def plotGsrResidue(theta, phi, residue, optTheta, optPhi, mvabTheta=None, mvabPhi=None, mvubTheta=None, mvubPhi=None):
fig = figure()
fig.clf()
# some matplotlib setup stuff which I don't fully understand but it works
tr = Affine2D().scale(pi/180., 1.) + PolarAxes.PolarTransform()
extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
lon_cycle = 360,
lat_cycle = None,
lon_minmax = None,
lat_minmax = (0, inf),
)
grid_locator1 = angle_helper.LocatorDMS(12)
tick_formatter1 = angle_helper.FormatterDMS()
grid_helper = GridHelperCurveLinear(tr,
extreme_finder=extreme_finder,
grid_locator1=grid_locator1,
tick_formatter1=tick_formatter1
)
ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
fig.add_subplot(ax1)
ax1.axis["right"].major_ticklabels.set_visible(True)
ax1.axis["top"].major_ticklabels.set_visible(True)
ax1.axis["right"].get_helper().nth_coord_ticks=0
ax1.axis["bottom"].get_helper().nth_coord_ticks=1
# draw the filled contoured map in polar coordinates
ax1.contour(transpose(mat(theta))*mat(cos(phi*pi/180)), transpose(mat(theta))*mat(sin(phi*pi/180)), 1/transpose(reshape(residue, (phi.size,-1))), 100, lw=0.1)
cc = ax1.contourf(transpose(mat(theta))*mat(cos(phi*pi/180)), transpose(mat(theta))*mat(sin(phi*pi/180)), 1/transpose(reshape(residue, (phi.size,-1))), 100)
# remove gaps between the contour lines
for c in cc.collections:
c.set_antialiased(False)
# show the MVAB direction
if mvabTheta is not None and mvabPhi is not None:
ax1.plot(mvabTheta*cos(mvabPhi*pi/180), mvabTheta*sin(mvabPhi*pi/180), 'sk', markersize=8)
# show the MVUB direction
if mvubTheta is not None and mvubPhi is not None:
ax1.plot(mvubTheta*cos(mvubPhi*pi/180), mvubTheta*sin(mvubPhi*pi/180), 'dk', markersize=8)
# show the optimal direction
ax1.plot(optTheta*cos(optPhi*pi/180), optTheta*sin(optPhi*pi/180), '.k', markersize=15)
# aspect and initial axes limits
ax1.set_aspect(1.)
ax1.set_xlim(-90, 90)
ax1.set_ylim(-90, 90)
# add grid
ax1.grid(True)
# add colobar
cb = colorbar(cc, pad=0.07)
cb.locator = MaxNLocator(14)
cb.update_ticks()
cb.set_label(r"$1/\tilde{\mathcal{R}}$")
# save
if toSave:
savefig(resultsDir+'/eps/gsr_ResidualMap.eps', format='eps')
savefig(resultsDir+'/png/gsr_ResidualMap.png', format='png')
def plotGsrResidue(theta,
phi,
residue,
optTheta,
optPhi,
mvabTheta=None,
mvabPhi=None,
mvubTheta=None,
mvubPhi=None):
fig = figure()
fig.clf()
# some matplotlib setup stuff which I don't fully understand but it works
tr = Affine2D().scale(pi / 180., 1.) + PolarAxes.PolarTransform()
extreme_finder = angle_helper.ExtremeFinderCycle(
20,
20,
lon_cycle=360,
lat_cycle=None,
lon_minmax=None,
lat_minmax=(0, inf),
)
grid_locator1 = angle_helper.LocatorDMS(12)
tick_formatter1 = angle_helper.FormatterDMS()
