Bugfix for r_power_n_segmented branch (#63)

* Fixed bug in geom_spread_power_n_segmented function related to 'hinge_distances' argument.

* Removed brackets from 'geom_spread_n_exponents' and 'geom_spread_n_distances' example in comments.

* Require 'hinge_distances' argument of geom_spread_r_power_n_segmented function to correspond to start of each segment instead of distances separating segments.

* Updated check on length of hinge distances for segmented geometrical spreading model in _geometrical_spreading_coefficient function.

* Updated example and comment related to 'geom_spread_n_exponents' and 'geom_spread_n_distances' configuration parameters for segmented geometrical spreading model.

* Small fix in explanation of 'geom_spread_n_distances' configuration parameter.

* Fix a line too long

---------

Co-authored-by: Claudio Satriano <satriano@gmail.com>

sourcespec/config_files/configspec.conf

@@ -375,14 +375,17 @@ geom_spread_model = option('r_power_n', 'r_power_n_segmented', 'boatwright', def
 #   geom_spread_n_exponent = 1 (default, body wave in a homogeneous full-space)
 #   geom_spread_n_exponent = 0.5 (surface wave in a homogeneous half-space)
 geom_spread_n_exponent = float(min=0, default=1)
-# Exponents and distances (in km) separating segments with different exponents
+# Exponents and hypocentral distances (in km) defining different segments
 # for the "r_power_n_segmented" geometrical spreading function.
-# The number of exponents must be one more than the number of distances.
+# The number of exponents must be equal to the number of distances.
+# Distances correspond to the start of each segment.
+# Note that no geometrical spreading correction is considered
+# below the smallest distance. This distance is generally set to 1 km.
 # Example:
-#   geom_spread_n_exponents = [1., 0., 0.5]
-#   geom_spread_n_distances = [70, 130]
+#   geom_spread_n_exponents = 1., 0., 0.5
+#   geom_spread_n_distances = 1, 70, 130
 geom_spread_n_exponents = float_list(min=0, default=None)
-geom_spread_n_distances = float_list(default=None)
+geom_spread_n_distances = float_list(min=0, default=None)
 # Geometrical spreading cutoff hypocentral distance, in km, for the
 # "boatwright" model:
 geom_spread_cutoff_distance = float(min=0.01, default=50)

sourcespec/ssp_build_spectra.py

@@ -277,11 +277,11 @@ def _geometrical_spreading_coefficient(config, spec):
     if config.geom_spread_model == 'r_power_n_segmented':
         exponents = config.geom_spread_n_exponents
         hinge_distances = config.geom_spread_n_distances
-        if len(hinge_distances) != len(exponents) - 1:
+        if len(hinge_distances) != len(exponents):
             raise ValueError(
-                f'The number of exponents must be one more than the number of '
-                f'hinge distances. You provided {len(exponents)} exponents and '
-                f'{len(hinge_distances)} hinge distances'
+                f'The number of exponents must be equal to the number of '
+                f'hinge distances. You provided {len(exponents)} exponents '
+                f'and {len(hinge_distances)} hinge distances'
             )
         return geom_spread_r_power_n_segmented(hypo_dist_in_km, exponents,
                                                hinge_distances)

sourcespec/ssp_util.py

@@ -276,9 +276,9 @@ def geom_spread_r_power_n_segmented(hypo_dist_in_km, exponents,
     :param hypo_dist_in_km: Hypocentral distance (km).
     :type hypo_dist_in_km: float
     :param exponents: Exponents for different powerlaw segments
+    :type exponents: numpy.ndarray
+    :param hinge_distances: Distances defining start of powerlaw segments
     :type hinge_distances: numpy.ndarray
-    :param hinge_distances: Distances between different powerlaw segments
-    :type exponent: numpy.ndarray
     :return: Geometrical spreading correction (for distance in m)
     :rtype: float
     """
@@ -288,8 +288,8 @@ def geom_spread_r_power_n_segmented(hypo_dist_in_km, exponents,
     else:
         hypo_dist_in_km = np.asarray(hypo_dist_in_km, dtype='float')
         is_scalar = False
-    Rref = 1.
-    hinge_distances = np.hstack([[Rref], hinge_distances or []])
+    hinge_distances = np.asarray(hinge_distances)
+    Rref = hinge_distances[0]
     exponents = -np.asarray(exponents)
     # Do not allow distances less than Rref (1 km)
     hypo_dist_in_km = np.maximum(Rref, hypo_dist_in_km)