diff --git a/python/amunpy/src/amunpy/amun.py b/python/amunpy/src/amunpy/amun.py index 6bf7aa9..1ec4b1a 100644 --- a/python/amunpy/src/amunpy/amun.py +++ b/python/amunpy/src/amunpy/amun.py @@ -240,18 +240,18 @@ class Amun: """ Get dataset array of name dataset_name from the file n. """ - import numpy as np + import numpy dataset = self.variables[dataset_name] if dataset == 'mlev': - dset = np.zeros(self.chunks[chunk_number]['dims']) + dset = numpy.zeros(self.chunks[chunk_number]['dims']) for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] = self.chunks[chunk_number]['levels'][p] elif dataset == 'logd': - dset = np.log10(self.__read_binary_data__('dens', chunk_number)) + dset = numpy.log10(self.__read_binary_data__('dens', chunk_number)) elif dataset == 'logp': - dset = np.log10(self.__read_binary_data__('pres', chunk_number)) + dset = numpy.log10(self.__read_binary_data__('pres', chunk_number)) elif dataset == 'velo': tmp = self.__read_binary_data__('velx', chunk_number) dset = tmp**2 @@ -259,7 +259,7 @@ class Amun: dset += tmp**2 tmp = self.__read_binary_data__('velz', chunk_number) dset += tmp**2 - dset = np.sqrt(dset) + dset = numpy.sqrt(dset) elif dataset == 'vvec': dset = [self.__read_binary_data__('velx', chunk_number), \ self.__read_binary_data__('vely', chunk_number), \ @@ -271,7 +271,7 @@ class Amun: dset += tmp**2 tmp = self.__read_binary_data__('magz', chunk_number) dset += tmp**2 - dset = np.sqrt(dset) + dset = numpy.sqrt(dset) elif dataset == 'bvec': dset = [self.__read_binary_data__('magx', chunk_number), \ self.__read_binary_data__('magy', chunk_number), \ @@ -302,10 +302,10 @@ class Amun: dset = vy * bz - vz * by if self.attributes['resistivity'] > 0: if self.attributes['ndims'] == 3: - tmp = (np.roll(by, 1, axis=0) - np.roll(by, -1, axis=0)) - tmp += (np.roll(bz, -1, axis=1) - np.roll(bz, 1, axis=1)) + tmp = (numpy.roll(by, 1, axis=0) - numpy.roll(by, -1, axis=0)) + tmp += (numpy.roll(bz, -1, axis=1) - numpy.roll(bz, 1, axis=1)) else: - tmp = (np.roll(bz, -1, axis=0) - np.roll(bz, 1, axis=0)) + tmp = (numpy.roll(bz, -1, axis=0) - numpy.roll(bz, 1, axis=0)) for p in range(self.chunks[chunk_number]['dblocks']): tmp[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -318,10 +318,10 @@ class Amun: dset = vz * bx - vx * bz if self.attributes['resistivity'] > 0: if self.attributes['ndims'] == 3: - tmp = (np.roll(bx, -1, axis=0) - np.roll(bx, 1, axis=0)) - tmp += (np.roll(bz, 1, axis=2) - np.roll(bz, -1, axis=2)) + tmp = (numpy.roll(bx, -1, axis=0) - numpy.roll(bx, 1, axis=0)) + tmp += (numpy.roll(bz, 1, axis=2) - numpy.roll(bz, -1, axis=2)) else: - tmp = (np.roll(bz, 1, axis=1) - np.roll(bz, -1, axis=1)) + tmp = (numpy.roll(bz, 1, axis=1) - numpy.roll(bz, -1, axis=1)) for p in range(self.chunks[chunk_number]['dblocks']): tmp[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -334,11 +334,11 @@ class Amun: dset = vx * by - vy * bx if self.attributes['resistivity'] > 0: if self.attributes['ndims'] == 3: - tmp = (np.roll(bx, 1, axis=1) - np.roll(bx, -1, axis=1)) - tmp += (np.roll(by, -1, axis=2) - np.roll(by, 1, axis=2)) + tmp = (numpy.roll(bx, 1, axis=1) - numpy.roll(bx, -1, axis=1)) + tmp += (numpy.roll(by, -1, axis=2) - numpy.roll(by, 1, axis=2)) else: - tmp = (np.roll(bx, 1, axis=0) - np.roll(bx, -1, axis=0)) - tmp += (np.roll(by, -1, axis=1) - np.roll(by, 1, axis=1)) + tmp = (numpy.roll(bx, 1, axis=0) - numpy.roll(bx, -1, axis=0)) + tmp += (numpy.roll(by, -1, axis=1) - numpy.roll(by, 1, axis=1)) for p in range(self.chunks[chunk_number]['dblocks']): tmp[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -351,10 +351,10 @@ class Amun: dtmp = v1 * b2 - v2 * b1 if self.attributes['resistivity'] > 0: if self.attributes['ndims'] == 3: - tmp = (np.roll(b1, 1, axis=0) - np.roll(b1, -1, axis=0)) - tmp += (np.roll(b2, -1, axis=1) - np.roll(b2, 1, axis=1)) + tmp = (numpy.roll(b1, 1, axis=0) - numpy.roll(b1, -1, axis=0)) + tmp += (numpy.roll(b2, -1, axis=1) - numpy.roll(b2, 1, axis=1)) else: - tmp = (np.roll(b2, -1, axis=0) - np.roll(b2, 1, axis=0)) + tmp = (numpy.roll(b2, -1, axis=0) - numpy.roll(b2, 1, axis=0)) for p in range(self.chunks[chunk_number]['dblocks']): tmp[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -366,10 +366,10 @@ class Amun: dtmp = v2 * b1 - v1 * b2 if self.attributes['resistivity'] > 