def plot_husid(acceleration, time_step, start_level=0., end_level=1.0,
figure_size=(7, 5), filename=None, filetype="png", dpi=300):
"""
Creates a Husid plot for the record
:param tuple figure_size:
Size of the output figure (Width, Height)
:param str filename:
Name of the file to export
:param str filetype:
Type of file for export
:param int dpi:
FIgure resolution in dots per inch.
"""
plt.figure(figsize=figure_size)
husid, time_vector = get_husid(acceleration, time_step)
husid_norm = husid / husid[-1]
idx = np.where(np.logical_and(husid_norm >= start_level,
husid_norm <= end_level))[0]
plt.plot(time_vector, husid_norm, "b-", linewidth=2.0,
label="Original Record")
plt.plot(time_vector[idx], husid_norm[idx], "r-", linewidth=2.0,
label="%5.3f - %5.3f Arias" % (start_level, end_level))
plt.xlabel("Time (s)", fontsize=14)
plt.ylabel("Fraction of Arias Intensity", fontsize=14)
plt.title("Husid Plot")
plt.legend(loc=4, fontsize=14)
_save_image(filename, filetype, dpi)
plt.show()
def plot_model_configuration(self, marker_style="o", figure_size=(7, 5),
filename=None, filetype="png", dpi=300):
"""
Produces a 3D plot of the current model configuration
"""
fig = plt.figure(figsize=figure_size)
ax = fig.add_subplot(111, projection='3d')
# Wireframe rupture surface mesh
rupture_mesh = self.surface.get_mesh()
ax.plot_wireframe(rupture_mesh.lons,
rupture_mesh.lats,
-rupture_mesh.depths,
rstride=1,
cstride=1)
# Scatter the target sites
ax.scatter(self.target_sites.mesh.lons,
self.target_sites.mesh.lats,
np.ones_like(self.target_sites.mesh.lons),
c='r',
marker=marker_style)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
ax.set_zlabel('Depth (km)')
_save_image(filename, filetype, dpi)
plt.show()
def create_plot(self):
"""
"""
data = self.residuals.residuals[self.gmpe][self.imt]
if not data:
print("No residuals found for %s (%s)" % (self.gmpe, self.imt))
return
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
if self.num_plots > 1:
nrow = 3
ncol = 1
else:
nrow = 1
ncol = 1
tloc = 1
for res_type in data.keys():
vs30 = self._get_vs30(self.gmpe, self.imt, res_type)
self._residual_plot(
plt.subplot(nrow, ncol, tloc),
vs30,
data,
res_type)
tloc += 1
_save_image(self.filename, self.filetype, self.dpi)
if self.show:
plt.show()
def create_plot(self, bin_width=0.5):
"""
Creates a histogram plot
"""
data = self.residuals.residuals[self.gmpe][self.imt]
if not data:
print("No residuals found for %s (%s)" % (self.gmpe, self.imt))
return
statistics = self.residuals.get_residual_statistics()
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
if self.num_plots > 1:
nrow = 2
ncol = 2
else:
nrow = 1
ncol = 1
tloc = 1
for res_type in data.keys():
self._density_plot(
plt.subplot(nrow, ncol, tloc),
data,
res_type,
statistics,
bin_width)
tloc += 1
_save_image(self.filename, self.filetype, self.dpi)
if self.show:
plt.show()
def db_magnitude_distance_by_site(db1, dist_type, classification="NEHRP",
figure_size=(7, 5), filename=None, filetype="png", dpi=300):
"""
Plot magnitude-distance comparison by site NEHRP or Eurocode 8 Site class
"""
if classification == "NEHRP":
site_bounds = NEHRP_BOUNDS
elif classification == "EC8":
site_bounds = EC8_BOUNDS
else:
raise ValueError("Unrecognised Site Classifier!")
