code: def test_decode_numpy_scalar_with_explicit_scalar_codec():
      """Decoding a row that has a field with the codec set explicitly"""
  
      MatrixSchema = Unischema(
          "TestSchema",
          [
              UnischemaField(
                  "scalar",
                  np.float64,
                  (),
                  ScalarCodec(DoubleType()),
                  False,
              )
          ],
      )
      row = {"scalar": 42.0}
      decoded_value = decode_row(row, MatrixSchema)["scalar"]
      assert decoded_value == 42
      assert isinstance(decoded_value, np.float64)
  
file_path: petastorm/petastorm/tests/test_decode_row.py
imports: from decimal import Decimal
  import numpy
  import pytest
  from pyspark.sql.types import DoubleType
  from petastorm.codecs import NdarrayCodec, ScalarCodec
  from petastorm.unischema import UnischemaField, Unischema
  from petastorm.utils import decode_row, DecodeFieldError
label_desc: Use image node_id 5 for calling a global function with example usage: test_decode_numpy_scalar_with_explicit_scalar_codec() without return types