option: use absolute

pinky/src/data.py

@@ -3,7 +3,7 @@
 import tensorflow as tf
 from pyrocko.io import save, load
 from pyrocko.model import load_stations
-from pyrocko.guts import Object, String, Int, Float, Tuple
+from pyrocko.guts import Object, String, Int, Float, Tuple, Bool
 from pyrocko.gui import marker
 from pyrocko.gf.seismosizer import Engine, Target
 from pyrocko import orthodrome
@@ -47,6 +47,7 @@ class DataGenerator(Object):
     _shape = None
     fn_stations = String.T()
     need_same_dimensions = True # bin mir nicht sicher, ob das sein muss...
+    absolute = Bool.T(help='Use absolute amplitudes', default=False)
     effective_deltat = Float.T(optional=True)
     sample_length = Float.T(help='length [s] of data window')
     reference_target = Target.T(
@@ -97,6 +98,10 @@ class DataGenerator(Object):
     def fit_data_into_chunk(self, traces, chunk, indices=None, tref=0):
         indices = indices or range(len(traces))
         for i, tr in zip(indices, traces):
+
+            if self.absolute:
+                tr.data = num.abs(tr.data)
+
             data_len = len(tr.data)
             istart_trace = int((tr.tmin - tref) / tr.deltat)
             istart_array = max(istart_trace, 0)
@@ -203,7 +208,7 @@ class PileData(DataGenerator):
                     _trs.append(tr)
                 trs = _trs
                 if not len(trs):
-                    logging.debug('no data at tmin=%s' % m.tmin)
+                    logging.debug('No data at tmin=%s' % m.tmin)
                     continue
                 chunk = self.get_raw_data_chunk()
                 indices = [nslc_to_index[tr.nslc_id] for tr in trs]