selector = SMRecordSelector(db1)
plt.figure(figsize=figure_size)
total_idx = []
for site_class in site_bounds.keys():
site_idx = _site_selection(db1, site_class, classification)
if site_idx:
site_db = selector.select_records(site_idx, as_db=True)
mags, dists = get_magnitude_distances(site_db, dist_type)
plt.plot(np.array(dists), np.array(mags), "o", mec='k',
mew=0.5, label="Site Class %s" % site_class)
total_idx.extend(site_idx)
unc_idx = set(range(db1.number_records())).difference(set(total_idx))
unc_db = selector.select_records(unc_idx, as_db=True)
mag, dists = get_magnitude_distances(site_db, dist_type)
plt.semilogx(np.array(dists), np.array(mags), "o", mfc="None", mec='k',
mew=0.5, label="Unclassified", zorder=0)
plt.xlabel(DISTANCE_LABEL[dist_type], fontsize=14)
plt.ylabel("Magnitude", fontsize=14)
plt.grid()
plt.legend(ncol=2,loc="lower right", numpoints=1)
plt.title("Magnitude vs Distance (by %s Site Class)" % classification,
fontsize=18)
_save_image(filename, filetype, dpi)
plt.show()
def create_plot(self, bin_width=0.5):
"""
Creates a histogram plot
"""
data = self.residuals.residuals[self.gmpe][self.imt]
statistics = self.residuals.get_residual_statistics()
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
if self.num_plots > 1:
nrow = 2
ncol = 2
else:
nrow = 1
ncol = 1
tloc = 1
for res_type in data.keys():
self._density_plot(
plt.subplot(nrow, ncol, tloc),
data,
res_type,
statistics,
bin_width)
tloc += 1
_save_image(self.filename, self.filetype, self.dpi)
plt.show()
def db_magnitude_distance_by_trt(db1,
dist_type,
figure_size=(7, 5),
filename=None,
filetype="png",
dpi=300):
"""
Plot magnitude-distance comparison by tectonic region
"""
trts = []
for i in db1.records:
trts.append(i.event.tectonic_region)
trt_types = list(set(trts))
selector = SMRecordSelector(db1)
plt.figure(figsize=figure_size)
for trt in trt_types:
subdb = selector.select_trt_type(trt, as_db=True)
mag, dists = get_magnitude_distances(subdb, dist_type)
plt.semilogx(dists, mag, "o", mec='k', mew=0.5, label=trt)
plt.xlabel(DISTANCE_LABEL[dist_type], fontsize=14)
plt.ylabel("Magnitude", fontsize=14)
plt.title("Magnitude vs Distance by Tectonic Region", fontsize=18)
plt.legend(loc='lower right', numpoints=1)
plt.grid()
_save_image(filename, plt.gcf(), filetype, dpi)
plt.show()
def plot_model_configuration(self, marker_style="o", figure_size=(7, 5),
filename=None, filetype="png", dpi=300):
"""
Produces a 3D plot of the current model configuration
"""
fig = plt.figure(figsize=figure_size)
ax = fig.add_subplot(111, projection='3d')
# Wireframe rupture surface mesh
lons = []
lats = []
depths = []
for pnt in [self.surface.top_left, self.surface.top_right,
self.surface.bottom_right, self.surface.bottom_left,
self.surface.top_left]:
lons.append(pnt.longitude)
lats.append(pnt.latitude)
depths.append(-pnt.depth)
ax.plot(lons, lats, depths, "k-", lw=2)
# Scatter the target sites
ax.scatter(self.target_sites.mesh.lons,
self.target_sites.mesh.lats,
np.ones_like(self.target_sites.mesh.lons),
c='r',
marker=marker_style)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
ax.set_zlabel('Depth (km)')
ax.set_zlim(np.floor(min(depths)), 0.0)
_save_image(filename, filetype, dpi)
plt.show()
def plot_husid(acceleration, time_step, start_level=0., end_level=1.0,
figure_size=(7, 5), filename=None, filetype="png", dpi=300):
"""
Creates a Husid plot for the record
:param tuple figure_size:
Size of the output figure (Width, Height)
:param str filename:
Name of the file to export
:param str filetype:
Type of file for export
:param int dpi:
FIgure resolution in dots per inch.
