ScientiMate is a coastal and ocean data analysis library. ScientiMate is a collection of functions and tools (in MATLAB and Python) developed for metocean, oceanography, coastal engineering, and earth science data analysis. The examples of ScientiMate's applications are (but not limited to) ocean wave analysis, time series data analysis, signal processing, wind engineering, etc.

To use MATLAB version of ScientiMate library:

• Install MATLAB or GNU Octave

  • MATLAB: https://www.mathworks.com
  • GNU Octave: https://octave.org

• Download ScientiMate:

  • Version 1.1 (GitHub): https://github.com/akarimp/ScientiMate/releases/download/2.0/scientimate.zip

• Unzip ScientiMate in any location you choose such as "C:\"

• Open MATLAB or GNU Octave

• Add ScientiMate folder to MATLAB or GNU Octave path

• Open MATLAB or GNU Octave
• Change a current folder (working directory) to a folder that contains ScientiMate files, for example "C:\scientimate", in MATLAB or GNU Octave.
• Run a file named add_scientimate_to_path.m in MATLAB or GNU Octave to add ScientiMate folder to MATLAB or GNU Octave path.

MATLAB users may need to install additional MATLAB Toolboxes such as Signal Processing Toolbox for some functions.

GNU Octave users may need to install/load additional packages such as GNU Octave Signal package for some functions. To find the list of the GNU Octave's pre-installed packages, run the following command in the Command Window:

>> pkg list

For example, GNU Octave comes with Signal package but it needs to loaded every time GNU Octave starts. The Signal package can be loaded inside GNU Octave by running the following command in the Command Window (This should be done every time GNU Octave is opened):

>> pkg load signal

If GNU Octave Signal Package is not already installed, it should be first installed from https://packages.octave.org, and then get loaded by running the following commands in the Command Window:

>> pkg install "https://downloads.sourceforge.net/project/octave/Octave%20Forge%20Packages/Individual%20Package%20Releases/signal-1.4.5.tar.gz"
>> pkg load signal

x(:,1)=linspace(1,10,10);
y(:,1)=1+rand(10,1);
y(:,2)=2+rand(10,1);
plot2d(x,y,'line_confid','blue_red','large')

To use Python version of ScientiMate library:

• Install Python
• Install ScientiMate

1) Install Python

First, you need to install Python programming language.

• Method 1:

  Install Python from https://www.python.org and then use the pip command to install required packages

• Method 2 (Recommended):

  Install Anaconda Python distribution from https://www.anaconda.com and then use the conda command to install required packages

2) Install ScientiMate

After Python is installed, you need to install ScientiMate library.

If you installed Python, then you need to install ScientiMate via pip (https://pypi.org/project/scientimate). To do that, open the Command Prompt (or Terminal) and run:

pip install scientimate

If you installed Anaconda Python distribution, then you need to install ScientiMate via Anaconda cloud (https://anaconda.org/akarimp/scientimate). To do that, open the Anaconda Prompt and run:

conda install -c akarimp scientimate

Following packages are required:

• NumPy (https://numpy.org)
• SciPy (https://www.scipy.org)
• pandas (https://pandas.pydata.org)
• Matplotlib (https://matplotlib.org)

import scientimate as sm
import numpy as np

print(sm.__version__)

x=np.linspace(1,10,10)
y=np.zeros((10,2))
y[:,0]=1+np.random.rand(10)
y[:,1]=2+np.random.rand(10)
sm.plot2d(x,y,'line_confid','blue_red','large')

ScientiMate code can be run on Microsoft Windows, Mac, and Linux. However, make sure any given path is compatible with a running operating system. In particular, "\" is used in Windows path, while "/" is used in Mac or Linux path. For example, if a path is "C:\" on Windows machine, it would be "C:/" on Mac or Linux.

This library can be run by using MATLAB (https://www.mathworks.com), GNU Octave (https://octave.org), or Python (https://www.python.org).

Cite ScientiMate as:

Karimpour, A. (2023). ScientiMate, Coastal and Ocean Data Analysis Library (Version 2.0) [Computer software]. https://github.com/akarimp/ScientiMate

Ocean Wave Data Analysis Introduction to Time Series Analysis, Signal Processing, and Wave Prediction. Order at Amazon: https://www.amazon.com/dp/0692109978 Read Online: https://github.com/akarimp/Ocean-Wave-Data-Analysis	Fundamentals of Data Science with MATLAB Introduction to Scientific Computing, Data Analysis, and Data Visualization. Order at Amazon: https://www.amazon.com/dp/1735241016 Read Online: https://github.com/akarimp/Fundamentals-of-Data-Science-with-MATLAB	Principles of Data Science with Python Introduction to Scientific Computing, Data Analysis, and Data Visualization. Order at Amazon: https://www.amazon.com/dp/1735241008 Read Online: https://github.com/akarimp/Principles-of-Data-Science-with-Python

OCEANLYZ Ocean Wave Analyzing Toolbox Download: https://github.com/akarimp/Oceanlyz	ScientiMate Coastal and Ocean Data Analysis Library Download: https://github.com/akarimp/ScientiMate	AsanPlot Data cleaning and plotting software Download: https://github.com/akarimp/AsanPlot

ScientiMate: Coastal and Ocean Data Analysis Library

Copyright (c) 2023 Arash Karimpour

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