some tests

flint/validation.py

@@ -197,6 +197,8 @@ class SourceCounts(NamedTuple):
     """Euclidean normalised source counts"""
     euclid_counts_err: np.ndarray
     """Rough estimate of error on the euclidean normalised source counts"""
+    area: float
+    """The area in square degrees that the sources cover, i.e. image footprint sky-area"""
     area_fraction: Optional[np.ndarray] = None
     """The fraction of the image that was above a sigma level per flux bin. This may be used as a rough term to scale the Euclidean Normalised source counts. This is not intended to be a robust way of correcting the source counts - just quick"""
 
@@ -592,6 +594,7 @@ def get_source_counts(
         counts_per_bin_err=counts_err,
         euclid_counts=scount,
         euclid_counts_err=scount_err,
+        area=area,
         area_fraction=area_fraction,
     )
 

tests/test_validation.py

@@ -7,9 +7,13 @@
 import pkg_resources
 import pytest
 
+import matplotlib.pyplot as plt
+
 from flint.validation import (
     RMSImageInfo,
+    SourceCounts,
     calculate_area_correction_per_flux,
+    get_source_counts,
     get_parser,
     get_rms_image_info,
 )
@@ -30,6 +34,25 @@ def rms_path(tmpdir):
     return rms_path
 
 
+def test_source_counts():
+    fluxes = np.linspace(0.00003, 0.01, 10000)
+
+    source_counts = get_source_counts(fluxes=fluxes, area=10)
+
+    assert isinstance(source_counts, SourceCounts)
+    assert source_counts.area == 10.0
+
+
+def test_source_counts_with_rms(rms_path):
+    fluxes = np.linspace(0.00003, 0.01, 10000)
+
+    source_counts = get_source_counts(fluxes=fluxes, area=10, rms_image_path=rms_path)
+
+    assert isinstance(source_counts, SourceCounts)
+    assert source_counts.area == 10.0
+    assert isinstance(source_counts.area_fraction, np.ndarray)
+
+
 def test_calculate_area_correction(rms_path):
     """This is not an entirely robust check as the rms image is only
     10 x 15 pixels. More testing for errors in the calling."""