Exports And Reproducibility#

The desktop app produces several kinds of outputs: figures, re-exported EDI files, station metadata tables, pipeline configuration files, solver input folders, interpretation products, logs, and the desktop session state. Treat these as different artifacts. A figure explains a decision; an EDI folder stores a processed data product; a JSON configuration makes the workflow repeatable.

The guiding rule is simple: every exported result should carry enough context for another user to understand what data state it came from and which settings produced it.

Export Types#

Output	Desktop Surface	Typical Use
Figure files	More > Export Figure, panel export buttons	Save the current map, profile, QC, correction, forward, or inversion plot for reports and processing notes.
Batch figures	Tools > Batch Export Plots…	Save every open canvas figure into one folder.
Survey metadata	Tools > Format Converter…	Export station metadata to CSV or JSON.
Re-exported EDI files	Tools > Format Converter…, correction tools, pipeline export	Save a processed or converted survey as station EDI files.
Recomputed EDIs	Tools > Recompute EDIs…	Rotate tensors, trim frequency range, fill missing values, recompute resistivity/phase, and write an optional manifest CSV.
Pipeline configuration	Processing Pipeline > Save config	Preserve method and parameter choices for a repeatable processing chain.
Inversion input/output	Inversion Wizard	Store solver input files, logs, and results in a run-specific working directory.
Interpretation products	Interpretation Studio	Export Oasis Montaj XYZ, LAS, CSV tables, and VTK grids.
Desktop session	File > Save Session	Restore theme, recent files, selected station, window geometry, and preferences.

Figure Export#

Most desktop plots are matplotlib figures. Use More > Export Figure or a panel’s own Export button to save the active figure. The export dialog delegates to Figure.savefig and supports:

Format	Type	Best Use
`PNG`	Raster, lossless	Screenshots, documentation, quick sharing, and web pages.
`TIFF`	Raster, high resolution	Journal or report workflows that require high-DPI raster figures.
`PDF`	Vector	Reports, print, and figures that need sharp text and lines.
`SVG`	Vector	Web documentation or editing in vector graphics tools.
`EPS`	Vector, legacy	Older publishing pipelines that still request EPS.

The dialog defaults to 300 DPI, which is a good report setting for raster exports. Use 150 DPI for quick review images, 300 DPI for most reports, and 600 DPI only when a publisher or print workflow needs it. Vector formats are usually better for line plots, rose diagrams, and profile curves because labels remain sharp at any zoom level.

When exporting a figure for a processing decision, put the decision in the filename:

qc/L30_coverage_before_frequency_edit.png
qc/L30_snr_after_noise_filter.png
corrections/L30_static_shift_before_after.pdf
strike/L30_strike_stability_bands.svg

Avoid generic names such as figure1.png. They become untraceable as soon as several windows are open.

Batch Plot Export#

Use Tools > Batch Export Plots… when several panel windows are open and you want to capture the current desktop evidence in one folder. The batch exporter collects visible matplotlib canvases from open panel windows and saves them as <label>.<format>.

Batch export supports PNG, PDF, SVG, EPS, and TIFF. It also lets you choose DPI and whether the background should be transparent. Transparent backgrounds are useful for slide decks, but they can make dark theme labels hard to read on a light page. For documentation and reports, prefer a normal opaque background unless you know the final page color.

Use batch export after a review pass:

Open the map, profile, QC, and correction windows you want to document.
Set each window to the exact plot and station/band selection you want.
Run batch export to a dated folder.
Rename or annotate key figures if the automatic label is not specific enough.

Batch export saves visual evidence. It does not save the processing settings that produced corrected data. Pair it with pipeline JSON, correction notes, or exported EDIs when reproducibility matters.

Survey Metadata Export#

Use Tools > Format Converter… to export station metadata from the loaded survey. The converter can write:

survey_stations.csv for spreadsheet review and quick station inventory;
survey_stations.json for structured downstream tools;
EDI re-exports when the loaded station objects expose an EDI writer.

The CSV and JSON metadata include station name, latitude, longitude, frequency count, minimum and maximum period, and whether impedance error data are present. Use these files as an inventory, not as the full MT/CSAMT data product.

Metadata export is useful before sharing a survey because it lets a reviewer check station count, coordinate coverage, and frequency availability without opening every EDI file.

EDI Data Products#

EDI outputs are the data products that other tools can reload. The desktop can write EDI files from several places:

Format Converter can re-export the currently loaded survey when station objects support EDI writing.
Data Corrections can export Stratagem-corrected EDIs from the Stratagem correction path.
Processing Pipeline writes processed EDIs during its final Export step using pycsamt.emtools.export_edis.
Recompute EDIs writes a transformed EDI set with optional tensor rotation, frequency trimming, missing-value fill, and resistivity/phase recomputation.

