The following are code examples for showing how to use . They are extracted from open source Python projects. You can vote up the examples you like or vote down the exmaples you don’t like. You can also save this page to your account.
Example 1
def write_metadata(path, meta='.meta.yaml', **params):
"""Writes metadata for a dataset.
Args:
path (str): path to **dataset** (not meta file) whose metadata
is to be written. If the meta file already exists, it will be
overwritten.
meta (str): suffix identifying the dataset's meta file
**params: all other keyword arguments are treated as dataset attributes,
and added to the meta file
"""
if 'n_channels' in params:
del params['n_channels']
if 'n_samples' in params:
del params['n_samples']
if os.path.isdir(path):
metafile = os.path.join(path, meta[1:])
else:
metafile = path + meta
for k, v in params.items():
if isinstance(v, (np.ndarray, np.generic)):
params[k] = v.tolist()
with codecs.open(metafile, 'w', encoding='utf-8') as yaml_file:
yaml_file.write(yaml.safe_dump(params, default_flow_style=False)) Example 2
def json_conversion(obj):
"""Encode additional objects to JSON."""
try:
# numpy isn't an explicit dependency of bowtie
# so we can't assume it's available
import numpy as np
if isinstance(obj, (np.ndarray, np.generic)):
return obj.tolist()
except ImportError:
pass
try:
# pandas isn't an explicit dependency of bowtie
# so we can't assume it's available
import pandas as pd
if isinstance(obj, pd.Index):
return obj.tolist()
except ImportError:
pass
if isinstance(obj, (datetime, time, date)):
return obj.isoformat()
raise TypeError('Not sure how to serialize {} of type {}'.format(obj, type(obj))) Example 3
def encoders(obj):
"""Convert Python object to msgpack encodable ones."""
try:
# numpy isn't an explicit dependency of bowtie
# so we can't assume it's available
import numpy as np
if isinstance(obj, (np.ndarray, np.generic)):
# https://docs.scipy.org/doc/numpy/reference/arrays.scalars.html
return obj.tolist()
except ImportError:
pass
try:
# pandas isn't an explicit dependency of bowtie
# so we can't assume it's available
import pandas as pd
if isinstance(obj, pd.Index):
return obj.tolist()
except ImportError:
pass
if isinstance(obj, (datetime, time, date)):
return obj.isoformat()
return obj Example 4
def fmt(obj, nest_level=0):
""" Format any common object """
if nest_level > 10:
return ""
if isinstance(obj, float):
return "{0:.3f}".format(obj)
if isinstance(obj, list):
return "(" + ",".join(map(lambda x: fmt(x, nest_level + 1), obj)) + ")"
if isinstance(obj, (numpy.ndarray, numpy.generic)):
return fmt(obj.tolist(), nest_level + 1)
if isinstance(obj, dict):
pairs = map(lambda x, y: "(" + fmt(x) + "," + fmt(y, nest_level + 1) + ")", obj.items())
return fmt(pairs)
if isinstance(obj, Vector3):
return "({},{},{})".format(fmt(obj.x), fmt(obj.y), fmt(obj.z))
if isinstance(obj, Quaternion):
return "({},{},{},{})".format(fmt(obj.x), fmt(obj.y), fmt(obj.z), fmt(obj.w))
# print " obj " + str(obj) + " is of type " + str(type(obj))
return str(obj) Example 5
def np2gdal_dtype(d):
"""
Get GDAL RasterBand datatype that corresponds with NumPy datatype
Input should be numpy array or numpy dtype
"""
dt_dict = gdal_array.codes
if isinstance(d, (np.ndarray, np.generic)):
d = d.dtype
#This creates dtype from another built-in type
#d = np.dtype(d)
if isinstance(d, np.dtype):
if d.name == 'int8':
gdal_dt = 1
elif d.name == 'bool':
#Write out as Byte
gdal_dt = 1
else:
gdal_dt = list(dt_dict.keys())[list(dt_dict.values()).index(d)]
else:
print("Input must be NumPy array or NumPy dtype")
gdal_dt = None
return gdal_dt Example 6
def test_describe_typefiltering_category_bool(self):
df = DataFrame({'A_cat': pd.Categorical(['foo', 'foo', 'bar'] * 8),
'B_str': ['a', 'b', 'c', 'd'] * 6,
'C_bool': [True] * 12 + [False] * 12,
'D_num': np.arange(24.) + .5,
'E_ts': tm.makeTimeSeries()[:24].index})
desc = df.describe()
expected_cols = ['D_num']
expected = DataFrame(dict((k, df[k].describe())
for k in expected_cols),
columns=expected_cols)
assert_frame_equal(desc, expected)
desc = df.describe(include=["category"])
self.assertTrue(desc.columns.tolist() == ["A_cat"])