0: if self.attributes['ndims'] == 3: - tmp = (np.roll(b1, -1, axis=0) - np.roll(b1, 1, axis=0)) - tmp += (np.roll(b2, 1, axis=2) - np.roll(b2, -1, axis=2)) + tmp = (numpy.roll(b1, -1, axis=0) - numpy.roll(b1, 1, axis=0)) + tmp += (numpy.roll(b2, 1, axis=2) - numpy.roll(b2, -1, axis=2)) else: - tmp = (np.roll(b2, 1, axis=1) - np.roll(b2, -1, axis=1)) + tmp = (numpy.roll(b2, 1, axis=1) - numpy.roll(b2, -1, axis=1)) for p in range(self.chunks[chunk_number]['dblocks']): tmp[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -381,17 +381,17 @@ class Amun: dtmp = v1 * b2 - v2 * b1 if self.attributes['resistivity'] > 0: if self.attributes['ndims'] == 3: - tmp = (np.roll(b1, 1, axis=1) - np.roll(b1, -1, axis=1)) - tmp += (np.roll(b2, -1, axis=2) - np.roll(b2, 1, axis=2)) + tmp = (numpy.roll(b1, 1, axis=1) - numpy.roll(b1, -1, axis=1)) + tmp += (numpy.roll(b2, -1, axis=2) - numpy.roll(b2, 1, axis=2)) else: - tmp = (np.roll(b1, 1, axis=0) - np.roll(b1, -1, axis=0)) - tmp += (np.roll(b2, -1, axis=1) - np.roll(b2, 1, axis=1)) + tmp = (numpy.roll(b1, 1, axis=0) - numpy.roll(b1, -1, axis=0)) + tmp += (numpy.roll(b2, -1, axis=1) - numpy.roll(b2, 1, axis=1)) for p in range(self.chunks[chunk_number]['dblocks']): tmp[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] dtmp -= 0.5 * self.attributes['resistivity'] * tmp dset += dtmp**2 - dset = np.sqrt(dset) + dset = numpy.sqrt(dset) elif dataset == 'evec': b1 = self.__read_binary_data__('magy', chunk_number) b2 = self.__read_binary_data__('magz', chunk_number) @@ -400,10 +400,10 @@ class Amun: wx = v1 * b2 - v2 * b1 if self.attributes['resistivity'] > 0: if self.attributes['ndims'] == 3: - tmp = (np.roll(b1, 1, axis=0) - np.roll(b1, -1, axis=0)) - tmp += (np.roll(b2, -1, axis=1) - np.roll(b2, 1, axis=1)) + tmp = (numpy.roll(b1, 1, axis=0) - numpy.roll(b1, -1, axis=0)) + tmp += (numpy.roll(b2, -1, axis=1) - numpy.roll(b2, 1, axis=1)) else: - tmp = (np.roll(b2, -1, axis=0) - np.roll(b2, 1, axis=0)) + tmp = (numpy.roll(b2, -1, axis=0) - numpy.roll(b2, 1, axis=0)) for p in range(self.chunks[chunk_number]['dblocks']): tmp[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -414,10 +414,10 @@ class Amun: wy = v2 * b1 - v1 * b2 if self.attributes['resistivity'] > 0: if self.attributes['ndims'] == 3: - tmp = (np.roll(b1, -1, axis=0) - np.roll(b1, 1, axis=0)) - tmp += (np.roll(b2, 1, axis=2) - np.roll(b2, -1, axis=2)) + tmp = (numpy.roll(b1, -1, axis=0) - numpy.roll(b1, 1, axis=0)) + tmp += (numpy.roll(b2, 1, axis=2) - numpy.roll(b2, -1, axis=2)) else: - tmp = (np.roll(b2, 1, axis=1) - np.roll(b2, -1, axis=1)) + tmp = (numpy.roll(b2, 1, axis=1) - numpy.roll(b2, -1, axis=1)) for p in range(self.chunks[chunk_number]['dblocks']): tmp[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -428,11 +428,11 @@ class Amun: wz = v1 * b2 - v2 * b1 if self.attributes['resistivity'] > 0: if self.attributes['ndims'] == 3: - tmp = (np.roll(b1, 1, axis=1) - np.roll(b1, -1, axis=1)) - tmp += (np.roll(b2, -1, axis=2) - np.roll(b2, 1, axis=2)) + tmp = (numpy.roll(b1, 1, axis=1) - numpy.roll(b1, -1, axis=1)) + tmp += (numpy.roll(b2, -1, axis=2) - numpy.roll(b2, 1, axis=2)) else: - tmp = (np.roll(b1, 1, axis=0) - np.roll(b1, -1, axis=0)) - tmp += (np.roll(b2, -1, axis=1) - np.roll(b2, 1, axis=1)) + tmp = (numpy.roll(b1, 1, axis=0) - numpy.roll(b1, -1, axis=0)) + tmp += (numpy.roll(b2, -1, axis=1) - numpy.roll(b2, 1, axis=1)) for p in range(self.chunks[chunk_number]['dblocks']): tmp[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -470,21 +470,21 @@ class Amun: dset += tmp**2 tmp = self.__read_binary_data__('velz', chunk_number) dset += tmp**2 - dset = 1.0 / np.sqrt(1.0 - dset) + dset = 1.0 / numpy.sqrt(1.0 - dset) elif dataset == 'divv': p = self.attributes['ndims'] - 1 tmp = self.__read_binary_data__('velx', chunk_number) - dset = (np.roll(tmp, -1, axis=p) \ - - np.roll(tmp, 1, axis=p)) + dset = (numpy.roll(tmp, -1, axis=p) \ + - numpy.roll(tmp, 1, axis=p)) p -= 1 tmp = self.__read_binary_data__('vely', chunk_number) - dset += (np.roll(tmp, -1, axis=p) \ - - np.roll(tmp, 1, axis=p)) + dset += (numpy.roll(tmp, -1, axis=p) \ + - numpy.roll(tmp, 1, axis=p)) p -= 1 if p >= 0: tmp = self.