Python numpy.fromiter() Examples
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Example #1
Source File: __init__.py From python-in-practice with GNU General Public License v3.0 | 8 votes |
def create_array(width, height, background=None): """returns an array.array or numpy.array of the correct size and with the given background color""" if numpy is not None: if background is None: return numpy.zeros(width * height, dtype=numpy.uint32) else: iterable = (background for _ in range(width * height)) return numpy.fromiter(iterable, numpy.uint32) else: # Use the smallest typecode that can store a 32-bit unsigned integer typecode = "I" if array.array("I").itemsize >= 4 else "L" background = (background if background is not None else ColorForName["transparent"]) return array.array(typecode, [background] * width * height) # Taken from rgb.txt and converted to ARGB (with the addition of # transparent). Default is solid black.
Example #2
Source File: plyfile.py From pointnet-registration-framework with MIT License | 7 votes |
def make2d(array, cols=None, dtype=None): ''' Make a 2D array from an array of arrays. The `cols' and `dtype' arguments can be omitted if the array is not empty. ''' if (cols is None or dtype is None) and not len(array): raise RuntimeError("cols and dtype must be specified for empty " "array") if cols is None: cols = len(array[0]) if dtype is None: dtype = array[0].dtype return _np.fromiter(array, [('_', dtype, (cols,))], count=len(array))['_']
Example #3
Source File: util.py From Computable with MIT License | 6 votes |
def cartesian_product(X): ''' Numpy version of itertools.product or pandas.compat.product. Sometimes faster (for large inputs)... Examples -------- >>> cartesian_product([list('ABC'), [1, 2]]) [array(['A', 'A', 'B', 'B', 'C', 'C'], dtype='|S1'), array([1, 2, 1, 2, 1, 2])] ''' lenX = np.fromiter((len(x) for x in X), dtype=int) cumprodX = np.cumproduct(lenX) a = np.roll(cumprodX, 1) a[0] = 1 b = cumprodX[-1] / cumprodX return [np.tile(np.repeat(x, b[i]), np.product(a[i])) for i, x in enumerate(X)]
Example #4
Source File: modeller.py From InSilicoSeq with MIT License | 6 votes |
def divide_qualities_into_bins(qualities, n_bins=4): """Divides the raw quality scores in bins according to the mean phred quality of the sequence they come from Args: qualities (list): raw count of all the phred scores and mean sequence quality n_bins (int): number of bins to create (default: 4) Returns: list: a list of lists containing the binned quality scores """ logger = logging.getLogger(__name__) logger.debug('Dividing qualities into mean clusters') bin_lists = [[] for _ in range(n_bins)] # create list of `n_bins` list ranges = np.split(np.array(range(40)), n_bins) for quality in qualities: mean = int(quality[0][1]) # mean is at 1 and same regardless of b pos which_array = 0 for array in ranges: if mean in array: read = np.fromiter((q[0] for q in quality), dtype=np.float) bin_lists[which_array].append(read) which_array += 1 return bin_lists
Example #5
Source File: sorting.py From recruit with Apache License 2.0 | 6 votes |
def decons_obs_group_ids(comp_ids, obs_ids, shape, labels, xnull): """ reconstruct labels from observed group ids Parameters ---------- xnull: boolean, if nulls are excluded; i.e. -1 labels are passed through """ if not xnull: lift = np.fromiter(((a == -1).any() for a in labels), dtype='i8') shape = np.asarray(shape, dtype='i8') + lift if not is_int64_overflow_possible(shape): # obs ids are deconstructable! take the fast route! out = decons_group_index(obs_ids, shape) return out if xnull or not lift.any() \ else [x - y for x, y in zip(out, lift)] i = unique_label_indices(comp_ids) i8copy = lambda a: a.astype('i8', subok=False, copy=True) return [i8copy(lab[i]) for lab in labels]
Example #6
Source File: test_array.py From vnpy_crypto with MIT License | 6 votes |
def test_constructor_object_dtype(self): # GH 11856 arr = SparseArray(['A', 'A', np.nan, 'B'], dtype=np.object) assert arr.dtype == np.object assert np.isnan(arr.fill_value) arr = SparseArray(['A', 'A', np.nan, 'B'], dtype=np.object, fill_value='A') assert arr.dtype == np.object assert arr.fill_value == 'A' # GH 17574 data = [False, 0, 100.0, 0.0] arr = SparseArray(data, dtype=np.object, fill_value=False) assert arr.dtype == np.object assert arr.fill_value is False arr_expected = np.array(data, dtype=np.object) it = (type(x) == type(y) and x == y for x, y in zip(arr, arr_expected)) assert np.fromiter(it, dtype=np.bool).all()
Example #7
Source File: test_array.py From recruit with Apache License 2.0 | 6 votes |
