rename config entry ifcs to image_function_contributions

README.md

@@ -129,8 +129,8 @@ autogrid_radius_factor: 1.5
 ## Grid density factor used when automatically choosing a grid
 autogrid_density_factor: 10.0
 
-## Image function contributions
-ifcs:
+## Composition of image function
+image_function_contributions:
 - !lassie.WavePacketIFC
   name: 'P'
   weight: 1.0
@@ -170,10 +170,10 @@ coda wave packets travelling with characteristic speeds, packet durations and
 frequency content through the network. To detect such events automatically, we
 can compose an image function with two contributions, one for each dominant
 phase. Such image function contributions (IFCs) can be defined under the
-`image_function_contributions` key in Lassie's configuration [TODO: to be
-renamed]. Different types of IFCs are available and can be combined. Here, we
-use the `WavePacketIFC` which applies a normalized envelope based
-pre-processing to the waveforms before travel-time compensated stacking.
+`image_function_contributions` key in Lassie's configuration. Different types
+of IFCs are available and can be combined. Here, we use the `WavePacketIFC`
+which applies a normalized envelope based pre-processing to the waveforms
+before travel-time compensated stacking.
 
 #### Running the detector
 
@@ -181,8 +181,7 @@ To test the configuration, select a short processing time span around one of
 the known events in the dataset. The time span can be restricted with the
 `tmin` and `tmax` entries in Lassie's configuration or with corresponding
 command line options `--tmin='YYYY-MM-DD HH:MM:SS'` and `--tmax='YYYY-MM-DD
-HH:MM:SS.XXX'` [TODO: to be implemented], which override configuration
-settings.
+HH:MM:SS.XXX'`, which override configuration settings.
 
 Now run the detector with 
 

apps/lassie

@@ -193,8 +193,8 @@ autogrid_radius_factor: 1.5
 ## Grid density factor used when automatically choosing a grid
 autogrid_density_factor: 10.0
 
-## Image function contributions
-ifcs:
+## Image function composition
+image_function_contributions:
 - !lassie.WavePacketIFC
   name: 'P'
   weight: 1.0

src/config.py

@@ -54,7 +54,7 @@ class Config(Object):
         help='grid density factor used when automatically choosing a grid '
              'spacing')
 
-    ifcs = List.T(
+    image_function_contributions = List.T(
         ifc.IFC.T(),
         help='image function contributions')
 
@@ -95,9 +95,11 @@ class Config(Object):
                 receivers = self.get_receivers()
 
                 fsmooth_max = max(
-                    ifc.get_fsmooth() for ifc in self.ifcs)
+                    ifc.get_fsmooth() for ifc in
+                    self.image_function_contributions)
 
-                vmin = min(ifc.shifter.get_vmin() for ifc in self.ifcs)
+                vmin = min(ifc.shifter.get_vmin() for ifc in
+                           self.image_function_contributions)
 
                 spacing = vmin / fsmooth_max / self.autogrid_density_factor
 

src/core.py

@@ -37,9 +37,11 @@ def scan(
 
     norm_map = gridmod.geometrical_normalization(grid, receivers)
 
+    ifcs = config.image_function_contributions
+
     shift_tables = []
     tshift_maxs = []
-    for ifc in config.ifcs:
+    for ifc in ifcs:
         shift_tables.append(ifc.shifter.get_table(grid, receivers))
         tshift_maxs.append(shift_tables[-1].max())
 
@@ -47,9 +49,9 @@ def scan(
 
     tinc = tshift_max * 10
 
-    tpad = max(ifc.get_tpad() for ifc in config.ifcs) + tshift_max
+    tpad = max(ifc.get_tpad() for ifc in ifcs) + tshift_max
 
-    fsmooth_min = min(ifc.get_fsmooth() for ifc in config.ifcs)
+    fsmooth_min = min(ifc.get_fsmooth() for ifc in ifcs)
 
     blacklist = set(tuple(s.split('.')) for s in config.blacklist)
 
@@ -93,7 +95,7 @@ def scan(
         pdata = []
         trs_debug = []
         shift_maxs = []
-        for iifc, ifc in enumerate(config.ifcs):
+        for iifc, ifc in enumerate(ifcs):
             dataset = ifc.preprocess(trs, wmin, wmax, tshift_max)
             if not dataset:
                 continue
@@ -207,8 +209,8 @@ def scan(
                 f.close()
 
             if show_detections:
-                fmin = min(ifc.fmin for ifc in config.ifcs)
-                fmax = min(ifc.fmax for ifc in config.ifcs)
+                fmin = min(ifc.fmin for ifc in ifcs)
+                fmax = min(ifc.fmax for ifc in ifcs)
                 plot.plot_detection(
                     grid, receivers, frames, tmin_frames,
                     deltat_cf, imax, iframe, fsmooth_min, xpeak, ypeak, zpeak,