__read_binary_data__('velz', chunk_number) - dset += (np.roll(tmp, -1, axis=p) \ - - np.roll(tmp, 0, axis=p)) + dset += (numpy.roll(tmp, -1, axis=p) \ + - numpy.roll(tmp, 0, axis=p)) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): @@ -492,15 +492,15 @@ class Amun: elif dataset == 'vorx': if self.attributes['ndims'] == 3: tmp = self.__read_binary_data__('vely', chunk_number) - dset = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + dset = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('velz', chunk_number) - dset += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) + dset += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) else: tmp = self.__read_binary_data__('velz', chunk_number) - dset = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) + dset = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): @@ -508,15 +508,15 @@ class Amun: elif dataset == 'vory': if self.attributes['ndims'] == 3: tmp = self.__read_binary_data__('velx', chunk_number) - dset = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) + dset = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) tmp = self.__read_binary_data__('velz', chunk_number) - dset += (np.roll(tmp, 1, axis=2) \ - - np.roll(tmp, -1, axis=2)) + dset += (numpy.roll(tmp, 1, axis=2) \ + - numpy.roll(tmp, -1, axis=2)) else: tmp = self.__read_binary_data__('velz', chunk_number) - dset = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + dset = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): @@ -524,18 +524,18 @@ class Amun: elif dataset == 'vorz': if self.attributes['ndims'] == 3: tmp = self.__read_binary_data__('velx', chunk_number) - dset = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + dset = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) tmp = self.__read_binary_data__('vely', chunk_number) - dset += (np.roll(tmp, -1, axis=2) \ - - np.roll(tmp, 1, axis=2)) + dset += (numpy.roll(tmp, -1, axis=2) \ + - numpy.roll(tmp, 1, axis=2)) else: tmp = self.__read_binary_data__('velx', chunk_number) - dset = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + dset = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('vely', chunk_number) - dset += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) + dset += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): @@ -543,32 +543,32 @@ class Amun: elif dataset == 'wvec': if self.attributes['ndims'] == 3: tmp = self.__read_binary_data__('velx', chunk_number) - wy = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) - wz = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + wy = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) + wz = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) tmp = self.__read_binary_data__('vely', chunk_number) - wz += (np.roll(tmp, -1, axis=2) \ - - np.roll(tmp, 1, axis=2)) - wx = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + wz += (numpy.roll(tmp, -1, axis=2) \ + - numpy.roll(tmp, 1, axis=2)) + wx = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('velz', chunk_number) - wx += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) - wy += (np.roll(tmp, 1, axis=2) \ - - np.roll(tmp, -1, axis=2)) + wx += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) + wy += (numpy.roll(tmp, 1, axis=2) \ + - numpy.roll(tmp, -1, axis=2)) else: tmp = self.__read_binary_data__('velx', chunk_number) - wz = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + wz = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('vely', chunk_number) - wz += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) + wz += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) tmp = self.__read_binary_data__('velz', chunk_number) - wx = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) - wy = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + wx = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) + wy = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) for p in range(self.chunks[chunk_number]['dblocks']): h = 2 * self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -580,47 +580,47 @@ class Amun: elif dataset == 'vort': if self.attributes['ndims'] == 3: tmp = self.__read_binary_data__('velx', chunk_number) - wy = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) - wz = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + wy = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) + wz = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) tmp = self.