NumPy Cookbook Python 2nd Edition by Ivan Idris 1784390941 9781784390945

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ISBN 10: 1784390941 

ISBN 13: 9781784390945

Author: Ivan Idris

If you are a Python developer with some experience of working on scientific, mathematical, and statistical applications and want to gain an expert understanding of NumPy programming in relation to science, math, and finance using practical recipes, then this book is for you.

Table of contents:

1. Winding Along with IPython
Introduction
Installing IPython
How to do it…
How it works…
See also
Using IPython as a shell
How to do it…
How it works…
See also
Reading manual pages
How to do it…
How it works…
Installing matplotlib
How to do it…
See also
Running an IPython notebook
Getting ready
How to do it…
How it works…
See also
Exporting an IPython notebook
How to do it…
Importing a web notebook
How to do it…
Configuring a notebook server
How to do it…
How it works…
See also
Exploring the SymPy profile
Getting ready
How to do it…
See also

2. Advanced Indexing and Array Concepts
Introduction
Installing SciPy
Getting ready
How to do it…
How it works…
See also
Installing PIL
How to do it…
See also
Resizing images
Getting ready
How to do it…
How it works…
See also
Creating views and copies
Getting ready
How to do it…
How it works…
See also
Flipping Lena
How to do it…
See also
Fancy indexing
How to do it…
How it works…
See also
Indexing with a list of locations
How to do it…
See also
Indexing with Booleans
How to do it…
How it works…
See also
Stride tricks for Sudoku
How to do it…
How it works…
See also
Broadcasting arrays
How to do it…
See also

3. Getting to Grips with Commonly Used Functions
Introduction
Summing Fibonacci numbers
How to do it…
How it works…
See also
Finding prime factors
How to do it…
How it works…
Finding palindromic numbers
How to do it…
How it works…
There’s more…
The steady state vector
How to do it…
How it works…
See also
Discovering a power law
How to do it…
How it works…
See also
Trading periodically on dips
Getting ready
How to do it…
How it works…
See also
Simulating trading at random
Getting ready
How to do it…
How it works…
See also
Sieving integers with the Sieve of Eratosthenes
How to do it…

4. Connecting NumPy with the Rest of the World
Introduction
Using the buffer protocol
Getting ready
How to do it…
How it works…
See also
Using the array interface
Getting ready
How to do it…
How it works…
See also
Exchanging data with MATLAB and Octave
Getting ready
How to do it…
See also
Installing RPy2
How to do it…
See also
Interfacing with R
Getting ready
How to do it…
See also
Installing JPype
How to do it…
Sending a NumPy array to JPype
How to do it…
How it works…
See also
Installing Google App Engine
How to do it…
Deploying the NumPy code on the Google Cloud
How to do it…
How it works…
Running the NumPy code in a PythonAnywhere web console
How to do it…
How it works…

5. Audio and Image Processing
Introduction
Loading images into memory maps
Getting ready
How to do it…
How it works…
See also
Combining images
Getting ready
How to do it…
How it works…
See also
Blurring images
How to do it…
How it works…
See also
Repeating audio fragments
How to do it…
How it works…
See also
Generating sounds
How to do it…
How it works…
See also
Designing an audio filter
How to do it…
How it works…
Edge detection with the Sobel filter
How to do it…
How it works…

6. Special Arrays and Universal Functions
Introduction
Creating a universal function
How to do it…
How it works…
See also
Finding Pythagorean triples
How to do it…
How it works…
See also
Performing string operations with chararray
How to do it…
How it works…
See also
Creating a masked array
How to do it…
How it works…
See also
Ignoring negative and extreme values
How to do it…
How it works…
See also
Creating a scores table with a recarray function
How to do it…
How it works…
See also

7. Profiling and Debugging
Introduction
Profiling with timeit
How to do it…
How it works…
See also
Profiling with IPython
How to do it…
How it works…
See also
Installing line_profiler
Getting ready
How to do it…
See also
Profiling code with line_profiler
How to do it…
How it works…
See also
Profiling code with the cProfile extension
How to do it…
See also
Debugging with IPython
How to do it…
How it works…
See also
Debugging with PuDB
How to do it…
See also

8. Quality Assurance
Introduction
Installing Pyflakes
Getting ready
How to do it…
See also
Performing static analysis with Pyflakes
How to do it…
How it works…
Analyzing code with Pylint
Getting ready
How to do it…
How it works…
See also
Performing static analysis with Pychecker
How to do it…
Testing code with docstrings
How to do it…
How it works…
See also
Writing unit tests
How to do it…
How it works…
Testing code with mocks
How to do it…
How it works…
See also
Testing the BDD way
How to do it…
How it works…
See also

9. Speeding Up Code with Cython
Introduction
Installing Cython
How to do it…
See also
Building a Hello World program
How to do it…
How it works…
See also
Using Cython with NumPy
How to do it…
How it works…
See also
Calling C functions
How to do it…
How it works…
See also
Profiling the Cython code
How to do it…
How it works…
See also
Approximating factorials with Cython
How to do it…
How it works…
See also

10. Fun with Scikits
Introduction
Installing scikit-learn
Getting ready
How to do it…
Loading an example dataset
How to do it…
Clustering Dow Jones stocks with scikits-learn
How to do it…
How it works…
See also
Installing statsmodels
How to do it…
Performing a normality test with statsmodels
How to do it…
How it works…
Installing scikit-image
How to do it…
Detecting corners
Getting ready
How to do it…
How it works…
See also
Detecting edges
How to do it…
See also
Installing pandas
How to do it…
See also
Estimating correlation of stock returns with pandas
How to do it…
How it works…
See also
Loading data as pandas objects from statsmodels
Getting ready
How to do it…
How it works…
See also
Resampling time series data
How to do it…
How it works…
See also

11. Latest and Greatest NumPy
Introduction
Fancy indexing in place for ufuncs with the at() method
How to do it…
See also
Partial sorting via selection for fast median with the partition() function
How to do it…
How it works…
See also
Skipping NaNs with the nanmean(), nanvar(), and nanstd() functions
How to do it…
How it works…
See also
Creating value initialized arrays with the full() and full_like() functions
How to do it…
How it works…
Random sampling with numpy.random.choice()
How to do it…
How it works…
See also
Using the datetime64 type and related API
How to do it…
How it works…
See also

12. Exploratory and Predictive Data Analysis with NumPy
Introduction
Exploring atmospheric pressure
Getting ready
How to do it…
See also
Exploring the day-to-day pressure range
How to do it…
How it works…
See also
Studying annual atmospheric pressure averages
How to do it…
How it works…
See also
Analyzing maximum visibility
How to do it…
How it works…
See also
Predicting pressure with an autoregressive model
How to do it…
How it works…
See also
Predicting pressure with a moving average model
Getting started
How to do it…
How it works…
See also
Studying intrayear average pressure
How to do it…
How it works…
See also
Studying extreme values of atmospheric pressure
How to do it…
How it works…
See also

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Tags: Ivan Idris, NumPy, Cookbook, Python