本文整理汇总了Python中pylab.zeros函数的典型用法代码示例。如果您正苦于以下问题:Python zeros函数的具体用法?Python zeros怎么用?Python zeros使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了zeros函数的20个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的Python代码示例。
示例1: gadget_merge_ics
def gadget_merge_ics( outfile, filename1, filename2, offset1, offset2, voffset1=[0.,0.,0.], voffset2=[0.,0.,0.] ):
snap1 = gadget_readsnapname( filename1 )
snap2 = gadget_readsnapname( filename2 )
for i in range(3):
snap1.pos[:,i] += offset1[i]
snap2.pos[:,i] += offset2[i]
for i in range(3):
snap1.vel[:,i] += voffset1[i]
snap2.vel[:,i] += voffset2[i]
npart = snap1.npart + snap2.npart
data = {}
data[ 'count' ] = npart
data[ 'pos' ] = pylab.zeros( [npart, 3] )
data[ 'pos' ][ 0:snap1.npart, : ] = snap1.pos
data[ 'pos' ][ snap1.npart:npart, : ] = snap2.pos
data[ 'vel' ] = pylab.zeros( [npart, 3] )
data[ 'vel' ][ 0:snap1.npart, : ] = snap1.vel
data[ 'vel' ][ snap1.npart:npart, : ] = snap2.vel
data[ 'mass' ] = pylab.zeros( npart )
data[ 'mass' ][ 0:snap1.npart ] = snap1.data["mass"]
data[ 'mass' ][ snap1.npart:npart ] = snap2.data["mass"]
data[ 'u' ] = pylab.zeros( npart )
data[ 'u' ][ 0:snap1.npart ] = snap1.data["u"]
data[ 'u' ][ snap1.npart:npart ] = snap2.data["u"]
nxnuc = pylab.shape( snap1.data["xnuc"] )[1]
data[ 'xnuc' ] = pylab.zeros( [npart, nxnuc] )
data[ 'xnuc' ][ 0:snap1.npart, : ] = snap1.data["xnuc"]
data[ 'xnuc' ][ snap1.npart:npart, : ] = snap2.data["xnuc"]
gadget_write_ics( outfile, data, transpose=False )
return
开发者ID:boywert,项目名称:SussexBigRun2013,代码行数:34,代码来源:gadget.py
示例2: findcurve
def findcurve(psi1,psi2,n=3,nn_fit=4,nn_out=100):
'''
Function to find the elastica curve for start and end orientations
psi1 and psi2. It finds the best curve across all directions from start
and end, i.e. the direction independent elastica curve.
Inputs
------------
psi1,psi2: start and end orientations.
n: degree of estimation polynomial.
nn: number of points on the curve.
- nn_fit: for fittin purposes
- nn_out: for the output
Outputs
------------
Returns a tuple (s,psi).
s: points on the curve.
psi: curvature of the curve as a function of s.
