Python numpy.ScalarType() Examples
The following are 30 code examples for showing how to use numpy.ScalarType(). These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.
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Example 1
| Project: recruit Author: Frank-qlu File: test_classes.py License: Apache License 2.0 | 6 votes |
|
def test_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 2
| Project: auto-alt-text-lambda-api Author: abhisuri97 File: test_classes.py License: MIT License | 6 votes |
|
def check_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 3
| Project: vnpy_crypto Author: birforce File: test_classes.py License: MIT License | 6 votes |
|
def check_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 4
| Project: Computable Author: ktraunmueller File: test_distributions.py License: MIT License | 6 votes |
|
def test_rvs(self):
vals = stats.randint.rvs(5,30,size=100)
assert_(numpy.all(vals < 30) & numpy.all(vals >= 5))
assert_(len(vals) == 100)
vals = stats.randint.rvs(5,30,size=(2,50))
assert_(numpy.shape(vals) == (2,50))
assert_(vals.dtype.char in typecodes['AllInteger'])
val = stats.randint.rvs(15,46)
assert_((val >= 15) & (val < 46))
assert_(isinstance(val, numpy.ScalarType), msg=repr(type(val)))
val = stats.randint(15,46).rvs(3)
assert_(val.dtype.char in typecodes['AllInteger'])
Example 5
| Project: Mastering-Elasticsearch-7.0 Author: PacktPublishing File: test_classes.py License: MIT License | 6 votes |
|
def test_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 6
| Project: GraphicDesignPatternByPython Author: Relph1119 File: test_classes.py License: MIT License | 6 votes |
|
def test_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 7
| Project: predictive-maintenance-using-machine-learning Author: awslabs File: test_classes.py License: Apache License 2.0 | 6 votes |
|
def test_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 8
| Project: pySINDy Author: luckystarufo File: test_classes.py License: MIT License | 6 votes |
|
def test_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 9
| Project: mxnet-lambda Author: awslabs File: test_classes.py License: Apache License 2.0 | 6 votes |
|
def check_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 10
| Project: ImageFusion Author: pfchai File: test_classes.py License: MIT License | 6 votes |
|
def check_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 11
| Project: dowel Author: rlworkgroup File: tensor_board_output.py License: MIT License | 6 votes |
|
def _record_tabular(self, data, step):
if self._x_axis:
nonexist_axes = []
for axis in [self._x_axis] + self._additional_x_axes:
if axis not in data.as_dict:
nonexist_axes.append(axis)
if nonexist_axes:
self._warn('{} {} exist in the tabular data.'.format(
', '.join(nonexist_axes),
'do not' if len(nonexist_axes) > 1 else 'does not'))
for key, value in data.as_dict.items():
if isinstance(value,
np.ScalarType) and self._x_axis in data.as_dict:
if self._x_axis is not key:
x = data.as_dict[self._x_axis]
self._record_kv(key, value, x)
for axis in self._additional_x_axes:
if key is not axis and key in data.as_dict:
x = data.as_dict[axis]
self._record_kv('{}/{}'.format(key, axis), value, x)
else:
self._record_kv(key, value, step)
data.mark(key)
Example 12
| Project: elasticintel Author: securityclippy File: test_classes.py License: GNU General Public License v3.0 | 6 votes |
|
def check_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 13
| Project: coffeegrindsize Author: jgagneastro File: test_classes.py License: MIT License | 6 votes |
|
def test_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 14
| Project: Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda Author: PacktPublishing File: test_classes.py License: MIT License | 6 votes |
|
def test_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 15
| Project: twitter-stock-recommendation Author: alvarobartt File: test_classes.py License: MIT License | 6 votes |
|
def test_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 16
| Project: keras-lambda Author: sunilmallya File: test_classes.py License: MIT License | 6 votes |
|
def check_truediv(Poly):
