1. Prerequisites#
The user guide is the practical companion to the pyCSAMT science API, applications, and command-line tools. It covers the full life of a survey: turning raw instrument output or field-hardware exports into EDI, loading and inspecting that data, running quality control and processing, correcting for terrain and static shift, building maps and pseudosections, choosing an inversion path, interpreting the result, and automating any of the above with agents.
This section is organized as an operational workspace rather than a single narrative. Each page documents one package and stands on its own: open it directly when you already know what you need. The reading paths below exist for the more common case, where the question is not “what does this function do” but “where do I even start.”
1.1. Reading Paths#
Different users arrive here with different goals. Pick the path that matches yours; they share pages on purpose, so do not be surprised to see the same link twice.
New survey users, starting from a folder of EDI files, should read Data Loading, then EM Tools Guide for quality control, then Map Tools to see stations and profiles on a map.
Users with non-EDI instrument output (AVG, J-files, raw cross-power spectra, time series, or a transient TDEM decay) should start at Transformers to reach EDI first, then continue as a new survey user above.
Geometrics/EMI Stratagem users should read Stratagem Surveys end to end; it covers the WinGLink hand-off, coordinate injection, and QC steps that are specific to that hardware before the data ever reaches EM Tools Guide.
IoT and edge-acquisition users should read IoT-Enabled Field Acquisition for device configuration, edge QC, telemetry, and provenance, then bridge into the normal workflow through Data Loading.
Processing and QC users should work through EM Tools Guide for static shift, frequency editing, noise removal, and dimensionality, pairing it with Site Tools for station-level selection, editing, and export.
Terrain and mapping users should read Topography before Map Tools; topography has to be extracted and draped before a section plot reflects real ground elevation instead of a flat datum.
Inversion users should read Inversion first – it is the decision point between the classical engines in Classical model integrations, the learned workflows in AI inversion, and, upstream of both, the synthetic-data and sensitivity work in Forward Modelling.
Interpretation users, once an inversion result exists, should read Interpretation for hydrogeophysical context, uncertainty, and reporting, using Topography and Map Tools for the section and overlay figures that go into that interpretation.
AI and agent users who want automation rather than manual API calls should read Agents; it links back into AI inversion for the model-level detail behind the AI inversion agents specifically.
Reproducible / team workflows should read Pipeline System to turn a manual sequence of the pages above into a named, versioned, re-runnable recipe.
1.2. Section Map#
The table below lists every user guide section in reading order, the package it documents, and what to expect on arrival.
Section |
Package |
What it covers |
|---|---|---|
Turning files, directories, or parsed objects into a station-ordered
|
||
Converting AVG, J-file, raw spectra EDI, time-series, or TDEM decay input into EDI. |
||
Station maps, profile pseudosections, 3-D quick-look maps, and figure export from Python code. |
||
Embedding real station elevation into 2-D sections so plots drape over terrain. |
||
The decision point between classical, AI, and forward-modelling paths; the backend-neutral API and adapters. |
||
– |
Connecting reviewed inversion products to geology, uncertainty, and defensible reporting. |
|
Configuring and auditing the operational layer of an IoT-enabled field survey. |
||
The post-acquisition workflow for Geometrics/EMI Stratagem hardware, from raw files to processed EDI. |
||
Quality control, frequency editing, static shift, noise removal, tensor/strike analysis, and source diagnostics. |
||
Station-centric selection, editing, normalization, profiles, and export/reporting for site collections. |
||
Predicting responses from a known earth model: solvers, synthetic datasets, and noise models. |
||
Reproducible, named processing recipes connecting steps, configuration files, and CLI execution. |
Two sections sit outside this table because they are not linear reading, but they are just as central: Classical model integrations and AI inversion are the classical and learned engine layers nested under Inversion, and Agents is documented as its own top-level guide alongside this one, not a child page of it.
1.3. Relationship To Other Sections#
Getting Started covers installation, environment setup, and the first end-to-end run; read it first if pyCSAMT is not installed yet or a workflow has not been run once already.
Scientific Background gives the scientific background – response functions, distortion effects, and inversion concepts – behind the tools documented here.
Tutorials gives longer, worked, end-to-end examples that combine several of the sections above.
API reference is the complete public class and function reference; every
pycsamt.<subpackage>link on this page resolves there.