Basic Class Structure and Xarray Methods

The three primary classes (Survey, Tabular, and Raster) all contain data and metadata within Xarray Datasets. This example demonstrates how to access the xarray object for each class, and methods for exploring the data and metadata.

This example uses ASEG-formatted raw AEM data from the Tempest system, and a 2-D GeoTiFF of magnetic data.

Dataset Reference: Minsley, B.J., James, S.R., Bedrosian, P.A., Pace, M.D., Hoogenboom, B.E., and Burton, B.L., 2021, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2019 - March 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9E44CTQ.

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

First Create the Survey & Data Objects

# Initialize the Survey
data_path = '..//..//supplemental//region//MAP'
metadata = join(data_path, "data//Tempest_survey_md.json")
survey = Survey(metadata)

# Add Tabular and Raster Datasets
t_data = join(data_path, 'data//Tempest.dat')
t_supp = join(data_path, 'data//Tempest_data_md.json')
survey.add_tabular(type='aseg', data_filename=t_data, metadata_file=t_supp)
r_supp = join(data_path, 'data//Tempest_raster_md.json')
survey.add_raster(metadata_file = r_supp)

Accessing the Xarray object

# Survey
# The Survey's metadata is accessed through the xarray property
print(survey.xarray)

# To look just at the attributes
print(survey.xarray.attrs)

# Or expand a specific variable
print(survey.xarray['survey_information'])

# Tabular & Raster
# Datasets are attached to the Survey as lists, however if only one Dataset of a given
# type is present then the xarray object is returned simply by the name of the group

# tabular
print(survey.tabular)

# raster
print(survey.raster)

# If more than one Dataset is present under the group, then the list begins indexing
# For example, let's add a second Tabular Dataset
m_data = join(data_path, 'model//Tempest_model.dat')
m_supp = join(data_path, 'model//Tempest_model_md.json')
survey.add_tabular(type='aseg', data_filename=m_data, metadata_file=m_supp)

# Now the first dataset is accessed at index 0
print(survey.tabular[0])

# and the second is located at index 1
print(survey.tabular[1])

Coordinates, Dimensions, and Attributes