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from pathlib import Path |
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import numpy as np |
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import zarr |
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from vcelldata.mesh import CartesianMesh |
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from vcelldata.simdata_models import PdeDataSet, DataBlockHeader, DataFunctions, NamedFunction, VariableType |
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def write_zarr(pde_dataset: PdeDataSet, data_functions: DataFunctions, mesh: CartesianMesh, zarr_dir: Path) -> None: |
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volume_data_vars: list[DataBlockHeader] = [v for v in pde_dataset.variables_block_headers() |
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if v.variable_type == VariableType.VOLUME] |
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volume_functions: list[NamedFunction] = [f for f in data_functions.named_functions |
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if f.variable_type == VariableType.VOLUME] |
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num_channels = len(volume_data_vars) + len(volume_functions) + 1 |
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num_t: int = len(pde_dataset.times()) |
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times: list[float] = pde_dataset.times() |
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header = pde_dataset.first_data_zip_file_metadata().file_header |
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num_x: int = header.sizeX |
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num_y: int = header.sizeY |
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num_z: int = header.sizeZ |
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z1 = zarr.open(str(zarr_dir.absolute()), mode='w', shape=(num_t, num_channels, num_z, num_y, num_x), chunks=(1,1,num_z,num_y,num_x), dtype=float) |
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channel_metadata: list[dict] = [] |
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for t in range(num_t): |
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bindings = {} |
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region_map = mesh.volume_region_map.reshape((num_z, num_y, num_x)) |
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z1[t, 0, :, :, :] = region_map |
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if t == 0: |
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channel_metadata.append({"index": 0, |
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"label": "region_mask", |
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"domain_name": "all", |
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"min_value": np.min(region_map), |
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"max_value": np.max(region_map)}) |
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for i, v in enumerate(volume_data_vars): |
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var_data: np.ndarray = pde_dataset.get_data(v.var_name, times[t]).reshape((num_z, num_y, num_x)) |
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c = i + 1 |
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z1[t, c, :, :, :] = var_data |
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domain_name = v.var_name.split("::")[0] |
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var_name = v.var_name.split("::")[1] |
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bindings[var_name] = var_data |
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if t == 0: |
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channel_metadata.append({"index": c, |
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"label": var_name, |
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"domain_name": domain_name, |
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"min_values": [], |
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"max_values": [], |
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"mean_values": []}) |
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channel_metadata[c]["min_values"].append(np.min(var_data)) |
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channel_metadata[c]["max_values"].append(np.max(var_data)) |
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channel_metadata[c]["mean_values"].append(np.mean(var_data)) |
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for j, f in enumerate(volume_functions): |
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func_data = f.evaluate(variable_bindings=bindings).reshape((num_z, num_y, num_x)) |
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c = i + j + 2 |
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z1[t, c, :, :, :] = func_data |
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domain_name = f.name.split("::")[0] |
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function_name = f.name.split("::")[1] |
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if t == 0: |
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channel_metadata.append({"index": (i + j + 2), |
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"label": function_name, |
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"domain_name": domain_name, |
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"min_values": [], |
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"max_values": [], |
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"mean_values": []}) |
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channel_metadata[c]["min_values"].append(np.min(func_data)) |
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channel_metadata[c]["max_values"].append(np.max(func_data)) |
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channel_metadata[c]["mean_values"].append(np.mean(func_data)) |
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z1.attrs["metadata"] = { |
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"axes": [ |
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{"name": "t", "type": "time", "unit": "second"}, |
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{"name": "c", "type": "channel", "unit": None}, |
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{"name": "z", "type": "space", "unit": "micrometer"}, |
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{"name": "y", "type": "space", "unit": "micrometer"}, |
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{"name": "x", "type": "space", "unit": "micrometer"} |
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], |
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"channels": channel_metadata, |
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"times": times, |
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"mesh": { |
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"size": mesh.size, |
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"extent": mesh.extent, |
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"origin": mesh.origin, |
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"volume_regions": [{"region_index": mesh.volume_regions[i][0], |
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"domain_type_index": mesh.volume_regions[i][1], |
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"volume": mesh.volume_regions[i][2], |
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"domain_name": mesh.volume_regions[i][3]} for i in range(len(mesh.volume_regions))], |
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} |
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} |
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z1.attrs["metadata"]["mesh"] = { |
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"size": mesh.size, |
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"extent": mesh.extent, |
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"origin": mesh.origin, |
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"volume_regions": [{"region_index": mesh.volume_regions[i][0], |
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"domain_type_index": mesh.volume_regions[i][1], |
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"volume": mesh.volume_regions[i][2], |
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"domain_name": mesh.volume_regions[i][3]} for i in range(len(mesh.volume_regions))], |
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} |
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