + def test_linspace_equivalence(self): + y,st = np.linspace(2,10,retstep=1) + assert_almost_equal(st,8/49.0) + assert_array_almost_equal(y,mgrid[2:10:50j],13) + def test_nd(self): c = mgrid[-1:1:10j,-2:2:10j] d = mgrid[-1:1:0.1,-2:2:0.2] |