def step02(self):
label = 'test'
tmps = '../data/tmp/ruptures.hdf5'
rupture_hdf5_fname = os.path.abspath(os.path.join(
BASE_DATA_PATH, tmps))
output_folder = os.path.join(BASE_DATA_PATH, '../tmp/')
investigation_t = '1.'
create(label, rupture_hdf5_fname, output_folder, investigation_t)
def test_create(self):
"""
Test rupture creation
"""
reff = os.path.join(BASE_DATA_PATH, '../data/ini/')
calculate_ruptures(self.ini_fname, False, reff)
label = 'test'
tmps = '../data/tmp/ruptures.hdf5'
rupture_hdf5_fname = os.path.abspath(os.path.join(
BASE_DATA_PATH, tmps))
output_folder = os.path.join(BASE_DATA_PATH, '../data/tmp/')
investigation_t = '1.'
create(label, rupture_hdf5_fname, output_folder, investigation_t)
def main(config_fname: str, output_folder: str, *,
trt: str=TRT.SUBDUCTION_INTRASLAB):
investigation_t = 1.0
# Parsing config
model = toml.load(config_fname)
path = os.path.dirname(config_fname)
# Creating xml
for key in model['sources']:
ini_fname = os.path.join(path, model['sources'][key]['ini_fname'])
config = configparser.ConfigParser()
config.read_file(open(ini_fname))
tmp = config.get('main', 'out_hdf5_fname')
rupture_hdf5_fname = os.path.join(path, tmp)
outf = os.path.join(output_folder, key)
create_folder(outf)
create(key, rupture_hdf5_fname, outf, investigation_t, trt)
def test01(self):
""" Test smoothing """
# Create the ruptures
self.reff = os.path.join(BASE_DATA_PATH, '..', 'data', 'ini')
calculate_ruptures(self.ini, False, self.reff)
# Create .xml with OQ input
label = 'test'
rupture_hdf5_fname = self.config['main']['out_hdf5_fname']
investigation_t = '1.'
create(label, rupture_hdf5_fname, self.out_path, investigation_t)
# Read .xml and calculate the rates of occurrence within each
# magnitude bin
pattern = os.path.join(self.out_path, '*.xml')
rates = []
for source_model_fname in sorted(glob.glob(pattern)):
mag, rate = get_mags_rates(source_model_fname, 1.0)
rates.append([mag, rate])
rates = np.array(rates)
# Calculate the expected rates
mags = np.arange(8.0, 8.21, 0.1)
agr = float(self.config['main']['agr'])
bgr = float(self.config['main']['bgr'])
rates_gr = 10**(agr-bgr*mags[:-1]) - 10**(agr-bgr*mags[1:])
print(rates, rates_gr)
np.testing.assert_almost_equal(rates[:, 1], rates_gr, decimal=3)
if PLOTTING:
# See https://docs.pyvista.org/user-guide/index.html# note also
# that the zone crosses the IDL
vscaling = -0.01
import pyvista as pv
plt_smooth = True
plt_rup_wei = False
plt_smooth = False
plt_rup_wei = True
plotter = pv.Plotter()
plotter.set_background('grey')
# Smoothing
fname = os.path.join(self.out_path, 'smoothing.hdf5')
f = h5py.File(fname, 'r')
slo = f['lons'][:]
slo[slo < 0] = slo[slo < 0]+360
sla = f['lats'][:]
sde = f['deps'][:] * vscaling
swe = f['values'][:]
f.close()
points = np.array([slo, sla, sde]).T
# Catalogue
fname = os.path.join(self.reff,
self.config['main']['catalogue_pickle_fname'])
cat = get_catalogue(fname)
lo = cat.data['longitude']
cat.data['longitude'][lo < 0] = lo[lo < 0]+360
flg = ((cat.data['longitude'] > min(points[:, 0])) &
(cat.data['longitude'] < max(points[:, 0])) &
(cat.data['latitude'] > min(points[:, 1])) &
(cat.data['latitude'] < max(points[:, 1])) &
(cat.data['depth'] > 30))
catc = [(x, y, z) for x, y, z in zip(cat.data['longitude'][flg],
cat.data['latitude'][flg], cat.data['depth'][flg] * vscaling)]
catc = np.array(catc)
# Ruptures
fname = os.path.join(self.out_path, '8.05.hdf5')
f = h5py.File(fname, 'r')
coo = f['src_test_8pt05']['hypocenter'][:]
coo[coo[:, 0] < 0, 0] = coo[coo[:, 0] < 0, 0]+360
coo[:, 2] *= vscaling
prb = f['src_test_8pt05']['probs_occur'][:]
f.close()
# Catalogue
mesh = pv.PolyData(catc)
_ = plotter.add_mesh(mesh=mesh, color='red',
render_points_as_spheres=True)
if plt_smooth:
mesh = pv.PolyData(points)
minval = 1e-7
swe[swe < minval] = np.nan
mesh['scalars'] = swe
i = np.isfinite(swe)
opac = np.zeros_like(swe)
opac[i] = (swe[i] + 0.2 - minval) / max(swe[i])
_ = plotter.add_mesh(mesh=mesh, cmap='jet',
show_scalar_bar=True,
point_size=7.0, nan_opacity=0.0,
use_transparency=True, style='points',
opacity=opac)
if plt_rup_wei:
mesh = pv.PolyData(coo)
minval = 1e-7
swe = prb[:, 1]
swe[swe < minval] = np.nan
mesh['scalars'] = swe
_ = plotter.add_mesh(mesh=mesh, cmap='jet',
show_scalar_bar=True, point_size=15.0,
nan_opacity=0.0, opacity=1.0,
style='points')
_ = plotter.show(interactive=True)