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Original /initialize working

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Charlotte Weaver
2018-06-22 11:00:22 -07:00
parent 1621d20bc4
commit 9b4bcb7f7b
3 changed files with 24 additions and 32 deletions
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backend/app/scanpy_engine/scanpy_engine.py
+10 -22
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@@ -56,8 +56,7 @@ class ScanpyEngine(CXGDriver):
:param filter:
:return: iterator through cell ids
"""
cell_idx = np.ones((self.cell_count,), dtype=bool)
# TODO does this need to be a generator too?
cell_idx = np.ones((self.cell_count(),), dtype=bool)
for key, value in filter.items():
if value["variable_type"] == "categorical":
key_idx = np.in1d(getattr(self.data.obs, key), value["query"])
@@ -71,34 +70,27 @@ class ScanpyEngine(CXGDriver):
if max_:
key_idx = np.array((getattr(self.data.obs, key) <= min_).data)
cell_idx = np.logical_and(cell_idx, key_idx)
# If this is slow, could vectorize with logical array and then loop through that
for idx in range(self.cell_count):
if cell_idx[idx]:
yield self.data.obs.index[idx]
return self.data[cell_idx, :]
def metadata_ranges(self, cells_iterator=None):
def metadata_ranges(self, df=None):
metadata_ranges = {}
if cells_iterator:
data = self.data.obs.iloc[[i for i in cells_iterator], :]
else:
data = self.data.obs
if not df:
df = self.data
for field in self.schema:
if self.schema[field]["variabletype"] == "categorical":
group_by = field
if group_by == "CellName":
group_by = 'cell_name'
metadata_ranges[field] = {"options": data.groupby(group_by).size().to_dict()}
metadata_ranges[field] = {"options": df.obs.groupby(group_by).size().to_dict()}
else:
metadata_ranges[field] = {
"range": {
"min": data[field].min(),
"max": data[field].max()
"min": df.obs[field].min(),
"max": df.obs[field].max()
}
}
return metadata_ranges
# Should this return the order of metadata fields as the first value?
def metadata(self, cells_iterator, fields=None):
"""
Generator for metadata. Gets the metadata values cell by cell and returns all value
@@ -129,13 +121,9 @@ class ScanpyEngine(CXGDriver):
def diffexp(self, cells_iterator_1, cells_iterator_2):
"""
Computes the top differentially expressed genes between two clusters
pass
:param cells_iterator_1: First set of cell ids
:param cells_iterator_2: Second set of cell ids
:return: Up in the air: I recommend [gene name, mean_expression_cells1, mean_expression_cells2, average_difference, statistic_value]
"""
def expression(self, ):
pass