# 'all' includes numpy-dtypes + category
desc1 = df.describe(include="all")
desc2 = df.describe(include=[np.generic, "category"])
assert_frame_equal(desc1, desc2) Example 7
def __setitem__(self, in_slice, value):
"""Set ndarray value"""
if not self.writable:
raise ValueError('trying to assign to a readonly NDArray')
if isinstance(in_slice, int):
sliced_arr = self._at(in_slice)
sliced_arr[:] = value
return
if not isinstance(in_slice, slice) or in_slice.step is not None:
raise ValueError('NDArray only support continuous slicing on axis 0')
if in_slice.start is not None or in_slice.stop is not None:
sliced_arr = self._slice(in_slice.start, in_slice.stop)
sliced_arr[:] = value
return
if isinstance(value, NDArray):
if value.handle is not self.handle:
value.copyto(self)
elif isinstance(value, numeric_types):
NDArray._set_value(float(value), out=self)
elif isinstance(value, (np.ndarray, np.generic)):
self._sync_copyfrom(value)
else:
raise TypeError('type %s not supported' % str(type(value))) Example 8
def read_attr(self, path, attr_name, default=False):
"""Read an attribute of an HDF5 group."""
_check_hdf5_path(self._h5py_file, path)
attrs = self._h5py_file[path].attrs
if attr_name in attrs:
try:
out = attrs[attr_name]
if (isinstance(out, (np.ndarray, np.generic)) and
out.dtype.kind == 'S'):
out = out.tostring().decode('UTF-8')
out = out.replace('\x00', '')
return out
except (TypeError, IOError):
logger.debug("Unable to read attribute `%s` at `%s`.",
attr_name, path)
return
elif default is False:
raise KeyError("The attribute '{0:s}' ".format(attr_name) +
"at `{}` doesn't exist.".format(path))
return default Example 9
def capture_frame(self, frame):
if not isinstance(frame, (np.ndarray, np.generic)):
raise error.InvalidFrame(
'Wrong type {} for {} (must be np.ndarray or np.generic)'.format(type(frame), frame))
if frame.shape != self.frame_shape:
raise error.InvalidFrame(
"Your frame has shape {}, but the VideoRecorder is configured for shape {}.".format(
frame.shape, self.frame_shape))
if frame.dtype != np.uint8:
raise error.InvalidFrame(
"Your frame has data type {}, but we require uint8 (i.e. RGB values from 0-255).".format(frame.dtype))
if distutils.version.LooseVersion(np.__version__) >= distutils.version.LooseVersion('1.9.0'):
self.proc.stdin.write(frame.tobytes())
else:
self.proc.stdin.write(frame.tostring()) Example 10
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 11
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 12
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 13
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 14
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 15
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 16
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 17
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 18
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 19
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 20
def get_generic_name():
# may need to make this a search for the first non-kdllib reference
# make generic name from highest calling context
prev_function_name = None
for i in range(len(inspect.stack())):
(frame, filename, line_number,
function_name, lines, index) = inspect.stack()[i]
#print(frame, filename, line_number, function_name, lines, index)
# Use stack to get easier function name than parsing the code itself
if i > 0:
_, _, _, prev_function_name, _, _ = inspect.stack()[i - 1]
else:
prev_function_name = function_name
script_name = filename.split(os.sep)[-1]
lib_location = os.path.realpath(__file__)
lib_name = lib_location.split(os.sep)[-1]
# cover .py and .pyc
if script_name != lib_name and script_name != lib_name[:-1]:
name = script_name + "_" + prev_function_name
#print(frame, filename, line_number, function_name, lines, index)
return name
raise ValueError("Issue in generic name getter")
# Many of these from Ishaan G. Example 21
def default(self, obj):
if isinstance(obj, np.ndarray) and obj.ndim == 1:
return obj.tolist()
elif isinstance(obj, np.generic):
return obj.item()
return json.JSONEncoder.default(self, obj) Example 22
def test_oddfeatures_3(self):
