3000 menjelaskan solusi kode untuk 75 teknologi
import numpy as np array = np.empty(10) array.fill(5)ctrl + cimport numpy as np
memuat modul Numpy untuk Python
.emptymenghasilkan array Numpy kosong dari bentuk yang ditentukan
10kami membuat array kosong dari 10 elemen
.fillisi array dengan nilai yang ditentukan
5kita akan mengisi array kita dengan nilai 5
21 contoh kode Python ditemukan terkait dengan " fill array". Anda dapat memilih yang Anda suka atau memilih yang tidak Anda sukai, dan pergi ke proyek asli atau file sumber dengan mengikuti tautan di atas setiap contoh
def visitFillArrayData(method, dex, instr_d, type_data, block, instr): width, arrdata = instr_d[instr.args[1]].fillarrdata at = type_data.arrs[instr.args[0]] block.loadAsArray(instr.args[0]) if at is arrays.NULL: block.u8(ATHROW) else: if len(arrdata) == 0: # fill-array-data throws a NPE if array is null even when # there is 0 data, so we need to add an instruction that # throws a NPE in this case block.u8(ARRAYLENGTH) block.add(ir.Pop()) else: st, elet = arrays.eletPair(at) # check if we need to sign extend if elet == b'B' or elet == b'Z': arrdata = [util.signExtend(x, 8) & 0xFFFFFFFF for x in arrdata] elif elet == b'S': arrdata = [util.signExtend(x, 16) & 0xFFFFFFFF for x in arrdata] block.fillarraydata(_arrStoreOps.get(elet, AASTORE), st, arrdata) _
def fill_array(self, array, field, add=False, maximize=False): """ Given a full array (for the while image), fill it with the data on the edges. """ self.fix_shapes() for i in xrange(self.n_chunks): for side in ['left', 'right', 'top', 'bottom']: edge = getattr(self, side).ravel()[i] if add: array[edge.slice] += getattr(edge, field) elif maximize: array[edge.slice] = np.maximum(array[edge.slice], getattr(edge, field)) else: array[edge.slice] = getattr(edge, field) return array
def visitFillArrayData(method, dex, instr_d, type_data, block, instr): width, arrdata = instr_d[instr.args[1]].fillarrdata at = type_data.arrs[instr.args[0]] block.loadAsArray(instr.args[0]) if at is arrays.NULL: block.u8(ATHROW) else: if len(arrdata) == 0: # fill-array-data throws a NPE if array is null even when # there is 0 data, so we need to add an instruction that # throws a NPE in this case block.u8(ARRAYLENGTH) block.add(ir.Pop()) else: st, elet = arrays.eletPair(at) # check if we need to sign extend if elet == b'B': arrdata = [util.signExtend(x, 8) & 0xFFFFFFFF for x in arrdata] elif elet == b'S': arrdata = [util.signExtend(x, 16) & 0xFFFFFFFF for x in arrdata] block.fillarraydata(_arrStoreOps.get(elet, AASTORE), st, arrdata)
def visit_fill_array(self, array, value): self.write_ind() array.visit(self) self.write(' = {', data="ARRAY_FILLED") data = value.get_data() tab = [] elem_size = value.element_width # Set type depending on size of elements data_types = {1: 'b', 2: 'h', 4: 'i', 8: 'd'} if elem_size in data_types: elem_id = data_types[elem_size] else: # FIXME for other types we just assume bytes... logger.warning("Unknown element size {} for array. Assume bytes.".format(elem_size)) elem_id = 'b' elem_size = 1 for i in range(0, value.size*elem_size, elem_size): tab.append('%s' % unpack(elem_id, data[i:i+elem_size])[0]) self.write(', '.join(tab), data="COMMA") self.write('}', data="ARRAY_FILLED_END") self.end_ins() _
def visit_fill_array(self, array, value): self.write_ind() array.visit(self) self.write(' = {', data="ARRAY_FILLED") data = value.get_data() tab = [] elem_size = value.element_width if elem_size == 4: for i in range(0, value.size * 4, 4): tab.append('%s' % unpack('i', data[i:i + 4])[0]) else: # FIXME: other cases for i in range(value.size): tab.append('%s' % unpack('b', data[i])[0]) self.write(', '.join(tab), data="COMMA") self.write('}', data="ARRAY_FILLED_END") self.end_ins()
def visitFillArrayData(method, dex, instr_d, type_data, block, instr): width, arrdata = instr_d[instr.args[1]].fillarrdata at = type_data.arrs[instr.args[0]] block.loadAsArray(instr.args[0]) if at is arrays.NULL: block.u8(ATHROW) else: if len(arrdata) == 0: # fill-array-data throws a NPE if array is null even when # there is 0 data, so we need to add an instruction that # throws a NPE in this case block.u8(ARRAYLENGTH) block.u8(POP) else: st, elet = arrays.eletPair(at) # check if we need to sign extend if elet == b'B': arrdata = [util.signExtend(x, 8) & 0xFFFFFFFF for x in arrdata] elif elet == b'S': arrdata = [util.signExtend(x, 16) & 0xFFFFFFFF for x in arrdata] block.fillarraydata(_arrStoreOps.get(elet, AASTORE), st, arrdata) _
def fill_array(array, fill, length): assert length >= array.shape[0], "Cannot fill" if length == array.shape[0]: return array array2 = fill * np.ones((length), dtype=array.dtype) array2[:array.shape[0]] = array return array2
