How to analyze a huge data file with pandas (codes included)
We learn how to read huge csv file containing time series data by breaking it into chunks and then visualizing it with matplotlib
We learn how to read huge csv file containing time series data by breaking it into chunks and then visualizing it with matplotlib
This tutorial gives a brief description of scientific computing using Pandas by introducing Series, DataFrame, Pandas common operations, methods, conditional...
This tutorial gives a brief description of scientific computing using numpy by introducing arrays, methods, attributes, random numbers, indexing, broadcastin...
We learn how to make the three-dimensional map using both GMT and PyGMT
GMT or generic mapping tools have become synonymous with plotting maps in Earth, Ocean, and Planetary sciences. It can be used for processing data, generatin...
Codes for plotting advanced 2D plots using matplotlib library in Python. Includes simple 2D plot, error bars, bar graphs, histograms, multiple plots, etc
In this post, we will see how we can use Python to low-pass filter the 10 year long daily fluctuations of GPS time series. We need to use the “Scipy” package...
A simple tutorial on how to plot high resolution topographic map using GMT tools in Python
This post demonstrate how to use Python to set up clip topographic map based on coastlines.
Tutorial on how to use Git and GitHub for team collaboration on a project. Content includes installing, setting up, creating a repository, making commits, un...
In this tutorial post, I give a quick demo of how to install Python (using anaconda) and then getting started with writing simple scripts.
We will learn the basic concepts of wavelet tranform and multi-resolution analysis starting from the Fourier Transform, and Gabor Transform.
An introduction to the wavelet analysis for a real geophysical data set. I compared the analysis to the Fourier analysis. Codes included!
An introduction to the basics of genetic algorithm along with a simple numerical example and solution of an earthquake location problem
The common geophysical problems most often have multimodal objective function with many possible minima. In this post, we will look into the Monte Carlo meth...
Quickly plot record section of a stream using Obspy. I will introduce you how to make a stream from a set of SAC data, plot the record section and store it a...
Least-squares method is a popular approach in geophysical inversion to estimate the parameters of a postulated Earth model from given observations. This meth...
Most often data analyst consider correlation between two time-series as a causation effect. Two time-series are correlated that does not imply that one cause...
Seismic resolution and fidelity are the two important measures of the quality of the seismic record and the seismic images. Seismic resolution quantifies the...
Simple earthquake location problem and its solution using Geiger’s method
Factor Analysis is an exploratory data analysis method used to search influential underlying factors or latent variables from a set of observed variables
Python code to automatically plot the record section for the highest magnitude earthquake in the given time range
Introduction to the concepts of tomography with equations and codes. Introduction to the concepts of overdetermined, underdetermined and mix-determined probl...
A simple tutorial on how to plot high resolution topographic map using GMT tools in Python
This post demonstrate how to use Python to set up clip topographic map based on coastlines.
Librosa can efficiently compute the spectrogram for large time series data in seconds. We will use that to plot the spectrogram using matplotlib
How you can plot the shear-wave splitting measurements from splitting database using PyGMT.
In this post, we will see how can we retrive the available seismic waveforms information for a given network, station, channel and client in a given period o...
I concatenate the daily seismic traces for 15 days into one miniseed file for further analysis. Then I obtained the spectrogram of the 15 days seismic data. ...
Read the seismic traces from the miniseed files and compute the cross-correlation and spectrogram
We will learn the basics of Fourier analysis and implement it to remove noise from the synthetic and real signals
We will learn how to convert a mseed data file into mat format and then read and analyze it using MATLAB
In geophysics, it is important to understand and identify the complex and unknown relationships between two time-series. Cross-correlation is an established ...
Quickly plot record section of a stream using Obspy. I will introduce you how to make a stream from a set of SAC data, plot the record section and store it a...
In this post, I will read a ASCII file whose first few lines contains the header information and then the three-component data. I will read using the pandas ...
Seismic resolution and fidelity are the two important measures of the quality of the seismic record and the seismic images. Seismic resolution quantifies the...
Simple earthquake location problem and its solution using Geiger’s method
This post is aimed to resolve the issues regarding the conflicts of using obspy and basemap libraries together.
Obspy is an open-source Python framework developed for the processing of seismological data. In this post, I will introduce how to use Obspy along with some ...
A simple tutorial on how to plot high resolution topographic map using GMT tools in Python
Short demostration of how to plot the distance vs seismic waveforms and mark the P and S arrival times using the IASP91 earth model. Codes are included.
Short demonstration of the ppsd class defined in Obspy using 3 days of data for station PB-B075
Python code to automatically plot the record section for the highest magnitude earthquake in the given time range
We will inspect the L-BFGS optimization method using one example and compare its performance with the gradient descent method
While analyzing time series data, we often come across data that is non-uniformly sampled, i.e., they have non-equidistant time-steps. Infact, most of the re...
We will see compare the convolution functions in Python (Numpy) with the conv function in MATLAB. If you have tried them both then you would know that its no...
We will learn the basics of the maximum likelihood method, and then apply it on a regression problem. We will also compare it with the least-squares estimati...
The boundary value problems require information at the present time and a future time. We will see how we can use shooting method to solve problems where we ...
Runge-Kutta methods are most popular method to solve ordinary differential equations (ODEs) with a better approximation than the Euler method. We compare the...
The simplest algorithm to solve a system of differential equations is the Euler method. We understand the Euler method by looking into a simple heat transfer...
The Newton–Raphson method (commonly known as Newton’s method) is developed for finding roots of a given function or polynomial iteratively. We show two examp...
Empirical Orthogonal Functions analysis decomposes the continuous space-time field into a set of orthogonal spatial patterns along with a set of associated u...
We will learn the basics of Fourier analysis and implement it to remove noise from the synthetic and real signals
An introduction to the basics of genetic algorithm along with a simple numerical example and solution of an earthquake location problem
The common geophysical problems most often have multimodal objective function with many possible minima. In this post, we will look into the Monte Carlo meth...
Least-squares method is a popular approach in geophysical inversion to estimate the parameters of a postulated Earth model from given observations. This meth...
Seismic resolution and fidelity are the two important measures of the quality of the seismic record and the seismic images. Seismic resolution quantifies the...
Factor Analysis is an exploratory data analysis method used to search influential underlying factors or latent variables from a set of observed variables
We test for the correlation coefficients or the covariance between two sets of random numbers selected from normal distribution using the Monte Carlo simulat...
Using Randomization to test the disprove the null hypothesis