# Tests some generic features
atest = array([10], mask=True)
btest = array([20])
idx = atest.mask
atest[idx] = btest[idx]
assert_equal(atest, [20]) Example 23
def test_tolist_specialcase(self):
# Test mvoid.tolist: make sure we return a standard Python object
a = array([(0, 1), (2, 3)], dtype=[('a', int), ('b', int)])
# w/o mask: each entry is a np.void whose elements are standard Python
for entry in a:
for item in entry.tolist():
assert_(not isinstance(item, np.generic))
# w/ mask: each entry is a ma.void whose elements should be
# standard Python
a.mask[0] = (0, 1)
for entry in a:
for item in entry.tolist():
assert_(not isinstance(item, np.generic)) Example 24
def test_masked_where_oddities(self):
# Tests some generic features.
atest = ones((10, 10, 10), dtype=float)
btest = zeros(atest.shape, MaskType)
ctest = masked_where(btest, atest)
assert_equal(atest, ctest) Example 25
def _call(self, *args, **kwargs):
axis = kwargs['axis'] if 'axis' in kwargs else None
if len(args) == 0:
raise Exception('number of arguments must be more than 0')
if builtins.any(
not isinstance(_, (core.ndarray, numpy.ndarray, numpy.generic))
for _ in args):
raise TypeError('Invalid argument type for \'{}\': ({})'.format(
self.name,
', '.join(repr(type(_)) for _ in args)))
def is_cupy_data(a):
return isinstance(a, (core.ndarray, numpy.generic))
if builtins.all(is_cupy_data(_) for _ in args):
types = [_.dtype for _ in args]
key = tuple(types)
if key not in self._memo:
if self.input_num is not None:
nin = self.input_num
else:
nin = len(args)
f = _get_fusion(self.func, nin, self.reduce,
self.post_map, self.identity, types, self.name)
self._memo[key] = f
f = self._memo[key]
if self.reduce is None:
return f(*args)
else:
return f(*args, axis=axis)
else:
if builtins.any(type(_) is core.ndarray for _ in args):
types = '.'.join(repr(type(_)) for _ in args)
message = "Can't fuse \n %s(%s)" % (self.name, types)
warnings.warn(message)
if self.reduce is None:
return self.func(*args)
elif axis is None:
return self.post_map(self.reduce(self.func(*args)))
else:
return self.post_map(self.reduce(self.func(*args), axis=axis)) Example 26
def tensor_to_protobuf(tensor):
pb_tensor = ops_pb.Tensor()
pb_tensor.info.dtype = dtype_to_protobuf(tensor.dtype)
pb_tensor.info.shape.extend(tensor.shape)
if isinstance(tensor, (np.ndarray, np.generic)):
pb_tensor.data = tensor.tobytes()
else:
raise ValueError("Unknown tensor value of {}".format(tensor))
return pb_tensor Example 27
def is_scalar_type(value):
return value is None or \
isinstance(value, (str, six.text_type, float, bool, Axis,
AxesMap, dict, slice, np.generic) +
six.integer_types) Example 28
def assign_scalar(message, value):
"""
Adds the appropriate scalar type of value to the protobuf message
"""
if value is None:
message.null_val = True
elif isinstance(value, np.generic):
assign_scalar(message, np.asscalar(value))
elif isinstance(value, (str, six.text_type)):
message.string_val = value
elif isinstance(value, np.dtype):
message.dtype_val = dtype_to_protobuf(value)
elif isinstance(value, float):
message.double_val = value
elif isinstance(value, bool):
message.bool_val = value
elif isinstance(value, six.integer_types):
message.int_val = value
elif isinstance(value, slice):
slice_val = ops_pb.Slice()
if value.start is not None:
slice_val.start.value = value.start
if value.step is not None:
slice_val.step.value = value.step
if value.stop is not None:
slice_val.stop.value = value.stop
message.slice_val.CopyFrom(slice_val)
elif isinstance(value, dict):
for key in value:
assign_scalar(message.map_val.map[key], value[key])
# This encodes an empty dict for deserialization
assign_scalar(message.map_val.map['_ngraph_map_sentinel_'], '')
elif isinstance(value, Axis):
message.axis.CopyFrom(axis_to_protobuf(value))
elif isinstance(value, AxesMap):
message.axes_map.CopyFrom(axes_map_to_protobuf(value))
else:
raise unhandled_scalar_value(value) Example 29
def protobuf_to_op(pb_op):
"""
This will convert a protobuf Op object into its corresponding Python object. But this cannot
setup links to other ops (such as args, control_deps) since those ops may not
exist yet.
