def subplot_xy(ax, x, y, **kwargs):
if is_np_array_type(y.__class__):
if y.ndim > 1:
for i in range(y.shape[0]):
subplot_xy(ax, x, y[i], **kwargs)
else:
ax.plot(x, y, **kwargs)
elif isinstance(y, list):
for i in range(y.__len__()):
subplot_xy(ax, x, y[i], **kwargs)
else:
ax.plot(x, y, **kwargs)
def subplot_xy(ax, x, y, **kwargs):
if is_np_array_type(y.__class__):
if y.ndim > 1:
for i in range(y.shape[0]):
subplot_xy(ax, x, y[i], **kwargs)
else:
ax.plot(x, y, **kwargs)
elif isinstance(y, list):
for i in range(y.__len__()):
subplot_xy(ax, x, y[i], **kwargs)
else:
ax.plot(x, y, **kwargs)
def W(p=None, w=None, k=None, fc=100e3, c=1480, N=500):
if p==None:
error('\'p\' are missing. Aborting.')
return
if k!=None:
k_abs = k
elif p!=None and fc!=None and c!=None:
k_abs = 2*pi*fc/c
else:
error('Either \'k\', or \'c\' and \'fc\' must be supplied. Aborting.')
return
theta = np.linspace(-0.5,0.5,N)*pi
k = Coordinate(r=k_abs, theta=theta, phi=None)
def compute_W(ax,ay,az, w):
Wx = dot( ax, w )
Wy = dot( ay, w )
Wz = dot( az, w )
Wxyz = vstack((Wx,Wy,Wz)).T
return Wxyz
# pT = p.T.copy()
ax = exp(1j*outer( k[:,0], p[:,0]))
ay = exp(1j*outer( k[:,1], p[:,1]))
az = exp(1j*outer( k[:,2], p[:,2]))
if type(w) == list:
W = []
for wi in w:
W.append(compute_W(ax,ay,az, wi))
elif is_np_array_type(w.__class__):
if w.ndim == 1:
W = []
W.append( compute_W(ax,ay,az,w) )
elif w.ndim == 2:
W1 = compute_W(ax,ay,az,w[0])
W = np.zeros((w.shape[0],W1.shape[0],W1.shape[1]),dtype=W1.dtype)
W[0] = W1
for i in range(1,w.shape[0]):
W[i] = compute_W(ax,ay,az, w[i])
elif w.ndim == 3:
W1 = compute_W(ax,ay,az,w[0,0]) # Not exactly efficient, but shouldn't be noticeable
W = np.zeros((w.shape[0],w.shape[1],W1.shape[0],W1.shape[1]),dtype=W1.dtype)
for i in range(0,w.shape[0]):
for j in range(0,w.shape[1]):
W[i,j] = compute_W(ax,ay,az, w[i,j])
else:
print 'EE: Not implemented.'
else:
W = []
W.append( compute_W(ax,ay,az,w) )
return W