__read_binary_data__('vely', chunk_number) - wz += (np.roll(tmp, -1, axis=2) \ - - np.roll(tmp, 1, axis=2)) - wx = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + wz += (numpy.roll(tmp, -1, axis=2) \ + - numpy.roll(tmp, 1, axis=2)) + wx = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('velz', chunk_number) - wx += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) - wy += (np.roll(tmp, 1, axis=2) \ - - np.roll(tmp, -1, axis=2)) + wx += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) + wy += (numpy.roll(tmp, 1, axis=2) \ + - numpy.roll(tmp, -1, axis=2)) else: tmp = self.__read_binary_data__('velx', chunk_number) - wz = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + wz = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('vely', chunk_number) - wz += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) + wz += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) tmp = self.__read_binary_data__('velz', chunk_number) - wx = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) - wy = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + wx = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) + wy = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) - dset = 0.5 * np.sqrt(wx**2 + wy**2 + wz**2) + dset = 0.5 * numpy.sqrt(wx**2 + wy**2 + wz**2) for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] elif dataset == 'dvxdx': p = self.attributes['ndims'] - 1 tmp = self.__read_binary_data__('velx', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] elif dataset == 'dvxdy': p = self.attributes['ndims'] - 2 tmp = self.__read_binary_data__('velx', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -628,23 +628,23 @@ class Amun: p = self.attributes['ndims'] - 3 tmp = self.__read_binary_data__('velx', chunk_number) if p >= 0: - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] else: - dset = np.zeros_like(tmp) + dset = numpy.zeros_like(tmp) elif dataset == 'dvydx': p = self.attributes['ndims'] - 1 tmp = self.__read_binary_data__('vely', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] elif dataset == 'dvydy': p = self.attributes['ndims'] - 2 tmp = self.__read_binary_data__('vely', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -652,23 +652,23 @@ class Amun: p = self.attributes['ndims'] - 3 tmp = self.__read_binary_data__('vely', chunk_number) if p >= 0: - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] else: - dset = np.zeros_like(tmp) + dset = numpy.zeros_like(tmp) elif dataset == 'dvzdx': p = self.attributes['ndims'] - 1 tmp = self.__read_binary_data__('velz', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] elif dataset == 'dvzdy': p = self.attributes['ndims'] - 2 tmp = self.__read_binary_data__('velz', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -676,26 +676,26 @@ class Amun: p = self.attributes['ndims'] - 3 tmp = self.__read_binary_data__('velz', chunk_number) if p >= 0: - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] else: - dset = np.zeros_like(tmp) + dset = numpy.zeros_like(tmp) elif dataset == 'divb': p = self.attributes['ndims'] - 1 tmp = self.__read_binary_data__('magx', chunk_number) - dset = (np.roll(tmp, -1, axis=p) \ - - np.roll(tmp, 1, axis=p)) + dset = (numpy.roll(tmp, -1, axis=p) \ + - numpy.roll(tmp, 1, axis=p)) p -= 1 tmp = self.__read_binary_data__('magy', chunk_number) - dset += (np.roll(tmp, -1, axis=p) \ - - np.roll(tmp, 1, axis=p)) + dset += (numpy.roll(tmp, -1, axis=p) \ + - numpy.roll(tmp, 1, axis=p)) p -= 1 if p >= 0: tmp = self.__read_binary_data__('magz', chunk_number) - dset += (np.roll(tmp, -1, axis=p) \ - - np.roll(tmp, 0, axis=p)) + dset += (numpy.roll(tmp, -1, axis=p) \ + - numpy.roll(tmp, 0, axis=p)) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): @@ -703,15 +703,15 @@ class Amun: elif dataset == 'curx': if self.attributes['ndims'] == 3: tmp = self.__read_binary_data__('magy', chunk_number) - dset = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + dset = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('magz', chunk_number) - dset += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) + dset += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) else: tmp = self.__read_binary_data__('magz', chunk_number) - dset = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) + dset = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): @@ -719,15 +719,15 @@ class Amun: elif dataset == 'cury': if self.attributes['ndims'] == 3: tmp = self.