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NumPy
=====

Provides
  1. An array object of arbitrary homogeneous items
  2. Fast mathematical operations over arrays
  3. Linear Algebra, Fourier Transforms, Random Number Generation

How to use the documentation
----------------------------(more...)

src/h/a/HaeffnerLabLattice-HEAD/scripts/dataAnalysis/General_plots_for_presentation_etc/ion_fitting/ion_fitting_sample.py   HaeffnerLabLattice(Download)
import numpy as np
from ion_state_detector import ion_state_detector
 
#load the full image and truncate it to to test image procesing of a partial image
# image = np.load('single.npy')

src/n/i/nipy-0.3.0/nipy/algorithms/statistics/models/tests/exampledata.py   nipy(Download)
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
 
import os
import numpy as np

src/a/l/algopy-HEAD/documentation/sphinx/examples/hessian_of_potential_function.py   algopy(Download)
#Loading the required packages
import scipy as sp
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from scipy import linalg, optimize, constants
 
import numpy
import algopy
import time

src/m/a/matplotlib-1.3.1/doc/users/plotting/examples/demo_gridspec06.py   matplotlib(Download)
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import numpy as np
 
try:

src/s/t/statsmodels-0.5.0/statsmodels/tsa/vector_ar/tests/example_svar.py   statsmodels(Download)
import numpy as np
import statsmodels.api as sm
from statsmodels.tsa.api import VAR, SVAR
import matplotlib.pyplot as plt
import statsmodels.tsa.vector_ar.util as util

src/s/t/statsmodels-0.5.0/statsmodels/sandbox/tsa/examples/try_ld_nitime.py   statsmodels(Download)
'''Levinson Durbin recursion adjusted from nitime
 
'''
 
import numpy as np

src/s/t/statsmodels-0.5.0/statsmodels/sandbox/tsa/examples/ex_mle_garch.py   statsmodels(Download)
 
 
import numpy as np
from numpy.testing import assert_almost_equal
 

src/s/t/statsmodels-0.5.0/statsmodels/sandbox/tsa/examples/ex_mle_arma.py   statsmodels(Download)
"""
 
import numpy as np
from numpy.testing import assert_almost_equal
 

src/s/t/statsmodels-0.5.0/statsmodels/sandbox/tsa/examples/example_var.py   statsmodels(Download)
"""
Look at some macro plots, then do some VARs and IRFs.
"""
 
import numpy as np

src/s/t/statsmodels-0.5.0/statsmodels/sandbox/examples/thirdparty/try_interchange.py   statsmodels(Download)
"""
 
import numpy as np
import scikits.timeseries as ts
 

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