def add_order_comparison_figure(report, nid, figure, caption,
x_order, y_order, xlabel, ylabel):
print('add_order_comparison_figure(%s)' % nid)
x_order = np.array(x_order.flat)
y_order = np.array(y_order.flat)
n = x_order.size
assert x_order.max() == n - 1
assert y_order.max() == n - 1
with report.plot(nid, figsize=(fsize, fsize)) as pylab:
set_spines_look_A(pylab)
pylab.plot(x_order, y_order, 'ms', **get_plot_params(x_order.size))
pylab.xlabel(xlabel)
pylab.ylabel(ylabel)
pylab.xticks([0, n - 1], ['0', '$n-1$'])
pylab.yticks([0, n - 1], ['0', '$n-1$'])
r = correlation_coefficient(x_order, y_order)
pylab.annotate('corr. = %.4f' % r,
va='top',
ha='right',
xy=(0.95, 0.95), # 0.25 for other
xycoords='figure fraction')
pylab.axis([0, n - 1, 0, n - 1])
pylab.gca().xaxis.set_label_coords(0.5, -0.25)
pylab.gca().yaxis.set_label_coords(-0.25, 0.5)
report.last().add_to(figure, caption)
def add_order_comparison_figure(report, nid, figure, caption, x_order, y_order,
xlabel, ylabel):
print('add_order_comparison_figure(%s)' % nid)
x_order = np.array(x_order.flat)
y_order = np.array(y_order.flat)
n = x_order.size
assert x_order.max() == n - 1
assert y_order.max() == n - 1
with report.plot(nid, figsize=(fsize, fsize)) as pylab:
set_spines_look_A(pylab)
pylab.plot(x_order, y_order, 'ms', **get_plot_params(x_order.size))
pylab.xlabel(xlabel)
pylab.ylabel(ylabel)
pylab.xticks([0, n - 1], ['0', '$n-1$'])
pylab.yticks([0, n - 1], ['0', '$n-1$'])
r = correlation_coefficient(x_order, y_order)
pylab.annotate(
'corr. = %.4f' % r,
va='top',
ha='right',
xy=(0.95, 0.95), # 0.25 for other
xycoords='figure fraction')
pylab.axis([0, n - 1, 0, n - 1])
pylab.gca().xaxis.set_label_coords(0.5, -0.25)
pylab.gca().yaxis.set_label_coords(-0.25, 0.5)
report.last().add_to(figure, caption)
def set_spines_look_A_demo(r):
""" Displaying only left and bottom spines. """
f = r.figure()
x = np.linspace(0, 2 * np.pi, 100)
y = 2 * np.sin(x)
for off in [0, 10, 50]:
with f.plot(figsize=(3, 2),
caption="set_spines_look_A(pylab, outward_offset=%s)" %
off) as pylab:
pylab.plot(x, y)
set_spines_look_A(pylab, outward_offset=off)
def set_spines_look_A_demo(r):
''' Displaying only left and bottom spines. '''
f = r.figure()
x = np.linspace(0, 2 * np.pi, 100)
y = 2 * np.sin(x)
for off in [0, 10, 50]:
with f.plot(
figsize=(3, 2),
caption='set_spines_look_A(pylab, outward_offset=%s)' % off
) as pylab:
pylab.plot(x, y)
set_spines_look_A(pylab, outward_offset=off)
def util_plot_euclidean_coords2d(report, f, nid, S, caption=None):
print('util_plot_euclidean_coords2d(%s)' % nid)
with report.plot(nid, figsize=(fsize, fsize), caption=caption) as pylab:
set_spines_look_A(pylab)
# do not rasterize, they are small
pylab.plot(S[0, :], S[1, :], 'ks', markersize=0.5)
#M = np.abs(S).max()
M = 1.1
