From 95d703dbf2ed9d76adc795ef8976deefcdf1e2d3 Mon Sep 17 00:00:00 2001 From: ftong Date: Fri, 22 Aug 2025 14:58:49 +0200 Subject: [PATCH] revert a3078353a8371fa8d7b2b9b5cc46490e335c1cd7 revert Update src/seismic_hazard_forecasting.py --- src/seismic_hazard_forecasting.py | 301 ++++++++++++++++++++++---------------- 1 file changed, 175 insertions(+), 126 deletions(-) diff --git a/src/seismic_hazard_forecasting.py b/src/seismic_hazard_forecasting.py index 5ca0733..a364284 100644 --- a/src/seismic_hazard_forecasting.py +++ b/src/seismic_hazard_forecasting.py @@ -1,154 +1,203 @@ # -*- coding: utf-8 -*- -# --- Configuration Constants --- -DEFAULT_IMT_MIN = 0.01 -DEFAULT_IMT_MAX = 2.0 -DEFAULT_MAGNITUDE = 5.0 -RUPTURE_ARATIO = 1.5 -STRIKE = 0 -DIP = 90 -RAKE = 0 +import numpy as np +from scipy.stats import t, norm +from scipy.optimize import root_scalar +from timeit import default_timer as timer +import logging +logger = logging.getLogger(__name__) -def _get_lasocki_record_count(gsim_model: Any, imt_name: str) -> int: - """ - Extracts the number of ground motion records for the Lasocki2013 model. - """ - if imt_name == 'PGA': - return gsim_model.COEFFS.non_sa_coeffs[PGA()]['N'] - else: - try: - # Extract frequency from SA(freq) string - freq = float(imt_name[imt_name.find('(') + 1:imt_name.find(')')]) - coeffs = gsim_model.COEFFS.get_coeffs('N') - first_index = np.where(coeffs[0] == freq)[0][0] - return coeffs[1][first_index][0] - except (ValueError, IndexError): - logger.error(f"Could not parse frequency from IMT: {imt_name}") - return 0 +from openquake.hazardlib.geo import Point #This class represents a geographical point in terms of longitude, latitude, and depth (with respect to the Earth surface). +from openquake.hazardlib.geo.surface.planar import PlanarSurface +from openquake.hazardlib.source.characteristic import CharacteristicFaultSource +from openquake.hazardlib.mfd import ArbitraryMFD +from openquake.hazardlib.tom import PoissonTOM +from openquake.hazardlib.scalerel import WC1994 #Wells and Coppersmith magnitude – rupture area relationships +from openquake.hazardlib.site import Site, SiteCollection +from openquake.hazardlib.contexts import ContextMaker +from openquake.hazardlib.valid import gsim +from openquake.hazardlib.imt import PGA +import sys -def _create_openquake_context(rx_lat: float, rx_lon: float, model: str, imt: str) -> tuple: +def my_trivial_task(x): """ - Creates and returns the OpenQuake GSIM, Source, and Context objects. + A function that does a trivial task """ + return x * x + +def compute_IMT_exceedance(rx_lat, rx_lon, r, fr, p, lambdas, D, percentages_D, magnitudes, magnitude_pdf, magnitude_cdf, model, imt='PGA', IMT_min=0.01, IMT_max=2.0, rx_label=None, rtol=0.1, use_cython=False, **kwargs): + + n_events = len(r) + try: - gsim_model = gsim(model) - except Exception: - msg = f"{model} was not found in the openquake gsim directory." + gmpes = [gsim(model)] + except: + msg = f"{model} was not found in the openquake gsim directory" logger.error(msg) - raise Exception(msg) - - # Use a dummy hypocenter since it's a placeholder - receiver_point = Point(rx_lon, rx_lat, 0.0) + raise Exception(msg) - # Create the planar surface based on the WC1994 magnitude-scaling relationship + if model == 'Lasocki2013': #this model requires the number of earthquake records + + if imt=='PGA': #extract number of records for PGA + num_ground_motion_records = gmpes[0].COEFFS.non_sa_coeffs[PGA()]['N'] + else: #extract number of records for SA() + freq = float(imt[imt.find('(')+1:imt.find(')')]) # get the desired frequency of SA + first_index = np.where(gmpes[0].COEFFS.get_coeffs('N')[0]==freq)[0][0] + num_ground_motion_records = gmpes[0].COEFFS.get_coeffs('N')[1][first_index][0] + else: + num_ground_motion_records = 0 + + #placeholder values that do not have any effect + Mag = 5.0 #placeholder mag, must be valid for that context; will be overwritten in loop + rupture_aratio = 1.5 + Strike = 0 + Dip = 90 + Rake = 0 + + Hypocenter = Point(rx_lon, rx_lat, 0.0) #does not matter in our case; just set eq location to be same as receiver + #according to the magnitude and MSR calculate planar surface planar_surface = PlanarSurface.from_hypocenter( - hypoc=receiver_point, - msr=WC1994(), - mag=DEFAULT_MAGNITUDE, - aratio=RUPTURE_ARATIO, - strike=STRIKE, - dip=DIP, - rake=RAKE, - ) + hypoc=Hypocenter, + msr=WC1994(), + mag=Mag, + aratio=rupture_aratio, + strike=Strike, + dip=Dip, + rake=Rake, + ) - site_collection = SiteCollection([Site(location=receiver_point)]) + # site for which we compute (receiver location) + site_collection = SiteCollection([Site(location=Point(rx_lon, rx_lat, 0))]) - # Required for context maker - imtls = {SA(float(imt[imt.find('(')+1:imt.find(')')])) if 'SA' in imt else PGA(): [0]} - - context_maker = ContextMaker('Induced', [gsim_model], {'imtls': imtls, 'mags': [DEFAULT_MAGNITUDE]}) + imtls = {s: [0] for s in [imt]} #required for context maker, M = 2 IMTs - # Placeholder source, since it's overwritten by the cython core function - source = CharacteristicFaultSource( - source_id=1, - name='rup', - tectonic_region_type='Induced', - mfd=ArbitraryMFD([DEFAULT_MAGNITUDE], [0.01]), - temporal_occurrence_model=PoissonTOM(50.), - surface=planar_surface, - rake=RAKE - ) + context_maker = ContextMaker('Induced', gmpes, {'imtls': imtls, 'mags': [Mag]}) #necessary contexts builder - context = context_maker.from_srcs([source], site_collection)[0] - - return gsim_model, context_maker, context + src = CharacteristicFaultSource(source_id = 1, + name = 'rup', + tectonic_region_type = 'Induced', + mfd = ArbitraryMFD([Mag], [0.01]), #this does not have any effect + temporal_occurrence_model = PoissonTOM(50.), #this is also not really used + surface = planar_surface, + rake = Rake) + + ctx = context_maker.from_srcs([src], site_collection)[0] #returns one context from the source for one rupture + + if use_cython: -def compute_IMT_exceedance( - rx_lat: float, - rx_lon: float, - r: List[float], - fr: List[float], - p: float, - lambdas: List[float], - D: List[float], - percentages_D: List[float], - magnitudes: List[float], - magnitude_pdf: List[float], - magnitude_cdf: List[float], - model: str, - imt: str = 'PGA', - IMT_min: float = DEFAULT_IMT_MIN, - IMT_max: float = DEFAULT_IMT_MAX, - rx_label: Optional[str] = None, - rtol: float = 0.1, - use_cython: bool = True, - **kwargs -) -> float: - """ - Computes the IMT value for a given exceedance probability using a root-finding algorithm. - """ - if not use_cython: - raise NotImplementedError("The non-cython version is not implemented in this refactor.") - - try: from cython_exceedance import exceedance_core - except ImportError: - logger.error("Could not import cython_exceedance. Make sure the module is compiled and available.") - return np.nan - - gsim_model, context_maker, context = _create_openquake_context(rx_lat, rx_lon, model, imt) - num_ground_motion_records = _get_lasocki_record_count(gsim_model, imt) if model == 'Lasocki2013' else 0 + def exceedance_root_function(a): + return exceedance_core(a, r, fr, lambdas, D, percentages_D, magnitudes, + magnitude_pdf, magnitude_cdf, context_maker, ctx, + model, num_ground_motion_records) - p - def exceedance_root_function(imt_value: float) -> float: - """The function whose root we are trying to find.""" - return exceedance_core( - imt_value, r, fr, lambdas, D, percentages_D, magnitudes, - magnitude_pdf, magnitude_cdf, context_maker, context, - model, num_ground_motion_records - ) - p + else: - # Check function values at the interval endpoints + def exceedance_root_function(a): + exceedance_prob_sum = 0 + log_a = np.log(a) # Precompute log(a) + + for j in range(len(lambdas)): #loop through all lambdas + lambda_j = lambdas[j] + D_j_val = percentages_D[j] * D # Use a different name to avoid shadowing D + lambda_D_j = lambda_j * D_j_val + denom_j = (1 - np.exp(-lambda_D_j)) + if denom_j == 0: # Avoid division by zero if lambda_D_j is very small or zero + continue + + for i in range(n_events): #loop through all events + ri = r[i] # Epicentral distance + fr_i = fr[i] # Location probability f(r) + ctx.repi = ri + + # Precompute terms only dependent on lambda_j, D_j, m + lambda_D_j_f_m = lambda_D_j * magnitude_pdf + exp_term_m = np.exp(-lambda_D_j * (1 - magnitude_cdf)) + f_conditional_base_m = (lambda_D_j_f_m * exp_term_m) / denom_j + + for k in range(len(magnitudes)): #loop through all values of magnitude pdf and cdf + m = magnitudes[k] + ctx.mag = m # update context magnitude + + # Calculate f_conditional (simpler now) + f_conditional = f_conditional_base_m[k] + + mean, sig, _, _ = context_maker.get_mean_stds(ctx) + log_gm_predicted = mean[0][0][0] + variance_term = sig[0][0][0] + residual = log_a - log_gm_predicted # Use precomputed log_a + + if residual <= 0: + exceedance_probability = 1.0 + else: + # Avoid division by zero or very small numbers if variance_term is ~0 + if variance_term < 1e-15: # Adjust threshold as needed + exceedance_probability = 0.0 + else: + t_value = residual / variance_term + + if model == 'Lasocki2013': + exceedance_probability = t.sf(t_value, num_ground_motion_records - 3) # student t distribution, degrees of freedom: n-3; sf = 1 - cdf + else: + exceedance_probability = norm.sf(t_value) # equivalent to 1.0 - norm.cdf(t_value) + + location_exceedance_prob = exceedance_probability * f_conditional * fr_i + exceedance_prob_sum += location_exceedance_prob + + return exceedance_prob_sum - p + + + + # Check function values at different test points + IMT_mid = (IMT_max-IMT_min)/2 + + + lower_bound_value = exceedance_root_function(IMT_min) + + + mid_point_value = exceedance_root_function(IMT_mid) + + + upper_bound_value = exceedance_root_function(IMT_max) - logger.info(f"Receiver: {rx_label or 'N/A'}") - logger.info(f"Function value at {imt} = {IMT_min:.2f}: {lower_bound_value:.2f}") - logger.info(f"Function value at {imt} = {IMT_max:.2f}: {upper_bound_value:.2f}") - + + + + logger.info(f"Receiver: {str(rx_label)}") + logger.info(f"Function value at {imt} = {str(IMT_min)} : {lower_bound_value}") + logger.info(f"Function value at {imt} = {str(IMT_mid)} : {mid_point_value}") + logger.info(f"Function value at {imt} = {str(IMT_max)} : {upper_bound_value}") + + + if np.sign(lower_bound_value) == np.sign(upper_bound_value): - msg = ("Function values at the interval endpoints must differ in sign " - "for root finding to work. Try expanding the interval or check the model.") + msg = "Function values at the interval endpoints must differ in sign for fsolve to work. Expand the interval or use a different model." logger.error(msg) - return np.nan + gm_est = np.nan + return gm_est + # raise ValueError(msg) - # Find the root of the function using Brent's method - start_time = timer() - gm_est = np.nan - try: - output = root_scalar( - exceedance_root_function, - bracket=[IMT_min, IMT_max], - rtol=rtol, - method='brenth' - ) - gm_est = output.root - logger.debug(f"Root finding converged: {output.converged}") + + + # Find root of function + start = timer() + + try: + method='brenth' + logger.debug("Now trying Scipy " + method) + #output = root_scalar(exceedance_root_function, bracket=[IMT_min, IMT_max], rtol=rtol, method=method) + #gm_est = output.root + gm_est = np.nan except Exception as error: - logger.error(f"An exception occurred during root finding: {error}") - - end_time = timer() - logger.info(f"Ground motion estimation computation time: {end_time - start_time:.1f} seconds") - logger.info(f"Estimated {imt}: {gm_est:.4f}") + logger.error(f"An exception occurred: {error}") + logger.info("Set ground motion value to nan") + gm_est = np.nan + + end = timer() + logger.info(f"Ground motion estimation computation time: {round(end - start,1)} seconds") + logger.info(f"Estimated {imt}: {gm_est}") return gm_est