"""
plt.figure(figsize=figure_size)
husid, time_vector = get_husid(acceleration, time_step)
husid_norm = husid / husid[-1]
idx = np.where(np.logical_and(husid_norm >= start_level,
husid_norm <= end_level))[0]
plt.plot(time_vector, husid_norm, "b-", linewidth=2.0,
label="Original Record")
plt.plot(time_vector[idx], husid_norm[idx], "r-", linewidth=2.0,
label="%5.3f - %5.3f Arias" % (start_level, end_level))
plt.xlabel("Time (s)", fontsize=14)
plt.ylabel("Fraction of Arias Intensity", fontsize=14)
plt.title("Husid Plot")
plt.legend(loc=4, fontsize=14)
_save_image(filename, filetype, dpi)
plt.show()
def plot_model_configuration(self,
marker_style="o",
figure_size=(7, 5),
filename=None,
filetype="png",
dpi=300):
"""
Produces a 3D plot of the current model configuration
"""
fig = plt.figure(figsize=figure_size)
ax = fig.add_subplot(111, projection='3d')
# Wireframe rupture surface mesh
rupture_mesh = self.surface.get_mesh()
ax.plot_wireframe(rupture_mesh.lons,
rupture_mesh.lats,
-rupture_mesh.depths,
rstride=1,
cstride=1)
# Scatter the target sites
ax.scatter(self.target_sites.mesh.lons,
self.target_sites.mesh.lats,
np.ones_like(self.target_sites.mesh.lons),
c='r',
marker=marker_style)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
ax.set_zlabel('Depth (km)')
ax.set_zlim(-np.ceil(np.max(rupture_mesh.depths)), 0.0)
_save_image(filename, filetype, dpi)
plt.show()
def plot_distance_comparisons(self,
distance1,
distance2,
logaxis=False,
figure_size=(7, 5),
filename=None,
filetype="png",
dpi=300):
"""
Creates a plot comparing different distance metrics for the
specific rupture and target site combination
"""
xdist = self._calculate_distance(distance1)
ydist = self._calculate_distance(distance2)
plt.figure(figsize=figure_size)
if logaxis:
plt.loglog(xdist, ydist, color='b', marker='o', linestyle='None')
else:
plt.plot(xdist, ydist, color='b', marker='o', linestyle='None')
plt.xlabel("%s (km)" % distance1, size='medium')
plt.ylabel("%s (km)" % distance2, size='medium')
plt.title('Rupture: M=%6.1f, Dip=%3.0f, Ztor=%4.1f, Aspect=%5.2f' %
(self.magnitude, self.dip, self.ztor, self.aspect))
_save_image(filename, filetype, dpi)
plt.show()
def create_plot(self, bin_width=0.1):
"""
Creates a histogram plot
"""
#data = self.residuals.residuals[self.gmpe][self.imt]
lh_vals, statistics = self.residuals.get_likelihood_values()
lh_vals = lh_vals[self.gmpe][self.imt]
statistics = statistics[self.gmpe][self.imt]
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
if self.num_plots > 1:
nrow = 2
ncol = 2
else:
nrow = 1
ncol = 1
tloc = 1
for res_type in lh_vals.keys():
self._density_plot(
plt.subplot(nrow, ncol, tloc),
lh_vals[res_type],
res_type,
statistics[res_type],
bin_width)
tloc += 1
_save_image(self.filename, self.filetype, self.dpi)
if self.show:
plt.show()
def plot_model_configuration(self, marker_style="o", figure_size=(7, 5),
filename=None, filetype="png", dpi=300):
"""
Produces a 3D plot of the current model configuration
"""
fig = plt.figure(figsize=figure_size)
ax = fig.add_subplot(111, projection='3d')
# Wireframe rupture surface mesh
lons = []
lats = []
depths = []
for pnt in [self.surface.top_left, self.surface.top_right,
self.surface.bottom_right, self.surface.bottom_left,
self.surface.top_left]:
lons.append(pnt.longitude)
lats.append(pnt.latitude)
depths.append(-pnt.depth)
ax.plot(lons, lats, depths, "k-", lw=2)
# Scatter the target sites
ax.scatter(self.target_sites.mesh.lons,
self.target_sites.mesh.lats,
np.ones_like(self.target_sites.mesh.lons),
c='r',