#pylab.axis('equal')
pylab.axis([-M, +M, -M, +M])
report.last().add_to(f)
def util_plot_euclidean_coords2d(report, f, nid, S, caption=None):
print('util_plot_euclidean_coords2d(%s)' % nid)
with report.plot(nid, figsize=(fsize, fsize), caption=caption) as pylab:
set_spines_look_A(pylab)
# do not rasterize, they are small
pylab.plot(S[0, :], S[1, :], 'ks', markersize=0.5)
#M = np.abs(S).max()
M = 1.1
#pylab.axis('equal')
pylab.axis([-M, +M, -M, +M])
report.last().add_to(f)
def add_distance_vs_sim_figure(report, nid, figure, caption,
D, R, xlabel, ylabel, degrees=False):
print('add_distance_vs_sim_figure(%s)' % nid)
D = np.array(D.flat)
R = np.array(R.flat)
with report.plot(nid, figsize=(fsize, fsize)) as pylab:
set_spines_look_A(pylab)
plot_params = get_plot_params(nsamples=D.size)
print(' using plot params: %s' % plot_params)
pylab.plot(D, R, 'bs', **plot_params)
pylab.xlabel(xlabel)
pylab.ylabel(ylabel)
pylab.axis([D.min(), D.max(), R.min(), R.max()])
m = D.max()
def set_ticks(t, M):
pos = [a for a, _ in t]
val = [b for _, b in t]
if degrees:
val = add_textdegree(val)
pylab.xticks(np.deg2rad(pos), val)
pylab.axis([0, np.deg2rad(M), -0.3, +1])
# TODO: euclidean geometry
if m < np.pi / 4:
set_ticks([(0, '0'),
(10, '10'),
(20, '20'),
(30, '30'),
(40, '40'),
(50, '50')], 50)
elif m < np.pi / 2:
set_ticks([(0, '0'),
(15, ''),
(30, '30'),
(45, ''),
(60, '60'),
(75, ''),
(90, '90')], 90)
else:
set_ticks([(0, '0'),
(45, '45'),
(90, '90'),
(135, '135'),
(180, '180')], 180)
report.last().add_to(figure, caption)
def plot_feature_comparison(r, f, Z, Zpred):
def normalize(x):
return x / np.abs(x).max()
Z = normalize(Z)
Zpred = normalize(Zpred)
Z_order = scale_score_norm(Z)
Zpred_order = scale_score_norm(Zpred)
#print Zpred_order[Z_order == 0]
if Zpred_order[Z_order == 0] > 0.5:
Zpred = -Zpred
Zpred_order = scale_score_norm(Zpred)
#print Zpred_order[Z_order == 0]
M = 1
def lab(pylab):
pass
if False:
pylab.ylabel('predicted $\\hat{z}$')
pylab.xlabel('observed $z$')
def ticks(cord):
l = ['-1', '', '0', '', '+1']
pylab.xticks(cord, l)
pylab.yticks(cord, l)
with r.plot('Z_Z2', figsize=PlotParams.figsize_order,
caption='Feature vs predicted feature') as pylab:
set_spines_look_A(pylab, PlotParams.spines_outward)
pylab.plot(Z, Zpred, 'ks', markersize=0.6)
pylab.axis([-M, M, -M, M])
ticks([-1, -0.5, 0, 0.5, 1])
lab(pylab)
r.last().add_to(f)
with r.plot('Z_Z2_order', figsize=PlotParams.figsize_order,
caption="order(feature) vs order(predicted feat.)") as pylab:
pylab.plot(Z_order, Zpred_order, 'ks', markersize=0.6)
lab(pylab)
set_spines_look_A(pylab, PlotParams.spines_outward)
pylab.axis([0, 1, 0, 1])
ticks([0, 0.25, 0.5, 0.75, 1])
lab(pylab)
r.last().add_to(f)
def add_distance_vs_sim_figure(report,
nid,
figure,
caption,
D,
R,
xlabel,
ylabel,