grid_helper = GridHelperCurveLinear(tr,
extreme_finder=extreme_finder,
grid_locator1=grid_locator1,
tick_formatter1=tick_formatter1)
ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
fig.add_subplot(ax1)
ax1.axis["right"].major_ticklabels.set_visible(True)
ax1.axis["top"].major_ticklabels.set_visible(True)
ax1.axis["right"].get_helper().nth_coord_ticks = 0
ax1.axis["bottom"].get_helper().nth_coord_ticks = 1
# draw the filled contoured map in polar coordinates
ax1.contour(transpose(mat(theta)) * mat(cos(phi * pi / 180)),
transpose(mat(theta)) * mat(sin(phi * pi / 180)),
1 / transpose(reshape(residue, (phi.size, -1))),
100,
lw=0.1)
cc = ax1.contourf(
transpose(mat(theta)) * mat(cos(phi * pi / 180)),
transpose(mat(theta)) * mat(sin(phi * pi / 180)),
1 / transpose(reshape(residue, (phi.size, -1))), 100)
# remove gaps between the contour lines
for c in cc.collections:
c.set_antialiased(False)
# show the MVAB direction
if mvabTheta is not None and mvabPhi is not None:
ax1.plot(mvabTheta * cos(mvabPhi * pi / 180),
mvabTheta * sin(mvabPhi * pi / 180),
'sk',
markersize=8)
# show the MVUB direction
if mvubTheta is not None and mvubPhi is not None:
ax1.plot(mvubTheta * cos(mvubPhi * pi / 180),
mvubTheta * sin(mvubPhi * pi / 180),
'dk',
markersize=8)
# show the optimal direction
ax1.plot(optTheta * cos(optPhi * pi / 180),
optTheta * sin(optPhi * pi / 180),
'.k',
markersize=15)
# aspect and initial axes limits
ax1.set_aspect(1.)
ax1.set_xlim(-90, 90)
ax1.set_ylim(-90, 90)
# add grid
ax1.grid(True)
# add colobar
cb = colorbar(cc, pad=0.07)
cb.locator = MaxNLocator(14)
cb.update_ticks()
cb.set_label(r"$1/\tilde{\mathcal{R}}$")
# save
if toSave:
savefig(resultsDir + '/eps/gsr_ResidualMap.eps', format='eps')
savefig(resultsDir + '/png/gsr_ResidualMap.png', format='png')
class PolarPlot:
''' plots heading angle and signal strength in polar coor in 2d'''
def __init__(self):
plt.ion()
self.fig = plt.figure(num=2, figsize=(10,7))
tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()
# 20, 20 : number of sampling points along x, y direction
extreme_finder = angle_helper.ExtremeFinderCycle(50, 50,
lon_cycle = 360,
lat_cycle = None,
lon_minmax = None,
lat_minmax = (0, np.inf),
)
grid_locator1 = angle_helper.LocatorDMS(15)
tick_formatter1 = angle_helper.FormatterDMS()
# And also uses an appropriate formatter. Note that,the
# acceptable Locator and Formatter class is a bit different than
# that of mpl's, and you cannot directly use mpl's Locator and
# Formatter here (but may be possible in the future).
grid_helper = GridHelperCurveLinear(tr,
extreme_finder=extreme_finder,
grid_locator1=grid_locator1,
tick_formatter1=tick_formatter1
)
self.ax1 = SubplotHost(self.fig, 1, 1, 1, grid_helper=grid_helper)
