lamm-mit Minerals Visualization
Generate publication-quality charts for critical minerals data using the cmm_data visualizations module. Supports world production bar charts, production time series, import reliance charts, and multi-commodity comparisons.
Usage
World production chart:
python3 {baseDir}/scripts/generate_chart.py --chart-type production --commodity lithi
Time series:
python3 {baseDir}/scripts/generate_chart.py --chart-type timeseries --commodity cobal
Import reliance:
python3 {baseDir}/scripts/generate_chart.py --chart-type import-reliance --commodity raree
Custom output:
python3 {baseDir}/scripts/generate_chart.py --chart-type production --commodity lithi --output lithium_prod.png --format png
Parameters
| Parameter | Description | Default |
|---|---|---|
--chart-type |
Chart type: production, timeseries, import-reliance | Required |
--commodity |
USGS commodity code (e.g., lithi, cobal, raree, graph, nicke) | Required |
--output |
Output file path | auto-generated |
--format |
Image format: png, svg | png |
--top-n |
Number of countries in production chart | 10 |
Chart Types
| Type | Description | Data Source |
|---|---|---|
production |
Horizontal bar chart of top producers | USGS world production |
timeseries |
Line chart of production over time | USGS salient statistics |
import-reliance |
NIR bar chart with threshold line | USGS salient statistics |
USGS Commodity Codes
| Code | Commodity | Code | Commodity |
|---|---|---|---|
lithi |
Lithium | cobal |
Cobalt |
raree |
Rare Earths | graph |
Graphite |
nicke |
Nickel | manga |
Manganese |
galli |
Gallium | germa |
Germanium |
coppe |
Copper | tungs |
Tungsten |
Examples
# Lithium top producers
python3 {baseDir}/scripts/generate_chart.py --chart-type production --commodity lithi --top-n 10
# Cobalt production time series
python3 {baseDir}/scripts/generate_chart.py --chart-type timeseries --commodity cobal --output cobalt_trend.png
# Rare earth import reliance (SVG)
python3 {baseDir}/scripts/generate_chart.py --chart-type import-reliance --commodity raree --format svg
Notes
- Requires matplotlib (install with: pip install matplotlib)
- USGS data files must be present in cmm-data data directory
- Output defaults to current directory with auto-generated filename
- SVG format recommended for publications and reports
- For raw data access, use the
minerals-dataskill