E: curvature energy of the curve
'''
#
# define the starting conditions
a0 = pl.zeros(n+1)
# Set a high energy:
E_best = 10000
# and predfine output curve
s = pl.linspace(0,1,nn_out) # points on the curve
psi_out = pl.zeros(nn_out) # curvature at points in curve
# across all the start and end directions find the curve with the lowest energy
for dpsi1 in (-pl.pi,0,pl.pi):
for dpsi2 in (-pl.pi,0,pl.pi):
# For the starting variables,
# the first two polygon variables can be estimated from the Sharon paper derivation
# For different starting variables the solution can be hard to find
a0[-2] = 4*( pl.arcsin(- (pl.sin(psi1+dpsi1)+ pl.sin(psi2+dpsi2))/4) -(psi1+dpsi1+psi2+dpsi2)/2 )
a0[-1] = 2*a0[-2]/pl.cos( (psi1+dpsi1+psi2+dpsi2)/2 + a0[-2]/4 )
# find the best variables to minimize the elastica energy
fit = fsolve(errors,a0,args=(psi1+dpsi1,psi2+dpsi2,nn_fit))
# find the curve and its derivative for the fitted variables
a = fit[:-1]
psi = Psi(a,s,psi1+dpsi1,psi2+dpsi2)
dpsi = dPsi(a,s,psi1+dpsi1,psi2+dpsi2)
# find the energy of this curve
E = sum(dpsi**2)*s[1]
# check against the lowest energy
if E_best > E:
E_best = E
psi_out[:] = pl.copy(psi)
return (s,psi_out,E_best)
开发者ID:swkeemink,项目名称:elastica,代码行数:60,代码来源:elastica.py
示例3: Global_Stiffness
def Global_Stiffness(self):
'''
Generates Global Stiffness Matrix for the plane structure
'''
elem = self.element;
B = py.zeros((6,6))
for i in range (0,py.size(elem,0)):
#for each element find the stifness matrix
K = py.zeros((self.n_nodes*2,self.n_nodes*2))
el = elem[i]
#nodes formatted for input
[node1, node2, node3] = el;
node1x = 2*(node1-1);node2x = 2*(node2-1);node3x = 2*(node3-1);
node1y = 2*(node1-1)+1;node2y = 2*(node2-1)+1;node3y = 2*(node3-1)+1;
#Area, Strain Matrix and E Matrix multiplied to get element stiffness
[J,B] = self.B(el)
local_k =0.5*abs(J)*py.dot(py.transpose(B),py.dot(self.E_matrix,B))
if self.debug:
print 'K for elem', el, '\n', local_k
#Element K-Matrix converted into Global K-Matrix format
K[py.ix_([node1x,node1y,node2x,node2y,node3x,node3y],[node1x,node1y,node2x,node2y,node3x,node3y])] = K[py.ix_([node1x,node1y,node2x,node2y,node3x,node3y],[node1x,node1y,node2x,node2y,node3x,node3y])]+local_k
#Adding contibution into Global Stiffness
self.k_global = self.k_global + K
if self.debug:
print 'Global Stiffness','\n', self.k_global
开发者ID:gkumar08,项目名称:finite_element_projects,代码行数:30,代码来源:CST.py
示例4: sample
def sample(self, model, evidence):
g = evidence['g']
h = evidence['h']
C = evidence['C']
z = evidence['z']
shot_id = evidence['shot_id']
noise_proportion = evidence['noise_proportion']
observation_var_g = evidence['observation_var_g']
observation_var_h = evidence['observation_var_h']
canopy_cover = model.known_params['canopy_cover']
z_min = model.known_params['z_min']
z_max = model.known_params['z_max']
prior_p = model.hyper_params['T']['p']
N = len(z)
T = zeros(N)
noise_rv = stats.uniform(z_min, z_max - z_min)
min_index = min(z.index)
for i in shot_id.index:
l = zeros(3)
index = i-min_index
shot_index = shot_id[i]-min(shot_id)
l[0] = noise_proportion*noise_rv.pdf(z[i])
g_norm = stats.norm(g[shot_index], sqrt(observation_var_g))
C_i = canopy_cover[C[shot_index]]
l[1] = (1-noise_proportion)*(1-C_i)*g_norm.pdf(z[i])
h_norm = stats.norm(h[shot_index] + g[shot_index], sqrt(observation_var_h))
if z[i] > g[shot_index]+3:
l[2] = (1-noise_proportion)*(C_i)*h_norm.pdf(z[i])
p = l/sum(l)
T[index] = Categorical(p).rvs()
return T
开发者ID:bwallin,项目名称:thesis-code,代码行数:35,代码来源:model_simulation_eta.py
示例5: sample
def sample(self, T, g, g0=None):
if g0==None:
g0 = g
v, h = self.v, self.h
VH, HH, b_init = self
V = zeros((T, v))
H = zeros((T, h))
B = zeros((T, h))
VH_t = 1*VH
VH_t[2] = VH[2] + b_init
V[[0]], H_t_stoch = rbm.sample(VH_t, g0, 1, self.vis_gauss)
H[[0]] = sigmoid(VH_t * V[[0]])
if self.vis_gauss:
V[[0]] = VH_t.T() * H_t_stoch
else:
V[[0]] = sigmoid(VH_t.T() * H_t_stoch)
for t in range(1, T):
B[[t]] = HH*H[[t-1]]
VH_t[2] = VH[2] + B[t]
V[[t]], H_t_stoch = rbm.sample(VH_t, g, 1, self.vis_gauss)
H[[t]] = sigmoid(VH_t * V[[t]])
if self.vis_gauss:
V[[t]] = VH_t.T() * H_t_stoch
else:
V[[t]] = sigmoid(VH_t.T() * H_t_stoch)
return V
开发者ID:sidsig,项目名称:NIPS-2014,代码行数:32,代码来源:rnn_trbm.py
示例6: openRomb
def openRomb(integrand, a, b,eps=1e-6,jmax=14,k=5):
"""
Returns the integral on the _open_interval_ (a,b).