degrees=False):
print('add_distance_vs_sim_figure(%s)' % nid)
D = np.array(D.flat)
R = np.array(R.flat)
with report.plot(nid, figsize=(fsize, fsize)) as pylab:
set_spines_look_A(pylab)
plot_params = get_plot_params(nsamples=D.size)
print(' using plot params: %s' % plot_params)
pylab.plot(D, R, 'bs', **plot_params)
pylab.xlabel(xlabel)
pylab.ylabel(ylabel)
pylab.axis([D.min(), D.max(), R.min(), R.max()])
m = D.max()
def set_ticks(t, M):
pos = [a for a, _ in t]
val = [b for _, b in t]
if degrees:
val = add_textdegree(val)
pylab.xticks(np.deg2rad(pos), val)
pylab.axis([0, np.deg2rad(M), -0.3, +1])
# TODO: euclidean geometry
if m < np.pi / 4:
set_ticks([(0, '0'), (10, '10'), (20, '20'), (30, '30'),
(40, '40'), (50, '50')], 50)
elif m < np.pi / 2:
set_ticks([(0, '0'), (15, ''), (30, '30'), (45, ''), (60, '60'),
(75, ''), (90, '90')], 90)
else:
set_ticks([(0, '0'), (45, '45'), (90, '90'), (135, '135'),
(180, '180')], 180)
report.last().add_to(figure, caption)
def plot_kernel(r, f, name, directions, kernel, caption=None):
middle = kernel[kernel.shape[0] / 2]
if middle < 0:
kernel *= -1
kernel = kernel / np.abs(kernel).max()
with r.plot(name, caption=caption,
figsize=PlotParams.figsize_kernel) as pylab:
set_spines_look_A(pylab, PlotParams.spines_outward)
theta = np.rad2deg(directions)
for i in [-1, 0, 1]:
plot_horizontal_line(pylab, i, 'k--', linewidth=0.6)
l = pylab.plot(theta, kernel, 'g-', linewidth=1)
l[0].set_clip_on(False)
pylab.axis([-180, 180, -1, +1])
#pylab.xlabel('directions')
#pylab.ylabel('kernel')
xt = [-180, -90, 0, +90, 180]
pylab.xticks(xt,
add_deg(['-180', '', '0', '', '+180']))
# add_deg(['-180', '-90', '0', '+90', '+180']))
xt = [-1, -0.5, 0, 0.5, +1]
xtt = ['-1.0', "-0.5", "0", "0.5", '+1.0']
pylab.yticks(xt, xtt)
#pylab.gca().yaxis.set_label_coords(-0.05, 0.5)
#pylab.gca().xaxis.set_label_coords(0.5, -0.05)
r.last().add_to(f)
def plot_image(r, fig, nid, cells, field, caption=None, scale_params={},
colors='scale',
scale_format=None):
print('plot_image(%s)' % nid)
assert colors in ['scale', 'posneg', 'cmap']
cells.check_compatible_shape(field)
d_edges = cells.d_edges
a_edges = cells.a_edges
nd = len(d_edges) - 1
properties = get_rgb(field, colors, **scale_params)
colorbar = properties['color_bar']
rgb = properties['rgb']
figparams = dict(figsize=PlotParams.figsize)
with r.plot(nid, caption=caption, **figparams) as pl:
# left bottom width height
# L = 0.6
# axes2 = pl.axes([L, 0.0, 1 - L, 0.1])
# for loc, spine in axes2.spines.iteritems():
# spine.set_color('none') # don't draw spi
## pl.xticks([], [])
## pl.yticks([], [])
# #pl.sca(ax)
#
# pl.axes([0, 0, L - 0.2, 1])
#ax = pl.gca()
set_spines_look_A(pl, PlotParams.spines_outward)
for a, d in itertools.product(range(len(a_edges) - 1),
range(len(d_edges) - 1)):
a_min = a_edges[a]