Always keep raw EDIs separate from corrected or recomputed EDIs. A practical layout is:

raw_edi/
corrected_edi/static_shift_ama/
corrected_edi/source_effect_test/
recomputed_edi/rotated_to_strike/
pipeline/L30_qc_ss_rotate/exported_edi/

After exporting an EDI product, reload it in a fresh desktop session or clear mental state by reopening the folder. Check the station count, map geometry, profile curves, and QC coverage before using the exported product for inversion.

Recomputed EDIs#

The Recompute EDIs… tool is for controlled data-product generation. It can use the loaded stations or a selected EDI file/folder as input, then write a new EDI set with chosen transformations.

Important options:

Rotation angle – rotates impedance and/or tipper components when a strike decision has already been justified.
Frequency limits – trims the output to a trusted frequency band.
Fill missing values – fills missing data according to the selected strategy; document this choice carefully.
Recompute resistivity/phase – updates derived values from impedance.
Manifest CSV – writes a station-level record of the operation.
Filename template – controls output names, for example {source_stem}.edi.

Use recomputed EDIs when you need a clean, explicit handoff to external software. Do not use this tool as a hidden correction step; save the manifest and the diagnostic figures that justify every transformation.

Pipeline Configurations#

The processing pipeline can save and load its configuration as JSON. The JSON stores each step ID, step name, selected method, and method parameters. It does not replace the exported EDIs; it explains how those EDIs were generated.

Save the pipeline JSON beside the pipeline output:

pipeline/
  L30_qc_ss_rotate.json
  L30_qc_ss_rotate.log
  exported_edi/
  figures/

When you rerun a saved configuration, confirm that step 1 is using the intended input source. A valid JSON file can still produce the wrong output if it is run against a different active survey.

Inversion Exports#

The inversion wizard writes into the selected working directory. For external engines such as Occam2D, ModEM, and MARE2DEM, input-file generation is already an export worth preserving. Keep one folder per run attempt:

inversion/
  L30_occam2d_corrected_ss_v01/
    inputs/
    logs/
    results/
    figures/

Use run names that identify line, data state, engine, and attempt number. A folder such as modem_run is not enough once several corrected data states exist.

Before archiving an inversion folder, save:

the input files generated by the builder;
the solver log or desktop run log;
the starting model or forward-model parameters;
result plots;
the QC and correction figures that define the input data state.

Interpretation Exports#

The Interpretation Studio exports derived geological products. Available exports include:

XYZ for Oasis Montaj style workflows;
LAS for station or borehole-style logs;
CSV for flat interpretation tables;
VTK for gridded model visualization.

These files are downstream interpretation products. Save them under a folder that points back to the inversion run and corrected EDI set that produced them:

interpretation/
  from_L30_occam2d_corrected_ss_v01/
    L30_interpretation.csv
    L30_model.vtk
    station_logs/

Session And Settings#

Use File > Save Session to persist the desktop session. The session is stored at ~/.pycsamt/session.json and includes theme, recent files, last data directory, selected station, frequency preferences, window geometry, solver paths, default inversion work directory, logging level, map tile provider, and API key setting.

Session state is useful for convenience, but it is not a project archive. It does not guarantee that another user can reconstruct a processing product. For project reproducibility, save exported data, figures, pipeline JSON, and inversion/interpretation folders in the project directory.

Settings profiles are separate JSON snapshots of application/API settings. Use them when you want to move a configuration between machines or preserve a known set of plotting and processing defaults.

Recommended Project Layout#

A complete desktop project folder can look like this:

L30_project/
  raw_edi/
  metadata/
    survey_stations.csv
  qc/
    L30_coverage_before_processing.png
    L30_snr_before_processing.png
  corrections/
    static_shift_ama/
      figures/
      corrected_edi/
  strike/
    L30_strike_analysis.pdf
    L30_strike_stability_bands.svg
  forward/
    geothermal_starting_model.json
    synthetic_response.png
  pipeline/
    L30_qc_ss_rotate.json
    L30_qc_ss_rotate.log
    exported_edi/
  inversion/
    L30_occam2d_corrected_ss_v01/
  interpretation/
    from_L30_occam2d_corrected_ss_v01/
  session/
    notes.md

The exact folder names can change, but the structure should separate raw data, processed data, diagnostic figures, configurations, solver runs, and final interpretation products.

Export Checklist#

Before sharing or archiving a desktop result, check that you have:

raw input EDIs or a link to their immutable location;
exported corrected/recomputed EDIs if the active data were changed;
QC figures before and after major corrections;
strike, dimensionality, or topography figures when they affected modelling;
pipeline JSON and logs for automated workflows;
inversion input files, logs, and result figures;
interpretation exports with a clear parent inversion run;
a short note explaining the data state and major assumptions.

This is the difference between “I saved the plot” and “I can reproduce the result.” The second one is the one future you will thank present you for.