# true division is valid only if the denominator is a Number and
# not a python bool.
p1 = Poly([1,2,3])
p2 = p1 * 5
for stype in np.ScalarType:
if not issubclass(stype, Number) or issubclass(stype, bool):
continue
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in (int, long, float):
s = stype(5)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for stype in [complex]:
s = stype(5, 0)
assert_poly_almost_equal(op.truediv(p2, s), p1)
assert_raises(TypeError, op.truediv, s, p2)
for s in [tuple(), list(), dict(), bool(), np.array([1])]:
assert_raises(TypeError, op.truediv, p2, s)
assert_raises(TypeError, op.truediv, s, p2)
for ptype in classes:
assert_raises(TypeError, op.truediv, p2, ptype(1))
Example 17
| Project: GraphicDesignPatternByPython Author: Relph1119 File: test_distributions.py License: MIT License | 5 votes |
|
def test_rvs(self):
vals = stats.randint.rvs(5, 30, size=100)
assert_(numpy.all(vals < 30) & numpy.all(vals >= 5))
assert_(len(vals) == 100)
vals = stats.randint.rvs(5, 30, size=(2, 50))
assert_(numpy.shape(vals) == (2, 50))
assert_(vals.dtype.char in typecodes['AllInteger'])
val = stats.randint.rvs(15, 46)
assert_((val >= 15) & (val < 46))
assert_(isinstance(val, numpy.ScalarType), msg=repr(type(val)))
val = stats.randint(15, 46).rvs(3)
assert_(val.dtype.char in typecodes['AllInteger'])
Example 18
| Project: cupy Author: cupy File: test_fallback.py License: MIT License | 5 votes |
|
def numpy_fallback_array_equal(name='xp'):
"""
Decorator that checks fallback_mode results are equal to NumPy ones.
Checks ndarrays.
Args:
name(str): Argument name whose value is either
``numpy`` or ``cupy`` module.
"""
def decorator(impl):
@functools.wraps(impl)
def test_func(self, *args, **kwargs):
kwargs[name] = fallback_mode.numpy
fallback_result = impl(self, *args, **kwargs)
kwargs[name] = numpy
numpy_result = impl(self, *args, **kwargs)
if isinstance(numpy_result, numpy.ndarray):
# if numpy returns ndarray, cupy must return ndarray
assert isinstance(fallback_result, fallback.ndarray)
fallback_mode.numpy.testing.assert_array_equal(
numpy_result, fallback_result)
assert fallback_result.dtype == numpy_result.dtype
elif isinstance(numpy_result, numpy.ScalarType):
# if numpy returns scalar
# cupy may return 0-dim array
assert numpy_result == fallback_result._cupy_array.item() or \
(numpy_result == fallback_result._numpy_array).all()
else:
assert False
return test_func
return decorator
Example 19
| Project: malib Author: ying-wen File: tensor_board_output.py License: MIT License | 5 votes |
|
def _record_kv(self, key, value, step):
if isinstance(value, np.ScalarType):
self._writer.add_scalar(key, value, step)
elif isinstance(value, plt.Figure):
self._writer.add_figure(key, value, step)
elif isinstance(value, scipy.stats._distn_infrastructure.rv_frozen):
shape = (self._histogram_samples,) + value.mean().shape
self._writer.add_histogram(key, value.rvs(shape), step)
elif isinstance(value, scipy.stats._multivariate.multi_rv_frozen):
self._writer.add_histogram(key, value.rvs(self._histogram_samples), step)
elif isinstance(value, Histogram):
self._writer.add_histogram(key, value, step)
Example 20
| Project: dowel Author: rlworkgroup File: tensor_board_output.py License: MIT License | 5 votes |
|
def _record_kv(self, key, value, step):
if isinstance(value, np.ScalarType):
self._writer.add_scalar(key, value, step)
elif isinstance(value, plt.Figure):
self._writer.add_figure(key, value, step)
elif isinstance(value, scipy.stats._distn_infrastructure.rv_frozen):
shape = (self._histogram_samples, ) + value.mean().shape
self._writer.add_histogram(key, value.rvs(shape), step)
elif isinstance(value, scipy.stats._multivariate.multi_rv_frozen):
self._writer.add_histogram(key, value.rvs(self._histogram_samples),
step)
elif isinstance(value, Histogram):
self._writer.add_histogram(key, value, step)
Example 21
| Project: deeppy Author: andersbll File: elementwise.py License: MIT License | 5 votes |
|
def __call__(self, lhs, rhs):
if lhs is rhs:
return 2*lhs
if isinstance(lhs, np.ScalarType) and lhs == 0:
return rhs
if isinstance(rhs, np.ScalarType) and rhs == 0:
return lhs
return super(Add, self).__call__(lhs, rhs)
Example 22
| Project: deeppy Author: andersbll File: elementwise.py License: MIT License | 5 votes |
|
def __call__(self, lhs, rhs):
if lhs is rhs:
return 0.0
if isinstance(lhs, np.ScalarType) and lhs == 0:
return -rhs
if isinstance(rhs, np.ScalarType) and rhs == 0:
return lhs
return super(Subtract, self).__call__(lhs, rhs)
Example 23
| Project: deeppy Author: andersbll File: elementwise.py License: MIT License | 5 votes |
|
def __call__(self, lhs, rhs):
if lhs is rhs:
return lhs**2
if isinstance(lhs, np.ScalarType) and lhs == 1:
return rhs
if isinstance(rhs, np.ScalarType) and rhs == 1:
return lhs
return super(Multiply, self).__call__(lhs, rhs)
Example 24
| Project: deeppy Author: andersbll File: elementwise.py License: MIT License | 5 votes |
|
def __call__(self, lhs, rhs):
if lhs is rhs:
return 1.0
if isinstance(rhs, np.ScalarType) and rhs == 1:
return lhs
return super(Divide, self).__call__(lhs, rhs)
Example 25
| Project: lambda-packs Author: ryfeus File: extras.py License: MIT License | 4 votes |
|
def __getitem__(self, key):
if isinstance(key, str):
raise MAError("Unavailable for masked array.")
