added datasets with out black or white and warn

.gitignore

@@ -133,4 +133,6 @@ dmypy.json
 notebooks/data*
 
 # ignore test data
-tests/testdata/specim_data
+tests/testdata/specim_data
+tests/testdata/no_white
+tests/testdata/no_black

pyproject.toml

@@ -139,6 +139,12 @@ markers = [
     "slow: marks tests as slow",
     "unit: fast offline tests",
 ]
+filterwarnings = [
+    "error",
+    "ignore::UserWarning",
+    # note the use of single quote below to denote "raw" strings in TOML
+    'ignore:function ham\(\) is deprecated:DeprecationWarning',
+]
 
 [tool.tox]
 legacy_tox_ini = """

src/specarray/io/specim_folder.py

@@ -6,6 +6,8 @@
 import xarray as xr
 from spectral.io.bilfile import BilFile
 
+import warnings
+
 
 def _find_files(folder: Path):
     """Find all files in the folder"""
@@ -85,8 +87,11 @@ def from_specim_folder(
                     raise ValueError("No capture data found")
             elif mode == "black":
                 black = data_array
+                # warning that there is no Dark Reference
+                warnings.warn("No Dark Reference found")
             elif mode == "white":
                 white = data_array
+                warnings.warn("No White Reference found")
         except Exception as exception:
             print(f"An error occurred reading {mode}: {exception}")
     return capture, metadata, wavelengths, black, white

src/specarray/specarray.py

@@ -41,29 +41,43 @@ def shape(self):
         """Return the shape of the data"""
         return self.capture.shape
 
+    @property
+    def has_black(self) -> bool:
+        return self.black.shape != ()
+
+    @property
+    def has_white(self) -> bool:
+        return self.white.shape != ()
+
     @property
     def spectral_albedo(self):
         """Calculate and return the spectral albedo. The values are limited to 0 and 1."""
-        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)
-        spectral_albedo.name = "spectral albedo"
-        return spectral_albedo
+        if self.has_black and self.has_white:
+            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)
+            spectral_albedo.name = "spectral albedo"
+            return spectral_albedo
+        else:
+            raise ValueError("No black or white reference")
 
     @property
     def broadband_albedo(self):
         """Calculate and return the broadband albedo"""
-        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
+        if self.has_black and self.has_white:
+            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
+        else:
+            raise ValueError("No black or white reference")
 
     def _gen_wavelength_point_df(self, raw_array: ndarray) -> pd.DataFrame:
         """Generate a dataframe with the wavelenghts as index and points as colums"""

tests/conftest.py

@@ -5,6 +5,8 @@
 
 from pathlib import Path
 import shutil
+from os import remove
+from time import sleep
 
 import pandas as pd
 import spectral.io.envi as envi
@@ -13,7 +15,10 @@
 
 thisdir = Path(__file__).parent.absolute()
 testdatadir = thisdir / "testdata"
-testdatadir1 = thisdir / "testdata" / "specim_data" / "capture"
+specim_data_dir = thisdir / "testdata" / "specim_data"
+no_black_dir = testdatadir / "no_black"
+no_white_dir = testdatadir / "no_white"
+testdatadir1 = specim_data_dir / "capture"
 specim_ex_name = "fake"
 
 
@@ -32,22 +37,41 @@ def _save_image_ndarray(prefix=""):
 
 
 def gen_data():
-    shutil.rmtree(testdatadir1, ignore_errors=True)
+    shutil.rmtree(specim_data_dir, ignore_errors=True)
+    shutil.rmtree(no_black_dir, ignore_errors=True)
+    shutil.rmtree(no_white_dir, ignore_errors=True)
     testdatadir1.mkdir(parents=True, exist_ok=True)
     _save_image_ndarray()
     _save_image_ndarray("DARKREF_")
     _save_image_ndarray("WHITEREF_")
     # rename all files from .img to .raw
     for f in testdatadir1.glob("*.img"):
         f.rename(f.with_suffix(".raw"))
+    # copy folder
+    shutil.copytree(specim_data_dir, no_black_dir)
+    shutil.copytree(specim_data_dir, no_white_dir)
+    remove(no_black_dir / "capture" / "DARKREF_fake.hdr")
+    remove(no_black_dir / "capture" / "DARKREF_fake.raw")
+    remove(no_white_dir / "capture" / "WHITEREF_fake.raw")
+    remove(no_white_dir / "capture" / "WHITEREF_fake.hdr")
 
 
 gen_data()
 
 
 @pytest.fixture()
 def testdata_specim_folder() -> Path:
-    return Path(__file__).parent.absolute() / "testdata/specim_data"
+    return specim_data_dir
+
+
+@pytest.fixture()
+def testdata_no_black() -> Path:
+    return no_black_dir
+
+
+@pytest.fixture()
+def testdata_no_white() -> Path:
+    return no_white_dir
 
 
 @pytest.fixture()

tests/test_integration.py

@@ -1,7 +1,25 @@
 from specarray import SpecArray
+from pathlib import Path
 
 from pytest_check import check
+import pytest
 
 
 def test_from_dir(testdata_specim: SpecArray):
     check.equal(testdata_specim.shape, (2, 1024, 448))
+
+
+def test_no_black(testdata_no_black: Path):
+    with pytest.warns(UserWarning):
+        no_black = SpecArray.from_folder(testdata_no_black)
+    check.is_instance(no_black, SpecArray)
+    check.equal(no_black.shape, (2, 1024, 448))
+    check.equal(no_black.black.shape, ())
+
+
+def test_no_white(testdata_no_white: Path):
+    with pytest.warns(UserWarning):
+        no_white = SpecArray.from_folder(testdata_no_white)
+    check.is_instance(no_white, SpecArray)
+    check.equal(no_white.shape, (2, 1024, 448))
+    check.equal(no_white.white.shape, ())