def test_constructor_object_dtype(self): # GH 11856 arr = SparseArray(['A', 'A', np.nan, 'B'], dtype=np.object) assert arr.dtype == SparseDtype(np.object) assert np.isnan(arr.fill_value) arr = SparseArray(['A', 'A', np.nan, 'B'], dtype=np.object, fill_value='A') assert arr.dtype == SparseDtype(np.object, 'A') assert arr.fill_value == 'A' # GH 17574 data = [False, 0, 100.0, 0.0] arr = SparseArray(data, dtype=np.object, fill_value=False) assert arr.dtype == SparseDtype(np.object, False) assert arr.fill_value is False arr_expected = np.array(data, dtype=np.object) it = (type(x) == type(y) and x == y for x, y in zip(arr, arr_expected)) assert np.fromiter(it, dtype=np.bool).all()
Example #8
Source File: sorting.py From vnpy_crypto with MIT License | 6 votes |
def decons_obs_group_ids(comp_ids, obs_ids, shape, labels, xnull): """ reconstruct labels from observed group ids Parameters ---------- xnull: boolean, if nulls are excluded; i.e. -1 labels are passed through """ if not xnull: lift = np.fromiter(((a == -1).any() for a in labels), dtype='i8') shape = np.asarray(shape, dtype='i8') + lift if not is_int64_overflow_possible(shape): # obs ids are deconstructable! take the fast route! out = decons_group_index(obs_ids, shape) return out if xnull or not lift.any() \ else [x - y for x, y in zip(out, lift)] i = unique_label_indices(comp_ids) i8copy = lambda a: a.astype('i8', subok=False, copy=True) return [i8copy(lab[i]) for lab in labels]
Example #9
Source File: data_util_hdf5.py From BERT with Apache License 2.0 | 6 votes |
def load_word2vec(word2vec_model_path,embed_size): """ load pretrained word2vec in txt format :param word2vec_model_path: :return: word2vec_dict. word2vec_dict[word]=vector """ #word2vec_object = codecs.open(word2vec_model_path,'r','utf-8') #open(word2vec_model_path,'r') #lines=word2vec_object.readlines() #word2vec_dict={} #for i,line in enumerate(lines): # if i==0: continue # string_list=line.strip().split(" ") # word=string_list[0] # vector=string_list[1:][0:embed_size] # word2vec_dict[word]=vector ###################### word2vec_dict = {} with open(word2vec_model_path, errors='ignore') as f: meta = f.readline() for line in f.readlines(): items = line.split(' ') #if len(items[0]) > 1 and items[0] in vocab: word2vec_dict[items[0]] = np.fromiter(items[1:][0:embed_size], dtype=float) return word2vec_dict
Example #10
Source File: plyfile.py From Pointnet_Pointnet2_pytorch with MIT License | 6 votes |
def make2d(array, cols=None, dtype=None): ''' Make a 2D array from an array of arrays. The `cols' and `dtype' arguments can be omitted if the array is not empty. ''' if (cols is None or dtype is None) and not len(array): raise RuntimeError("cols and dtype must be specified for empty " "array") if cols is None: cols = len(array[0]) if dtype is None: dtype = array[0].dtype return _np.fromiter(array, [('_', dtype, (cols,))], count=len(array))['_']
Example #11
Source File: stl.py From pymesh with MIT License | 5 votes |
def __load_ascii(fh, header): return numpy.fromiter(Stl.__ascii_reader(fh, header), dtype=Stl.stl_dtype)
Example #12
Source File: test_numeric.py From Computable with MIT License | 5 votes |
def test_lengths(self): expected = array(list(self.makegen())) a = fromiter(self.makegen(), int) a20 = fromiter(self.makegen(), int, 20) self.assertTrue(len(a) == len(expected)) self.assertTrue(len(a20) == 20) self.assertRaises(ValueError, fromiter, self.makegen(), int, len(expected) + 10)
Example #13
Source File: test_regression.py From Computable with MIT License | 5 votes |
def test_mem_fromiter_invalid_dtype_string(self, level=rlevel): x = [1, 2, 3] self.assertRaises(ValueError, np.fromiter, [xi for xi in x], dtype='S')
Example #14
Source File: test_numeric.py From Computable with MIT License | 5 votes |
def test_2592(self): # Test iteration exceptions are correctly raised. count, eindex = 10, 5 self.assertRaises(NIterError, np.fromiter, self.load_data(count, eindex), dtype=int, count=count)
Example #15
Source File: test_numeric.py From Computable with MIT License | 5 votes |
def test_2592_edge(self): # Test iter. exceptions, edge case (exception at end of iterator). count = 10 eindex = count-1 self.assertRaises(NIterError, np.fromiter, self.load_data(count, eindex), dtype=int, count=count)
Example #16
Source File: test_numeric.py From Computable with MIT License | 5 votes |
def test_values(self): expected = array(list(self.makegen())) a = fromiter(self.makegen(), int) a20 = fromiter(self.makegen(), int, 20) self.assertTrue(alltrue(a == expected, axis=0)) self.assertTrue(alltrue(a20 == expected[:20], axis=0))
Example #17
Source File: test_numeric.py From vnpy_crypto with MIT License | 5 votes |