Integration is performed by Romberg's method of order 2k,
where, e.g., k=2 is Simpson's rule.
"""
jmaxp=jmax+1
s = 0.*M.zeros(jmaxp)
h = 0.*M.zeros(jmaxp+1)
ss = 0.
dss = 0.
h[0]=1.0
for j in range(0,jmax):
s[j]=tripleInt(integrand,a,b,s[j],j)
if j >= k:
ss,dss = interpPoly(h[j-k:j],s[j-k:j],k,0.0)
if M.fabs(dss) <= eps*M.fabs(ss):
return ss
s[j+1]=s[j]
h[j+1]=h[j]/9.
print 'Non-convergence in openRomb'
return ss
开发者ID:astrofanlee,项目名称:project_TL,代码行数:25,代码来源:utils.py
示例7: mk_image
def mk_image(galaxy):
base = './../../images_v5/GS_2.5as_matched/gs_all_'
i_img = pyf.getdata(base+str(galaxy)+'_I.fits')
j_img = pyf.getdata(base+str(galaxy)+'_J.fits')
h_img = pyf.getdata(base+str(galaxy)+'_H.fits')
x = pyl.hstack(i_img)
i_lim = scoreatpercentile(x,99)
x = pyl.hstack(j_img)
j_lim = scoreatpercentile(x,99)
x = pyl.hstack(h_img)
h_lim = scoreatpercentile(x,99)
img = pyl.zeros((h_img.shape[0], h_img.shape[1], 3), dtype=float)
img[:,:,0] = img_scale.asinh(h_img, scale_max=h_lim, non_linear=0.5)
img[:,:,1] = img_scale.asinh(j_img, scale_max=j_lim, non_linear=0.5)
img[:,:,2] = img_scale.asinh(i_img, scale_max=i_lim, non_linear=0.5)
img = pyl.zeros((h_img.shape[0], h_img.shape[1], 3), dtype=float)
img[:,:,0] = img_scale.asinh(h_img, scale_min=-0.1*h_lim, scale_max=h_lim,
non_linear=0.5)
img[:,:,1] = img_scale.asinh(j_img, scale_min=-0.1*j_lim, scale_max=j_lim,
non_linear=0.5)
img[:,:,2] = img_scale.asinh(i_img, scale_min=-0.1*i_lim, scale_max=i_lim,
non_linear=0.5)
return img
开发者ID:boada,项目名称:ICD,代码行数:28,代码来源:outlier_montage.py
示例8: _get_angles
def _get_angles(steps,track_length):
angles = pl.zeros(track_length-2)
polar = pl.zeros(pl.shape(steps))
for i in range(track_length-1):
polar[i,0] = pl.norm(steps[i,:])
polar[i,1] = pl.arctan(steps[i,0]/steps[i,1])
if pl.isnan( polar[i,1]):
polar[i,1] = 0
if (steps[i,0] >= 0):
if (steps[i,1] >= 0):
pass
elif (steps[i,1] < 0):
polar[i,1] += 2.*pl.pi
elif (steps[i,0] < 0):
if (steps[i,1] >= 0):
polar[i,1] += pl.pi
elif (steps[i,1] < 0):
polar[i,1] += pl.pi
for i in range(track_length-2):
angles[i] = polar[i+1,1] - polar[i,1]
return angles
开发者ID:r-medina,项目名称:TIAM-,代码行数:25,代码来源:FeatureSpace.py
示例9: spikefano
def spikefano(timestamps, start_time=0, zero_times=0, end_time=None, window_len=.1, subwindow_len=None):
"""Given the time stamps compute the fano factor with a jumping window.