We have to wait until all ops are created before connecting them back up together in a second
pass, so args, etc will be uninitialized.
"""
cls = get_ngraph_op_cls(pb_op.op_type)
# Skip the class constructor but we'll use the generic op constructor because it sets a lot of
# helpful defaults
py_op = cls.__new__(cls)
op_graph.Op.__init__(py_op)
py_op.name = str(pb_op.name)
if 'valfun_value' in pb_op.attrs:
valfun_value = pb_to_tensor(pb_op.attrs['valfun_value'].tensor)
py_op.valfun = lambda x: valfun_value
# op.uuid
py_op.uuid = uuid.UUID(bytes=pb_op.uuid.uuid)
# op.metadata and remaining keys
ignored_keys = {'valfun_value', 'dtype', 'metadata'}
remaining_keys = set(pb_op.attrs.keys()).difference(ignored_keys)
for key in remaining_keys:
if key == '_ngraph_ser_handle':
py_op._ngraph_ser_handle = True
if key.startswith('_ngraph_metadata_'):
value = pb_op.attrs[key]
py_op.metadata[key[17:]] = protobuf_attr_to_python(value)
elif not key.startswith('_is_') and key not in EXCEPTION_ATTRIBUTES and \
key.startswith('_'):
continue
else:
value = pb_op.attrs[key]
setattr(py_op, key, protobuf_attr_to_python(value))
return py_op Example 30
def test_similarity():
UserDataRow = Row(
"normalized_channel", "geo_city", "subsession_length", "os", "locale",
"active_addons", "bookmark_count", "tab_open_count", "total_uri", "unique_tlds"
)
test_user_1 = UserDataRow("release", "Boston", 10, "Windows", "en-US", [], 1, 2, 3, 4)
test_user_2 = UserDataRow("release", "notsoB", 10, "swodniW", "SU-ne", [], 1, 2, 3, 4)
test_user_3 = UserDataRow("release", "Boston", 0, "Windows", "en-US", [], 0, 0, 0, 0)
test_user_4 = UserDataRow("release", "notsoB", 0, "swodniW", "SU-ne", [], 0, 0, 0, 0)
# The following user contains a None value for "total_uri" and geo_city
# (categorical feature). The latter should never be possible, but let's be cautious.
test_user_5 = UserDataRow("release", None, 10, "swodniW", "SU-ne", [], 1, None, 3, 4)
# Identical users should be very close (0 distance) and the result must not
# be a Numpy number.
similarity_result = taar_similarity.similarity_function(test_user_1, test_user_1)
assert not isinstance(similarity_result, np.generic)
assert np.isclose(similarity_result, 0.0)
# Users with completely different categorical features but identical
# continuous features should be slightly different.
assert np.isclose(taar_similarity.similarity_function(test_user_1, test_user_2), 0.001)
# Users with completely different continuous features but identical
# categorical features should be very close.
assert np.isclose(taar_similarity.similarity_function(test_user_1, test_user_3), 0.0)
# Completely different users should be far away.
assert taar_similarity.similarity_function(test_user_1, test_user_4) >= 1.0
# Partial user information should not break the similarity function.
assert taar_similarity.similarity_function(test_user_1, test_user_5) Example 31
def set_theta(self, theta):
"""
Function sets theta. Can be called from constructor or outside.
