def sticks(date,u,v,tnorm=0.1,figurewidth=8,pickind=1,color='blue'):
"""
sticks - create velocity stick plot
sticks(date, u, v, tnorm=0.1, color='blue' \
figurewidth=8, pickind=1)
date - list/array of datetime elements
u - list/array of velocity in eastern direction
v - list/array of velocity in northern direction
tnorm - length of a u=max(u,v) as part of the time axis
color - color of sticks
figurewidth - width of the figure in inch
pickind - plot every "pickind"-vector
"""
onedt=(date[-1]-date[0])
onedt=timedelta(tnorm*onedt.days,tnorm*onedt.seconds)
daynorm=onedt.days+onedt.seconds/86400.0
u=np.asarray(u)
v=np.asarray(v)
norm=np.maximum(np.absolute(u).max(),np.absolute(v).max())
t=[]
f=[]
mask=[]
fac=pickind
for i in range(int(len(date)/fac)):
t.append(plt.date2num(date[i*fac]))
f.append(0.0)
mask.append(False)
t.append(plt.date2num(date[i*fac] \
+ timedelta(u[i*fac]/norm*onedt.days,u[i*fac]/norm*onedt.seconds)))
f.append(v[i*fac]/norm*daynorm)
mask.append(False)
t.append(plt.date2num(date[i*fac]))
f.append(0.0)
mask.append(True)
t=np.asarray(t)
f=np.asarray(f)
mask=np.asarray(mask)
f=np.ma.masked_array(f,mask=mask)
plt.figure(figsize=(figurewidth,tnorm*figurewidth))
plt.plot_date(t,f,'-',color=color)
ax=plt.gca()
ax.set_aspect('equal')
ax.set_xlim(t[0],t[-1])
ax.set_ylim(-1.0*daynorm,1.0*daynorm)
ax.set_frame_on(False)
ax.yaxis.set_visible(False)
def sticks(date, u, v, tnorm=0.1, figurewidth=8, pickind=1, color='blue'):
"""
sticks - create velocity stick plot
sticks(date, u, v, tnorm=0.1, color='blue' \
figurewidth=8, pickind=1)
date - list/array of datetime elements
u - list/array of velocity in eastern direction
v - list/array of velocity in northern direction
tnorm - length of a u=max(u,v) as part of the time axis
color - color of sticks
figurewidth - width of the figure in inch
pickind - plot every "pickind"-vector
"""
onedt = (date[-1] - date[0])
onedt = timedelta(tnorm * onedt.days, tnorm * onedt.seconds)
daynorm = onedt.days + onedt.seconds / 86400.0
u = np.asarray(u)
v = np.asarray(v)
norm = np.maximum(np.absolute(u).max(), np.absolute(v).max())
t = []
f = []
mask = []
fac = pickind
for i in range(int(len(date) / fac)):
t.append(plt.date2num(date[i * fac]))
f.append(0.0)
mask.append(False)
t.append(plt.date2num(date[i*fac] \
+ timedelta(u[i*fac]/norm*onedt.days,u[i*fac]/norm*onedt.seconds)))
f.append(v[i * fac] / norm * daynorm)
mask.append(False)
t.append(plt.date2num(date[i * fac]))
f.append(0.0)
mask.append(True)
t = np.asarray(t)
f = np.asarray(f)
mask = np.asarray(mask)
f = np.ma.masked_array(f, mask=mask)
plt.figure(figsize=(figurewidth, tnorm * figurewidth))
plt.plot_date(t, f, '-', color=color)
ax = plt.gca()
ax.set_aspect('equal')
ax.set_xlim(t[0], t[-1])
ax.set_ylim(-1.0 * daynorm, 1.0 * daynorm)
ax.set_frame_on(False)
ax.yaxis.set_visible(False)
def signature(self,m=0,n=0, component='s_mag',
vmax = None, vs_time=False, cbar_label=None,
*args, **kwargs):
'''
Visualization of a NetworkSet.
Creates a colored image representing the some component
of each Network in the NetworkSet, vs frequency.
Parameters
------------
m : int
first s-parameters index
n : int
second s-parameter index
component : ['s_mag','s_db','s_deg' ..]
scalar component of Network to visualize. should
be a property of the Network object.
vmax : number
sets upper limit of colorbar, if None, will be set to
3*mean of the magnitude of the complex difference
vs_time: Boolean
if True, then we assume each Network.name was made with
rf.now_string, and we make the y-axis a datetime axis
cbar_label: String
label for the colorbar
\*args,\*\*kw : arguments, keyword arguments
passed to :func:`~pylab.imshow`
'''
mat = npy.array([self[k].__getattribute__(component)[:,m,n] \
for k in range(len(self))])
#if vmax is None:
# vmax = 3*mat.mean()
if vs_time:
# create a datetime index
dt_idx = [now_string_2_dt(k.name ) for k in self]
mpl_times = plb.date2num(dt_idx)
y_max = mpl_times[0]
y_min = mpl_times[-1]
else:
y_min = len(self)
y_max = 0
# creates x and y scales
freq = self[0].frequency
extent = [freq.f_scaled[0], freq.f_scaled[-1], y_min ,y_max]
# set default imshow kwargs
kw ={'extent':extent,'aspect':'auto', 'interpolation':'nearest',
'vmax':vmax }
# update the users kwargs
kw.update(kwargs)
img = plb.imshow(mat, *args, **kw)
if vs_time:
ax =plb.gca()
ax.yaxis_date()
#date_format = plb.DateFormatter('%M:%S.%f')
#ax.yaxis.set_major_formatter(date_format)
#cbar.set_label('Magntidue (dB)')
plb.ylabel('Time')
else:
plb.ylabel('Network #')
plb.grid(0)
freq.labelXAxis()
cbar = plb.colorbar()
if cbar_label is not None:
cbar.set_label(cbar_label)
return img