# make ticklabels of right and top axis visible.
self.ax1.axis["right"].major_ticklabels.set_visible(True)
self.ax1.axis["top"].major_ticklabels.set_visible(True)
self.ax1.axis["left"].major_ticklabels.set_visible(True)
# let right axis shows ticklabels for 1st coordinate (angle)
self.ax1.axis["right"].get_helper().nth_coord_ticks=0
# let bottom axis shows ticklabels for 1st coordinate (angle)
self.ax1.axis["bottom"].get_helper().nth_coord_ticks=0
self.ax1.axis["left"].get_helper().nth_coord_ticks=0
temp = self.ax1.set_title('Signal strength & heading polar plots')
temp.set_y(1.05)
self.ax1.grid(True)
# insert x and y axises
self.ax = self.fig.add_subplot(self.ax1)
self.ax1.spines['left'].set_position('center')
self.ax1.spines['right'].set_color('red')
self.ax1.spines['bottom'].set_position('center')
self.ax1.spines['top'].set_color('none')
self.ax1.spines['left'].set_smart_bounds(True)
self.ax1.spines['bottom'].set_smart_bounds(True)
self.ax1.xaxis.set_ticks_position('bottom')
self.ax1.yaxis.set_ticks_position('left')
self.ax1.axhline(linewidth=2, color='blue')
self.ax1.axvline(linewidth=2, color='blue')
# label x and y axises manually
ticks = np.linspace(0, 255, 6)
offset = np.zeros([1,255])
for i in range(1,5):
self.ax1.annotate(str(ticks[i]),size=10, xy=(ticks[i], -15))
blah = self.ax1.plot(ticks[i],0, 'bo')
self.ax1.annotate(str(ticks[i]),size=10, xy=(5, ticks[i]))
blah = self.ax1.plot(0,ticks[i], 'bo')
# annotate figure
bbox_props = dict(boxstyle="round", fc="w", ec="0.5", alpha=0.9)
# self.annotation = self.ax1.annotate('init',size=20, xy=(100, 100), bbox = bbox_props)
self.annotation = plt.figtext(0.02, 0.9, 'rssi = ', size=20, alpha = 0.9, bbox = bbox_props)
self.Freq = plt.figtext(0.85, 0.85, 'freq = ???', size=10, alpha = 0.9, bbox = bbox_props)
self.Freq = plt.figtext(0.85, 0.9, 'Horizontal Plane', size=10, alpha = 0.9, bbox = bbox_props)
# initialize arrow
self.quiverLine = self.ax1.quiver(0,0,50,50,angles='xy',scale_units='xy',scale=1)
self.ax1.set_aspect(1.)
self.ax1.set_xlim(-255, 255)
self.ax1.set_ylim(-255, 255)
# initialize mesh plot
self.xdata = []
self.ydata = []
self.polarline, = self.ax1.plot(self.xdata,self.ydata)
def update(self, signalStrength, yaw):
U = signalStrength*cos(yaw*pi/180)
V = signalStrength*sin(yaw*pi/180)
self.xdata.append(U)
self.ydata.append(V)
self.polarline.set_data(self.xdata,self.ydata)
self.quiverLine.set_UVC(U,V)
self.annotation.set_text('rssi = ' + str(signalStrength))
plt.draw()
def get_smith(fig,
rect=111,
plot_impedance=True,
plot_ticks=False,
plot_admittance=False,
plot_labels=False):
'''Function which returns an axis with a blank smith chart, provide a figure and optional rect coords'''
#Example use:
# fig3 = plt.figure(3)
# ax31 = pySmith.get_smith(fig3, 221)
# ax31.plot(np.real(filtsmatrix[0,:,0,0]),np.imag(filtsmatrix[0,:,0,0]))
# ax32= pySmith.get_smith(fig3, 222)
# ax32.plot(np.real(filtsmatrix[0,:,0,1]),np.imag(filtsmatrix[0,:,0,1]))
# ax33 = pySmith.get_smith(fig3, 223)
# ax33.plot(np.real(filtsmatrix[0,:,1,0]),np.imag(filtsmatrix[0,:,1,0]))
# ax34 = pySmith.get_smith(fig3, 224)
# ax34.plot(np.real(filtsmatrix[0,:,1,1]),np.imag(filtsmatrix[0,:,1,1]))
try:
#font definition
font = {
'family': 'sans-serif',
'color': 'black',
'weight': 'normal',
'size': 16,
}
#plot radial tick marks
tr = PolarAxes.PolarTransform()
num_thetas = 8 #*3 #12 gives in 30 deg intervals, 8 in 45 deg, 24 in 15deg
thetas = np.linspace(0.0, math.pi * (1 - 2.0 / num_thetas),
num_thetas // 2)
angle_ticks = [] #(0, r"$0$"),
for theta in thetas:
angle_info = []
angle_info.append(theta)
deg = int(round(180.0 * theta / math.pi))
angle_info.append(r'%d$^{\circ}$' % deg)
angle_ticks.append(angle_info)
grid_locator1 = FixedLocator([v for v, s in angle_ticks])
tick_formatter1 = DictFormatter(dict(angle_ticks))
thetas2 = np.linspace(math.pi, 2 * math.pi * (1 - 1.0 / num_thetas),
num_thetas // 2)
angle_ticks2 = [] #(0, r"$0$"),
for theta in thetas2:
angle_info = []
angle_info.append(theta)
deg = int(round(180.0 * theta / math.pi))
angle_info.append(r'%d$^{\circ}$' % deg)
angle_ticks2.append(angle_info)
grid_locator2 = FixedLocator([v for v, s in angle_ticks2])
tick_formatter2 = DictFormatter(dict(angle_ticks2))
grid_helper1 = floating_axes.GridHelperCurveLinear(
tr,
extremes=(math.pi, 0, 1, 0),
grid_locator1=grid_locator1,
#grid_locator2=grid_locator2,
tick_formatter1=tick_formatter1 #,
#tick_formatter2=None,
)
grid_helper2 = floating_axes.GridHelperCurveLinear(
tr,
extremes=(2 * math.pi, math.pi, 1, 0),
grid_locator1=grid_locator2,
#grid_locator2=grid_locator2,
tick_formatter1=tick_formatter2 #,
#tick_formatter2=None,
)
r1 = int(math.floor(rect / 100))
r2 = int(math.floor((rect - 100 * r1) / 10))
r3 = int(math.floor((rect - 100 * r1 - 10 * r2)))
ax = SubplotHost(fig, r1, r2, r3, grid_helper=grid_helper1)
ax2 = SubplotHost(fig, r1, r2, r3, grid_helper=grid_helper2)
#ax.set_aspect(math.pi/180.0,'datalim')
fig.add_subplot(ax)
fig.add_subplot(ax2)
ax.axis["bottom"].major_ticklabels.set_axis_direction("top")
ax.axis["bottom"].major_ticklabels.set_fontsize(13)
ax.axis["left"].set_visible(False)
ax.axis["left"].toggle(all=False)
ax.axis["right"].set_visible(False)
ax.axis["right"].toggle(all=False)
ax.axis["top"].set_visible(False)
ax.axis["top"].toggle(all=False)
ax.patch.set_visible(False)
ax2.axis["bottom"].major_ticklabels.set_fontsize(13)
ax2.axis["left"].set_visible(False)
ax2.axis["left"].toggle(all=False)
ax2.axis["right"].set_visible(False)
ax2.axis["right"].toggle(all=False)
ax2.axis["top"].set_visible(False)
ax2.axis["top"].toggle(all=False)
#ax = fig.add_subplot(rect)
#remove axis labels
ax.axis('off')
#set aspect ratio to 1
ax.set_aspect(1) #, 'datalim')
#set limits
ax.set_xlim([-1.02, 1.02])
ax.set_ylim([-1.02, 1.02])
#remove axis labels
ax2.axis('off')
#set aspect ratio to 1
ax2.set_aspect(1) #,'datalim')
#set limits
ax2.set_xlim([-1.02, 1.02])
ax2.set_ylim([-1.02, 1.02])
ax2.patch.set_visible(False)