marker=marker_style)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
ax.set_zlabel('Depth (km)')
ax.set_zlim(np.floor(min(depths)), 0.0)
_save_image(filename, filetype, dpi)
plt.show()
def create_plot(self, bin_width=0.1):
"""
Creates a histogram plot
"""
#data = self.residuals.residuals[self.gmpe][self.imt]
lh_vals, statistics = self.residuals.get_likelihood_values()
lh_vals = lh_vals[self.gmpe][self.imt]
statistics = statistics[self.gmpe][self.imt]
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
if self.num_plots > 1:
nrow = 2
ncol = 2
else:
nrow = 1
ncol = 1
tloc = 1
for res_type in lh_vals.keys():
self._density_plot(
plt.subplot(nrow, ncol, tloc),
lh_vals[res_type],
res_type,
statistics[res_type],
bin_width)
tloc += 1
_save_image(self.filename, self.filetype, self.dpi)
plt.show()
def plot_time_series(acceleration,
time_step,
velocity=[],
displacement=[],
units="cm/s/s",
figure_size=(8, 6),
filename=None,
filetype="png",
dpi=300,
linewidth=1.5):
"""
Creates a plot of acceleration, velocity and displacement for a specific
ground motion record
"""
acceleration = convert_accel_units(acceleration, units)
accel_time = get_time_vector(time_step, len(acceleration))
if not len(velocity):
velocity, dspl = get_velocity_displacement(time_step, acceleration)
vel_time = get_time_vector(time_step, len(velocity))
if not len(displacement):
displacement = dspl
disp_time = get_time_vector(time_step, len(displacement))
fig = plt.figure(figsize=figure_size)
fig.set_tight_layout(True)
ax = plt.subplot(3, 1, 1)
# Accleration
ax.plot(accel_time, acceleration, 'k-', linewidth=linewidth)
ax.set_xlabel("Time (s)", fontsize=12)
ax.set_ylabel("Acceleration (cm/s/s)", fontsize=12)
end_time = np.max(np.array([accel_time[-1], vel_time[-1], disp_time[-1]]))
pga = np.max(np.fabs(acceleration))
ax.set_xlim(0, end_time)
ax.set_ylim(-1.1 * pga, 1.1 * pga)
ax.grid()
# Velocity
ax = plt.subplot(3, 1, 2)
ax.plot(vel_time, velocity, 'b-', linewidth=linewidth)
ax.set_xlabel("Time (s)", fontsize=12)
ax.set_ylabel("Velocity (cm/s)", fontsize=12)
pgv = np.max(np.fabs(velocity))
ax.set_xlim(0, end_time)
ax.set_ylim(-1.1 * pgv, 1.1 * pgv)
ax.grid()
# Displacement
ax = plt.subplot(3, 1, 3)
ax.plot(disp_time, displacement, 'r-', linewidth=linewidth)
ax.set_xlabel("Time (s)", fontsize=12)
ax.set_ylabel("Displacement (cm)", fontsize=12)
pgd = np.max(np.fabs(displacement))
ax.set_xlim(0, end_time)
ax.set_ylim(-1.1 * pgd, 1.1 * pgd)
ax.grid()
_save_image(filename, filetype, dpi)
plt.show()
def plot_fourier_spectrum(time_series, time_step, figure_size=(7, 5), filename=None, filetype="png", dpi=300):
"""
Plots the Fourier spectrum of a time series
"""
freq, amplitude = get_fourier_spectrum(time_series, time_step)
plt.figure(figsize=figure_size)
plt.loglog(freq, amplitude, "b-")
plt.xlabel("Frequency (Hz)", fontsize=14)
plt.ylabel("Fourier Amplitude", fontsize=14)
_save_image(filename, filetype, dpi)
plt.show()
def plot_fourier_spectrum(time_series, time_step, figure_size=(7, 5),
filename=None, filetype="png", dpi=300):
"""
Plots the Fourier spectrum of a time series
"""
freq, amplitude = get_fourier_spectrum(time_series, time_step)
plt.figure(figsize=figure_size)
plt.loglog(freq, amplitude, 'b-')
plt.xlabel("Frequency (Hz)", fontsize=14)
plt.ylabel("Fourier Amplitude", fontsize=14)
_save_image(filename, filetype, dpi)
plt.show()
def create_plot(self):
"""
Creates the plot
"""
phi_ss, phi_s2ss = self.residuals.residual_statistics()
data = self._get_site_data()
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
self._residual_plot(fig, data, phi_ss[self.gmpe][self.imt], phi_s2ss[self.gmpe][self.imt])