a_max = a_edges[a + 1]
d_min = d
d_max = d + 1
quatx = [a_min, a_min, a_max, a_max]
quaty = [d_min, d_max, d_max, d_min]
pl.fill(quatx, quaty, color=rgb[d, a, :])
labels_at = [0.16, 0.20, 0.30, 0.40, 0.5, 0.6, 0.70, 1]
tick_pos = []
tick_label = []
for l in labels_at:
closest = np.argmin(np.abs(d_edges - l))
tick_pos.append(closest)
tick_label.append('%.2f' % l)
pl.yticks(tick_pos, tick_label)
bar_w = 15
bar_x = 180 + 3 * bar_w
pl.axis((-180, bar_x + bar_w * 4, 0, nd))
def putcolorbar():
if colorbar is not None:
f = 3
plot_vertical_colorbar(pl, colorbar,
bar_x=bar_x, bar_w=bar_w,
bar_y_min=f, bar_y_max=nd - f,
vdist=0.40,
min_value=properties['min_value'],
max_value=properties['max_value'],
scale_format=scale_format)
if True:
putcolorbar()
pl.axis((-180, bar_x + bar_w * 4, 0, nd))
# ex = [180, bar_x + bar_w * 4, 0.4, 0.5]
# pl.fill([ex[0], ex[0], ex[1], ex[1]],
# [ex[2], ex[3], ex[3], ex[2]], facecolor='w',
# edgecolor='none')
else:
pl.axis((-180, 180, 0, nd))
putcolorbar()
# pl.gca().set_position([0, 0, L - 0.2, 1])
#
# else:
# pl.axis((-180, 180, 0, nd))
# L = 0.8
# pl.gca().set_position([0.125, 0.1, L, 0.9])
#
# ax = pl.gca()
#
# # left bottom width height
# axes2 = pl.axes([L, 0.0, 1 - L, 1])
# for loc, spine in axes2.spines.iteritems():
# spine.set_color('none') # don't draw spi
# pl.xticks([], [])
# pl.yticks([], [])
#
# putcolorbar()
#
#
# pl.sca(ax)
pl.xticks([-180, -135, -90, -45, 0, 45, +90, 135, 180],
add_deg(["-180", "", "-90", "", "0",
"", "+90", "", "180"]))
# pl.xlabel('axis angle \\ $\\varphi$ (deg)')
pl.xlabel('axis angle $\\varphi$')
pl.ylabel('distance from wall $d$ (m)')
#pl.gca().xaxis.set_label_coords(0.38, -0.02)
#pl.gca().yaxis.set_label_coords(-0.17, 0.5)
if r != fig:
r.last().add_to(fig)
def util_plot_3D_points(report, f, nid, S, caption=None):
print('util_plot_3D_points(%s)' % nid)
# let (1,0,0) be (0,0,1)
S1 = np.empty_like(S)
S1[0, :] = S[2, :]
S1[1, :] = S[1, :]
S1[2, :] = S[0, :]
if np.mean(S1[0, :]) < 0:
S1[0, :] *= -1
# switch Y and Z if necessary
if np.mean(np.abs(S1[1, :])) < np.mean(np.abs(S1[2, :])):
S2 = np.empty_like(S1)
S2[0, :] = S1[0, :]
S2[1, :] = S1[2, :]
S2[2, :] = S1[1, :]
S1 = S2
AE = azi_elev_from_directions(S1)
A = AE[0, :]
E = AE[1, :]
A_deg = np.rad2deg(A)
E_deg = np.rad2deg(E)
with report.plot(nid, figsize=figsize_points) as pylab:
set_spines_look_A(pylab)
pylab.plot(A_deg, E_deg, 'bs', markersize=0.2)
max_azi_deg = np.max(A_deg)
max_ele_deg = np.max(E_deg)
#print('max_azi_deg', max_azi_deg)
#print('max_ele', np.max(E_deg))
if max_azi_deg < 60: # mino
#print('config mino')
set_xticks_from_seq(
pylab,
[ #(-45, '-45'),
(-30, '-30'),
(-15, ''),
(0, '0'),
(+15, ''),
(30, '30'),
#(45, '+45')
])
MA = 30
elif max_azi_deg < 90: # GOPRO
#print('config gopro')
