def data(self, index, role):
if not index.isValid():
return QtCore.QVariant()
if role == QtCore.Qt.DisplayRole:
pick = self.picks[index.row()]
# Map the column to an attribute.
column = index.column()
if column == 0:
return QtCore.QVariant(pick.waveform_id.getSEEDString())
elif column == 1:
phase_hint = pick.phase_hint
if phase_hint is None:
phase_hint = "-"
return QtCore.QVariant(str(phase_hint))
elif column == 2:
polarity = pick.polarity
if polarity is None:
polarity = "-"
return QtCore.QVariant(str(polarity))
elif column == 3:
evaluation_mode = pick.evaluation_mode
if evaluation_mode is None:
evaluation_mode = "-"
return QtCore.QVariant(str(evaluation_mode))
# The distance column.
elif column == 4:
coods = pick.data[0].stats.coordinates
distance = lat_long_to_distance(
self.event.origins[0].latitude,
self.event.origins[0].longitude,
self.event.origins[0].depth, coods.latitude,
coods.longitude, coods.elevation / 1000.0)
return QtCore.QVariant("%.3f" % distance)
elif column == 5:
if hasattr(pick, "data"):
return QtCore.QVariant("Yes")
return QtCore.QVariant("No")
# Set the background color for column id 4
if role == QtCore.Qt.BackgroundRole and index.column() == 5:
pick = self.picks[index.row()]
if hasattr(pick, "data"):
return QtGui.QBrush(QtGui.QColor("#e2ffa4"))
return QtGui.QBrush(QtGui.QColor("#ff8768"))
# Some tooltip for everything.
if role == QtCore.Qt.ToolTipRole:
pick = self.picks[index.row()]
coods = pick.data[0].stats.coordinates
coods = "Lat: %.4f | Lng: %.4f | Elevation: %.1f" % ( \
coods.latitude, coods.longitude, coods.elevation)
return QtCore.QVariant(coods)
def data(self, index, role):
if not index.isValid():
return QtCore.QVariant()
if role == QtCore.Qt.DisplayRole:
pick = self.picks[index.row()]
# Map the column to an attribute.
column = index.column()
if column == 0:
return QtCore.QVariant(pick.waveform_id.getSEEDString())
elif column == 1:
phase_hint = pick.phase_hint
if phase_hint is None:
phase_hint = "-"
return QtCore.QVariant(str(phase_hint))
elif column == 2:
polarity = pick.polarity
if polarity is None:
polarity = "-"
return QtCore.QVariant(str(polarity))
elif column == 3:
evaluation_mode = pick.evaluation_mode
if evaluation_mode is None:
evaluation_mode = "-"
return QtCore.QVariant(str(evaluation_mode))
# The distance column.
elif column == 4:
coods = pick.data[0].stats.coordinates
distance = lat_long_to_distance(self.event.origins[0].latitude,
self.event.origins[0].longitude,
self.event.origins[0].depth, coods.latitude,
coods.longitude, coods.elevation / 1000.0)
return QtCore.QVariant("%.3f" % distance)
elif column == 5:
if hasattr(pick, "data"):
return QtCore.QVariant("Yes")
return QtCore.QVariant("No")
# Set the background color for column id 4
if role == QtCore.Qt.BackgroundRole and index.column() == 5:
pick = self.picks[index.row()]
if hasattr(pick, "data"):
return QtGui.QBrush(QtGui.QColor("#e2ffa4"))
return QtGui.QBrush(QtGui.QColor("#ff8768"))
# Some tooltip for everything.
if role == QtCore.Qt.ToolTipRole:
pick = self.picks[index.row()]
coods = pick.data[0].stats.coordinates
coods = "Lat: %.4f | Lng: %.4f | Elevation: %.1f" % ( \
coods.latitude, coods.longitude, coods.elevation)
return QtCore.QVariant(coods)
def _calculate_final_values(self):
"""
Takes every dict stored in self.results and produces the final output.
"""
# If no results are available, nothing is to be done.
if len(self.results) == 0:
self.ui.mean_parameter_line_1.setText("-")
self.ui.mean_parameter_line_2.setText("-")
if hasattr(self, "current_status"):
self.current_status["final_results"] = {}
self.ui.save_file_button.setEnabled(False)
return
# Do all the calculations per station and phase.
stations = {}
for result in self.results:
station = ".".join(result["channel"].split(".")[:2])
if not station in stations:
stations[station] = { \
"p": [],
"s": []}
# The conditional is not strictly necessary but takes care that no
# other phases slip in.
if result["phase"].lower() == "p":
stations[station]["p"].append(result)
elif result["phase"].lower() == "s":
stations[station]["s"].append(result)
# Save the station count for later inclusion in the QuakeML file.
station_count = len(stations.keys())
# For every phase, calculate the seismic source parameters M_0 and r.
# Also take the mean of all Q values, just because they are available.
final_results = { \
"M_0": [],
"r": [],
"Q": []}
# Loop over all picks and calculate the values.
for station_id, phases in stations.iteritems():
for phase, results in phases.iteritems():
if len(results) == 0:
continue
# Collect the three variables extracted from the spectra.
omega_0 = [_i["omega_0"] for _i in results]
f_c = [_i["corner_frequency"] for _i in results]
Q = [_i["quality_factor"] for _i in results]
# The traveltime is necessary for the seismic moment
# calculation.
# XXX: This is also calculated for the pick table. Get it from
# there!
coordinates = None
for pick in self.current_state["event"].picks:
if ("%s.%s" % (pick.data[0].stats.network,
pick.data[0].stats.station)) == station_id:
coordinates = pick.data[0].stats.coordinates
if coordinates is None:
print "Warning: No coordinates for the station found."
