FaultScan

FaultScan analyzes dense local seismic-array recordings from the 2022 Anza/San Jacinto earthquake sequence. It aligns three-component waveforms, measures station and event timing corrections, builds coherent stacks, and produces plots and workbooks for evaluating subtle changes near the S wave.

The long-term scientific objective is to determine whether the subsurface near the San Jacinto fault changed across the M3.4 mainshock and during its early aftershock sequence. The current alignment, relocation, screening, and static correction work is intended to separate possible temporal structural changes from event-location, origin-time, station, site, and processing effects.

Main workflow

1. align_stack.py reads rp_input.json, the event catalog, station metadata, and waveform snippets or long traces.
2. align_utils.py supplies waveform reading, station rejection, horizontal rotation, TauP travel times, staged alignment, screening, and stacking.
3. DP1/DP2 horizontals are rotated to radial (R) and transverse (T) components using the source-receiver geometry and the project's orientation correction.
4. Traces are aligned relative to predicted P- or S-wave timing, screened by windowed correlation, and combined into event stacks.
5. The pipeline writes per-event products, station residuals, all-event stack plots, alignment workbooks, and a snapshot of the run parameters.
6. The post-processing programs summarize station statics, compare components, and optionally apply validated event-shift residuals to the catalog.

The pipeline currently uses the shared catalog column time shift for event origin corrections on all waveform components. Event-stack cross-correlation is a separate optional residual-alignment stage.

Repository layout

Path	Purpose
align_stack.py	Main waveform alignment, screening, stacking, plotting, and export pipeline.
align_utils.py	Shared waveform, geometry, travel-time, alignment, and plotting helpers.
rp_input.json	Active run configuration loaded automatically by align_stack.py.
TASKS.md	Curated queue of active, upcoming, waiting, proposed, and recently closed work.
plot_statics_by_station.py	Robust event-baseline correction, station-static estimation, plots, and Excel summaries.
augment_stations_with_statics.py	Merges robust station-static estimates into a station workbook.
plot_event_rt_snippets.py	Produces distance-ordered, overlaid radial/transverse snippet figures for one event.
plot_event_time_shifts.py	Compares radial- and transverse-derived event shifts stored in the catalog.
plot_station_static_basis_comparison.py	Compares R- and T-basis station-static estimates for each waveform component.
plot_station_component_static_comparison.py	Compares Z, R, and T station statics within each correction basis.
tools/update_catalog_time_shifts.py	Validates and applies measured event-stack residuals to a catalog workbook.
stacker.py	Compares and plots per-event component stacks from one explicit align_stack run.
mapper.py	Independent USGS seismicity download and mapping utility for the Pinyon Flat area.
scripts/	Data-preparation and output-regression utilities.
tests/	Unit and smoke tests for pipeline branches, helpers, and catalog updating.
Notes/	Scientific goals, current status, decisions, review findings, and conversation summaries.

The JSON files under reserve json files/ and rp_input real.json are retained configuration variants. They are not loaded by the main pipeline unless they are deliberately copied or supplied as the active configuration.

Data and outputs

The code and the research data are stored separately. Current defaults expect the research tree at:

/Users/jvidale/Documents/Research/FaultScanR/
├── event_sta_info/
│   ├── catalog_local_hand.xlsx
│   ├── stations.txt
│   └── stations.xlsx
├── Sgrams/
│   ├── 20220930_<rate>Hz/
│   └── Snippets_<rate>Hz/
└── output/

The principal inputs are:

• catalog_local_hand.xlsx: event IDs, origin times, locations, catalog time shifts, and event-selection metadata.
• stations.txt and stations.xlsx: station coordinates, identifiers, and optional station-static columns.
• MiniSEED waveforms: DPZ vertical data and DP1/DP2 horizontal data at the configured sample rate.
• rp_input.json: frequency band, time windows, phase, components, event list, input mode, alignment controls, and plotting options.

Each pipeline run creates a timestamped directory under output/. Depending on configuration, products include:

• Per-event aligned component stacks and MiniSEED files.
• Record-section, stage-stack, envelope, correlation, and station-map figures.
• A JSON snapshot of the parameters used for the run.
• All-event component-stack figures.
• Cross-event alignment workbooks and offset-stack figures.
• Per-event station-residual workbooks under output/Statics when station_static_mode is cross_correlation.