Inputs:
timestamps - the spike timestamps
window_len - length of window to look at ff (same units as timestamps). One window gets us one ff estimate
The fano factor is the LS fit of fano_windows (variance,mean) points
subwindow_len - length of one spike count computation window
Outputs:
t - time array
ff - fano factors
"""
window_edges, windows, subwindows = window_spike_train(timestamps, start_time, zero_times, end_time, window_len=window_len, subwindow_len=subwindow_len)
t = pylab.zeros(windows.shape[1])
ff = pylab.zeros(windows.shape[1])
for n in xrange(windows.shape[1]):
spk_count = pylab.zeros(subwindows.shape[1]*subwindows.shape[2])
for m in xrange(subwindows.shape[0]):#Epochs
for l in xrange(subwindows.shape[2]):#Subwindows
#FF computation
sbw0 = subwindows[m,n,l,0]
sbw1 = subwindows[m,n,l,1]
spk_count[m*subwindows.shape[2]+l] = sbw1 - sbw0
mean = spk_count.mean()
std = spk_count.std()
ff[n] = std**2/mean
t[n] = window_len * (n+.5)
return t, ff
开发者ID:kghose,项目名称:neurapy,代码行数:30,代码来源:spikes.py
示例10: SCpm
def SCpm(SC_0=SC_0, i=i, r=r, f=f, m_all_cause=m_all_cause, age_mesh=dm.get_param_age_mesh()):
SC = pl.zeros([2, len(age_mesh)])
p = pl.zeros(len(age_mesh))
m = pl.zeros(len(age_mesh))
SC[:, 0] = SC_0
p[0] = SC_0[1] / (SC_0[0] + SC_0[1])
m[0] = dismod3.utils.trim(
m_all_cause[age_mesh[0]] - f[age_mesh[0]] * p[0],
0.1 * m_all_cause[age_mesh[0]],
1 - dismod3.settings.NEARLY_ZERO,
) # trim m[0] to avoid numerical instability
for ii, a in enumerate(age_mesh[:-1]):
A = pl.array([[-i[a] - m[ii], r[a]], [i[a], -r[a] - m[ii] - f[a]]]) * (age_mesh[ii + 1] - age_mesh[ii])
SC[:, ii + 1] = pl.dot(scipy.linalg.expm(A), SC[:, ii])
p[ii + 1] = dismod3.utils.trim(
SC[1, ii + 1] / (SC[0, ii + 1] + SC[1, ii + 1]),
dismod3.settings.NEARLY_ZERO,
1 - dismod3.settings.NEARLY_ZERO,
)
m[ii + 1] = dismod3.utils.trim(
m_all_cause[age_mesh[ii + 1]] - f[age_mesh[ii + 1]] * p[ii + 1],
0.1 * m_all_cause[age_mesh[ii + 1]],
pl.inf,
)
SCpm = pl.zeros([4, len(age_mesh)])
SCpm[0:2, :] = SC
SCpm[2, :] = p
SCpm[3, :] = m
return SCpm
开发者ID:aflaxman,项目名称:gbd,代码行数:34,代码来源:generic_disease_model.py
示例11: grad
def grad(self,data,weightcost):
grad = zeros(0)
if type(data)!=type([]):
data = [data]
numcases = len(data)
numscoretypes = len(self.scorefuncs)
if not type(weightcost) == type([]):
weightcost = [weightcost] * numscoretypes
posgrad = [None]*numscoretypes
neggrad = [None]*numscoretypes
for k in range(numscoretypes):
if isscalar(weightcost[k]):
weightcost[k] = \
array([weightcost[k]]*len(self.scorefuncs[k].params))
posgrad[k] = zeros(self.scorefuncs[k].params.shape,dtype=float)
neggrad[k] = zeros(self.scorefuncs[k].params.shape,dtype=float)
for i in range(numcases):
poscliques = self.posdata(data[i])
negcliques = self.negdata(data[i])
for k in range(numscoretypes):
for posclique in poscliques[k]:
posgrad[k] += self.scorefuncs[k].grad(*posclique)
if self.normalizeacrosscliques:
posgrad[k] = posgrad[k]/double(len(poscliques[k]))
for weighting, negclique in negcliques[k]:
for w, neginst in zip(weighting,negclique):
neggrad[k] += w * self.scorefuncs[k].grad(*neginst)
if self.normalizeacrosscliques:
neggrad[k] = neggrad[k]/double(len(poscliques[k]))
for k in range(numscoretypes):
grad = concatenate((grad,(posgrad[k]-neggrad[k])/double(numcases)\
-weightcost[k]*self.scorefuncs[k].params))
return -grad
开发者ID:JohnPaton,项目名称:Master-Thesis,代码行数:33,代码来源:contrastive.py
示例12: jetWoGn
def jetWoGn(reverse=False):
"""
jetWoGn(reverse=False)
- returning a colormap similar to cm.jet, but without green.
