CSV to NetCDF

This example demonstrates how to convert comma-separated values (CSV) data to the GS NetCDF format. Specifically this example includes:

1. Raw AEM data, from the Resolve system

2. Inverted resistivity models

Dataset Reference: Burton, B.L., Minsley, B.J., Bloss, B.R., and Kress, W.H., 2021, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2018 - February 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9XBBBUU.

import matplotlib.pyplot as plt
from os.path import join
from gspy import Survey

Convert the resolve csv data to NetCDF

Initialize the Survey

# Path to example files
data_path = '..//..//supplemental//region//MAP'

# Survey metadata file
metadata = join(data_path, "data//Resolve_survey_md.json")

# Establish the Survey
survey = Survey(metadata)

Import raw AEM data from CSV-format. Define input data file and associated metadata file

d_data = join(data_path, 'data//Resolve.csv')
d_supp = join(data_path, 'data//Resolve_data_md.json')

# Add the raw AEM data as a tabular dataset
survey.add_tabular(type='csv', data_filename=d_data, metadata_file=d_supp)

Import inverted AEM models from CSV-format. Define input model file and associated metadata file

m_data = join(data_path, 'model//Resolve_model.csv')
m_supp = join(data_path, 'model//Resolve_model_md.json')

# Add the inverted AEM models as a tabular dataset
survey.add_tabular(type='csv', data_filename=m_data, metadata_file=m_supp)

Save to NetCDF file

d_out = join(data_path, 'model//Resolve.nc')
survey.write_netcdf(d_out)

Reading back in the GS NetCDF file

new_survey = Survey.open_netcdf(d_out)

# Check the Survey information
print(new_survey.xarray)

<xarray.Dataset>
Dimensions:                 ()
Coordinates:
    spatial_ref             float64 ...
Data variables:
    survey_information      float64 ...
    survey_units            float64 ...
    system_information      float64 ...
    flightline_information  float64 ...
    survey_equipment        float64 ...
Attributes:
    title:        Example Resolve Airborne Electromagnetic (AEM) Raw Data
    institution:  USGS Geology, Geophysics, & Geochemistry Science Center
    source:       Comma-separated text file exported from Geosoft
    history:      <date and time when the data were produced and/or modified>
    references:   <data release reference>
    comment:      <additional details or ancillary information>
    content:      <summary list of file contents, e.g. raw data (/survey/tabu...
    conventions:  CF-1.8, GS-0.0.1
    created_by:   gspy==0.0.1

Plotting

# Make a scatter plot of a specific data variable, using GSPy's plotter
# plt.figure()
# new_survey.tabular[0].gs_tabular.scatter(hue='DTM', vmin=30, vmax=50)


# Subsetting by line number, and plotting by distance along that line
# new_survey.tabular[0].gs_tabular.subset('line', 10010)
tmp = new_survey.tabular[0].where(new_survey.tabular[0]['line']==10010)
plt.figure()
# plt.subplot(121)
# tmp.gs_tabular.plot(hue='DTM')
# plt.subplot(122)
# tmp.gs_tabular.scatter(x='x', y='DTM')
tmp.gs_tabular.scatter(y='DTM')

#IF YOU SPECIFY HUE ITS A 2D COLOUR Plot
#OTHERWISE ITS JUST A PLOT (LINE POINTS ETC)

# Make a scatter plot of a specific model variable, using GSPy's plotter
# plt.figure()
# new_survey.tabular[1].gs_tabular.scatter(hue='DOI_STANDARD')
plt.show()