numpy.arange

All Samples(6995) | Call(6445) | Derive(0) | Import(550)

arange([start,] stop[, step,], dtype=None)

Return evenly spaced values within a given interval.

Values are generated within the half-open interval ``[start, stop)``
(in other words, the interval including `start` but excluding `stop`).
For integer arguments the function is equivalent to the Python built-in
`range <http://docs.python.org/lib/built-in-funcs.html>`_ function,
but returns a ndarray rather than a list.

Parameters
----------
start : number, optional
    Start of interval.  The interval includes this value.  The default
    start value is 0.
stop : number
    End of interval.  The interval does not include this value.
step : number, optional
    Spacing between values.  For any output `out`, this is the distance
    between two adjacent values, ``out[i+1] - out[i]``.  The default
    step size is 1.  If `step` is specified, `start` must also be given.
dtype : dtype
    The type of the output array.  If `dtype` is not given, infer the data
    type from the other input arguments.

Returns
-------
out : ndarray
    Array of evenly spaced values.

    For floating point arguments, the length of the result is
    ``ceil((stop - start)/step)``.  Because of floating point overflow,
    this rule may result in the last element of `out` being greater
    than `stop`.

See Also
--------
linspace : Evenly spaced numbers with careful handling of endpoints.
ogrid: Arrays of evenly spaced numbers in N-dimensions
mgrid: Grid-shaped arrays of evenly spaced numbers in N-dimensions

Examples
--------
>>> np.arange(3)
array([0, 1, 2])
>>> np.arange(3.0)
array([ 0.,  1.,  2.])
>>> np.arange(3,7)
array([3, 4, 5, 6])
>>> np.arange(3,7,2)
array([3, 5])

src/p/y/pydy-HEAD/examples/rollingdisc/plot_rollingdisc.py pydy(Download)

#!/usr/bin/env python
import rollingdisc_lib as rd
from scipy.integrate import odeint
from numpy import array, arange, zeros, roots, sin, cos, tan, pi, complex
import matplotlib.pyplot as plt
 
# Dimensions of a quarter

def plot_eval():
    #### Eigenvalue plot #####
    u2 = arange(-30, 30.01, 0.01, dtype=complex)
    n = len(u1)
    eval = zeros((n,3), dtype=complex)
    for i, u in enumerate(u1):
        eval[i] = rd.evals(u, (g, r))

ti = 0.0
ts = 0.001
tf = 1.0
t = arange(ti, tf+ts, ts)
n = len(t)
# Integrate the differential equations
x = odeint(rd.eoms, xi, t, args=(params,))

src/o/b/obspy-HEAD/misc/examples/generate_seismogram.py obspy(Download)

    nw=6./f/dt
    nw=2*np.floor(nw/2)+1
    nc=np.floor(nw/2)
    i=np.arange(1,nw,dtype='float64')
    alpha=(nc-i+1)*f*dt*np.pi
    beta=alpha**2
    return (1.0-beta*2.0)*np.exp(-beta)

plt.plot(wavelet)
plt.title("Ricker Wavelet")
plt.subplot(312)
plt.stem(np.arange(N),greenfct,markerfmt='.',basefmt='b-')
plt.title("Greens Function")
plt.ylim(-1.5,1.5)
plt.subplot(313)

src/m/a/matplotlib-HEAD/matplotlib/examples/pylab_examples/mri_with_eeg.py matplotlib(Download)

    print 'loading eeg', eegfile
    data = np.fromstring(file(eegfile, 'rb').read(), float)
    data.shape = numSamples, numRows
    t = 10.0 * np.arange(numSamples, dtype=float)/numSamples
    ticklocs = []
    ax = subplot(212)
    xlim(0,10)
    xticks(np.arange(10))

src/m/a/matplotlib-HEAD/examples/pylab_examples/mri_with_eeg.py matplotlib(Download)

    print 'loading eeg', eegfile
    data = np.fromstring(file(eegfile, 'rb').read(), float)
    data.shape = numSamples, numRows
    t = 10.0 * np.arange(numSamples, dtype=float)/numSamples
    ticklocs = []
    ax = subplot(212)
    xlim(0,10)
    xticks(np.arange(10))

src/m/a/Matplotlib--JJ-s-dev-HEAD/examples/pylab_examples/mri_with_eeg.py Matplotlib--JJ-s-dev(Download)

    print 'loading eeg', eegfile
    data = np.fromstring(file(eegfile, 'rb').read(), float)
    data.shape = numSamples, numRows
    t = 10.0 * np.arange(numSamples, dtype=float)/numSamples
    ticklocs = []
    ax = subplot(212)
    xlim(0,10)
    xticks(np.arange(10))

src/m/a/matplotlib-HEAD/py4science/examples/numpy_wrap/swig/testSeries.py matplotlib(Download)

    def testIntNegate(self):
        "Test the intNegate function"
        myArray = N.arange(5,dtype='i')
        Series.intNegate(myArray)
        N.testing.assert_array_equal(myArray, N.array([0,-1,-2,-3,-4]))
 
    #######################################################

    def testDoubleNegate(self):
        "Test the doubleNegate function"
        myArray = N.arange(5) * 1.0
        Series.doubleNegate(myArray)
        N.testing.assert_array_equal(myArray, N.array([0.,-1.,-2.,-3.,-4.]))
 
    #########################################################

src/m/a/matplotlib-HEAD/py4science/examples/iterators_example.py matplotlib(Download)

}
""" % (dt, dt, dt)
 
    b = np.arange(4, dtype=a.dtype)
    print '\n         A                  B     '
    print a, b
    # this reshaping is redundant, it would be the default broadcast

src/m/a/matplotlib-HEAD/py4science/examples/logistic/exercise01.py matplotlib(Download)

logmap = Logistic(0.9)
x = logmap.trajectory(x0, 100)
y = logmap.trajectory(y0, 100)
ind = np.arange(len(x), dtype=float)
 
# x-y \sim epsilon exp(lambda * t)
# log(|x-y|) = log(epsilon) + lambda*t (b=log(epsilon) and m=lambda)

src/m/a/matplotlib-HEAD/matplotlib/examples/mplot3d/mixed_subplots_demo.py matplotlib(Download)

################
# First subplot
################
t1 = np.arange(0.0, 5.0, 0.1)
t2 = np.arange(0.0, 5.0, 0.02)
t3 = np.arange(0.0, 2.0, 0.01)

# Second subplot
#################
ax = fig.add_subplot(2, 1, 2, projection='3d')
X = np.arange(-5, 5, 0.25)
xlen = len(X)
Y = np.arange(-5, 5, 0.25)
ylen = len(Y)

src/m/a/matplotlib-HEAD/examples/mplot3d/mixed_subplots_demo.py matplotlib(Download)

################
# First subplot
################
t1 = np.arange(0.0, 5.0, 0.1)
t2 = np.arange(0.0, 5.0, 0.02)
t3 = np.arange(0.0, 2.0, 0.01)

# Second subplot
#################
ax = fig.add_subplot(2, 1, 2, projection='3d')
X = np.arange(-5, 5, 0.25)
xlen = len(X)
Y = np.arange(-5, 5, 0.25)
ylen = len(Y)

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