adds masking option

docs/configuration.rst

@@ -20,10 +20,11 @@ is divided into sections:
 **paths** section
 ------------------
 
-There are four configurables for this section:
+There are five configurables for this section:
 
 - *overlappogram*: path to the overlappogram image to be inverted.
-- *weights*: path to the accompanying weights used in the inversion. Weights should be in units of :math:`\frac{1}{\sigma}` where :math:`\sigma` is the uncertainty or standard deviation
+- *weights*: path to the accompanying weights used in the inversion. Weights should be in units of :math:`\frac{1}{\sigma}` where :math:`\sigma` is the uncertainty or standard deviation. Weights are optional and the keyword can be omitted to run in weightless mode.
+- *mask*: path to the accompanying mask used in the inversion. This mask is optional and the keyword can be omitted to run without a mask.
 - *response*: path to the instrument response.
 - *gnt*: path to the file containing atomic physics values from Chianti, the *G(n, t)* function.
 

example_config.toml

@@ -1,6 +1,7 @@
 [paths]
 overlappogram = "./data/ECCCO_speedtest_runs/combined_ECCCO_trim_sw_lw_s_i_scaled.fits"
-weights = "data/ECCCO_speedtest_runs/combined_ECCCO_weights_trim_sw_lw_s_i_scaled.fits"
+weights = "data/ECCCO_speedtest_runs/combined_ECCCO_weights_trim_sw_lw_s_i_scaled.fits"  # optional, omit keyword to skip
+#mask = "no example" # mask has been commented out since we do not use it in this example
 response = "data/ECCCO_speedtest_runs/D27Feb2024_eccco_response_feldman_m_el_with_tables_trim_sw_lw_s_i_scaled.fits"
 gnt = "data/ECCCO_speedtest_runs/master_gnt_eccco_inphotons_cm3persperpix_with_tables.fits"
 
@@ -12,14 +13,14 @@ overwrite = true
 
 [inversion]
 solution_fov_width = 2
-detector_row_range = [0, 50]
+detector_row_range = [0, 500]
 field_angle_range = [-1227, 1227]
 response_dependency_name = "logt"
 response_dependency_list = [5.7, 5.8, 5.9, 6.0 , 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8]
 smooth_over = 'dependence'
 
 [model]
-alphas = [3E-5] #, 4E-5, 0.1] #[0.2, 0.1, 0.01, 0.005]
+alphas = [3E-5, 4E-5, 0.1, 0.2, 0.1, 0.01, 0.005]
 rhos = [0.1]
 warm_start = false
 tol = 1E-2

overlappogram/cli.py

@@ -32,7 +32,8 @@ def unfold(config):
     os.makedirs(config["output"]["directory"], exist_ok=True)  # make sure output directory exists
 
     overlappogram = load_overlappogram(config["paths"]["overlappogram"],
-                                       config["paths"]["weights"] if 'weights' in config['paths'] else None)
+                                       config["paths"]["weights"] if 'weights' in config['paths'] else None,
+                                       config["paths"]["mask"] if 'mask' in config['paths'] else None)
     response_cube = load_response_cube(config["paths"]["response"])
 
     inversion = Inverter(

overlappogram/io.py

@@ -19,7 +19,7 @@
                         'ELECDIST']
 
 
-def load_overlappogram(image_path: str, weights_path: str | None) -> NDCube:
+def load_overlappogram(image_path: str, weights_path: str | None = None, mask_path: str | None = None) -> NDCube:
     with fits.open(image_path) as image_hdul:
         image = image_hdul[0].data
         header = image_hdul[0].header
@@ -32,7 +32,13 @@ def load_overlappogram(image_path: str, weights_path: str | None) -> NDCube:
             weights = weights_hdul[0].data
             uncertainty = StdDevUncertainty(1 / weights)
 
-    return NDCube(image, wcs=wcs, uncertainty=uncertainty, meta=dict(header))
+    if mask_path is None:
+        mask = None
+    else:
+        with fits.open(mask_path) as mask_hdul:
+            mask = mask_hdul[0].data
+
+    return NDCube(image, wcs=wcs, uncertainty=uncertainty, mask=mask, meta=dict(header))
 
 
 def load_response_cube(path: str) -> NDCube:

pyproject.toml

@@ -5,7 +5,7 @@ requires = ["setuptools",
 
 [project]
 name = "overlappogram"
-version = "0.0.6"
+version = "0.0.7"
 dependencies = ["numpy<2.0.0",
     "astropy",
     "scikit-learn",