__read_binary_data__('magx', chunk_number) - dset = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) + dset = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) tmp = self.__read_binary_data__('magz', chunk_number) - dset += (np.roll(tmp, 1, axis=2) \ - - np.roll(tmp, -1, axis=2)) + dset += (numpy.roll(tmp, 1, axis=2) \ + - numpy.roll(tmp, -1, axis=2)) else: tmp = self.__read_binary_data__('magz', chunk_number) - dset = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + dset = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): @@ -735,18 +735,18 @@ class Amun: elif dataset == 'curz': if self.attributes['ndims'] == 3: tmp = self.__read_binary_data__('magx', chunk_number) - dset = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + dset = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) tmp = self.__read_binary_data__('magy', chunk_number) - dset += (np.roll(tmp, -1, axis=2) \ - - np.roll(tmp, 1, axis=2)) + dset += (numpy.roll(tmp, -1, axis=2) \ + - numpy.roll(tmp, 1, axis=2)) else: tmp = self.__read_binary_data__('magx', chunk_number) - dset = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + dset = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('magy', chunk_number) - dset += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) + dset += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): @@ -754,32 +754,32 @@ class Amun: elif dataset == 'jvec': if self.attributes['ndims'] == 3: tmp = self.__read_binary_data__('magx', chunk_number) - wy = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) - wz = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + wy = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) + wz = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) tmp = self.__read_binary_data__('magy', chunk_number) - wz += (np.roll(tmp, -1, axis=2) \ - - np.roll(tmp, 1, axis=2)) - wx = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + wz += (numpy.roll(tmp, -1, axis=2) \ + - numpy.roll(tmp, 1, axis=2)) + wx = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('magz', chunk_number) - wx += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) - wy += (np.roll(tmp, 1, axis=2) \ - - np.roll(tmp, -1, axis=2)) + wx += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) + wy += (numpy.roll(tmp, 1, axis=2) \ + - numpy.roll(tmp, -1, axis=2)) else: tmp = self.__read_binary_data__('magx', chunk_number) - wz = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + wz = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('magy', chunk_number) - wz += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) + wz += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) tmp = self.__read_binary_data__('magz', chunk_number) - wx = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) - wy = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + wx = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) + wy = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) for p in range(self.chunks[chunk_number]['dblocks']): h = 2 * self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -791,47 +791,47 @@ class Amun: elif dataset == 'curr': if self.attributes['ndims'] == 3: tmp = self.__read_binary_data__('magx', chunk_number) - wy = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) - wz = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + wy = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) + wz = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) tmp = self.__read_binary_data__('magy', chunk_number) - wz += (np.roll(tmp, -1, axis=2) \ - - np.roll(tmp, 1, axis=2)) - wx = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + wz += (numpy.roll(tmp, -1, axis=2) \ + - numpy.roll(tmp, 1, axis=2)) + wx = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('magz', chunk_number) - wx += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) - wy += (np.roll(tmp, 1, axis=2) \ - - np.roll(tmp, -1, axis=2)) + wx += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) + wy += (numpy.roll(tmp, 1, axis=2) \ + - numpy.roll(tmp, -1, axis=2)) else: tmp = self.__read_binary_data__('magx', chunk_number) - wz = (np.roll(tmp, 1, axis=0) \ - - np.roll(tmp, -1, axis=0)) + wz = (numpy.roll(tmp, 1, axis=0) \ + - numpy.roll(tmp, -1, axis=0)) tmp = self.