chagned name and added code

src/specarray/specarray.py

@@ -0,0 +1,141 @@
+#   ---------------------------------------------------------------------------------
+#   Copyright (c) Microsoft Corporation. All rights reserved.
+#   Licensed under the MIT License. See LICENSE in project root for information.
+#   ---------------------------------------------------------------------------------
+"""This is a Sample Python file."""
+
+
+from __future__ import annotations
+
+
+import spectral.io.envi as envi
+from spectral.io.bilfile import BilFile
+from dataclasses import dataclass
+from pathlib import Path
+import xarray as xr
+import pandas as pd
+from numpy import ndarray
+from spectral import imshow
+
+import dask.array as da
+import numpy as np
+
+
+@dataclass
+class Specim:
+    """Class for Specim hyperspectral Camera data"""
+
+    folder: Path
+    capture: xr.DataArray = None
+    black: xr.DataArray = None
+    white: xr.DataArray = None
+    metadata: dict = None
+    wavelengths: pd.Series = None
+
+    def __post_init__(self):
+        """Initialize the properties of the class"""
+        self.spectral_data = self._load_spectral_data(mode="capture")
+        self.metadata = self.spectral_data.metadata
+        self.wavelengths = self._get_wavelenghts()
+
+        modes = ["capture", "black", "white"]
+        for mode in modes:
+            spectral_data = self._load_spectral_data(mode=mode)
+            data_array = self._create_data_array(spectral_data, mode)
+            setattr(self, mode, data_array)
+
+    def __len__(self):
+        """Return the number of records"""
+        return len(self.capture)
+
+    def __getitem__(self, key):
+        return self.capture[key]
+
+    def _create_data_array(self, spectral_data: BilFile, mode: str) -> xr.DataArray:
+        data_array = xr.DataArray(
+            da.from_array(spectral_data.asarray()),
+            dims=["sample", "point", "band"],
+            name=mode,
+        )
+        data_array = data_array.assign_coords(band=self.wavelengths.values)
+        data_array = data_array.rename({"band": "wavelength"})
+        return data_array
+
+    @property
+    def shape(self):
+        """Return the shape of the data"""
+        return self.capture.shape
+
+    @property
+    def spectral_albedo(self):
+        spectral_albedo = (self.capture - self.black.mean(dim="sample")) / (
+            self.white.mean(dim="sample") - self.black.mean(dim="sample")
+        )
+        spectral_albedo = xr.where(spectral_albedo < 0.0, 0.0, spectral_albedo)
+        spectral_albedo = xr.where(spectral_albedo > 1.0, 1.0, spectral_albedo)
+        return spectral_albedo
+
+    @property
+    def broadband_albedo(self):
+        broadband_albedo = np.trapz(
+            self.spectral_albedo,
+            self.spectral_albedo.coords["wavelength"],
+        ) / (
+            self.spectral_albedo.coords["wavelength"].max().values
+            - self.spectral_albedo.coords["wavelength"].min().values
+        )
+        broadband_albedo = xr.DataArray(
+            broadband_albedo, dims=["sample", "point"], name="broadband_albedo"
+        )
+        return broadband_albedo
+
+    def _find_files(self):
+        """Find all files in the folder"""
+        capture_folder = self.folder / "capture"
+        hdr_files = list(capture_folder.glob("*.hdr"))
+        raw_files = list(capture_folder.glob("*.raw"))
+        return hdr_files, raw_files
+
+    def _load_spectral_data(self, mode="capture"):
+        """Load the spectral data"""
+        hdr_files, raw_files = self._find_files()
+
+        hdr_file_path = None
+        raw_file_path = None
+
+        for hdr_file, raw_file in zip(hdr_files, raw_files):
+            if mode == "capture":
+                if not hdr_file.stem.startswith(("WHITEREF", "DARKREF")):
+                    hdr_file_path = hdr_file
+                    raw_file_path = raw_file
+                    break
+            elif mode == "white":
+                prefix = "WHITEREF"
+                if hdr_file.stem.startswith(prefix):
+                    hdr_file_path = hdr_file
+                    raw_file_path = raw_file
+                    break
+            elif mode == "black":
+                prefix = "DARKREF"
+                if hdr_file.stem.startswith(prefix):
+                    hdr_file_path = hdr_file
+                    raw_file_path = raw_file
+                    break
+
+        if hdr_file_path is None or raw_file_path is None:
+            raise ValueError(f"No matching file found for mode {mode}")
+
+        return envi.open(hdr_file_path, raw_file_path)
+
+    def _get_wavelenghts(self):
+        """Set the wavelenghts"""
+        return pd.Series(
+            pd.to_numeric(self.metadata["wavelength"]), name="wavelenghts (nm)"
+        )
+
+    def _gen_wavelength_point_df(self, raw_array: ndarray):
+        """Generate a dataframe with the wavelenghts as index and points as colums"""
+        sample_df = pd.DataFrame(raw_array).transpose()
+        sample_df["wavelenght (nm)"] = self.wavelengths
+        sample_df.set_index("wavelenght (nm)", inplace=True)
+        return sample_df