Python numpy.core.multiarray.ndarray() Examples
The following are 30
code examples of numpy.core.multiarray.ndarray().
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.
You may also want to check out all available functions/classes of the module
numpy.core.multiarray
, or try the search function
.
Example #1
Source File: _methods.py From Computable with MIT License | 6 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning) # Cast bool, unsigned int, and int to float64 by default if dtype is None and issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') ret = um.add.reduce(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) else: ret = ret.dtype.type(ret / rcount) return ret
Example #2
Source File: _methods.py From ImageFusion with MIT License | 6 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning) # Cast bool, unsigned int, and int to float64 by default if dtype is None and issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #3
Source File: _methods.py From Fluid-Designer with GNU General Public License v3.0 | 6 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning) # Cast bool, unsigned int, and int to float64 by default if dtype is None and issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #4
Source File: _methods.py From auto-alt-text-lambda-api with MIT License | 6 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning) # Cast bool, unsigned int, and int to float64 by default if dtype is None and issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #5
Source File: _methods.py From coffeegrindsize with MIT License | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #6
Source File: _methods.py From elasticintel with GNU General Public License v3.0 | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #7
Source File: _methods.py From Splunking-Crime with GNU Affero General Public License v3.0 | 5 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) is_float16_result = False rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning, stacklevel=2) # Cast bool, unsigned int, and int to float64 by default if dtype is None: if issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') elif issubclass(arr.dtype.type, nt.float16): dtype = mu.dtype('f4') is_float16_result = True ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) if is_float16_result and out is None: ret = arr.dtype.type(ret) elif hasattr(ret, 'dtype'): if is_float16_result: ret = arr.dtype.type(ret / rcount) else: ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #8
Source File: _methods.py From ImageFusion with MIT License | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #9
Source File: _methods.py From GraphicDesignPatternByPython with MIT License | 5 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) is_float16_result = False rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning, stacklevel=2) # Cast bool, unsigned int, and int to float64 by default if dtype is None: if issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') elif issubclass(arr.dtype.type, nt.float16): dtype = mu.dtype('f4') is_float16_result = True ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) if is_float16_result and out is None: ret = arr.dtype.type(ret) elif hasattr(ret, 'dtype'): if is_float16_result: ret = arr.dtype.type(ret / rcount) else: ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #10
Source File: _methods.py From Splunking-Crime with GNU Affero General Public License v3.0 | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #11
Source File: _methods.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) is_float16_result = False rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning, stacklevel=2) # Cast bool, unsigned int, and int to float64 by default if dtype is None: if issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') elif issubclass(arr.dtype.type, nt.float16): dtype = mu.dtype('f4') is_float16_result = True ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) if is_float16_result and out is None: ret = arr.dtype.type(ret) elif hasattr(ret, 'dtype'): if is_float16_result: ret = arr.dtype.type(ret / rcount) else: ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #12
Source File: _methods.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #13
Source File: _methods.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
def _array_function(self, func, types, args, kwargs): # TODO: rewrite this in C # Cannot handle items that have __array_function__ other than our own. for t in types: if not issubclass(t, mu.ndarray) and hasattr(t, '__array_function__'): return NotImplemented # The regular implementation can handle this, so we call it directly. return func.__wrapped__(*args, **kwargs)
Example #14
Source File: _methods.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 5 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) is_float16_result = False rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning, stacklevel=2) # Cast bool, unsigned int, and int to float64 by default if dtype is None: if issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') elif issubclass(arr.dtype.type, nt.float16): dtype = mu.dtype('f4') is_float16_result = True ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) if is_float16_result and out is None: ret = arr.dtype.type(ret) elif hasattr(ret, 'dtype'): if is_float16_result: ret = arr.dtype.type(ret / rcount) else: ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #15
Source File: _methods.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #16
