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# scipy.misc.common.factorial

All Samples(30)  |  Call(22)  |  Derive(0)  |  Import(8)

```
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
```

```from scipy.special import lpmv,legendre
from scipy.special import sph_harm as sph_harm0
from scipy.misc.common import factorial
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

```

```# 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):
```

```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))
```

```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

```

```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

```

```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

```

```import numpy as np