_save_image(self.filename, self.filetype, self.dpi)
if self.show:
plt.show()
def create_plot(self):
"""
Creates the plot
"""
phi_ss, phi_s2ss = self.residuals.residual_statistics()
data = self._get_site_data()
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
self._residual_plot(fig, data, phi_ss[self.gmpe][self.imt],
phi_s2ss[self.gmpe][self.imt])
_save_image(self.filename, self.filetype, self.dpi)
plt.show()
def create_plot(self):
"""
Creates a residual plot
"""
data = self.get_plot_data()
# statistics = self.residuals.get_residual_statistics()
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
nrow, ncol = self.get_subplots_rowcols()
for tloc, res_type in enumerate(data.keys(), 1):
self._residual_plot(plt.subplot(nrow, ncol, tloc), data[res_type],
res_type)
_save_image(self.filename, plt.gcf(), self.filetype, self.dpi)
if self.show:
plt.show()
def db_magnitude_distance(db1, dist_type, figure_size=(7, 5),
figure_title=None,filename=None, filetype="png", dpi=300):
"""
Creates a plot of magnitude verses distance for a strong motion database
"""
plt.figure(figsize=figure_size)
mags, dists = get_magnitude_distances(db1, dist_type)
plt.semilogx(np.array(dists), np.array(mags), "o", mec='k', mew=0.5)
plt.xlabel(DISTANCE_LABEL[dist_type], fontsize=14)
plt.ylabel("Magnitude", fontsize=14)
if figure_title:
plt.title(figure_title, fontsize=18)
_save_image(filename, filetype, dpi)
plt.grid()
plt.show()
def create_plot(self):
"""
Creates a residual plot
"""
data = self.get_plot_data()
# statistics = self.residuals.get_residual_statistics()
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
nrow, ncol = self.get_subplots_rowcols()
for tloc, res_type in enumerate(data.keys(), 1):
self._residual_plot(plt.subplot(nrow, ncol, tloc), data[res_type],
res_type)
_save_image(self.filename, self.filetype, self.dpi)
if self.show:
plt.show()
def plot_time_series(acceleration, time_step, velocity=[], displacement=[],
units="cm/s/s", figure_size=(8, 6), filename=None, filetype="png",
dpi=300, linewidth=1.5):
"""
Creates a plot of acceleration, velocity and displacement for a specific
ground motion record
"""
acceleration = convert_accel_units(acceleration, units)
accel_time = get_time_vector(time_step, len(acceleration))
if not len(velocity):
velocity, dspl = get_velocity_displacement(time_step, acceleration)
vel_time = get_time_vector(time_step, len(velocity))
if not len(displacement):
displacement = dspl
disp_time = get_time_vector(time_step, len(displacement))
fig = plt.figure(figsize=figure_size)
fig.set_tight_layout(True)
ax = plt.subplot(3, 1, 1)
# Accleration
ax.plot(accel_time, acceleration, 'k-', linewidth=linewidth)
ax.set_xlabel("Time (s)", fontsize=12)
ax.set_ylabel("Acceleration (cm/s/s)", fontsize=12)
end_time = np.max(np.array([accel_time[-1], vel_time[-1], disp_time[-1]]))
pga = np.max(np.fabs(acceleration))
ax.set_xlim(0, end_time)
ax.set_ylim(-1.1 * pga, 1.1 * pga)
ax.grid()
# Velocity
ax = plt.subplot(3, 1, 2)
ax.plot(vel_time, velocity, 'b-', linewidth=linewidth)
ax.set_xlabel("Time (s)", fontsize=12)
ax.set_ylabel("Velocity (cm/s)", fontsize=12)
pgv = np.max(np.fabs(velocity))
ax.set_xlim(0, end_time)
ax.set_ylim(-1.1 * pgv, 1.1 * pgv)
ax.grid()
# Displacement
ax = plt.subplot(3, 1, 3)
ax.plot(disp_time, displacement, 'r-', linewidth=linewidth)
ax.set_xlabel("Time (s)", fontsize=12)
ax.set_ylabel("Displacement (cm)", fontsize=12)
pgd = np.max(np.fabs(displacement))
ax.set_xlim(0, end_time)
ax.set_ylim(-1.1 * pgd, 1.1 * pgd)
ax.grid()
