Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to scatter plot notes pdf hours course with increasing level of expertise, from beginner to expert.
Getting started with Python for science 1. How does Python compare to other solutions? Other scripting languages: Scilab, Octave, R, IDL, etc. The workflow: interactive environments and text editors 1. Reusing code: scripts and modules 1. Figures, Subplots, Axes and Ticks 1.
Other Types of Plots: examples and exercises 1. Scipy : high-level scientific computing 1. Summary exercises on scientific computing 1. Full code examples for the scipy chapter 1.
Image manipulation and processing using Numpy and Scipy 2. Mathematical optimization: finding minima of functions 2. A review of the different optimizers 2. Examples for the mathematical optimization chapter 2. Practical guide to optimization with scipy 2.
Hypothesis testing: comparing two groups 3. Linear models, multiple factors, and analysis of variance 3. More visualization: seaborn for statistical exploration 3. Sympy : Symbolic Mathematics in Python 3.
Slicing and dicing data: sources, modules and filters 3. Basic principles of machine learning with scikit-learn 3. Supervised Learning: Classification of Handwritten Digits 3. Supervised Learning: Regression of Housing Data 3. Unsupervised Learning: Dimensionality Reduction and Visualization 3. The eigenfaces example: chaining PCA and SVMs 3. Parameter selection, Validation, and Testing 3.
Plot Digitizer is a Java program used to digitize scanned plots of functional data. Often data is found presented in reports and references as functional X-Y type scatter or line plots. In order to use this data, it must somehow be digitized. To make the digitizing task easier, this program includes many handy features. You can insert points between two already digitized points by right clicking and choosing “Insert” from the pop-up menu. You can delete points by right-clicking on the points and choosing “Delete”. You can move points by clicking and dragging them.
A special feature of this program is the ability to semi-automatically digitize lines off a plot. The user simply indicates where the line is on the plot with a thick paint brush and the program attempts to automatically sort out the data from grid lines, etc. This auto-digitizing feature depends on an image vectorization program called “autotrace”. Will the auto-digitizing feature digitize any plot? After using the program a while you begin to learn what it can and can’t auto-digitize.
To install this program, simply drag the Plot Digitizer. In MacOS X this is usually the “Applications” directory, but you are free to put it anywhere you want. The application file should work properly on MacOS X 10. 7 right out of the box.