Many scripts contain user-specific absolute default paths. Check rp_input.json and each command's --help output before using the repository with a different research-data location.

Environment

Run the project in the vidale_main Conda environment. The main dependencies include Python, NumPy, pandas, SciPy, Matplotlib, ObsPy, and openpyxl.

conda run -n vidale_main python align_stack.py

The active configuration is read automatically from rp_input.json beside align_stack.py. A run should normally start by reviewing at least:

• events, input_mode, and analysis_hz
• component, all_channels, and align_phase
• min_freq, max_freq, and the time/correlation windows
• use_json_event_location
• use_event_static_correction
• station_static_mode and, for tabulated, its workbook/column
• Plotting switches

When all_channels is true, Z, R, and T are processed; component does not limit the run to a single component.

Event and station corrections are configured independently:

• use_event_static_correction: true applies the catalog time shift values; false leaves the catalog origin times uncorrected and measures cross-event stack residuals from the waveforms.
• station_static_mode: "none" uses only the relative TauP-predicted station travel times and performs no station residual-lag search.
• station_static_mode: "tabulated" adds the configured station-static workbook column to the TauP shifts.
• station_static_mode: "cross_correlation" adds residual lags estimated from the waveforms to the TauP shifts and writes station-residual workbooks.

For compatibility with older configuration files, use_station_static_correction: true maps to tabulated and false maps to cross_correlation. New configurations should use station_static_mode.

Common commands

Run the alignment pipeline:

conda run -n vidale_main python align_stack.py

Summarize the statics matching the active component and phase in rp_input.json:

conda run -n vidale_main python plot_statics_by_station.py

Select an explicit case:

conda run -n vidale_main python plot_statics_by_station.py \
  --component R --phase S

Plot R/T snippets for one event:

conda run -n vidale_main python plot_event_rt_snippets.py \
  --event CI_40353864

Compare Z and T stacks from an align_stack run. The fixed /Users/jvidale/Documents/Research/FaultScanR/output/2026 prefix is implicit:

conda run -n vidale_main python stacker.py \
  --run 0722_182322_4666 --components Z T

Running stacker.py with the VS Code triangle and no arguments uses the editable DEFAULT_* settings near the top of the file. Command-line options override those settings when supplied.

Preview a catalog shift update before modifying the workbook:

conda run -n vidale_main python tools/update_catalog_time_shifts.py \
  R /path/to/timestamped_run --dry-run

Only remove --dry-run after verifying the reported source column, baseline, residual, destination column, event list, and proposed values. The updater rejects alignment workbooks without measured cross-correlation residuals and guards against stale or ambiguous catalog provenance.

Compare two run-output directories for regressions:

conda run -n vidale_main python scripts/compare_outputs.py \
  /path/to/baseline /path/to/candidate

Use python <program> --help for the complete options of programs that expose a command-line interface.

Tests

Run the complete test suite with:

conda run -n vidale_main python -m unittest discover -s tests

The focused alignment smoke suite is:

conda run -n vidale_main python -m unittest tests.test_align_stack_smoke

Tests exercise important contracts, but they do not replace inspection of the scientific inputs, waveform alignment figures, workbook provenance, or output consistency from a representative run.

Scientific and project notes

• Notes/faultscan_science_goals.md explains the experiment, target signals, location controls, and criteria for a convincing structural observation.
• Notes/faultscan_project_status.md records the current processing state, active decisions, results, next steps, and open questions.
• Notes/faultscan_project_chat_summary.md preserves implementation history, scientific reasoning, recovery decisions, and detailed review findings.
• statics_results_explanation.html is a static explanatory snapshot of an earlier set of station-static plots; it is not an automatically regenerated report.

Use this README for the stable overview and normal entry points. Use Notes/ for evolving scientific interpretation, project history, and unresolved decisions.

Current scientific cautions

• Station and event corrections are enabling measurements, not final evidence of a time-dependent fault-zone change.
• Event location, origin time, source duration, magnitude, component orientation, site response, and waveform quality can all imitate or obscure the target signal.
• R- and T-derived timing/static results should not be treated as interchangeable without a documented physical and statistical justification.
• Generated reports and comparison workbooks are snapshots and should be regenerated after their source workbooks or configuration change.

Authorship

FaultScan is a research codebase developed by John Vidale with AI-assisted implementation and documentation. Scientific conclusions remain subject to data-quality review and independent validation.