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Some things to fix in a future version:
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- trim a bit of time
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- add more about ipython and my own python work, reduce that of others
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- add a final python pros/cons, esp.
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It will make things more balanced.
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NumPy
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NumPy
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Efficient numerics in Python
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Fernando\InsetSpace ~
Pérez
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<Fernando.Perez@berkeley.edu>
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John Hunter
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<jdh2358@gmail.com>
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Neuroscience, UC Berkeley
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UC Berkeley/Tradelink
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Joint Sciences Division, Claremont, CA
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Oct 25, 2008
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NCAR, 10/25/08
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Python is a general programming language
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Basic numbers: ints, floats and complex.
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Lists:
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flexible containers.
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math and cmath modules:
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basic functionality (sqrt, ext, sin, cos, etc)
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Is it good enough for scientific computing?
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Efficient numerical processing?
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Compiler-specific numbers needed: ints (32, 64-bit), floats, etc.
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Homogeneous arrays of such elements.
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Easy arithmetic on entire arrays that is efficient.
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Comprehensive math library to operate on arrays.
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Common linear algebra support.
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Needed for:
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Mathematics
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Image processing
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Data analysis
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...
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A tiny bit of history
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1990s-2004: Numeric
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Started by Jim Hugunin, MIT grad student.
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Developed by many: national labs, academia, industry.
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Fast and light C code.
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Difficult to maintain and extend.
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2004: Numarray
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Perry Greenfield and team (Hubble Space Telescope)
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Clean codebase, new ideas.
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Many new features and documentation.
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Some performace issues lingered
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2005-future: NumPy: unification effort
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Led by Travis Oliphant, with Perry's full support.
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Best of Numeric and Numarray, into a new codebase
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The whole community rallied behind the effort.
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Today: only NumPy for any new code!
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NumPy: key ideas
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A flexible, efficient, multidimensional array object.
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Homogeneous elements
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Supports all native types (ints, floats, etc).
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Convenient syntax for high-level operations.
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Math library that operates on arrays.
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Basic scientific functionality:
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Linear algebra
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FFTs
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Random number generation
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NumPy: flexible arrays
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Array is a container of objects
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Concept of
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Image credit: T.
Oliphant, Enthought Inc.
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NumPy: indexing
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Image credit: E.
Jones, Enthought Inc.
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NumPy: fancy indexing
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NumPy: broadcasting
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SciPy: numerical algorithms galore
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linalg
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