Taykhoom commited on
Commit
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1 Parent(s): b670f4c

Deduplicate causal and bidirectional configs

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README.md CHANGED
@@ -11,22 +11,14 @@ tags:
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  - hg38
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  - parquet
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  configs:
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- - config_name: canonical-causal
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  data_files:
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  - split: all
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  path: functional-upstream-gamba-causal.parquet
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- - config_name: canonical-bidi
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  data_files:
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  - split: all
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  path: functional-upstream-gamba-bidi.parquet
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- - config_name: noncoding-added-causal
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- data_files:
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- - split: all
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- path: functional-upstream-gamba-noncoding-added-causal.parquet
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- - config_name: noncoding-added-bidi
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- data_files:
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- - split: all
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- path: functional-upstream-gamba-noncoding-added-bidi.parquet
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  ---
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  # GAMBA Functional Regions: Feature vs Upstream
@@ -40,12 +32,11 @@ not overlap retained anchors from the same category.
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  | Config | Train rows | Test rows | Total |
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  |---|---:|---:|---:|
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- | `canonical-causal`, `canonical-bidi` | 135,692 | 33,982 | 169,674 |
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- | `noncoding-added-causal`, `noncoding-added-bidi` | 150,726 | 37,834 | 188,560 |
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- The `noncoding-added-*` configs are an explicit extension from
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- [Gamba-Processing](https://github.com/TaykhoomDalal/Gamba-Processing), not an
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- additional category emitted by GAMBA's current `create_eval_data.py`.
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  ## Choosing a context
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@@ -62,13 +53,13 @@ context and is not the paper protocol.
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  ```python
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  from datasets import load_dataset
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- canonical = load_dataset(
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  "Taykhoom/functional-upstream-gamba",
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- "canonical-bidi",
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  split="all",
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  )
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- train = canonical.filter(lambda row: row["split"] == "train")
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- test = canonical.filter(lambda row: row["split"] == "test")
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  ```
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  Here, `split="all"` tells Hugging Face to load the single physical parquet
 
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  - hg38
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  - parquet
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  configs:
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+ - config_name: causal
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  data_files:
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  - split: all
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  path: functional-upstream-gamba-causal.parquet
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+ - config_name: bidi
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  data_files:
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  - split: all
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  path: functional-upstream-gamba-bidi.parquet
 
 
 
 
 
 
 
 
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  ---
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  # GAMBA Functional Regions: Feature vs Upstream
 
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  | Config | Train rows | Test rows | Total |
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  |---|---:|---:|---:|
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+ | `causal`, `bidi` | 150,728 | 37,834 | 188,562 |
 
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+ Each config includes the `noncoding_regions` extension. Filter
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+ `category != "noncoding_regions"` to recover the exact 169,674-row,
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+ ten-category GAMBA paper dataset without storing those rows twice.
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  ## Choosing a context
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  ```python
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  from datasets import load_dataset
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+ dataset = load_dataset(
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  "Taykhoom/functional-upstream-gamba",
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+ "bidi",
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  split="all",
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  )
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+ paper = dataset.filter(lambda row: row["category"] != "noncoding_regions")
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+ test = paper.filter(lambda row: row["split"] == "test")
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  ```
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  Here, `split="all"` tells Hugging Face to load the single physical parquet
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