__read_binary_data__('magy', chunk_number) - wz += (np.roll(tmp, -1, axis=1) \ - - np.roll(tmp, 1, axis=1)) + wz += (numpy.roll(tmp, -1, axis=1) \ + - numpy.roll(tmp, 1, axis=1)) tmp = self.__read_binary_data__('magz', chunk_number) - wx = (np.roll(tmp, -1, axis=0) \ - - np.roll(tmp, 1, axis=0)) - wy = (np.roll(tmp, 1, axis=1) \ - - np.roll(tmp, -1, axis=1)) + wx = (numpy.roll(tmp, -1, axis=0) \ + - numpy.roll(tmp, 1, axis=0)) + wy = (numpy.roll(tmp, 1, axis=1) \ + - numpy.roll(tmp, -1, axis=1)) - dset = 0.5 * np.sqrt(wx**2 + wy**2 + wz**2) + dset = 0.5 * numpy.sqrt(wx**2 + wy**2 + wz**2) for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] elif dataset == 'dbxdx': p = self.attributes['ndims'] - 1 tmp = self.__read_binary_data__('magx', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] elif dataset == 'dbxdy': p = self.attributes['ndims'] - 2 tmp = self.__read_binary_data__('magx', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -839,23 +839,23 @@ class Amun: p = self.attributes['ndims'] - 3 tmp = self.__read_binary_data__('magx', chunk_number) if p >= 0: - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] else: - dset = np.zeros_like(tmp) + dset = numpy.zeros_like(tmp) elif dataset == 'dbydx': p = self.attributes['ndims'] - 1 tmp = self.__read_binary_data__('magy', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] elif dataset == 'dbydy': p = self.attributes['ndims'] - 2 tmp = self.__read_binary_data__('magy', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -863,23 +863,23 @@ class Amun: p = self.attributes['ndims'] - 3 tmp = self.__read_binary_data__('magy', chunk_number) if p >= 0: - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] else: - dset = np.zeros_like(tmp) + dset = numpy.zeros_like(tmp) elif dataset == 'dbzdx': p = self.attributes['ndims'] - 1 tmp = self.__read_binary_data__('magz', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] elif dataset == 'dbzdy': p = self.attributes['ndims'] - 2 tmp = self.__read_binary_data__('magz', chunk_number) - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] @@ -887,12 +887,12 @@ class Amun: p = self.attributes['ndims'] - 3 tmp = self.__read_binary_data__('magz', chunk_number) if p >= 0: - dset = np.roll(tmp, -1, axis=p) - np.roll(tmp, 1, axis=p) + dset = numpy.roll(tmp, -1, axis=p) - numpy.roll(tmp, 1, axis=p) dset *= 0.5 for p in range(self.chunks[chunk_number]['dblocks']): dset[...,p] /= self.cell_size[self.chunks[chunk_number]['levels'][p]] else: - dset = np.zeros_like(tmp) + dset = numpy.zeros_like(tmp) else: dset = self.__read_binary_data__(dataset, chunk_number) @@ -906,8 +906,7 @@ class Amun: the uniform mesh. """ from .interpolation import interpolate - import numpy as np - import sys + import numpy, sys if self.dataformat == None: raise Exception("Snapshot object has not been properly initialized!") @@ -915,26 +914,26 @@ class Amun: if not dataset_name in self.variables: raise Exception("Dataset '{}' is not available!\nAvailable datasets: {}\n".format(dataset_name, list(self.variables.keys()))) - dlo = np.array([self.attributes['xmin'], self.attributes['ymin']]) - dup = np.array([self.attributes['xmax'], self.attributes['ymax']]) - dln = np.array([self.attributes['xlen'], self.attributes['ylen']]) + dlo = numpy.array([self.attributes['xmin'], self.attributes['ymin']]) + dup = numpy.array([self.attributes['xmax'], self.attributes['ymax']]) + dln = numpy.array([self.attributes['xlen'], self.attributes['ylen']]) if self.attributes['ndims'] == 3: - dlo = np.append(dlo, self.attributes['zmin']) - dup = np.append(dup, self.attributes['zmax']) - dln = np.append(dln, self.attributes['zlen']) + dlo = numpy.append(dlo, self.attributes['zmin']) + dup = numpy.append(dup, self.attributes['zmax']) + dln = numpy.append(dln, self.attributes['zlen']) - slo = np.array(dlo) - sup = np.array(dup) + slo = numpy.array(dlo) + sup = numpy.array(dup) if extent != None: if len(extent) != 2 * self.attributes['ndims']: raise Exception("Wrong dimensions of the argument 'extent'!") - slo = np.array(extent)[0::2] - sup = np.array(extent)[1::2] + slo = numpy.array(extent)[0::2] + sup = numpy.array(extent)[1::2] if any(slo > dup) or any(sup < dlo) or any (slo >= sup): raise Exception("Wrong order of the dimensions in the argument 'extent'!") if maxlev != None: - if isinstance(maxlev, (int, np.int32)): + if isinstance(maxlev, (int, numpy.int32)): if 1 <= maxlev <= self.attributes['maxlev']: shrink = 2**(self.attributes['maxlev']-maxlev) elif maxlev > self.attributes['maxlev']: @@ -942,21 +941,21 @@ class Amun: else: raise Exception("Argument 'maxlev' must be an integer between 1 and {}.