if reverse=True, the map starts with red instead of blue.
"""
m=18 # magic number, which works fine
m0=pylab.floor(m*0.0)
m1=pylab.floor(m*0.2)
m2=pylab.floor(m*0.2)
m3=pylab.floor(m/2)-m2-m1
b_ = pylab.hstack( (0.4*pylab.arange(m1)/(m1-1.)+0.6, pylab.ones((m2+m3,)) ) )
g_ = pylab.hstack( (pylab.zeros((m1,)),pylab.arange(m2)/(m2-1.),pylab.ones((m3,))) )
r_ = pylab.hstack( (pylab.zeros((m1,)),pylab.zeros((m2,)),pylab.arange(m3)/(m3-1.)))
r = pylab.hstack((r_,pylab.flipud(b_)))
g = pylab.hstack((g_,pylab.flipud(g_)))
b = pylab.hstack((b_,pylab.flipud(r_)))
if reverse:
r = pylab.flipud(r)
g = pylab.flipud(g)
b = pylab.flipud(b)
ra = pylab.linspace(0.0,1.0,m)
cdict = {'red': zip(ra,r,r),
'green': zip(ra,g,g),
'blue': zip(ra,b,b)}
return LinearSegmentedColormap('new_RdBl',cdict,256)
开发者ID:garciaga,项目名称:pynmd,代码行数:32,代码来源:plot_settings.py
示例13: homog2D
def homog2D(xPrime, x):
"""
Compute the 3x3 homography matrix mapping a set of N 2D homogeneous
points (3xN) to another set (3xN)
"""
numPoints = xPrime.shape[1]
assert numPoints >= 4
A = None
for i in range(0, numPoints):
xiPrime = xPrime[:, i]
xi = x[:, i]
Ai_row0 = pl.concatenate((pl.zeros(3), -xiPrime[2] * xi, xiPrime[1] * xi))
Ai_row1 = pl.concatenate((xiPrime[2] * xi, pl.zeros(3), -xiPrime[0] * xi))
Ai = pl.row_stack((Ai_row0, Ai_row1))
if A is None:
A = Ai
else:
A = pl.vstack((A, Ai))
U, S, V = pl.svd(A)
V = V.T
h = V[:, -1]
H = pl.reshape(h, (3, 3))
return H
开发者ID:pjozog,项目名称:PylabUtils,代码行数:30,代码来源:dlt.py
示例14: homog3D
def homog3D(points2d, points3d):
"""
Compute a matrix relating homogeneous 3D points (4xN) to homogeneous
2D points (3xN)
Not sure why anyone would do this. Note that the returned transformation
*NOT* an isometry. But it's here... so deal with it.
