pyiwfm 1.1.3

Python package for reading, writing, visualizing, and comparing IWFM models

pyiwfm

Python package for reading, writing, visualizing, and comparing IWFM (Integrated Water Flow Model) models.

Installation

# Basic installation (includes matplotlib, geopandas, shapely, h5py)
pip install pyiwfm

# With mesh generation (triangle, gmsh)
pip install "pyiwfm[mesh]"

# With VTK 3D export
pip install "pyiwfm[viz]"

# With web viewer (FastAPI + React + vtk.js + deck.gl)
pip install "pyiwfm[webapi]"

# With PEST++ integration (scipy)
pip install "pyiwfm[pest]"

# With all optional dependencies
pip install "pyiwfm[all]"

# Development (editable install with dev tools)
pip install -e ".[dev]"

Budget Post-Processing

Export IWFM budget and zone budget results to Excel workbooks:

# Export budgets from a control file (one .xlsx per budget spec)
pyiwfm budget C2VSimFG_Budget_xlsx.in

# Export zone budgets from a control file
pyiwfm zbudget C2VSimFG_ZBudget_xlsx.in

Or use the Python API directly:

from pyiwfm.io import BudgetReader, budget_to_excel

reader = BudgetReader("GW_Budget.hdf")
budget_to_excel(
    reader, "GW_Budget.xlsx",
    volume_factor=2.29568e-05, volume_unit="AC.FT.",
)

Quick Start

from pyiwfm import AppGrid, Node, Element, Stratigraphy
import numpy as np

# Create a simple mesh
nodes = {
    1: Node(id=1, x=0.0, y=0.0),
    2: Node(id=2, x=100.0, y=0.0),
    3: Node(id=3, x=100.0, y=100.0),
    4: Node(id=4, x=0.0, y=100.0),
}

elements = {
    1: Element(id=1, vertices=(1, 2, 3, 4), subregion=1),
}

grid = AppGrid(nodes=nodes, elements=elements)
grid.compute_areas()
grid.compute_connectivity()

print(f"Grid: {grid.n_nodes} nodes, {grid.n_elements} elements")

Model I/O Example

from pathlib import Path
from pyiwfm.io import load_complete_model, save_complete_model

# Load a complete IWFM model from simulation main file
model = load_complete_model("Simulation/Simulation.in")

print(f"Loaded model with {model.grid.n_nodes} nodes")
print(f"Groundwater wells: {len(model.groundwater.wells) if model.groundwater else 0}")

# Save model to new directory
save_complete_model(model, Path("output_model"))

# Write time series to HEC-DSS (bundled C library)
from pyiwfm.io.dss import DSSTimeSeriesWriter, DSSPathnameTemplate

template = DSSPathnameTemplate(a_part="IWFM", c_part="HEAD", e_part="1DAY")
with DSSTimeSeriesWriter("output.dss") as writer:
    writer.write_timeseries(head_timeseries, template.make_pathname(location="WELL_1"))

Web Visualization

pyiwfm includes an interactive web viewer built with FastAPI (backend) and React + vtk.js + deck.gl (frontend). Launch it with:

# CRS is optional — defaults to C2VSimFG UTM Zone 10N for most models
pyiwfm viewer --model-dir /path/to/model

# Specify CRS explicitly if needed
pyiwfm viewer --model-dir /path/to/model --crs "+proj=utm +zone=10 +datum=NAD83 +units=us-ft +no_defs"

The viewer provides six tabs:

• Overview: Model summary, metadata, and mesh quality metrics
• 3D Mesh: Interactive vtk.js 3D rendering with layer visibility, cross-section slicing, stream network overlay, and z-exaggeration
• Results Map: deck.gl + MapLibre map showing head contours, drawdown with diverging color scale, subsidence surface, hydrograph locations, head statistics, and observation upload/comparison (CSV, TSV, SMP formats)
• Diagnostics: Convergence iteration charts, mass balance error timeseries, filterable message table
• Budgets: Plotly charts of water budget time series with location/column selection
• Z-Budgets: Zone budget visualization organized by spatial zones

Additional API endpoints:

• Data Export: CSV (heads, budgets, hydrographs), GeoJSON mesh, GeoPackage (multi-layer), and publication-quality matplotlib plots (PNG/SVG)
• Model Comparison: Load a second model and compare meshes/stratigraphy via the ModelDiffer engine
• Head Statistics: Time-aggregated min/max/mean/std per node across all timesteps

The frontend is pre-built into src/pyiwfm/visualization/webapi/static/. To rebuild from source:

cd frontend && npm install && npm run build

Calibration Tools

pyiwfm provides calibration tools that mirror and extend IWFM's Fortran utilities (IWFM2OBS, CalcTypHyd):

# Explicit SMP mode: interpolate simulated heads to observation times
pyiwfm iwfm2obs --obs observed.smp --sim simulated.smp --output interp.smp

# Model discovery mode: auto-discover .out files from simulation main file
pyiwfm iwfm2obs --model C2VSimFG.in --obs-gw gw_obs.smp --output-gw gw_out.smp

# With multi-layer T-weighted averaging and PEST instruction file
pyiwfm iwfm2obs --model C2VSimFG.in \
    --obs-gw gw_obs.smp --output-gw gw_out.smp \
    --well-spec obs_wells.txt \
    --multilayer-out GW_MultiLayer.out \
    --multilayer-ins GWHMultiLayer.ins

