Implementation of median amplitude normalization.

data/examples/unpack.bash

@@ -9,7 +9,7 @@ cd $(dirname ${BASH_SOURCE[0]})
 wd=$PWD
 
 for filename in \
-    20090407201255351.tgz 20210809074550.tgz 20SPECFEM3D_SGT.tgz SPECFEM3D_SAC.tgz;
+    20090407201255351.tgz 20210809074550.tgz SPECFEM3D_SGT.tgz SPECFEM3D_SAC.tgz;
 do
     cd $wd
     cd $(dirname $filename)

mtuq/graphics/annotations.py

@@ -3,6 +3,8 @@
 
 from matplotlib import pyplot
 from obspy.geodetics import gps2dist_azimuth
+# location to degree distance with obspy
+from obspy.geodetics import locations2degrees
 
 
 def station_label_writer(ax, station, origin, units='km'):
@@ -31,7 +33,8 @@ def station_label_writer(ax, station, origin, units='km'):
         label = '%d km' % round(distance_in_m/1000.)
 
     elif units=='deg':
-        label = '%d%s' % (round(m_to_deg(distance_in_m)), u'\N{DEGREE SIGN}')
+        label = '%d%s' % (round(locations2degrees(origin.latitude, origin.longitude,
+            station.latitude, station.longitude)), u'\N{DEGREE SIGN}')
 
     pyplot.text(0.2,0.35, label, fontsize=11, transform=ax.transAxes)
 
@@ -89,4 +92,3 @@ def _getattr(trace, name, *args):
     else:
         raise TypeError("Wrong number of arguments")
 
-

mtuq/graphics/header.py

@@ -114,7 +114,7 @@ def parse_data_processing(self):
         if not self.process_bw:
             pass
         if not self.process_sw:
-            raise Excpetion()
+            raise Exception()
 
         if self.process_sw.freq_max > 1.:
             units = 'Hz'

mtuq/graphics/waveforms.py

@@ -62,6 +62,17 @@ def plot_waveforms1(filename,
 
     max_amplitude = _max(data, synthetics)
 
+    if normalize == 'median_amplitude':
+        # Using the updated _median_amplitude function to calculate the median of non-zero maximum amplitudes
+        max_amplitude_median = _median_amplitude(data, synthetics)
+        max_amplitudes = np.array([max_amplitude_median if len(data[i]) > 0 and len(synthetics[i]) > 0 else 0.0 for i in range(len(data))])
+    elif normalize == 'maximum_amplitude':
+        max_amplitudes = np.array([max_amplitude if len(data[i]) > 0 and len(synthetics[i]) > 0 else 0.0 for i in range(len(data))])
+    elif normalize == 'station_amplitude' or normalize == 'trace_amplitude':
+        pass
+    else:
+        raise ValueError("Invalid normalization method specified.")
+
     #
     # loop over stations
     #
@@ -100,7 +111,7 @@ def plot_waveforms1(filename,
                 continue
 
             _plot_ZRT(axes[ir], 1, dat, syn, component, 
-                normalize, trace_label_writer, max_amplitude, total_misfit)
+                normalize, trace_label_writer, max_amplitudes[_i], total_misfit)
 
         ir += 1
 
@@ -153,6 +164,23 @@ def plot_waveforms2(filename,
     max_amplitude_sw = _max(data_sw, synthetics_sw)
 