Source File: _methods.py From twitter-stock-recommendation with MIT License | 5 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) is_float16_result = False rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning, stacklevel=2) # Cast bool, unsigned int, and int to float64 by default if dtype is None: if issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') elif issubclass(arr.dtype.type, nt.float16): dtype = mu.dtype('f4') is_float16_result = True ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) if is_float16_result and out is None: ret = arr.dtype.type(ret) elif hasattr(ret, 'dtype'): if is_float16_result: ret = arr.dtype.type(ret / rcount) else: ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #17
Source File: _methods.py From twitter-stock-recommendation with MIT License | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #18
Source File: _methods.py From Mastering-Elasticsearch-7.0 with MIT License | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #19
Source File: _methods.py From mxnet-lambda with Apache License 2.0 | 5 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) is_float16_result = False rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning, stacklevel=2) # Cast bool, unsigned int, and int to float64 by default if dtype is None: if issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') elif issubclass(arr.dtype.type, nt.float16): dtype = mu.dtype('f4') is_float16_result = True ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) if is_float16_result and out is None: ret = arr.dtype.type(ret) elif hasattr(ret, 'dtype'): if is_float16_result: ret = arr.dtype.type(ret / rcount) else: ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #20
Source File: dense_transform.py From SpaceNet_Off_Nadir_Solutions with Apache License 2.0 | 5 votes |
def __call__(self, sample): sample["img"] = torch.from_numpy(sample["img"].transpose((2, 0, 1))).float() sample["angle"] = torch.from_numpy(sample["angle"].transpose((2, 0, 1))).float() if isinstance(sample["mask"], ndarray): sample["mask"] = torch.from_numpy(sample["mask"].transpose((2, 0, 1))).float() return sample
Example #21
Source File: utils.py From py-image-dataset-generator with MIT License | 5 votes |
def save_file(processed_image: ndarray, folder_path: str, file_prefix: str): FileUtil.create_folder(folder_path) full_destination = FileUtil.generate_next_file_path(folder_path, file_prefix) io.imsave(full_destination, processed_image)
Example #22
Source File: utils.py From py-image-dataset-generator with MIT License | 5 votes |
def open(path: str) -> ndarray: return io.imread(path)
Example #23
Source File: _methods.py From pySINDy with MIT License | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #24
Source File: _methods.py From pySINDy with MIT License | 5 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) is_float16_result = False rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning, stacklevel=2) # Cast bool, unsigned int, and int to float64 by default if dtype is None: if issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') elif issubclass(arr.dtype.type, nt.float16): dtype = mu.dtype('f4') is_float16_result = True ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) if is_float16_result and out is None: ret = arr.dtype.type(ret) elif hasattr(ret, 'dtype'): if is_float16_result: ret = arr.dtype.type(ret / rcount) else: ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #25
Source File: _methods.py From Fluid-Designer with GNU General Public License v3.0 | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #26
Source File: _methods.py From Computable with MIT License | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) else: ret = ret.dtype.type(um.sqrt(ret)) return ret
Example #27
Source File: _methods.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #28
Source File: _methods.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) is_float16_result = False rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning, stacklevel=2) # Cast bool, unsigned int, and int to float64 by default if dtype is None: if issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') elif issubclass(arr.dtype.type, nt.float16): dtype = mu.dtype('f4') is_float16_result = True ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) if is_float16_result and out is None: ret = arr.dtype.type(ret) elif hasattr(ret, 'dtype'): if is_float16_result: ret = arr.dtype.type(ret / rcount) else: ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret
Example #29
Source File: _methods.py From GraphicDesignPatternByPython with MIT License | 5 votes |
def _std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, keepdims=keepdims) if isinstance(ret, mu.ndarray): ret = um.sqrt(ret, out=ret) elif hasattr(ret, 'dtype'): ret = ret.dtype.type(um.sqrt(ret)) else: ret = um.sqrt(ret) return ret
Example #30
Source File: _methods.py From Mastering-Elasticsearch-7.0 with MIT License | 5 votes |
def _mean(a, axis=None, dtype=None, out=None, keepdims=False): arr = asanyarray(a) is_float16_result = False rcount = _count_reduce_items(arr, axis) # Make this warning show up first if rcount == 0: warnings.warn("Mean of empty slice.", RuntimeWarning, stacklevel=2) # Cast bool, unsigned int, and int to float64 by default if dtype is None: if issubclass(arr.dtype.type, (nt.integer, nt.bool_)): dtype = mu.dtype('f8') elif issubclass(arr.dtype.type, nt.float16): dtype = mu.dtype('f4') is_float16_result = True ret = umr_sum(arr, axis, dtype, out, keepdims) if isinstance(ret, mu.ndarray): ret = um.true_divide( ret, rcount, out=ret, casting='unsafe', subok=False) if is_float16_result and out is None: ret = arr.dtype.type(ret) elif hasattr(ret, 'dtype'): if is_float16_result: ret = arr.dtype.type(ret / rcount) else: ret = ret.dtype.type(ret / rcount) else: ret = ret / rcount return ret