"""
numPoints = points2d.shape[1]
assert numPoints >= 4
A = None
for i in range(0, numPoints):
xiPrime = points2d[:, i]
xi = points3d[:, i]
Ai_row0 = pl.concatenate((pl.zeros(4), -xiPrime[2] * xi, xiPrime[1] * xi))
Ai_row1 = pl.concatenate((xiPrime[2] * xi, pl.zeros(4), -xiPrime[0] * xi))
Ai = pl.row_stack((Ai_row0, Ai_row1))
if A is None:
A = Ai
else:
A = pl.vstack((A, Ai))
U, S, V = pl.svd(A)
V = V.T
h = V[:, -1]
P = pl.reshape(h, (3, 4))
return P
开发者ID:pjozog,项目名称:PylabUtils,代码行数:33,代码来源:dlt.py
示例15: checkmodelgrad
def checkmodelgrad(model,e,RETURNGRADS=False,*args):
from pylab import norm
"""Check the correctness of passed-in model in terms of cost-/gradient-
computation, using gradient approximations with perturbances of
size e.
"""
def updatemodelparams(model, newparams):
model.params *= 0.0
model.params += newparams.copy()
def cost(params,*args):
paramsold = model.params.copy()
updatemodelparams(model,params.copy().flatten())
result = model.cost(*args)
updatemodelparams(model,paramsold.copy())
return result
def grad(params,*args):
paramsold = model.params.copy()
updatemodelparams(model, params.copy().flatten())
result = model.grad(*args)
updatemodelparams(model, paramsold.copy())
return result
dy = model.grad(*args)
l = len(model.params)
dh = zeros(l,dtype=float)
for j in range(l):
dx = zeros(l,dtype=float)
dx[j] = e
y2 = cost(model.params+dx,*args)
y1 = cost(model.params-dx,*args)
dh[j] = (y2 - y1)/(2*e)
print "analytic: \n", dy
print "approximation: \n", dh
if RETURNGRADS: return dy,dh
else: return norm(dh-dy)/norm(dh+dy)
开发者ID:fangzheng354,项目名称:nnutils,代码行数:34,代码来源:util.py
示例16: correl_single_window
def correl_single_window(sbwA, sbwB):
"""sbwA and sbwB are obtained as subwindowsA[:,n,:,:], with n marching through all the windows.
Indexes - 0 -> epochs
1 -> subwindows
2 -> start/stop
"""
N0 = sbwA.shape[0]
N1 = sbwA.shape[1]
spk_countA = pylab.zeros((N0,N1))
spk_countB = pylab.zeros((N0,N1))
for n in xrange(N0): #Epochs
for m in xrange(N1): #subwindows
spk_countA[n,m] = sbwA[n,m,1] - sbwA[n,m,0]
spk_countB[n,m] = sbwB[n,m,1] - sbwB[n,m,0]
spk_countA = spk_countA.flatten() - spk_countA.mean()
spk_countB = spk_countB.flatten() - spk_countB.mean()
R = pylab.corrcoef(spk_countA, spk_countB)
if R.size:
r = R[0,1]
else:
r = 0
return r
开发者ID:kghose,项目名称:neurapy,代码行数:26,代码来源:spikes.py
示例17: getMatrix
def getMatrix(AllData):
# create matrices for all the data
numQs = len(AllData.keys())
subjects = 12 #len(AllData[1]['RT'])
correct = np.array(py.zeros([numQs, subjects]))
confA = np.array(py.zeros([numQs, subjects]))
confB = np.array(py.zeros([numQs, subjects]))
RTs = np.array(py.zeros([numQs, subjects]))
#print(AllData)
for i in xrange(subjects):
# rows
for j in xrange(1,17):
# columns
correct[j-1,i] = AllData[j]['correct'][i]
for i in xrange(subjects):
for j in xrange(1,17):
confA[j-1,i] = AllData[j]['confA'][i]
for i in xrange(subjects):
for j in xrange(1,17):
confB[j-1,i] = AllData[j]['confB'][i]
for i in xrange(subjects):
for j in xrange(1,17):
RTs[j-1,i] = AllData[j]['RT'][i]
print(py.shape(correct), py.shape(confA), py.shape(confB), py.shape(RTs))
return correct, confA, confB, RTs
开发者ID:acsutt0n,项目名称:WisdomOfCrowd,代码行数:27,代码来源:showConfData.py
示例18: sample
def sample(self, T, g, g0=None):
if g0==None:
g0 = g
v, h = self.v, self.h
VH, HH, b_init = self
V = zeros((T, v))
H = zeros((T, h))
B = zeros((T, h))
VH_t = 1*VH
VH_t[2] = VH[2] + b_init
V[[0]], H[[0]] = rbm.sample(VH_t, g0, 1, self.vis_gauss)
## mean-fieldize the output:
if self.vis_gauss:
V[[0]] = VH_t.T() * H[[0]]
else:
V[[0]] = sigmoid(VH_t.T() * H[[0]])
for t in range(1, T):
B[[t]] = HH*H[[t-1]]
VH_t[2] = VH[2] + B[t]
V[[t]], H[[t]] = rbm.sample(VH_t, g, 1, self.vis_gauss)