_save_image(filename, filetype, dpi)
plt.show()
def plot_husid(acceleration, time_step, start_level=0., end_level=1.0,
figure_size=(7, 5), filename=None, filetype="png", dpi=300):
"""
Creates a Husid plot for the record
"""
plt.figure(figsize=figure_size)
husid, time_vector = get_husid(acceleration, time_step)
husid_norm = husid / husid[-1]
idx = np.where(np.logical_and(husid_norm >= start_level,
husid_norm <= end_level))[0]
plt.plot(time_vector, husid_norm, "b-", linewidth=2.0,
label="Original Record")
plt.plot(time_vector[idx], husid_norm[idx], "r-", linewidth=2.0,
label="%5.3f - %5.3f Arias" % (start_level, end_level))
plt.xlabel("Time (s)", fontsize=14)
plt.ylabel("Fraction of Arias Intensity", fontsize=14)
plt.title("Husid Plot")
plt.legend(loc=4, fontsize=14)
_save_image(filename, filetype, dpi)
plt.show()
def create_plot(self):
"""
"""
phi_ss, phi_s2ss = self.residuals.residual_statistics()
data = self._get_site_data()
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
if self.num_plots > 1:
nrow = 3
ncol = 1
else:
nrow = 1
ncol = 1
tloc = 1
for res_type in self.residuals.types[self.gmpe][self.imt]:
self._residual_plot(fig.add_subplot(nrow, ncol, tloc), data,
res_type)
tloc += 1
_save_image(self.filename, self.filetype, self.dpi)
plt.show()
def create_plot(self):
"""
"""
data = self.residuals.residuals[self.gmpe][self.imt]
vs30 = self._get_vs30()
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
if self.num_plots > 1:
nrow = 3
ncol = 1
else:
nrow = 1
ncol = 1
tloc = 1
for res_type in data.keys():
self._residual_plot(plt.subplot(nrow, ncol, tloc), vs30, data,
res_type)
tloc += 1
_save_image(self.filename, self.filetype, self.dpi)
plt.show()
def create_plot(self):
"""
"""
phi_ss, phi_s2ss = self.residuals.residual_statistics()
data = self._get_site_data()
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
if self.num_plots > 1:
nrow = 3
ncol = 1
else:
nrow = 1
ncol = 1
tloc = 1
for res_type in self.residuals.types[self.gmpe][self.imt]:
self._residual_plot(fig.add_subplot(nrow, ncol, tloc), data, res_type)
tloc += 1
_save_image(self.filename, self.filetype, self.dpi)
if self.show:
plt.show()
def plot_distance_comparisons(self, distance1, distance2, logaxis=False,
figure_size=(7, 5), filename=None, filetype="png", dpi=300):
"""
Creates a plot comparing different distance metrics for the
specific rupture and target site combination
"""
xdist = self._calculate_distance(distance1)
ydist = self._calculate_distance(distance2)
plt.figure(figsize=figure_size)
if logaxis:
plt.loglog(xdist, ydist, color='b', marker='o', linestyle='None')
else:
plt.plot(xdist, ydist, color='b', marker='o', linestyle='None')
plt.xlabel("%s (km)" % distance1, size='medium')
plt.ylabel("%s (km)" % distance2, size='medium')
plt.title('Rupture: M=%6.1f, Dip=%3.0f, Ztor=%4.1f, Aspect=%5.2f'
% (self.magnitude, self.dip, self.ztor, self.aspect))
_save_image(filename, filetype, dpi)
plt.show()
def plot_response_spectra(spectra,
axis_type="loglog",
figure_size=(8, 6),
filename=None,
filetype="png",
dpi=300):
"""
Creates a plot of the suite of response spectra (Acceleration,
Velocity, Displacement, Pseudo-Acceleration, Pseudo-Velocity) derived
from a particular ground motion record
"""
fig = plt.figure(figsize=figure_size)
fig.set_tight_layout(True)
ax = plt.subplot(2, 2, 1)
# Acceleration
PLOT_TYPE[axis_type](ax, spectra["Period"], spectra["Acceleration"])
PLOT_TYPE[axis_type](ax, spectra["Period"], spectra["Pseudo-Acceleration"])
ax.set_xlabel("Periods (s)", fontsize=12)
ax.set_ylabel("Acceleration (cm/s/s)", fontsize=12)