 
+    if normalize == 'median_amplitude':
+        # For body wave data and synthetics
+        bw_median = _median_amplitude(data_bw, synthetics_bw)
+        max_amplitudes_bw = np.array([bw_median if len(data_bw[i]) > 0 and len(synthetics_bw[i]) > 0 else 0.0 for i in range(len(data_bw))])
+
+        # For surface wave data and synthetics
+        sw_median = _median_amplitude(data_sw, synthetics_sw)
+        max_amplitudes_sw = np.array([sw_median if len(data_sw[i]) > 0 and len(synthetics_sw[i]) > 0 else 0.0 for i in range(len(data_sw))])
+    elif normalize == 'maximum_amplitude':
+        max_amplitudes_bw = np.array([max_amplitude_bw if len(data_bw[i]) > 0 and len(synthetics_bw[i]) > 0 else 0.0 for i in range(len(data_bw))])
+        max_amplitudes_sw = np.array([max_amplitude_sw if len(data_sw[i]) > 0 and len(synthetics_sw[i]) > 0 else 0.0 for i in range(len(data_sw))])
+    elif normalize == 'station_amplitude' or normalize == 'trace_amplitude':
+        max_amplitudes_bw = np.array([_max(data_bw[i], synthetics_bw[i]) if len(data_bw[i]) > 0 and len(synthetics_bw[i]) > 0 else 0.0 for i in range(len(data_bw))])
+        max_amplitudes_sw = np.array([_max(data_sw[i], synthetics_sw[i]) if len(data_sw[i]) > 0 and len(synthetics_sw[i]) > 0 else 0.0 for i in range(len(data_sw))])
+    else:
+        raise ValueError("Invalid normalization method specified.")
+
     #
     # loop over stations
     #
@@ -191,7 +219,7 @@ def plot_waveforms2(filename,
                 continue
 
             _plot_ZR(axes[ir], 1, dat, syn, component, 
-                normalize, trace_label_writer, max_amplitude_bw, total_misfit_bw)
+                normalize, trace_label_writer, max_amplitudes_bw[_i], total_misfit_bw)
 
 
         #
@@ -216,7 +244,7 @@ def plot_waveforms2(filename,
                 continue
 
             _plot_ZRT(axes[ir], 3, dat, syn, component,
-                normalize, trace_label_writer, max_amplitude_sw, total_misfit_sw)
+                normalize, trace_label_writer, max_amplitudes_sw[_i], total_misfit_sw)
 
 
         ir += 1
@@ -373,7 +401,7 @@ def _initialize(nrows=None, ncolumns=None, column_width_ratios=None,
 
 def _plot_ZRT(axes, ic, dat, syn, component, 
     normalize='maximum_amplitude', trace_label_writer=None,
-    max_amplitude=1., total_misfit=1.):
+    normalization_amplitude=1., total_misfit=1.):
 
     # plot traces
     if component=='Z':
@@ -387,17 +415,13 @@ def _plot_ZRT(axes, ic, dat, syn, component,
 
     _plot(axis, dat, syn)
 
-    # normalize amplitude
+    # normalize amplitude -- logic for station_amplitude, median_amplitude, and maximum_amplitude is done at higher level
     if normalize=='trace_amplitude':
         max_trace = _max(dat, syn)
         ylim = [-1.5*max_trace, +1.5*max_trace]
         axis.set_ylim(*ylim)
-    elif normalize=='station_amplitude':
-        max_stream = _max(stream_dat, stream_syn)
-        ylim = [-1.5*max_stream, +1.5*max_stream]
-        axis.set_ylim(*ylim)
-    elif normalize=='maximum_amplitude':
-        ylim = [-0.75*max_amplitude, +0.75*max_amplitude]
+    elif normalize=='station_amplitude' or normalize=='median_amplitude' or normalize=='maximum_amplitude':
+        ylim = [-1.25*normalization_amplitude, +1.25*normalization_amplitude]
         axis.set_ylim(*ylim)
 
     if trace_label_writer is not None:
@@ -406,7 +430,7 @@ def _plot_ZRT(axes, ic, dat, syn, component,
 
 def _plot_ZR(axes, ic, dat, syn, component, 
     normalize='maximum_amplitude', trace_label_writer=None,
-    max_amplitude=1., total_misfit=1.):
+    normalization_amplitude=1., total_misfit=1.):
 
     # plot traces
     if component=='Z':
@@ -418,20 +442,15 @@ def _plot_ZR(axes, ic, dat, syn, component,
 
     _plot(axis, dat, syn)
 
