| import polars as pl |
| concentrations = pl.read_csv("concentrations.csv") |
| import scanpy as sc |
| from joblib import Parallel, delayed |
| import gc |
|
|
| drug_to_concentration = { |
| row[0]: row[1] |
| for row in concentrations.iter_rows() |
| } |
|
|
| def reduce(plate: int): |
| try: |
| print(f"Plate: {plate}") |
| X = sc.read_h5ad(f"../Data/h5ad/h5ad/plate{plate}_filt_Vevo_Tahoe100M_WServicesFrom_ParseGigalab.h5ad", backed="r") |
| print(f"Loaded: {plate}") |
| X = X[(X.obs["pass_filter"] == "full") & (X.obs["drugname_drugconc"].astype(str) == X.obs["drug"].map(lambda x: drug_to_concentration[x]).astype(str))] |
| print(f"Filtered: {plate}") |
| X.write_h5ad(f"../Data/h5ad/reduced/plate{plate}.h5ad") |
| print(f"Wrote: {plate}") |
| cells = X.n_vars |
| del X |
| gc.collect() |
| return cells |
| except Exception as e: |
| print(f"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") |
| print(f"ERROR loading {plate}") |
| print(f"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!") |
|
|
| results = Parallel(n_jobs=4)(delayed(reduce)(i) for i in range(1, 14 + 1)) |
| print(results) |
