mock

mock data.

make_dummy_cells

 make_dummy_cells (n:int)

source

make_dummy_genes

 make_dummy_genes (n:int)

source

make_mock_genes_x_tbins

 make_mock_genes_x_tbins (genes:Union[int,List[str],NoneType]=['wasf',
                          'colq', 'gpr1', 'chrm3', 'lmod2', 'tek',
                          'kank3', 'oca2', 'taz', 'map4k1'],
                          tbins:int=100)

df_trj = make_mock_genes_x_tbins()
df_trj.head()

	0	1	2	3	4	5	6	7	8	9	...	90	91	92	93	94	95	96	97	98	99
wasf	0	0	0	0	0	0	0	0	0	0	...	8	9	9	9	9	9	9	9	9	9
colq	9	9	9	9	9	8	8	8	8	8	...	0	0	0	0	0	0	0	0	0	0
gpr1	0	0	0	0	0	0	0	0	0	0	...	9	9	9	9	9	9	9	9	9	9
chrm3	9	9	9	9	9	9	9	9	9	9	...	0	0	0	0	0	0	0	0	0	0
lmod2	0	0	0	0	0	0	0	1	1	1	...	8	9	9	9	9	9	9	9	9	9

5 rows × 100 columns

source

make_mock_trajectories

 make_mock_trajectories (tbins:int=100, cells:int=50, genes:int=10)

trajs = make_mock_trajectories()
trajs.shape # (tbins, cells, genes)

(100, 50, 10)

source

df_trj_to_genes_x_tbins

 df_trj_to_genes_x_tbins (trajectories:numpy.ndarray, agg_fn=<function
                          mean at 0x7f5c4ed82a70>)

Transpose and aggregate trajectories matrix (timebinse, cells, gene) to produce (genes, timebins)

source

df_trj_to_cells_x_tbins

 df_trj_to_cells_x_tbins (trajectories:numpy.ndarray, agg_fn=<function
                          mean at 0x7f5c4ed82a70>)

Transpose and aggregate trajectories matrix (timebinse, cells, gene) to produce (cells, timebins)

df_trj_to_genes_x_tbins(trajs).shape

(10, 100)