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import yt | ||
import numpy as np | ||
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ds = yt.load('output_00080/info_00080.txt') | ||
sp = ds.sphere([.5]*3, (0.5, 'code_length')) | ||
ad = ds.all_data() | ||
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# def simple(field ,data): | ||
# if isinstance(data, yt.fields.field_detector.FieldDetector): | ||
# return data['pressure'] / data['dx'] | ||
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# # dest = np.zeros((6_000_000), dtype=np.float64) * np.nan | ||
# offset = 0 | ||
# cell_count = 0 | ||
# import ipdb; ipdb.set_trace() | ||
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# for i, subset in enumerate(data._current_chunk.objs): | ||
# oh = subset.domain.oct_handler | ||
# cell_count += data.selector.count_oct_cells(oh, subset.domain_id) | ||
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# dest = np.zeros(cell_count, dtype=np.float64) | ||
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# for i, subset in enumerate(data._current_chunk.objs): | ||
# # Extract *all* data in octree | ||
# tmp = subset['x'] | ||
# doffset = subset.select(subset.selector, tmp, dest, offset) | ||
# offset += doffset | ||
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# return data.apply_units(dest, tmp.units) | ||
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def simple(field ,data): | ||
if isinstance(data, yt.fields.field_detector.FieldDetector): | ||
return data['pressure'] / data['dx'] | ||
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chunks = list(data.index._chunk_io(data)) | ||
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all_data = [] | ||
for ichunk, chunk in enumerate(chunks): | ||
for subset in chunk.objs: | ||
tmp = subset['x'].T.reshape(-1, 8)# .T.reshape(-1, 8) | ||
oh = subset.domain.oct_handler | ||
selector = data.selector | ||
dom_cell_count = data.selector.count_oct_cells(oh, subset.domain_id) | ||
print(np.product(tmp.shape), dom_cell_count) | ||
levels, cell_inds, file_inds = oh.file_index_octs( | ||
selector, subset.domain_id, dom_cell_count) | ||
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tr = {} | ||
tr['x'] = np.zeros(dom_cell_count, 'float64') | ||
for ilevel in range(levels.max()): | ||
oh.fill_level(ilevel, levels, cell_inds, file_inds, tr, {'x': tmp}) | ||
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all_data.append(tr['x']) | ||
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dest = np.concatenate(all_data) | ||
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return data.apply_units(dest, tmp.units) | ||
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ds.add_field(('gas', 'test'), function=simple, units='code_length') | ||
test = ad['gas', 'test'] | ||
a = test.to('unitary').value | ||
b = sp['dx'].to('unitary').value | ||
assert np.allclose(a, b) | ||
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assert test.shape == ad['ones'].shape | ||
print('Yes!') | ||
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import sys | ||
sys.exit(0) | ||
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def generate_gradient(direction): | ||
idir = 'xyz'.index(direction) | ||
def grad(field, data): | ||
if isinstance(data, yt.fields.field_detector.FieldDetector): | ||
return data['pressure'] / data['dx'] | ||
offset = 0 | ||
cell_count = 0 | ||
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for i, subset in enumerate(data._current_chunk.objs): | ||
oh = subset.domain.oct_handler | ||
cell_count += data.selector.count_oct_cells(oh, subset.domain_id) | ||
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dest = np.zeros(cell_count, dtype=np.float64) | ||
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for i, subset in enumerate(data._current_chunk.objs): | ||
oh = subset.domain.oct_handler | ||
# # Extract *all* data in octree | ||
# data_in = {direction: subset[direction], | ||
# 'pressure': subset['pressure']} | ||
# data_out = oh.get_hypercube(subset, data_in) | ||
# # xin = data_in['x'][..., 100].to('code_length').value*64 + .5 | ||
# # xout = data_out['x'][1:3, 1:3, 1:3, 100].to('code_length').value*64 + .5 | ||
# sl = slice(1, 3) | ||
# sl1 = [sl]*3 + [slice(None)] | ||
# sl2 = [sl]*3 + [slice(None)] | ||
# sl3 = [sl]*3 + [slice(None)] | ||
# sl1[2-idir] = slice(0, 2) | ||
# sl2[2-idir] = slice(1, 3) | ||
# sl3[2-idir] = slice(2, 4) | ||
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# # Compute gradients | ||
# x = data_out[direction] | ||
# p = data_out['pressure'] | ||
# dpl = (p[sl3] - p[sl2]) / (x[sl3] - x[sl2]) | ||
# dpr = (p[sl2] - p[sl1]) / (x[sl2] - x[sl1]) | ||
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# maskl = np.isfinite(dpl) | ||
# maskr = np.isfinite(dpr) | ||
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# grad = np.where(maskl & maskr, (dpl + dpr) / 2, | ||
# np.where(maskl, dpl, dpr)) | ||
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# Select data in region | ||
tmp = subset['x'] | ||
doffset = oh.selector_fill(subset.selector, tmp, dest, offset) | ||
offset += doffset | ||
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return data.apply_units(dest, p.units / x.units) | ||
return grad | ||
# ds.add_field(('gas', 'p_grad_x'), function=generate_gradient('x'), sampling_type='cell', units='dyne/cm**3') | ||
# ds.add_field(('gas', 'p_grad_y'), function=generate_gradient('y'), sampling_type='cell', units='dyne/cm**3') | ||
# ds.add_field(('gas', 'p_grad_z'), function=generate_gradient('z'), sampling_type='cell', units='dyne/cm**3') | ||
# test = ad['gas', 'p_grad_x'] | ||
# mask = np.isfinite(test) | ||
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# p = yt.ProjectionPlot(ds, 'x', 'p_grad_x') | ||
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