if not isinstance(key, tuple):
key = (key,)
objs = []
scalars = []
final_dtypedescr = None
for k in range(len(key)):
scalar = False
if isinstance(key[k], slice):
step = key[k].step
start = key[k].start
stop = key[k].stop
if start is None:
start = 0
if step is None:
step = 1
if isinstance(step, complex):
size = int(abs(step))
newobj = np.linspace(start, stop, num=size)
else:
newobj = np.arange(start, stop, step)
elif isinstance(key[k], str):
if (key[k] in 'rc'):
self.matrix = True
self.col = (key[k] == 'c')
continue
try:
self.axis = int(key[k])
continue
except (ValueError, TypeError):
raise ValueError("Unknown special directive")
elif type(key[k]) in np.ScalarType:
newobj = asarray([key[k]])
scalars.append(k)
scalar = True
else:
newobj = key[k]
objs.append(newobj)
if isinstance(newobj, ndarray) and not scalar:
if final_dtypedescr is None:
final_dtypedescr = newobj.dtype
elif newobj.dtype > final_dtypedescr:
final_dtypedescr = newobj.dtype
if final_dtypedescr is not None:
for k in scalars:
objs[k] = objs[k].astype(final_dtypedescr)
res = concatenate(tuple(objs), axis=self.axis)
return self._retval(res)
Example 26
| Project: auto-alt-text-lambda-api Author: abhisuri97 File: extras.py License: MIT License | 4 votes |
|
def __getitem__(self, key):
if isinstance(key, str):
raise MAError("Unavailable for masked array.")
if not isinstance(key, tuple):
key = (key,)
objs = []
scalars = []
final_dtypedescr = None
for k in range(len(key)):
scalar = False
if isinstance(key[k], slice):
step = key[k].step
start = key[k].start
stop = key[k].stop
if start is None:
start = 0
if step is None:
step = 1
if isinstance(step, complex):
size = int(abs(step))
newobj = np.linspace(start, stop, num=size)
else:
newobj = np.arange(start, stop, step)
elif isinstance(key[k], str):
if (key[k] in 'rc'):
self.matrix = True
self.col = (key[k] == 'c')
continue
try:
self.axis = int(key[k])
continue
except (ValueError, TypeError):
raise ValueError("Unknown special directive")
elif type(key[k]) in np.ScalarType:
newobj = asarray([key[k]])
scalars.append(k)
scalar = True
else:
newobj = key[k]
objs.append(newobj)
if isinstance(newobj, ndarray) and not scalar:
if final_dtypedescr is None:
final_dtypedescr = newobj.dtype
elif newobj.dtype > final_dtypedescr:
final_dtypedescr = newobj.dtype
if final_dtypedescr is not None:
for k in scalars:
objs[k] = objs[k].astype(final_dtypedescr)
res = concatenate(tuple(objs), axis=self.axis)
return self._retval(res)
Example 27
| Project: Computable Author: ktraunmueller File: extras.py License: MIT License | 4 votes |
|
def __getitem__(self, key):
if isinstance(key, str):
raise MAError("Unavailable for masked array.")
if not isinstance(key, tuple):
key = (key,)
objs = []
scalars = []
final_dtypedescr = None
for k in range(len(key)):
scalar = False
if isinstance(key[k], slice):
step = key[k].step
start = key[k].start
stop = key[k].stop
if start is None:
start = 0
if step is None:
step = 1
if isinstance(step, complex):
size = int(abs(step))
newobj = np.linspace(start, stop, num=size)
else:
newobj = np.arange(start, stop, step)
elif isinstance(key[k], str):
if (key[k] in 'rc'):
self.matrix = True
self.col = (key[k] == 'c')
continue
try:
self.axis = int(key[k])
continue
except (ValueError, TypeError):
raise ValueError("Unknown special directive")
elif type(key[k]) in np.ScalarType:
newobj = asarray([key[k]])
scalars.append(k)
scalar = True
else:
newobj = key[k]
objs.append(newobj)
if isinstance(newobj, ndarray) and not scalar:
if final_dtypedescr is None:
final_dtypedescr = newobj.dtype
elif newobj.dtype > final_dtypedescr:
final_dtypedescr = newobj.dtype
if final_dtypedescr is not None:
for k in scalars:
objs[k] = objs[k].astype(final_dtypedescr)
res = concatenate(tuple(objs), axis=self.axis)
return self._retval(res)
Example 28
| Project: Fluid-Designer Author: Microvellum File: extras.py License: GNU General Public License v3.0 | 4 votes |
|
def __getitem__(self, key):
if isinstance(key, str):
raise MAError("Unavailable for masked array.")