\n".format(self.attributes['maxlev'])) - bm = np.array([ self.attributes['ncells'] ]*self.attributes['ndims']) + bm = numpy.array([ self.attributes['ncells'] ]*self.attributes['ndims']) if self.attributes['ndims'] == 3: - rm = np.array([self.attributes['zblocks'], self.attributes['yblocks'], self.attributes['xblocks']]) + rm = numpy.array([self.attributes['zblocks'], self.attributes['yblocks'], self.attributes['xblocks']]) else: - rm = np.array([self.attributes['yblocks'], self.attributes['xblocks']]) + rm = numpy.array([self.attributes['yblocks'], self.attributes['xblocks']]) dm = rm * self.attributes['ncells'] * 2**(self.attributes['toplev'] - 1) // shrink - ll = np.array(np.floor(dm[::-1] * (slo - dlo) / dln), dtype='int') - uu = np.array( np.ceil(dm[::-1] * (sup - dlo) / dln), dtype='int') + ll = numpy.array(numpy.floor(dm[::-1] * (slo - dlo) / dln), dtype='int') + uu = numpy.array( numpy.ceil(dm[::-1] * (sup - dlo) / dln), dtype='int') dm = (uu - ll)[::-1] if dataset_name in [ 'velocity', 'vorticity', 'magnetic field', 'current density', 'electric field']: - arr = [ np.zeros(dm[:]), np.zeros(dm[:]), np.zeros(dm[:]) ] + arr = [ numpy.zeros(dm[:]), numpy.zeros(dm[:]), numpy.zeros(dm[:]) ] else: - arr = np.zeros(dm[:]) + arr = numpy.zeros(dm[:]) if progress: sys.stdout.write("Snapshot's path:\n '{}'\n".format(self.path)) @@ -981,8 +980,8 @@ class Amun: if all(iu[:] > ll[:]) and all(il[:] < uu[:]): nb = il[:] - ll[:] ne = iu[:] - ll[:] - ib = np.maximum(nb[:], 0) - ie = np.minimum(ne[:], uu[:] - ll[:]) + ib = numpy.maximum(nb[:], 0) + ie = numpy.minimum(ne[:], uu[:] - ll[:]) jb = ib[:] - nb[:] je = ie[:] - ne[:] + cm[:] @@ -1016,10 +1015,9 @@ class Amun: """ Function converts dataset of the requested variable to AMR VTK file. """ + import numpy, os, sys from .octree import OcBase, OcNode from .vtkio import WriteVTK - import numpy as np - import os, sys if self.dataformat == None: raise Exception("Snapshot object has not been properly initialized!") @@ -1078,12 +1076,12 @@ class Amun: if progress: sys.stdout.write("Generating OverlappingAMR VTK files\n") - bm = np.array([ self.attributes['ncells'] ]*self.attributes['ndims']) + bm = numpy.array([ self.attributes['ncells'] ]*self.attributes['ndims']) if self.attributes['ndims'] == 3: - rm = np.array([self.attributes['zblocks'], self.attributes['yblocks'], self.attributes['xblocks']]) + rm = numpy.array([self.attributes['zblocks'], self.attributes['yblocks'], self.attributes['xblocks']]) else: - rm = np.array([self.attributes['yblocks'], self.attributes['xblocks']]) + rm = numpy.array([self.attributes['yblocks'], self.attributes['xblocks']]) ofile = "{}_{:06d}.vthb".format(dataset_name, self.attributes['isnap']) opath = "{}_{:06d}".format(dataset_name, self.attributes['isnap']) @@ -1109,9 +1107,9 @@ class Amun: no = 0 for item in base.getNodesFromLevel(lv): - lo = np.array(item.index) * bm + lo = numpy.array(item.index) * bm up = lo + bm - 1 - ll = np.stack((lo,up)).T.flatten() + ll = numpy.stack((lo,up)).T.flatten() if item.hasData: vfile = os.path.join(opath, fmt.format(dataset_name, lv, no)) WriteVTK(vfile, label, item.data, \ diff --git a/python/amunpy/src/amunpy/interpolation.py b/python/amunpy/src/amunpy/interpolation.py index c1cf00d..866d24b 100644 --- a/python/amunpy/src/amunpy/interpolation.py +++ b/python/amunpy/src/amunpy/interpolation.py @@ -29,7 +29,6 @@ -------------------------------------------------------------------------------- """ -import numpy as np try: from scipy.ndimage import zoom from scipy.interpolate import splrep, splev, interp1d, pchip_interpolate @@ -43,6 +42,8 @@ def rebin(a, newshape): Subroutine changes the size of the input array to to new shape, by copying cells or averaging them. ''' + import numpy + assert len(a.shape) == len(newshape) m = a.ndim - 1 @@ -58,7 +59,7 @@ def rebin(a, newshape): return a.reshape(nn).mean(3).mean(1) else: for n in