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Code Issues Packages Projects Releases Wiki Activity

initial support for corpora schema conventions (#1676)

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* initial support for corpora schema conventions

* remove debugging print

* add corpora util module

* tests

* lint

* PR review edits

* PR changes

* more PR changes

* more PR chnages

* PR fixes

* formatting

* PR updates

* lint

* PR review
This commit is contained in:
Bruce Martin
2020-07-28 17:32:27 -07:00
committed by GitHub
parent 5285556415
commit 59f989d26f
12 changed files with 450 additions and 104 deletions
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server/test/test_diffexp.py
+6 -5
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@@ -3,7 +3,7 @@ from server.data_common.matrix_loader import MatrixDataLoader
from server.test import PROJECT_ROOT, app_config
import server.compute.diffexp_cxg as diffexp_cxg
import server.compute.diffexp_generic as diffexp_generic
from server.converters.cxgtool import write_cxg
from server.converters.cxgtool import write_cxg, create_cxg_group_metadata
from server.test.create_test_matrix import create_test_h5ad
from server.data_common.fbs.matrix import encode_matrix_fbs, decode_matrix_fbs
import numpy as np
@@ -16,8 +16,7 @@ class DiffExpTest(unittest.TestCase):
adaptor types and different algorithms."""
def load_dataset(self, path, extra_server_config={}, extra_dataset_config={}):
config = app_config(path, extra_server_config=extra_server_config,
extra_dataset_config=extra_dataset_config)
config = app_config(path, extra_server_config=extra_server_config, extra_dataset_config=extra_dataset_config)
loader = MatrixDataLoader(path)
adaptor = loader.open(config)
return adaptor
@@ -105,13 +104,15 @@ class DiffExpTest(unittest.TestCase):
adata = adaptor_anndata.data
sparsename = os.path.join(dirname, "sparse.cxg")
write_cxg(adata=adata, container=sparsename, title="sparse", sparse_threshold=11)
cxg_group_metadata = create_cxg_group_metadata(adata=adata, basefname="sparse.h5ad", title="sparse",)
write_cxg(adata=adata, container=sparsename, cxg_group_metadata=cxg_group_metadata, sparse_threshold=11)
adaptor_sparse = self.load_dataset(sparsename)
assert adaptor_sparse.open_array("X").schema.sparse
assert adaptor_sparse.has_array("X_col_shift") == apply_col_shift
densename = os.path.join(dirname, "dense.cxg")
write_cxg(adata=adata, container=densename, title="dense", sparse_threshold=0)
cxg_group_metadata = create_cxg_group_metadata(adata=adata, basefname="dense.h5ad", title="dense",)
write_cxg(adata=adata, container=densename, cxg_group_metadata=cxg_group_metadata, sparse_threshold=0)
adaptor_dense = self.load_dataset(densename)
assert not adaptor_dense.open_array("X").schema.sparse
assert not adaptor_dense.has_array("X_col_shift")