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https://github.com/chanzuckerberg/cellxgene.git
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fb61bd6e9c
This splits the backend into two parts: the local backend for desktop cellxgene and the AWS backend for hosted cellxgene. The local backend is in local_server while the hosted remains in server. The general idea is to copy everything from server to local_server, pull unneeded stuff out of local_server, and keep server as-is for this PR. Not touching server means all the infra and deployment code will continue working just as it did before so we can make those changes incrementally.
45 lines
1.6 KiB
Python
45 lines
1.6 KiB
Python
import anndata
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import argparse
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import random
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import scipy
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import numpy as np
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def main():
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parser = argparse.ArgumentParser("A command to generate test h5ad files")
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parser.add_argument("output", help="Name of the output file")
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parser.add_argument("nobs", type=int, help="Number of observations (rows)")
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parser.add_argument("nvar", type=int, help="Number of variables (columns)")
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parser.add_argument("-n", "--nnz-percent", type=float, default=100, help="percent of non-zeros")
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parser.add_argument("-c", "--col-shift", action="store_true", help="add a random value to each column")
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parser.add_argument("--seed", type=int, default=None, help="add a random value to each column")
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args = parser.parse_args()
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create_test_h5ad(args.output, args.nobs, args.nvar, args.nnz_percent, args.col_shift, args.seed)
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def create_test_h5ad(outfile, nobs, nvar, nnz_percent=100, apply_col_shift=False, seed=None):
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random.seed(seed)
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np.random.seed(seed)
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x = create_X_array(nobs, nvar, nnz_percent, apply_col_shift)
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obsm = {"X_random": np.random.rand(nobs, 2).astype(np.float32)}
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adata = anndata.AnnData(x, obsm=obsm)
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adata.write(outfile)
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def create_X_array(nobs, nvar, nnz_percent, apply_col_shift):
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if nnz_percent < 100:
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array = scipy.sparse.random(nobs, nvar, nnz_percent * 0.01, dtype=np.float32, format="csc")
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else:
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array = np.random.rand(nobs, nvar).astype(np.float32)
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if apply_col_shift:
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col_shift = np.random.rand((nvar))
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array += col_shift
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return array
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if __name__ == "__main__":
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main()
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