def fill_array(arr, seq): if arr.ndim == 1: try: len_ = len(seq) except TypeError: len_ = 0 arr[:len_] = seq arr[len_:] = 0 else: for subarr, subseq in izip_longest(arr, seq, fillvalue=()): fill_array(subarr, subseq) _
def fill_array(vtk_arr, state, zf): vtk_arr.SetNumberOfComponents(state['numberOfComponents']) vtk_arr.SetNumberOfTuples(state['size']//state['numberOfComponents']) data = zf.read('data/%s' % state['hash']) dataType = arrayTypesMapping[vtk_arr.GetDataType()] elementSize = struct.calcsize(dataType) if vtk_arr.GetDataType() == 12: # we need to cast the data to Uint64 import numpy as np data = np.frombuffer(data, dtype=np.uint32).astype(np.uint64).tobytes() elementSize = 8 vtk_arr.SetVoidArray(data, len(data)//elementSize, 1) vtk_arr._reference = data _
def fill_with_array(self, var, arr): if isinstance(var.owner, Synapses) and var.name == 'delay': # Assigning is only allowed if the variable has been declared in the # Synapse constructor and is therefore scalar if not var.scalar: raise NotImplementedError( 'GeNN does not support assigning to the ' 'delay variable -- set the delay for all' 'synapses (heterogeneous delays are not ' 'supported) as an argument to the ' 'Synapses initializer.') else: # We store the delay so that we can later access it self.delays[var.owner.name] = numpy.asarray(arr).item() elif isinstance(var.owner, NeuronGroup) and var.name == 'lastspike': # Workaround for versions of Brian 2 <= 2.1.3.1 which initialize # a NeuronGroup's lastspike variable to -inf, no longer supported # by the new implementation of the timestep function if arr == -numpy.inf: logger.warn('Initializing the lastspike variable with -10000s ' 'instead of -inf to copy the behaviour of Brian 2 ' 'for versions >= 2.2 -- upgrade Brian 2 to remove ' 'this warning', name_suffix='lastspike_inf', once=True) arr = numpy.array(-1e4) super(GeNNDevice, self).fill_with_array(var, arr)
def fill_array(self, array, field, add=False, maximize=False): """ Given a full array (for the while image), fill it with the data on the edges. """ self.fix_shapes() for i in xrange(self.n_chunks): for side in ['left', 'right', 'top', 'bottom']: edge = getattr(self, side).ravel()[i] if add: array[edge.slice] += getattr(edge, field) elif maximize: array[edge.slice] = np.maximum(array[edge.slice], getattr(edge, field)) else: array[edge.slice] = getattr(edge, field) return array 0
def fill_array(self, array, field, add=False, maximize=False): """ Given a full array (for the while image), fill it with the data on the edges. """ self.fix_shapes() for i in xrange(self.n_chunks): for side in ['left', 'right', 'top', 'bottom']: edge = getattr(self, side).ravel()[i] if add: array[edge.slice] += getattr(edge, field) elif maximize: array[edge.slice] = np.maximum(array[edge.slice], getattr(edge, field)) else: array[edge.slice] = getattr(edge, field) return array 1
def fill_array(self, array, field, add=False, maximize=False): """ Given a full array (for the while image), fill it with the data on the edges. """ self.fix_shapes() for i in xrange(self.n_chunks): for side in ['left', 'right', 'top', 'bottom']: edge = getattr(self, side).ravel()[i] if add: array[edge.slice] += getattr(edge, field) elif maximize: array[edge.slice] = np.maximum(array[edge.slice], getattr(edge, field)) else: array[edge.slice] = getattr(edge, field) return array 2
def fill_array(self, array, field, add=False, maximize=False): """ Given a full array (for the while image), fill it with the data on the edges. """ self.fix_shapes() for i in xrange(self.n_chunks): for side in ['left', 'right', 'top', 'bottom']: edge = getattr(self, side).ravel()[i] if add: array[edge.slice] += getattr(edge, field) elif maximize: array[edge.slice] = np.maximum(array[edge.slice], getattr(edge, field)) else: array[edge.slice] = getattr(edge, field) return array _3
def fill_array(self, array, field, add=False, maximize=False): """ Given a full array (for the while image), fill it with the data on the edges. """ self.fix_shapes() for i in xrange(self.n_chunks): for side in ['left', 'right', 'top', 'bottom']: edge = getattr(self, side).ravel()[i] if add: array[edge.slice] += getattr(edge, field) elif maximize: array[edge.slice] = np.maximum(array[edge.slice], getattr(edge, field)) else: array[edge.slice] = getattr(edge, field) return array _4
def fill_array(self, array, field, add=False, maximize=False): """ Given a full array (for the while image), fill it with the data on the edges. """ self.fix_shapes() for i in xrange(self.n_chunks): for side in ['left', 'right', 'top', 'bottom']: edge = getattr(self, side).ravel()[i] if add: array[edge.slice] += getattr(edge, field) elif maximize: array[edge.slice] = np.maximum(array[edge.slice], getattr(edge, field)) else: array[edge.slice] = getattr(edge, field) return array 5