Stratagem instrument presets

The Zonge Stratagem workflow has its own end-to-end presets in pycsamt.pipeline.stratagem — full pipelines that go from raw instrument files (with survey coordinates and reprojection) all the way to processed, renamed EDIs. This example browses those presets; running one needs raw Stratagem data plus a coordinate file, so here we focus on the recipes themselves.

The Stratagem catalogue

stratagem_preset_catalogue() prints the available instrument workflows and what each does.

from pycsamt.pipeline import (
    list_stratagem_presets,
    stratagem_preset_catalogue,
)

print(stratagem_preset_catalogue())

Stratagem pipeline presets
────────────────────────────────────────────────────────────────
  basic                   Direct equivalent of the legacy stratagem_edi_process_script.py: inject GPS coords → AMA static-shift → frequency trim → noise removal → export → rename.
                          remove_static_shift → drop_frequencies → remove_noises → export → rename

  full_processing         QC report → AMA static-shift → hardware-aware frequency filter → noise removal with smoothing → export → rename.
                          run_qc → remove_static_shift → drop_frequencies → remove_noises → export → rename

  publication_ready       C&G standard: full QC, hardware SNR masking, tight AMT band (15 Hz – 100 kHz), aggressive smoothing → export → rename.
                          run_qc → remove_static_shift → drop_frequencies → remove_noises → export → rename

Presets as objects

list_stratagem_presets() returns StratagemPreset objects. Each bundles survey-wide defaults (projection, coordinate handling) with an ordered step list — a complete acquisition-to-EDI recipe.

presets = list_stratagem_presets()
print(f"{len(presets)} Stratagem presets:\n")
for p in presets:
    print(
        f"  {p.name:<18} {len(p.steps)} steps — {p.description.splitlines()[0]}"
    )

3 Stratagem presets:

  basic              5 steps — Direct equivalent of the legacy stratagem_edi_process_script.py: inject GPS coords → AMA static-shift → frequency trim → noise removal → export → rename.
  full_processing    6 steps — QC report → AMA static-shift → hardware-aware frequency filter → noise removal with smoothing → export → rename.
  publication_ready  6 steps — C&G standard: full QC, hardware SNR masking, tight AMT band (15 Hz – 100 kHz), aggressive smoothing → export → rename.

Inside a preset

The publication_ready preset is the fullest — its steps and survey defaults show exactly what a finished Stratagem run applies.

pub = next(p for p in presets if "pub" in p.name.lower())
print(f"preset {pub.name!r}: {pub.description}\n")
print("survey defaults:")
for k, v in pub.survey_defaults.items():
    print(f"  {k:<16} {v}")
print("\nsteps:")
for name, params in pub.steps:
    print(f"  {name:<20} {params if params else ''}")

preset 'publication_ready': C&G standard: full QC, hardware SNR masking, tight AMT band (15 Hz – 100 kHz), aggressive smoothing → export → rename.

survey defaults:
  epsg             32649
  utm_zone         49N

steps:
  run_qc               {'include_skew': True, 'min_frac_ok': 0.5, 'min_snr_med': 3.0, 'max_skew_med': 5.0}
  remove_static_shift  {'sort_by': 'lon', 'half_window': 5, 'weights': 'tri', 'max_skew': 5.0}
  drop_frequencies     {'fmin': 15.0, 'fmax': 100000.0, 'snr_thresh': 3.0, 'min_frac': 0.5, 'use_hardware_mask': True}
  remove_noises        {'mains_hz': 50.0, 'n_harm': 30, 'tol_hz': 0.05, 'hampel_win': 3, 'hampel_nsig': 3.0, 'smooth': True, 'smooth_win': 3}
  export
  rename

How you would run it

With raw data in hand it is a single call — run_stratagem_preset() — pointing at the raw directory and coordinate file:

from pycsamt.pipeline import run_stratagem_preset
result = run_stratagem_preset(
    "publication_ready",
    raw_dir="field/stratagem_raw/",
    outdir="processed/",
    epsg=32649, utm_zone="49N",
)

For step-by-step control, build a StratagemPipeline directly and call run.

Preset lengths at a glance

import matplotlib.pyplot as plt

names = [p.name for p in presets]
sizes = [len(p.steps) for p in presets]
order = sorted(range(len(presets)), key=lambda i: sizes[i])
fig, ax = plt.subplots(figsize=(7.5, 3.4), constrained_layout=True)
ax.barh([names[i] for i in order], [sizes[i] for i in order], color="#f15a29")
ax.set_xlabel("number of steps")
ax.set_title("Stratagem presets, by workflow length")
ax.margins(x=0.1)

Takeaway. The Stratagem presets package the whole instrument workflow — import, reprojection, processing, export — as reproducible recipes, the same philosophy as the generic presets applied to a specific acquisition system.