Add benchmark dataset creation

notebooks/nontargeting_experiments/make_benchmark_dataset.py

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+
+# %% Make an intermediate dataset
+import pandas as pd
+
+location = "/mnt/efs/dlmbl/G-et/csv/dataset_split_1168.csv"
+
+metadata = pd.read_csv(location)
+
+# %%
+assert "nontargeting" in metadata['gene'].values
+assert "CCT2" in metadata['gene'].values
+# %% Keep only the nontargeting and CCT2 genes
+sample = metadata[metadata['gene'].isin(["nontargeting", "CCT2"])]
+
+# %%
+sample[sample.split=="train"].gene.value_counts()
+
+# %%
+# Sub-sample the non-targeting ones to have the same number of cells as CCT2
+sampled_nontargeting = sample[sample.gene=="nontargeting"].sample(n=len(sample[sample.gene=="CCT2"]), random_state=42)
+sampled_cct2 = sample[sample.gene=="CCT2"]
+
+# %%
+sampled = pd.concat([sampled_nontargeting, sampled_cct2])
+
+# %%
+sampled.to_csv("/mnt/efs/dlmbl/G-et/csv/dataset_split_benchmark.csv", index=False)
+
+# %%