-    # normalize amplitude
+    # normalize amplitude -- logic for station_amplitude, median_amplitude, and maximum_amplitude is done at higher level
     if normalize=='trace_amplitude':
         max_trace = _max(dat, syn)
         ylim = [-1.5*max_trace, +1.5*max_trace]
         axis.set_ylim(*ylim)
-    elif normalize=='station_amplitude':
-        max_stream = _max(stream_dat, stream_syn)
-        ylim = [-1.5*max_stream, +1.5*max_stream]
-        axis.set_ylim(*ylim)
-    elif normalize=='maximum_amplitude':
-        ylim = [-0.75*max_amplitude, +0.75*max_amplitude]
+    elif normalize=='station_amplitude' or normalize=='median_amplitude' or normalize=='maximum_amplitude':
+        ylim = [-1.25*normalization_amplitude, +1.25*normalization_amplitude]
         axis.set_ylim(*ylim)
 
-
     if trace_label_writer is not None:
         trace_label_writer(axis, dat, syn, total_misfit)
 
@@ -450,9 +469,9 @@ def _plot(axis, dat, syn, label=None):
     s = syn.data
 
     axis.plot(t, d, 'k', linewidth=1.5,
-        clip_on=False, zorder=10)
+        clip_on=True, zorder=10)
     axis.plot(t, s[start:stop], 'r', linewidth=1.25, 
-        clip_on=False, zorder=10)
+        clip_on=True, zorder=10)
 
 
 def _add_component_labels1(axes, body_wave_labels=True, surface_wave_labels=True):
@@ -534,6 +553,19 @@ def _isempty(dataset):
 
 
 def _max(dat, syn):
+    """
+    Computes the maximum value from a set of two input data objects (observed and synthetics).
+
+    Parameters:
+    dat (Trace, Stream, or Dataset): observed data.
+    syn (Trace, Stream, or Dataset): synthetics.
+
+    Returns:
+    float: The maximum value for normalization purposes.
+
+    Raises:
+    TypeError: If the input objects are not of the same type (Trace, Stream, or Dataset).
+    """
     if type(dat)==type(syn)==Trace:
         return max(
             abs(dat.max()),
@@ -552,6 +584,43 @@ def _max(dat, syn):
     else:
         raise TypeError
 
+def _median_amplitude(data, synthetics):
+    """
+    Computes the median of the maximum non-zero amplitudes for pairs of data and synthetic traces.
+
+    Args:
+        data: A list of of observed data (can be Trace, Stream, or Dataset objects).
+        synthetics: A list of synthetic traces corresponding to the observed data.
+
+    Returns:
+        The median of the non-zero maximum amplitudes computed across all pairs.
+
+    Raises:
+        ValueError: If the lengths of data and synthetics lists differ.
+    """
+    # Validate input lengths
+    # If Trace directly input, make it a list
+    data = [data] if isinstance(data, Trace) else data
+    synthetics = [synthetics] if isinstance(synthetics, Trace) else synthetics
+
+    # Validate lengths
+    if len(data) != len(synthetics):
+        raise ValueError("Data and synthetics lists must have the same length.")
+
+    max_amplitudes = []
+
+    # Iterate over pairs and handle empty traces - This gets a list of maximum amplitudes for each pair of data and synthetics
+    for dat, syn in zip(data, synthetics):
+        if not dat or not syn:
+            max_amplitudes.append(0)
+        else:
+            max_amplitudes.append(_max(dat, syn))
+
+    # Convert to NumPy array for efficient filtering
+    max_amplitudes = np.array(max_amplitudes)
+
+    # Compute median of non-zero values or return 0 if none exist 
+    return np.median(max_amplitudes[max_amplitudes > 0]) if np.any(max_amplitudes > 0) else 0.0
 
 
 def _hide_axes(axes):
@@ -597,4 +666,3 @@ def _get_tag(tags, pattern):
     else:
         return None
 
-

setup.py

@@ -100,7 +100,7 @@ def run_tests(self):
     # (consider using a conda based installation instead)
     install_requires=[
         "numpy", 
-        "scipy",
+        "scipy<1.13.0",
         "pandas",
         "xarray",
         "netCDF4",