if not isinstance(key, tuple):
key = (key,)
objs = []
scalars = []
final_dtypedescr = None
for k in range(len(key)):
scalar = False
if isinstance(key[k], slice):
step = key[k].step
start = key[k].start
stop = key[k].stop
if start is None:
start = 0
if step is None:
step = 1
if isinstance(step, complex):
size = int(abs(step))
newobj = np.linspace(start, stop, num=size)
else:
newobj = np.arange(start, stop, step)
elif isinstance(key[k], str):
if (key[k] in 'rc'):
self.matrix = True
self.col = (key[k] == 'c')
continue
try:
self.axis = int(key[k])
continue
except (ValueError, TypeError):
raise ValueError("Unknown special directive")
elif type(key[k]) in np.ScalarType:
newobj = asarray([key[k]])
scalars.append(k)
scalar = True
else:
newobj = key[k]
objs.append(newobj)
if isinstance(newobj, ndarray) and not scalar:
if final_dtypedescr is None:
final_dtypedescr = newobj.dtype
elif newobj.dtype > final_dtypedescr:
final_dtypedescr = newobj.dtype
if final_dtypedescr is not None:
for k in scalars:
objs[k] = objs[k].astype(final_dtypedescr)
res = concatenate(tuple(objs), axis=self.axis)
return self._retval(res)
Example 29
| Project: cupy Author: cupy File: generate.py License: MIT License | 4 votes |
|
def __getitem__(self, key):
trans1d = self.trans1d
ndmin = self.ndmin
objs = []
scalars = []
arraytypes = []
scalartypes = []
if isinstance(key, str):
raise NotImplementedError
if not isinstance(key, tuple):
key = (key,)
for i, k in enumerate(key):
scalar = False
if isinstance(k, slice):
raise NotImplementedError
elif isinstance(k, str):
if i != 0:
raise ValueError(
'special directives must be the first entry.')
raise NotImplementedError
elif type(k) in numpy.ScalarType:
newobj = from_data.array(k, ndmin=ndmin)
scalars.append(i)
scalar = True
scalartypes.append(newobj.dtype)
else:
newobj = from_data.array(k, copy=False, ndmin=ndmin)
if ndmin > 1:
ndim = from_data.array(k, copy=False).ndim
if trans1d != -1 and ndim < ndmin:
newobj = self._output_obj(newobj, ndim, ndmin, trans1d)
objs.append(newobj)
if not scalar and isinstance(newobj, core.ndarray):
arraytypes.append(newobj.dtype)
final_dtype = numpy.find_common_type(arraytypes, scalartypes)
if final_dtype is not None:
for k in scalars:
objs[k] = objs[k].astype(final_dtype)
return join.concatenate(tuple(objs), axis=self.axis)
Example 30
| Project: ImageFusion Author: pfchai File: extras.py License: MIT License | 4 votes |
|
def __getitem__(self, key):
if isinstance(key, str):
raise MAError("Unavailable for masked array.")
if not isinstance(key, tuple):
key = (key,)
objs = []
scalars = []
final_dtypedescr = None
for k in range(len(key)):
scalar = False
if isinstance(key[k], slice):
step = key[k].step
start = key[k].start
stop = key[k].stop
if start is None:
start = 0
if step is None:
step = 1
if isinstance(step, complex):
size = int(abs(step))
newobj = np.linspace(start, stop, num=size)
else:
newobj = np.arange(start, stop, step)
elif isinstance(key[k], str):
if (key[k] in 'rc'):
self.matrix = True
self.col = (key[k] == 'c')
continue
try:
self.axis = int(key[k])
continue
except (ValueError, TypeError):
raise ValueError("Unknown special directive")
elif type(key[k]) in np.ScalarType:
newobj = asarray([key[k]])
scalars.append(k)
scalar = True
else:
newobj = key[k]
objs.append(newobj)
if isinstance(newobj, ndarray) and not scalar:
if final_dtypedescr is None:
final_dtypedescr = newobj.dtype
elif newobj.dtype > final_dtypedescr:
final_dtypedescr = newobj.dtype
if final_dtypedescr is not None:
for k in scalars:
objs[k] = objs[k].astype(final_dtypedescr)
res = concatenate(tuple(objs), axis=self.axis)
return self._retval(res)