if plot_impedance:
#make lines of constant resistance
res_log = np.linspace(-4, 4, 9)
react_log = np.linspace(-5, 5, 2001)
res = 2**res_log
react = 10**react_log
react2 = np.append(-1.0 * react[::-1], np.array([0]))
react = np.append(react2, react)
for r in res:
z = 1j * react + r
gam = (z - 1) / (z + 1)
x = np.real(gam)
y = np.imag(gam)
if abs(r - 1) > 1e-6:
ax.plot(x, y, c='k', linewidth=0.75, alpha=0.25)
else:
ax.plot(x, y, c='k', linewidth=1.0, alpha=0.4)
#make lines of constant reactance
react_log = np.linspace(-3, 3, 7)
res_log = np.linspace(-5, 5, 2001)
res = 10**res_log
react = 2**react_log
react2 = np.append(-1.0 * react[::-1], np.array([0]))
react = np.append(react2, react)
for chi in react:
z = 1j * chi + res
gam = (z - 1) / (z + 1)
x = np.real(gam)
y = np.imag(gam)
if abs(chi - 1) > 1e-6 and abs(chi +
1) > 1e-6 and abs(chi) > 1e-6:
ax.plot(x, y, c='k', linewidth=0.75, alpha=0.25)
else:
ax.plot(x, y, c='k', linewidth=1.0, alpha=0.4)
if plot_admittance:
#make lines of constant conductance
res_log = np.linspace(-4, 4, 9)
react_log = np.linspace(-5, 5, 2001)
res = 2**res_log
react = 10**react_log
react = np.append(-1.0 * react[::-1], react)
for r in res:
y = 1.0 / r + 1.0 / (1j * react)
gam = (1.0 / y - 1) / (1.0 / y + 1)
x = np.real(gam)
y = np.imag(gam)
if abs(r - 1) > 1e-6:
ax.plot(x, y, c='k', linewidth=0.75, alpha=0.25)
else:
ax.plot(x, y, c='k', linewidth=1.0, alpha=0.4)
#make lines of constant susceptance
react_log = np.linspace(-3, 3, 7)
res_log = np.linspace(-5, 5, 2001)
res = 10**res_log
react = 2**react_log
react = np.append(-1.0 * react[::-1], react)
for chi in react:
y = 1.0 / (1j * chi) + 1.0 / res
gam = (1.0 / y - 1) / (1.0 / y + 1)
x = np.real(gam)
y = np.imag(gam)
if abs(chi - 1) > 1e-6 and abs(chi + 1) > 1e-6:
ax.plot(x, y, c='k', linewidth=0.75, alpha=0.25)
else:
ax.plot(x, y, c='k', linewidth=1.0, alpha=0.4)
y = 1.0 / res
gam = (1.0 / y - 1) / (1.0 / y + 1)
x = np.real(gam)
y = np.imag(gam)
ax.plot(x, y, c='k', linewidth=1.0, alpha=0.75)
if plot_labels:
#naive text placement only works for default python figure size with 1 subplot
ax.text(-0.15, 1.04, r'$\Gamma$ = 1j', fontdict=font)
ax.text(-1.4, -0.035, r'$\Gamma$ = -1', fontdict=font)
ax.text(-0.17, -1.11, r'$\Gamma$ = -1j', fontdict=font)
ax.text(1.04, -0.035, r'$\Gamma$ = 1', fontdict=font)
if plot_ticks:
num_minorticks = 3
num_thetas = num_thetas * (num_minorticks + 1)
thetas = np.linspace(0, 2.0 * math.pi * (1.0 - 1.0 / num_thetas),
num_thetas)
r_inner = 0.985
r_outer = 1.0
rads = np.linspace(r_inner, r_outer, 2)
ticknum = 0
for theta in thetas:
x = rads * np.cos(theta)
y = rads * np.sin(theta)
if ticknum % (num_minorticks + 1) != 0:
ax.plot(x, y, c='k', linewidth=1.0, alpha=1.0)
ticknum = ticknum + 1
return ax
except Exception as e:
print('\nError in %s' % inspect.stack()[0][3])
print(e)
exc_type, exc_obj, exc_tb = sys.exc_info()
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
print(exc_type, fname, exc_tb.tb_lineno)
