Did I find the right examples for you? yes no

All Samples(36)  |  Call(34)  |  Derive(0)  |  Import(2)

src/p/y/pymaclab-0.95.9/pymaclab/dsge/solvers/modsolvers.py   pymaclab(Download)
            if locals().has_key('ranvec'):
                if count in indx:
                    ranvec = MAT.vstack((ranvec,N.sqrt(varia)*MAT.matrix(N.random.standard_normal(tlena))))
                else:
                    ranvec = MAT.vstack((ranvec,MAT.zeros((1,tlena))))
            else:
                if count in indx:
                    ranvec = np.sqrt(varia)*MAT.matrix(N.random.standard_normal(tlena))
            woy = np.zeros((osim_y.shape[1],3))
            lam = 1600
            yyf = MAT.matrix(hpfilter(data=yy,lam=1600))
            osim_y[i1,:] = yyf[0]
        # Now filter the state variables!
        for i1 in xrange(osim_x.shape[0]):
            xx = osim_x[i1,:].__array__().T
            wox = np.zeros((osim_x.shape[1],3))
            lam = 1600
            xxf = MAT.matrix(hpfilter(data=xx,lam=1600))
                woo = np.zeros((osim_o.shape[1],3))
                lam = 1600
                oof = MAT.matrix(hpfilter(data=oo,lam=1600))
                osim_o[i1,:] = oof[0]
 

src/p/y/pymaclab-0.95.9/pymaclab/filters/hpfilter.py   pymaclab(Download)
def hpfilter(data=None,lam=1600):
    if type(data) == type(np.matlib.matrix([1,2,3])) and len(data.shape) == 2:
        if data.shape[0] < data.shape[1]: data = data.__array__().T
        else: data = data.__array__()
    elif type(data) != type(np.array([1,2,3])):

src/p/y/pymaclab-0.95.9/pymaclab/filters/cffilter.py   pymaclab(Download)
def cffilter(data=None,low=6,high=32,drift=True):
    if type(data) == type(np.matlib.matrix([1,2,3])) and len(data.shape) == 2:
        if data.shape[0] < data.shape[1]: data = data.__array__().T
        else: data = data.__array__()
    elif type(data) != type(np.array([1,2,3])):

src/p/y/pymaclab-0.95.9/pymaclab/filters/bkfilter.py   pymaclab(Download)
def bkfilter(data=None,up=6,dn=32,kkl=12):
    if type(data) == type(np.matlib.matrix([1,2,3])) and len(data.shape) == 2:
        if data.shape[0] < data.shape[1]: data = data.__array__().T
        else: data = data.__array__()
    elif type(data) != type(np.array([1,2,3])):

src/t/o/topographica-0.9.8/topo/coordmapper/__init__.py   topographica(Download)
 
from numpy import exp,log,sqrt,sin,cos,ones,dot
from numpy.matlib import matrix
 
import param
    the offset (xoff,yoff).
    """
    return matrix([[1, 0, xoff],
                   [0, 1, yoff],
                   [0, 0,   1 ]])
    around the origin by t radians.
    """
    return matrix([[cos(t), -sin(t), 0],
                   [sin(t),  cos(t), 0],
                   [  0   ,    0   , 1]])
    the y-axis.
    """
    return matrix([[sx,  0, 0],
                   [ 0, sy, 0],
                   [ 0,  0, 1]])

src/t/o/topographica-HEAD/topo/coordmapper/__init__.py   topographica(Download)
 
from numpy import exp,log,sqrt,sin,cos,ones,dot
from numpy.matlib import matrix
 
import param
    the offset (xoff,yoff).
    """
    return matrix([[1, 0, xoff],
                   [0, 1, yoff],
                   [0, 0,   1 ]])
    around the origin by t radians.
    """
    return matrix([[cos(t), -sin(t), 0],
                   [sin(t),  cos(t), 0],
                   [  0   ,    0   , 1]])
    the y-axis.
    """
    return matrix([[sx,  0, 0],
                   [ 0, sy, 0],
                   [ 0,  0, 1]])