"""
if isinstance(theta, (np.ndarray, np.generic)):
self.theta = theta
elif isinstance(theta, list):
self.theta = np.array(theta)
else:
self.theta = None
self.history = self.set_list(
self.history, 0, (np.copy(self.theta), 0, None))
self.step_no = 0 Example 32
def filter_invalid_json_values(self, dict):
for k, v in six.iteritems(dict):
if isinstance(v, (np.ndarray, np.generic)):
dict[k] = v.tolist()
if math.isnan(v) or math.isinf(v):
dict[k] = -1 Example 33
def invalid_json_values(obj):
if isinstance(obj, np.generic):
return obj.item()
if isinstance(obj, np.ndarray):
return obj.tolist()
if isinstance(obj, bytes):
return obj.decode('cp437')
if isinstance(map, type) and isinstance(obj, map):
# python 3 map
return list(obj)
raise TypeError('Invalid data type passed to json encoder: ' + type(obj).__name__) Example 34
def contains(self, x):
if isinstance(x, int):
as_int = x
elif isinstance(x, (np.generic, np.ndarray)) and (x.dtype.kind in np.typecodes['AllInteger'] and x.shape == ()):
as_int = int(x)
else:
return False
return as_int >= 0 and as_int < self.n Example 35
def capture_frame(self, frame):
if not isinstance(frame, (np.ndarray, np.generic)):
raise error.InvalidFrame('Wrong type {} for {} (must be np.ndarray or np.generic)'.format(type(frame), frame))
if frame.shape != self.frame_shape:
raise error.InvalidFrame("Your frame has shape {}, but the VideoRecorder is configured for shape {}.".format(frame.shape, self.frame_shape))
if frame.dtype != np.uint8:
raise error.InvalidFrame("Your frame has data type {}, but we require uint8 (i.e. RGB values from 0-255).".format(frame.dtype))
if distutils.version.LooseVersion(np.__version__) >= distutils.version.LooseVersion('1.9.0'):
self.proc.stdin.write(frame.tobytes())
else:
self.proc.stdin.write(frame.tostring()) Example 36
def test_oddfeatures_3(self):
# Tests some generic features
atest = array([10], mask=True)
btest = array([20])
idx = atest.mask
atest[idx] = btest[idx]
assert_equal(atest, [20]) Example 37
def test_tolist_specialcase(self):
# Test mvoid.tolist: make sure we return a standard Python object
a = array([(0, 1), (2, 3)], dtype=[('a', int), ('b', int)])
# w/o mask: each entry is a np.void whose elements are standard Python
for entry in a:
for item in entry.tolist():
assert_(not isinstance(item, np.generic))
# w/ mask: each entry is a ma.void whose elements should be
# standard Python
a.mask[0] = (0, 1)
for entry in a:
for item in entry.tolist():
assert_(not isinstance(item, np.generic)) Example 38
def test_masked_where_oddities(self):
# Tests some generic features.
atest = ones((10, 10, 10), dtype=float)
btest = zeros(atest.shape, MaskType)
ctest = masked_where(btest, atest)
assert_equal(atest, ctest) Example 39
def feature_names(self, names):
"Stores the text labels for features"
if len(names) != self.num_features:
raise ValueError("Number of names do not match the number of features!")
if not isinstance(names, (Sequence, np.ndarray, np.generic)):
raise ValueError("Input is not a sequence. Ensure names are in the same order and length as features.")
