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src/m/r/mrjob-0.4.2/mrjob/examples/mr_travelling_salesman/mr_travelling_salesman.py   mrjob(Download)
 
from mrjob.job import MRJob
from scipy.misc.common import factorial
import sys
import numpy
        m = numpy.matrix(sales_trip['graph'])
        num_nodes = m.shape[0]
        num_tours = factorial(num_nodes - 1)
 
        #Here we break down the full range of possible tours into smaller

src/p/h/phoebe-2.0a1/phoebe/atmospheres/pulsations.py   phoebe(Download)
from scipy.special import lpmv,legendre
from scipy.special import sph_harm as sph_harm0
from scipy.misc.common import factorial
from scipy.integrate import dblquad,quad
from scipy.spatial import Delaunay
    P_l_m = (-1)**m_ * (1.-x**2)**(m_/2.) * deriv_legpoly
    if m<0:
        P_l_m = (-1)**m_ * float(factorial(l-m_)/factorial(l+m_)) * P_l_m
    return P_l_m
 
 
    """
    Nlm = sqrt((2*l+1)/(4*pi) * factorial(l-m)/factorial(l+m))
    return Nlm
 

src/s/c/scikits.scattpy-HEAD/scikits/scattpy/core.py   scikits.scattpy(Download)
# Core functions
from numpy import *
from scipy.special import sph_jn, sph_jnyn, lpmn
from scipy.misc.common import factorial
from math import atan, acos, asin
def norm(m, l):
    return sqrt((2 * l + 1) / 2. * factorial(l - m) / factorial(l + m))
 
 
def get_Pmn_normed(m, n, x):

src/s/c/scikits.scattpy-HEAD/scikits/scattpy/laboratory.py   scikits.scattpy(Download)
import core
from numpy import *
from scipy.special import sph_jn, sph_jnyn, lpmn
from scipy.misc.common import factorial
#from IPython.Debugger import Tracer; debug_here = Tracer()
                c_inc[:n - m + 1] = -1j ** (l - 1) / sina\
                                    * 2 * (2 * l + 1)\
                                    * factorial(l - m) / factorial(l + m)\
                * Pna
        return c_inc
        delta13 = 0
    l = arange(m, n + 1)
    ff = factorial(l + m) / factorial(l - m) * 2 / (2 * l + 1.)
    ff = transpose(repeat([ff], len(l), 0))
    l = transpose(repeat([l], len(l), 0))

src/g/a/gala-0.1.1/gala/features/convex_hull.py   gala(Download)
import numpy as np
from scipy import ndimage as nd
from scipy.misc.common import factorial
from numpy.linalg import det
try:
            pts = pts - np.repeat(pts[:,0][:, np.newaxis], pts.shape[1], axis=1)
            pts = pts[:,1:]
            vol += abs(1/float(factorial(pts.shape[0])) * det(pts))
            return vol,tri 
 

src/g/a/gala-HEAD/gala/features/convex_hull.py   gala(Download)
import numpy as np
from scipy import ndimage as nd
from scipy.misc.common import factorial
from numpy.linalg import det
try:
            pts = pts - np.repeat(pts[:,0][:, np.newaxis], pts.shape[1], axis=1)
            pts = pts[:,1:]
            vol += abs(1/float(factorial(pts.shape[0])) * det(pts))
            return vol,tri 
 

src/r/a/ray-HEAD/ray/features/convex_hull.py   ray(Download)
import numpy as np
from scipy import ndimage as nd
from scipy.misc.common import factorial
from numpy.linalg import det
try:
            pts = pts - np.repeat(pts[:,0][:, np.newaxis], pts.shape[1], axis=1)
            pts = pts[:,1:]
            vol += abs(1/float(factorial(pts.shape[0])) * det(pts))
            return vol,tri 
 

src/p/y/PyMF-0.1.9/lib/pymf/sivm_search.py   PyMF(Download)
import numpy as np
from scipy import inf
from scipy.misc.common import factorial
 
from dist import *