Dynamic calculations

Select the backend

Setting	Backend	Stress output selection
use_spherical=False	QSEIS2025, layered model	[0,0,0,1,0]
use_spherical=True	QSSP2020, spherical model	11 entries, index 5 set to 1

default_config=True chooses the matching list. For custom settings, keep this output enabled. QSEIS06 is not used by the current DynCFS dispatcher. Old Green’s-function libraries are not automatically migrated.

Build and synthesize

from pathlib import Path
from dyncfs.configuration import CfsConfig
from dyncfs.cfs_dynamic import create_dynamic_lib, compute_dynamic_cfs_sequential

if __name__ == "__main__":
    config = CfsConfig()
    config.read_config(str(Path("case.ini").resolve()))
    create_dynamic_lib(config)
    compute_dynamic_cfs_sequential(config)

For multiple workers, replace the last call with compute_dynamic_cfs_parallel(config). The complete run_all_dynamic(config) builds the library, computes observation faults and, if enabled, calculates the fixed-depth grid.

Both builders convert native tables to binary and request removal of converted text tables. QSSP creation also requests spectrum calculation. Retain metadata and model files with the library.

Synthesis resamples each source STF, normalizes it to seismic moment, queries the selected stress Green’s functions, subtracts the pre-P mean, convolves, sums and converts ENU to NED. The resulting tensor has shape (sampling_num, 6) for one receiver.

Fixed-depth receivers

Use compute_dynamic_cfs_fix_depth_sequential or compute_dynamic_cfs_fix_depth_parallel. Both accept an explicit depth and receiver mechanism. The sequential function additionally accepts geographic range/spacing overrides. For the parallel function, put those settings in the configuration.

For modes 0/1, the receiver mechanism comes from the function argument, then receiver_mechanism in [fixed_obs_depth], and otherwise from the summed source moment tensor. Set it in the INI or pass it through Python when the source average is not the intended receiver.

Static zero-frequency correction

Set correct_zero_freq=True only after computing static tensors for the same sources and receivers. Keep their row order, geometry and source normalization consistent. The loader checks receiver count, not the full scientific configuration.

The required files are:

• Faults: results/static/stress_tensor_plane<n>.npy.

• Depth grids: results/static/stress_tensor_dep_<depth to 2 decimals>.npy.

A missing tensor raises FileNotFoundError; a receiver-count mismatch raises ValueError. The high-level loader converts NED to ENU for the correction stage.

A finite max_slowness is also required. For QSEIS2025, its default is None, so correct_zero_freq=True alone does not apply the correction. The loader warns, but still requires the static file. Select a justified slowness bound in custom settings or assign config.max_slowness after parsing.

The correction interval is derived from earliest P time, maximum source–receiver distance, source duration and STF length, then clipped to the output window. Correction requires at least two interval samples. It differentiates stress, corrects the stress-rate integral toward the static tensor and integrates back.

Without a static tensor, a finite slowness bound may replace the late tail with a post-cutoff mean. Inspect the final time series and provide enough window length; the setting is not a simple late-time zeroing switch.

Scientific checks

Compare multiple sampling intervals, source/grid spacings and integration settings for your geometry. Check for aliasing, a sufficient time window, finite stress tensors and stable baselines. A static match after explicit correction is not independent evidence of dynamic accuracy.

The local documentation validation exercises the static tutorial. These dynamic recipes describe the current code and have not been claimed as new end-to-end dynamic validation.