ax.set_xlim(np.min(spectra["Period"]), np.max(spectra["Period"]))
ax.grid()
ax.legend(("Acceleration", "PSA"), loc=0)
ax = plt.subplot(2, 2, 2)
# Velocity
PLOT_TYPE[axis_type](ax, spectra["Period"], spectra["Velocity"])
PLOT_TYPE[axis_type](ax, spectra["Period"], spectra["Pseudo-Velocity"])
ax.set_xlabel("Periods (s)", fontsize=12)
ax.set_ylabel("Velocity (cm/s)", fontsize=12)
ax.set_xlim(np.min(spectra["Period"]), np.max(spectra["Period"]))
ax.grid()
ax.legend(("Velocity", "PSV"), loc=0)
ax = plt.subplot(2, 2, 3)
# Displacement
PLOT_TYPE[axis_type](ax, spectra["Period"], spectra["Displacement"])
ax.set_xlabel("Periods (s)", fontsize=12)
ax.set_ylabel("Displacement (cm)", fontsize=12)
ax.set_xlim(np.min(spectra["Period"]), np.max(spectra["Period"]))
ax.grid()
_save_image(filename, filetype, dpi)
plt.show()
def create_plot(self):
"""
Creates the plot
"""
data = self.residuals.residuals[self.gmpe][self.imt]
fig = plt.figure(figsize=self.figure_size)
fig.set_tight_layout(True)
if self.num_plots > 1:
nrow = 3
ncol = 1
else:
nrow = 1
ncol = 1
tloc = 1
for res_type in data.keys():
depths = self._get_depths(self.gmpe, self.imt, res_type)
self._residual_plot(plt.subplot(nrow, ncol, tloc), depths, data, res_type)
tloc += 1
_save_image(self.filename, self.filetype, self.dpi)
if self.show:
plt.show()
def db_magnitude_distance_by_trt(db1, dist_type,
figure_size=(7, 5), filename=None, filetype="png", dpi=300):
"""
Plot magnitude-distance comparison by tectonic region
"""
trts=[]
for i in db1.records:
trts.append(i.event.tectonic_region)
trt_types=list(set(trts))
selector = SMRecordSelector(db1)
plt.figure(figsize=figure_size)
for trt in trt_types:
subdb = selector.select_trt_type(trt, as_db=True)
mag, dists = get_magnitude_distances(subdb, dist_type)
plt.semilogx(dists, mag, "o", mec='k', mew=0.5, label=trt)
plt.xlabel(DISTANCE_LABEL[dist_type], fontsize=14)
plt.ylabel("Magnitude", fontsize=14)
plt.title("Magnitude vs Distance by Tectonic Region", fontsize=18)
plt.legend(loc='lower right', numpoints=1)
plt.grid()
_save_image(filename, filetype, dpi)
plt.show()
def plot_response_spectra(spectra, axis_type="loglog", figure_size=(8, 6),
filename=None, filetype="png", dpi=300):
"""
Creates a plot of the suite of response spectra (Acceleration,
Velocity, Displacement, Pseudo-Acceleration, Pseudo-Velocity) derived
from a particular ground motion record
"""
fig = plt.figure(figsize=figure_size)
fig.set_tight_layout(True)
ax = plt.subplot(2, 2, 1)
# Acceleration
PLOT_TYPE[axis_type](ax, spectra["Period"], spectra["Acceleration"])
PLOT_TYPE[axis_type](ax, spectra["Period"], spectra["Pseudo-Acceleration"])
ax.set_xlabel("Periods (s)", fontsize=12)
ax.set_ylabel("Acceleration (cm/s/s)", fontsize=12)
ax.set_xlim(np.min(spectra["Period"]), np.max(spectra["Period"]))
ax.grid()
ax.legend(("Acceleration", "PSA"), loc=0)
ax = plt.subplot(2, 2, 2)
# Velocity
PLOT_TYPE[axis_type](ax, spectra["Period"], spectra["Velocity"])
PLOT_TYPE[axis_type](ax, spectra["Period"], spectra["Pseudo-Velocity"])
ax.set_xlabel("Periods (s)", fontsize=12)
ax.set_ylabel("Velocity (cm/s)", fontsize=12)
ax.set_xlim(np.min(spectra["Period"]), np.max(spectra["Period"]))
ax.grid()
ax.legend(("Velocity", "PSV"), loc=0)
ax = plt.subplot(2, 2, 3)
# Displacement
PLOT_TYPE[axis_type](ax, spectra["Period"], spectra["Displacement"])
ax.set_xlabel("Periods (s)", fontsize=12)
ax.set_ylabel("Displacement (cm)", fontsize=12)
ax.set_xlim(np.min(spectra["Period"]), np.max(spectra["Period"]))
ax.grid()
_save_image(filename, filetype, dpi)
plt.show()