continue
# Hypocentral distance in meter.
distance = lat_long_to_distance( \
self.current_state["event"].origins[0].latitude,
self.current_state["event"].origins[0].longitude,
self.current_state["event"].origins[0].depth,
coordinates.latitude,
coordinates.longitude,
coordinates.elevation / 1000.0) * 1000.0
# Now everything necessary is available. Call the function
# necessary to calculate everything.
M_0 = moment_from_low_freq_amplitude(omega_0,
self.current_state["density"],
self.current_state["p_wave_speed"],
distance, phase)
source_radius = source_radius_from_corner_frequency(f_c,
self.current_state["s_wave_speed"], phase)
# Append it to the final result.
final_results["M_0"].append(M_0)
final_results["r"].append(source_radius)
final_results["Q"].extend(Q)
# Now calculate the composite result.
station_count = len(final_results["M_0"])
M_0 = sum(final_results["M_0"]) / float(len(final_results["M_0"]))
mag = moment_to_moment_magnitude(M_0)
source_radius = \
sum(final_results["r"]) / float(len(final_results["r"]))
stress_drop = calculate_stress_drop(M_0, source_radius)
quality_factor = sum(final_results["Q"]) / \
float(len(final_results["Q"]))
self.final_result = { \
"seismic_moment": M_0,
"moment_magnitude": mag,
"source_radius": source_radius,
"stress_drop": stress_drop,
"quality_factor": quality_factor,
"station_count": station_count}
string = u"M₀: %.3e [Nm] || Mw: %.3f || Q: %.1f" % \
(M_0, mag, quality_factor)
self.ui.mean_parameter_line_1.setText(string)
string = u"Source radius: %.1f || Stress drop: %.2f" % \
(source_radius, stress_drop / 1E5)
self.ui.mean_parameter_line_2.setText(string)
self.ui.save_file_button.setEnabled(True)
def _calculate_final_values(self):
"""
Takes every dict stored in self.results and produces the final output.
"""
# If no results are available, nothing is to be done.
if len(self.results) == 0:
self.ui.mean_parameter_line_1.setText("-")
self.ui.mean_parameter_line_2.setText("-")
if hasattr(self, "current_status"):
self.current_status["final_results"] = {}
self.ui.save_file_button.setEnabled(False)
return
# Do all the calculations per station and phase.
stations = {}
for result in self.results:
station = ".".join(result["channel"].split(".")[:2])
if not station in stations:
stations[station] = { \
"p": [],
"s": []}
# The conditional is not strictly necessary but takes care that no
# other phases slip in.
if result["phase"].lower() == "p":
stations[station]["p"].append(result)
elif result["phase"].lower() == "s":
stations[station]["s"].append(result)
# Save the station count for later inclusion in the QuakeML file.
station_count = len(stations.keys())
# For every phase, calculate the seismic source parameters M_0 and r.
# Also take the mean of all Q values, just because they are available.
final_results = { \
"M_0": [],
"r": [],
"Q": []}
# Loop over all picks and calculate the values.
for station_id, phases in stations.iteritems():
for phase, results in phases.iteritems():
if len(results) == 0:
continue
# Collect the three variables extracted from the spectra.
omega_0 = [_i["omega_0"] for _i in results]
f_c = [_i["corner_frequency"] for _i in results]
Q = [_i["quality_factor"] for _i in results]
# The traveltime is necessary for the seismic moment
# calculation.
# XXX: This is also calculated for the pick table. Get it from
# there!
coordinates = None
for pick in self.current_state["event"].picks:
if ("%s.%s" % (pick.data[0].stats.network,
pick.data[0].stats.station)) == station_id:
coordinates = pick.data[0].stats.coordinates
if coordinates is None:
print "Warning: No coordinates for the station found."
continue
# Hypocentral distance in meter.
distance = lat_long_to_distance( \
self.current_state["event"].origins[0].latitude,
self.current_state["event"].origins[0].longitude,
self.current_state["event"].origins[0].depth,
coordinates.latitude,
coordinates.longitude,
coordinates.elevation / 1000.0) * 1000.0
# Now everything necessary is available. Call the function
# necessary to calculate everything.
M_0 = moment_from_low_freq_amplitude(
omega_0, self.current_state["density"],
self.current_state["p_wave_speed"], distance, phase)
source_radius = source_radius_from_corner_frequency(
f_c, self.current_state["s_wave_speed"], phase)
# Append it to the final result.
final_results["M_0"].append(M_0)
final_results["r"].append(source_radius)
final_results["Q"].extend(Q)
# Now calculate the composite result.
station_count = len(final_results["M_0"])
M_0 = sum(final_results["M_0"]) / float(len(final_results["M_0"]))
mag = moment_to_moment_magnitude(M_0)
source_radius = \
sum(final_results["r"]) / float(len(final_results["r"]))
stress_drop = calculate_stress_drop(M_0, source_radius)
quality_factor = sum(final_results["Q"]) / \
float(len(final_results["Q"]))
self.final_result = { \
"seismic_moment": M_0,
"moment_magnitude": mag,
"source_radius": source_radius,
"stress_drop": stress_drop,
"quality_factor": quality_factor,
"station_count": station_count}
string = u"M₀: %.3e [Nm] || Mw: %.3f || Q: %.1f" % \
(M_0, mag, quality_factor)
self.ui.mean_parameter_line_1.setText(string)
string = u"Source radius: %.1f || Stress drop: %.2f" % \
(source_radius, stress_drop / 1E5)
self.ui.mean_parameter_line_2.setText(string)
self.ui.save_file_button.setEnabled(True)