# CalcTypHyd with Fortran config file (produces PEST .out/.ins files)
pyiwfm calctyphyd --config CalcTypeHyd.in

# Deduplicate per-layer SMP output (strip %N suffixes)
pyiwfm iwfm2obs --deduplicate-smp GW_OUT.smp --output GW_OUT_dedup.smp

Or use the Python API:

from pyiwfm.calibration import iwfm2obs_from_model, discover_hydrograph_files

# Auto-discover .out files and interpolate to observation times
results = iwfm2obs_from_model(
    simulation_main_file="C2VSimFG.in",
    obs_smp_paths={"gw": "GW_Obs.smp"},
    output_paths={"gw": "GW_OUT.smp"},
)

PEST++ Calibration CLI

Set up, run, and analyze PEST++ calibration from the command line:

# Generate PEST++ files from an IWFM model
pyiwfm pest setup --model-dir /path/to/model --case-name c2vsim_cal

# Run PEST++ (requires pestpp-glm or pestpp-ies on PATH)
pyiwfm pest run --pst-file ./pest_setup/c2vsim_cal.pst --num-workers 8

# Analyze results
pyiwfm pest analyze --pst-file ./pest_setup/c2vsim_cal.pst --format json

Features

• Core Data Structures: Node, Element, Face, AppGrid, Stratigraphy, TimeSeries
• BaseComponent ABC: Common interface (validate(), n_items) for all model components (groundwater, streams, lakes, root zone, small watersheds, unsaturated zone)
• Complete Model I/O: Full roundtrip support for reading and writing IWFM models
  • ASCII files (nodes, elements, stratigraphy, time series)
  • Binary files (Fortran unformatted)
  • HDF5 files (efficient large model storage)
  • HEC-DSS 7 files (bundled C library)
• Budget Post-Processing: Parse IWFM budget/zbudget control files and export to Excel
  • One sheet per location/zone with title lines, bold headers, and auto-fitted columns
  • Unit conversion factors (FACTLTOU, FACTAROU, FACTVLOU) applied per column type
  • CLI commands: pyiwfm budget and pyiwfm zbudget
• Component Writers: Write complete IWFM input files with shared BaseComponentWriterConfig
  • Groundwater: wells, pumping, boundary conditions, aquifer parameters
  • Streams: nodes, reaches, diversions, bypasses, rating curves
  • Lakes: definitions, elements, rating curves, outflows
  • Root Zone: crop types, soil parameters, land use
  • Small Watersheds: watershed units, root zone/aquifer parameters
  • Unsaturated Zone: element layers, soil moisture
  • Simulation: main control file
• PreProcessor Integration: Load/save complete models from IWFM file structure
• Model Factory: Extracted construction helpers (reach building, coordinate resolution, parametric grids, binary loading) into pyiwfm.core.model_factory
• Mesh Generation: Triangle and Gmsh wrappers
• Calibration Tools: IWFM2OBS time interpolation with automatic model file discovery and Fortran-verified timestamp alignment, multi-layer T-weighted observation well processing (GW_MultiLayer.out + PEST .ins), fuzzy c-means well clustering, typical hydrograph computation (CalcTypHyd) with Fortran-format config file parsing and PEST output, and publication-quality calibration figures
• Visualization: GIS export (GeoPackage download), VTK 3D export, matplotlib plot generation (PNG/SVG), interactive web viewer with budget charts, head maps, hydrograph comparison, drawdown animation, and head statistics
• Model Comparison: Diff and comparison metrics, including web viewer comparison endpoint
• Drawdown Analysis: Compute drawdown relative to reference timesteps with per-node, per-element, max-map, and robust range calculations
• Stream Depletion: Compare baseline and pumping model runs to quantify stream flow depletion per reach
• Budget Checks: Mass balance sanity checks to detect timestep-level inflow/outflow/storage imbalance
• Mesh Quality: Element-level quality metrics (aspect ratio, skewness, min/max angle) with aggregate statistics
• Simulation Diagnostics: Parse SimulationMessages.out for convergence tracking, mass balance errors, and spatial hotspot analysis
• PEST++ CLI: pyiwfm pest setup/run/analyze for end-to-end calibration from the command line

Versioning

The package version is derived automatically from git tags using hatch-vcs. There is no hardcoded version string to maintain — pyiwfm.__version__, pyproject.toml metadata, and the Sphinx docs all read from the same source.

Scenario	Version produced
On a tagged commit (v1.0.4)	1.0.4
3 commits after a tag	1.0.5.dev3+gabcdef1
Uncommitted changes (dirty)	1.0.5.dev3+gabcdef1.d20260228

Release workflow:

git tag -a v1.0.4 -m "Release v1.0.4"
git push && git push origin v1.0.4
# CI builds and publishes automatically

Building locally:

pip install -e ".[dev]"          # editable install — version from git
python -m build                  # sdist + wheel — version baked into _version.py
python -c "import pyiwfm; print(pyiwfm.__version__)"

The auto-generated src/pyiwfm/_version.py is gitignored and should not be committed.

License

GPL-2.0 - Same as IWFM