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NumPy Cookbook

You're reading from   NumPy Cookbook If you're a Python developer with basic NumPy skills, the 70+ recipes in this brilliant cookbook will boost your skills in no time. Learn to raise productivity levels and code faster and cleaner with the open source mathematical library.

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Product type Paperback
Published in Oct 2012
Publisher Packt
ISBN-13 9781849518925
Length 226 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (17) Chapters Close

NumPy Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Winding Along with IPython 2. Advanced Indexing and Array Concepts FREE CHAPTER 3. Get to Grips with Commonly Used Functions 4. Connecting NumPy with the Rest of the World 5. Audio and Image Processing 6. Special Arrays and Universal Functions 7. Profiling and Debugging 8. Quality Assurance 9. Speed Up Code with Cython 10. Fun with Scikits Index

Sending a NumPy array to JPype


In this recipe, we will start a JVM and send a NumPy array to it. We will print the received array using standard Java calls. Obviously, you will need to have Java installed.

How to do it...

First, we need to start the JVM from JPype.

  1. Start the JVM.

    JPype is conveniently able to find the default JVM path:

    jpype.startJVM(jpype.getDefaultJVMPath())
  2. Print hello world.

    Just because of tradition, let's print hello world:

    jpype.java.lang.System.out.println("hello world")
  3. Send a NumPy array.

    Create a NumPy array, convert it to a Python list, and pass it to JPype. Now, it's trivial to print the array elements:

    values = numpy.arange(7)
    java_array = jpype.JArray(jpype.JDouble, 1)(values.tolist())
    
    for item in java_array:
        jpype.java.lang.System.out.println(item)
  4. Shutdown the JVM.

    After we are done, we will shutdown the JVM:

    jpype.shutdownJVM()

    Only one JVM can run at a time in JPype. If we forget to shutdown the JVM, it could lead to unexpected errors. The program output is as...

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