range(a.ndim): - a = np.repeat(a, newshape[n] // a.shape[n], axis=n) + a = numpy.repeat(a, newshape[n] // a.shape[n], axis=n) return(a) @@ -66,6 +67,8 @@ def interpolate(a, newshape, nghosts=0, method=None, order=1): ''' Subroutine rescales the block by interpolating its values. ''' + import numpy + if method == None or method == 'rebin' or not scipy_available: ng = nghosts @@ -85,48 +88,48 @@ def interpolate(a, newshape, nghosts=0, method=None, order=1): elif method in [ 'monotonic', 'pchip' ]: - dims = np.arange(a.ndim) + dims = numpy.arange(a.ndim) q = a for n in dims: - d2 = np.roll(q,-1, axis=0) + np.roll(q, 1, axis=0) - 2.0 * q + d2 = numpy.roll(q,-1, axis=0) + numpy.roll(q, 1, axis=0) - 2.0 * q q = q - d2 / 24.0 - d = np.array(q.shape) + d = numpy.array(q.shape) - xo = (np.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts) - xn = np.arange(0.5, newshape[n]) / newshape[n] + xo = (numpy.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts) + xn = numpy.arange(0.5, newshape[n]) / newshape[n] u = q.reshape([d[0], q.size // d[0]]) - f = np.zeros([newshape[n], q.size // d[0]]) + f = numpy.zeros([newshape[n], q.size // d[0]]) for i in range(q.size // d[0]): f[:,i] = pchip_interpolate(xo, u[:,i], xn) d[0] = newshape[n] f = f.reshape(d) - q = f.transpose(np.roll(dims, -1)) + q = f.transpose(numpy.roll(dims, -1)) return q elif method == 'spline': - dims = np.arange(a.ndim) + dims = numpy.arange(a.ndim) q = a for n in dims: - d2 = np.roll(q,-1, axis=0) + np.roll(q, 1, axis=0) - 2.0 * q + d2 = numpy.roll(q,-1, axis=0) + numpy.roll(q, 1, axis=0) - 2.0 * q q = q - d2 / 24.0 - d = np.array(q.shape) + d = numpy.array(q.shape) - xo = (np.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts) - xn = np.arange(0.5, newshape[n]) / newshape[n] + xo = (numpy.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts) + xn = numpy.arange(0.5, newshape[n]) / newshape[n] u = q.reshape([d[0], q.size // d[0]]) - f = np.zeros([newshape[n], q.size // d[0]]) + f = numpy.zeros([newshape[n], q.size // d[0]]) for i in range(q.size // d[0]): t = splrep(xo, u[:,i], k=5, s=0.0) f[:,i] = splev(xn, t) @@ -134,27 +137,27 @@ def interpolate(a, newshape, nghosts=0, method=None, order=1): d[0] = newshape[n] f = f.reshape(d) - q = f.transpose(np.roll(dims, -1)) + q = f.transpose(numpy.roll(dims, -1)) return q else: - dims = np.arange(a.ndim) + dims = numpy.arange(a.ndim) q = a for n in dims: - d2 = np.roll(q,-1, axis=0) + np.roll(q, 1, axis=0) - 2.0 * q + d2 = numpy.roll(q,-1, axis=0) + numpy.roll(q, 1, axis=0) - 2.0 * q q = q - d2 / 24.0 - d = np.array(q.shape) + d = numpy.array(q.shape) - xo = (np.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts) - xn = np.arange(0.5, newshape[n]) / newshape[n] + xo = (numpy.arange(0.5, a.shape[n]) - nghosts) / (a.shape[n] - 2 * nghosts) + xn = numpy.arange(0.5, newshape[n]) / newshape[n] u = q.reshape([d[0], q.size // d[0]]) - f = np.zeros([newshape[n], q.size // d[0]]) + f = numpy.zeros([newshape[n], q.size // d[0]]) for i in range(q.size // d[0]): t = interp1d(xo, u[:,i], kind=method) f[:,i] = t(xn) @@ -162,6 +165,6 @@ def interpolate(a, newshape, nghosts=0, method=None, order=1): d[0] = newshape[n] f = f.reshape(d) - q = f.transpose(np.roll(dims, -1)) + q = f.transpose(numpy.roll(dims, -1)) return q diff --git a/python/amunpy/src/amunpy/octree.py b/python/amunpy/src/amunpy/octree.py index e1a2d48..296ee7b 100644 --- a/python/amunpy/src/amunpy/octree.py +++ b/python/amunpy/src/amunpy/octree.py @@ -176,7 +176,7 @@ class OcNode(object): ''' Function populates all nodes at lower levels with data from higher levels ''' def populateNodeData(self): from .interpolation import rebin - import numpy as np + import numpy if not self.isLeaf: for n in range(len(self.children)): @@ -191,7 +191,7 @@ class OcNode(object): bm = comp.shape dm = [ 2 * d for d in bm ] - arr = np.zeros(dm, dtype=comp.dtype) + arr = numpy.zeros(dm, dtype=comp.dtype) for k, j, i in itertools.product(range(2), range(2), range(2)): n = (k * 2 + j) * 2 + i @@ -206,7 +206,7 @@ class OcNode(object): bm = self.children[0].data.shape dm = [ 2 * d for d in bm ] - arr = np.zeros(dm, dtype=self.children[0].data.dtype) + arr = numpy.zeros(dm, dtype=self.children[0].data.dtype) for k, j, i in itertools.product(range(2), range(2), range(2)): n = (k * 2 + j) * 2 + i