Merge remote-tracking branch 'origin/main'

AstroM3Dataset.py

@@ -1,3 +1,4 @@
+import os
 from io import BytesIO
 import datasets
 import pandas as pd
@@ -5,7 +6,8 @@ import numpy as np
 import json
 from astropy.io import fits
 
-from utils import ParallelZipFile
+print('what what')
+from .utils.parallelzipfile import ParallelZipFile as ZipFile
 
 _DESCRIPTION = (
     "AstroM3 is a time-series astronomy dataset containing photometry, spectra, "
@@ -48,8 +50,8 @@ class AstroM3Dataset(datasets.GeneratorBasedBuilder):
             description=_DESCRIPTION,
             features=datasets.Features(
                 {
-                    "photometry": datasets.Array2D(shape=(None, 3), dtype="float32"),
-                    "spectra": datasets.Array2D(shape=(None, 3), dtype="float32"),
+                    "photometry": datasets.Sequence(datasets.Sequence(datasets.Value("float32"), length=3)),
+                    "spectra": datasets.Sequence(datasets.Sequence(datasets.Value("float32"), length=3)),
                     "metadata": datasets.Sequence(datasets.Value("float32"), length=38),
                     "label": datasets.Value("string"),
                 }
@@ -99,29 +101,6 @@ class AstroM3Dataset(datasets.GeneratorBasedBuilder):
 
         return np.vstack((wavelength, specflux, ivar)).T
 
-    @staticmethod
-    def _transform_metadata(row, info):
-        row_copy = row.copy(deep=True)
-
-        for transformation_type, value in info["metadata_func"].items():
-            if transformation_type == "abs":
-                for col in value:
-                    row_copy[col] = (
-                        row_copy[col] - 10 + 5 * np.log10(np.where(row_copy["parallax"] <= 0, 1, row_copy["parallax"]))
-                    )
-            elif transformation_type == "cos":
-                for col in value:
-                    row_copy[col] = np.cos(np.radians(row_copy[col]))
-            elif transformation_type == "sin":
-                for col in value:
-                    row_copy[col] = np.sin(np.radians(row_copy[col]))
-            elif transformation_type == "log":
-                for col in value:
-                    row_copy[col] = np.log10(row_copy[col])
-
-        row_copy = (row_copy - info["mean"]) / info["std"]
-        return row_copy
-
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators for train, val, and test."""
 
@@ -150,7 +129,7 @@ class AstroM3Dataset(datasets.GeneratorBasedBuilder):
 
         # Load photometry and init reader
         photometry_path = dl_manager.download(f"{_URL}/photometry.zip")
-        self.reader_v = ParallelZipFile(photometry_path)
+        self.reader_v = ZipFile(photometry_path)
 
         return [
             datasets.SplitGenerator(
@@ -181,29 +160,10 @@ class AstroM3Dataset(datasets.GeneratorBasedBuilder):
         with open(info_path) as f:
             info = json.loads(f.read())
 
-        for i, (idx, row) in enumerate(df.iterrows()):
+        for idx, row in df.iterrows():
             photometry = self._get_photometry(row["name"])
             spectra = self._get_spectra(spectra_files[row["spec_filename"]])
 
-            metadata = row[info["all_cols"]]
-            # metadata_norm = self._transform_metadata(metadata, info)
-
-            # yield idx, {
-            #     "photometry": photometry,
-            #     "spectra": spectra,
-            #     "metadata": {
-            #         "original": {
-            #             "photometry": metadata[info["photo_cols"]].to_dict(),
-            #             "metadata": metadata[info["meta_cols"]].to_dict()
-            #         },
-            #         "transformed": {
-            #             "photometry": metadata_norm[info["photo_cols"]].to_dict(),
-            #             "metadata": metadata_norm[info["meta_cols"]].to_dict()
-            #         }
-            #     },
-            #     "label": row["target"],
-            # }
-
             yield idx, {
                 "photometry": photometry,
                 "spectra": spectra,

spectra.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:82314a30eea81ca561ba69873140cb19c6484fc4433e610029de9b6419e4ec68
+size 1152905965