self.__feature_names = np.array(names) Example 40
def is_np_scalar(x):
"""
Check np types like np.int64
"""
return isinstance(x, np.generic) Example 41
def contains(self, x):
if not isinstance(x, (tuple, list, np.generic, np.ndarray)):
return False
return np.shape(x) == self.shape and np.sum(x) == 1 and np.max(x) == 1 Example 42
def contains(self, x):
if isinstance(x, int):
as_int = x
elif isinstance(x, (np.generic, np.ndarray)) and (x.dtype.kind in np.typecodes['AllInteger'] and x.shape == ()):
as_int = int(x)
else:
return False
return as_int >= 0 and as_int < self.n Example 43
def __setitem__(self, in_slice, value):
"""Set ndarray value"""
if (not isinstance(in_slice, slice) or
in_slice.start is not None
or in_slice.stop is not None):
raise ValueError('Array only support set from numpy array')
if isinstance(value, NDArray):
if value.handle is not self.handle:
value.copyto(self)
elif isinstance(value, (np.ndarray, np.generic)):
self._sync_copyfrom(value)
else:
raise TypeError('type %s not supported' % str(type(value))) Example 44
def _validate_date_like_dtype(dtype):
try:
typ = np.datetime_data(dtype)[0]
except ValueError as e:
raise TypeError('%s' % e)
if typ != 'generic' and typ != 'ns':
raise ValueError('%r is too specific of a frequency, try passing %r' %
(dtype.name, dtype.type.__name__)) Example 45
def _get_dtype_from_object(dtype):
"""Get a numpy dtype.type-style object. This handles the datetime64[ns]
and datetime64[ns, TZ] compat
Notes
-----
If nothing can be found, returns ``object``.
"""
# type object from a dtype
if isinstance(dtype, type) and issubclass(dtype, np.generic):
return dtype
elif is_categorical(dtype):
return CategoricalDtype().type
elif is_datetimetz(dtype):
return DatetimeTZDtype(dtype).type
elif isinstance(dtype, np.dtype): # dtype object
try:
_validate_date_like_dtype(dtype)
except TypeError:
# should still pass if we don't have a datelike
pass
return dtype.type
elif isinstance(dtype, compat.string_types):
if dtype == 'datetime' or dtype == 'timedelta':
dtype += '64'
try:
return _get_dtype_from_object(getattr(np, dtype))
except (AttributeError, TypeError):
# handles cases like _get_dtype(int)
# i.e., python objects that are valid dtypes (unlike user-defined
# types, in general)
# TypeError handles the float16 typecode of 'e'
# further handle internal types
pass
return _get_dtype_from_object(np.dtype(dtype)) Example 46
def test_oddfeatures_3(self):
# Tests some generic features
atest = array([10], mask=True)
btest = array([20])
idx = atest.mask
atest[idx] = btest[idx]
assert_equal(atest, [20]) Example 47
def test_tolist_specialcase(self):
# Test mvoid.tolist: make sure we return a standard Python object
a = array([(0, 1), (2, 3)], dtype=[('a', int), ('b', int)])
# w/o mask: each entry is a np.void whose elements are standard Python
for entry in a:
for item in entry.tolist():
assert_(not isinstance(item, np.generic))
# w/ mask: each entry is a ma.void whose elements should be
# standard Python
a.mask[0] = (0, 1)
for entry in a:
for item in entry.tolist():
assert_(not isinstance(item, np.generic)) Example 48
def to_numpy(var):
#if ia.is_numpy_array(var):
if isinstance(var, (np.ndarray, np.generic)):
return var
else:
return var.data.cpu().numpy() Example 49
def test_oddfeatures_3(self):
# Tests some generic features
atest = array([10], mask=True)
btest = array([20])
idx = atest.mask
atest[idx] = btest[idx]
assert_equal(atest, [20]) Example 50
def test_tolist_specialcase(self):
# Test mvoid.tolist: make sure we return a standard Python object
a = array([(0, 1), (2, 3)], dtype=[('a', int), ('b', int)])
# w/o mask: each entry is a np.void whose elements are standard Python
for entry in a:
for item in entry.tolist():
assert_(not isinstance(item, np.generic))
# w/ mask: each entry is a ma.void whose elements should be
# standard Python
a.mask[0] = (0, 1)
for entry in a:
for item in entry.tolist():
assert_(not isinstance(item, np.generic)) 