TIme Series toolKIT
Project description
TiSKitPy
Routines for time series data processing
Uses the obspy Stream (data) and Inventory (metadata) classes
Main Classes
SpectralDensity: Calculate and manipulate spectral density functions.Decimator: Decimate time series and update metadata with the decimator's responseCleanRotator: rotate data to minimize noise on vertical channelDataCleaner: Transfer_Function-based data cleaningResponseFunctions: Frequency response functions for a given input channel.Compliance: Seafloor ComplianceSeafloorSynthetic: Generate synthetic seafloor data, including compliance signal
Functions
FIR_corr: transform zero-phase data to minimum phase. Based on Scherbaum, Of Poles and Zeros. Only works for LCHEAPO loggers, need to update to calculate/work for any zero-phase filter)readMSEED: read in MSEED data, including if the file is too big (> 2 GB) for obspy's read() functionrptransient: calculate and remove periodic transient (VERY manual!).
Based on Matlab code by E Wielandt, used in Deen et al., 2017 and Aminian et al., 2025PetersonNoiseModel: return the Peterson High and Low Noise Models (Peterson, 1993)plot_compliance_stack(): plot, from top to bottom, Z PSD, P PSD, Z-P coherence and Z-P frequency response function.
Installation
First, install obspy using the instructions on their webpage.
Then, in the pip/conda environment that contains obspy, type
pip install tiskitpy
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