## mean-field-ize the output.
if self.vis_gauss:
V[[t]] = VH_t.T() * H[[t]]
else:
V[[t]] = sigmoid(VH_t.T() * H[[t]])
return V
开发者ID:sidsig,项目名称:NIPS-2014,代码行数:33,代码来源:trbm.py
示例19: Dirichlet_BC
def Dirichlet_BC(self):
'''
Apply grounding conditions for i-th DOF by making K[i,:]and K[:,i] zero and K[i,i] = 1.
Also i-th load is made zero.
'''
# Copy Global Stiffness, Global Load and number of nodes along each polar coordinate
K = self.k_global
l = self.load
n = self.N+1
if self.debug:
print '\n','\n','Dirichlet_BC', K, '\n','\n','\n load', l
#iteratively apply boundary conditions on all the grounded degrees of freedom
for i in range(0,n):
if self.debug:
print '\n every iteration' , 2*n*i+1, 2*n*(i+1)-2
#Y_displacement = 0 for nodes on X axis
K[2*n*i+1,:] = py.zeros((1,self.n_nodes*2))
K[:,2*n*i+1] = py.zeros((1,self.n_nodes*2))
K[2*n*i+1,2*n*i+1] = 1.0
l[2*n*i+1] = 0.0
#X_displacement = 0 for nodes on Y axis
K[2*n*(i+1)-2,:] = py.zeros((1,self.n_nodes*2))
K[:,2*n*(i+1)-2] = py.zeros((1,self.n_nodes*2))
K[2*n*(i+1)-2,2*n*(i+1)-2] = 1.0
l[2*n*(i+1)-2] = 0.0
self.k_global = K # copy new global
self.load = l # copy new load
if self.debug:
print '\n','Dirichlet_BC','\n', K, '\n','\n','\n load', l
开发者ID:gkumar08,项目名称:finite_element_projects,代码行数:33,代码来源:project.py
示例20: _stft
def _stft(self):
if not self._have_x:
print "Error: You need to load a sound file first: use self.load_audio('filename.wav')"
return False
fp = self._check_feature_params()
num_frames = len(self.x)
self.STFT = P.zeros((self.nfft/2+1, num_frames), dtype='complex')
self.win = P.ones(self.wfft) if self.window=='rect' else P.np.sqrt(P.hanning(self.wfft))
x = P.zeros(self.wfft)
buf_frames = 0
for k, nex in enumerate(self.x):
x = self._shift_insert(x, nex, self.nhop)
if self.nhop >= self.wfft - k*self.nhop : # align buffer on start of audio
self.STFT[:,k-buf_frames]=P.rfft(self.win*x, self.nfft).T
else:
buf_frames+=1
self.STFT = self.STFT / self.nfft
self._fftfrqs = P.arange(0,self.nfft/2+1) * self.sample_rate/float(self.nfft)
self._have_stft=True
if self.verbosity:
print "Extracted STFT: nfft=%d, hop=%d" %(self.nfft, self.nhop)
self.inverse=self._istftm
self.X = abs(self.STFT)
if not self.magnitude:
self.X = self.X**2
return True
开发者ID:BinRoot,项目名称:BregmanToolkit,代码行数:26,代码来源:features_base.py
注:本文中的pylab.zeros函数示例由纯净天空整理自Github/MSDocs等源码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。 |
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