def test_2592_edge(self): # Test iter. exceptions, edge case (exception at end of iterator). count = 10 eindex = count-1 assert_raises(NIterError, np.fromiter, self.load_data(count, eindex), dtype=int, count=count)
Example #18
Source File: test_numeric.py From vnpy_crypto with MIT License | 5 votes |
def test_2592(self): # Test iteration exceptions are correctly raised. count, eindex = 10, 5 assert_raises(NIterError, np.fromiter, self.load_data(count, eindex), dtype=int, count=count)
Example #19
Source File: test_numeric.py From auto-alt-text-lambda-api with MIT License | 5 votes |
def test_values(self): expected = np.array(list(self.makegen())) a = np.fromiter(self.makegen(), int) a20 = np.fromiter(self.makegen(), int, 20) self.assertTrue(np.alltrue(a == expected, axis=0)) self.assertTrue(np.alltrue(a20 == expected[:20], axis=0))
Example #20
Source File: test_numeric.py From vnpy_crypto with MIT License | 5 votes |
def test_values(self): expected = np.array(list(self.makegen())) a = np.fromiter(self.makegen(), int) a20 = np.fromiter(self.makegen(), int, 20) assert_(np.alltrue(a == expected, axis=0)) assert_(np.alltrue(a20 == expected[:20], axis=0))
Example #21
Source File: Globals.py From python-in-practice with GNU General Public License v3.0 | 5 votes |
def create_array(width, height, background=None): """returns anumpy.array of the correct size and with the given background color""" if background is None: return numpy.zeros(width * height, dtype=numpy.uint32) iterable = (background for _ in range(width * height)) return numpy.fromiter(iterable, numpy.uint32)
Example #22
Source File: test_numeric.py From auto-alt-text-lambda-api with MIT License | 5 votes |
def test_2592(self): # Test iteration exceptions are correctly raised. count, eindex = 10, 5 self.assertRaises(NIterError, np.fromiter, self.load_data(count, eindex), dtype=int, count=count)
Example #23
Source File: test_numeric.py From auto-alt-text-lambda-api with MIT License | 5 votes |
def test_2592_edge(self): # Test iter. exceptions, edge case (exception at end of iterator). count = 10 eindex = count-1 self.assertRaises(NIterError, np.fromiter, self.load_data(count, eindex), dtype=int, count=count)
Example #24
Source File: test_regression.py From auto-alt-text-lambda-api with MIT License | 5 votes |
def test_mem_fromiter_invalid_dtype_string(self, level=rlevel): x = [1, 2, 3] self.assertRaises(ValueError, np.fromiter, [xi for xi in x], dtype='S')
Example #25
Source File: test_numeric.py From vnpy_crypto with MIT License | 5 votes |
def test_lengths(self): expected = np.array(list(self.makegen())) a = np.fromiter(self.makegen(), int) a20 = np.fromiter(self.makegen(), int, 20) assert_(len(a) == len(expected)) assert_(len(a20) == 20) assert_raises(ValueError, np.fromiter, self.makegen(), int, len(expected) + 10)
Example #26
Source File: test_regression.py From auto-alt-text-lambda-api with MIT License | 5 votes |
def test_fromiter_bytes(self): # Ticket #1058 a = np.fromiter(list(range(10)), dtype='b') b = np.fromiter(list(range(10)), dtype='B') assert_(np.alltrue(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) assert_(np.alltrue(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
Example #27
Source File: test_regression.py From auto-alt-text-lambda-api with MIT License | 5 votes |
def test_fromiter_comparison(self, level=rlevel): a = np.fromiter(list(range(10)), dtype='b') b = np.fromiter(list(range(10)), dtype='B') assert_(np.alltrue(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) assert_(np.alltrue(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
Example #28
Source File: test_numeric.py From vnpy_crypto with MIT License | 5 votes |
def test_types(self): ai32 = np.fromiter(self.makegen(), np.int32) ai64 = np.fromiter(self.makegen(), np.int64) af = np.fromiter(self.makegen(), float) assert_(ai32.dtype == np.dtype(np.int32)) assert_(ai64.dtype == np.dtype(np.int64)) assert_(af.dtype == np.dtype(float))
Example #29
Source File: terrain_correction.py From pyeo with GNU General Public License v3.0 | 5 votes |
def generate_latlon(x, y,geotransform, transformer): x_geo, y_geo = cm.pixel_to_point_coordinates([y,x], geotransform) lon, lat, _ = transformer.TransformPoint(x_geo, y_geo) return np.fromiter((lat, lon),np.float)
Example #30
Source File: test_regression.py From auto-alt-text-lambda-api with MIT License | 5 votes |
def test_duplicate_field_names_assign(self): ra = np.fromiter(((i*3, i*2) for i in range(10)), dtype='i8,f8') ra.dtype.names = ('f1', 'f2') repr(ra) # should not cause a segmentation fault assert_raises(ValueError, setattr, ra.dtype, 'names', ('f1', 'f1'))