Python library for Ground Penetrating Radar (GPR): IO, processing and visualization
Project description
Siina
Description
Python library for Ground Penetrating Radar (GPR) data processing: IO, filters and visualization.
Tested with Python 3.6.
Installation
siina
can be installed with pip
pip install siina
Latest Github version
Either clone the repo and install with setup.py
git clone https://github.com/ahartikainen/siina
cd siina
python setup.py install
or with a pip
python -m pip install git+https://github.com/ahartikainen/siina
Underlying datastructures
Header information is saved as a dictionary: obj.header
Measurement data is saved as a list of ndarrays: obj.data_list
Main channel can be accessed with .data
-method
Example usage
import siina
# create RadarFile object
meas = siina.Radar()
# read in the data
meas.read_file("./example_path/example_file.DZT")
# set the center frequency for GPR (in Hertz) if not done
if meas.header.get('frequency', None) is None:
meas.header['frequency'] = 1e9 # 1 GHz
# print dimensions for the data
print("points in samples={}, samples={}, channels={}".format(meas.nrows, meas.ncols, meas.nchan)
# strip markers (important step with .DZT files)
meas.read_markers()
# center each sample (for each trace do func(trace[500:])
meas.func_dc(start=500)
# apply lowpass filter with cutoff= 6 * frequency
# if cutoff is float -> cutoff = cutoff
# if cutoff is str -> cutoff = float(cutoff) * frequency
meas.func_filter(cutoff='6')
import matplotlib.pyplot as plt
# plot mean function for the first channel
# all channels are found under obj.data_list
plt.plot(meas.data.mean(1))
plt.show()
# plot radargram with plt.imshow
# be careful with the profile size (meas.ncols < 5000)
plt.imshow(meas.data, aspect='auto')
plt.show()
Development
pip install -r requirements-test.txt
black siina
pylint siina
pydocstyle --convention=numpy siina
Project details
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