set_xticks_from_seq(pylab, [(-90, '-90'), (-75, ''), (-60, ''),
(-45, '-45'), (-30, ''), (-15, ''),
(0, '0'), (+15, ''), (30, ''),
(45, '45'), (60, ''), (75, ''),
(90, '+90')])
MA = 95
else: # omni
#print('config omni')
set_xticks_from_seq(pylab, [(-180, '-180'), (-135, ''),
(-90, '-90'), (-45, ''), (0, '0'),
(+45, ''), (90, '+90'), (135, ''),
(180, '+180')])
MA = 180
if max_ele_deg < 15:
ME = 15
set_yticks_from_seq(pylab, [(-15, '-15'), (-10, ''), (-5, ''),
(0, '0'), (5, ''), (10, ''),
(+15, '15')])
elif max_ele_deg < 55:
ME = 55
set_yticks_from_seq(pylab, [(-45, '-45'), (-30, ''), (-15, ''),
(0, '0'), (15, ''), (30, ''),
(+45, '45')])
else:
ME = 90
set_yticks_from_seq(pylab, [(-90, '-90'), (-45, '-45'), (0, '0'),
(+45, '+45'), (+90, '+90')])
pylab.axis([-MA, MA, -ME, ME])
pylab.ylabel('elevation')
pylab.xlabel('azimuth')
if False:
pylab.gca().xaxis.set_label_coords(0.5, -0.02)
pylab.gca().yaxis.set_label_coords(-0.02, 0.5)
report.last().add_to(f, caption)
def util_plot_3D_points(report, f, nid, S, caption=None):
print('util_plot_3D_points(%s)' % nid)
# let (1,0,0) be (0,0,1)
S1 = np.empty_like(S)
S1[0, :] = S[2, :]
S1[1, :] = S[1, :]
S1[2, :] = S[0, :]
if np.mean(S1[0, :]) < 0:
S1[0, :] *= -1
# switch Y and Z if necessary
if np.mean(np.abs(S1[1, :])) < np.mean(np.abs(S1[2, :])):
S2 = np.empty_like(S1)
S2[0, :] = S1[0, :]
S2[1, :] = S1[2, :]
S2[2, :] = S1[1, :]
S1 = S2
AE = azi_elev_from_directions(S1)
A = AE[0, :]
E = AE[1, :]
A_deg = np.rad2deg(A)
E_deg = np.rad2deg(E)
with report.plot(nid, figsize=figsize_points) as pylab:
set_spines_look_A(pylab)
pylab.plot(A_deg, E_deg, 'bs', markersize=0.2)
max_azi_deg = np.max(A_deg)
max_ele_deg = np.max(E_deg)
#print('max_azi_deg', max_azi_deg)
#print('max_ele', np.max(E_deg))
if max_azi_deg < 60: # mino
#print('config mino')
set_xticks_from_seq(pylab,
[#(-45, '-45'),
(-30, '-30'), (-15, ''), (0, '0'),
(+15, ''), (30, '30'),
#(45, '+45')
]
)
MA = 30
elif max_azi_deg < 90: # GOPRO
#print('config gopro')
set_xticks_from_seq(pylab,
[(-90, '-90'), (-75, ''), (-60, ''),
(-45, '-45'),
(-30, ''),
(-15, ''), (0, '0'),
(+15, ''), (30, ''), (45, '45'), (60, ''),
(75, ''), (90, '+90')])
MA = 95
else: # omni
#print('config omni')
set_xticks_from_seq(pylab,
[(-180, '-180'), (-135, ''), (-90, '-90'),
(-45, ''), (0, '0'),
(+45, ''), (90, '+90'), (135, ''),
(180, '+180')])
MA = 180
if max_ele_deg < 15:
ME = 15
set_yticks_from_seq(pylab,
[(-15, '-15'), (-10, ''), (-5, ''), (0, '0'),
(5, ''), (10, ''), (+15, '15')])
elif max_ele_deg < 55:
ME = 55
set_yticks_from_seq(pylab,
[(-45, '-45'), (-30, ''), (-15, ''), (0, '0'), (15, ''), (30, ''),
(+45, '45')])
else:
ME = 90
set_yticks_from_seq(pylab,
[(-90, '-90'), (-45, '-45'), (0, '0'),
(+45, '+45'), (+90, '+90')])
pylab.axis([-MA, MA, -ME, ME])
pylab.ylabel('elevation')
pylab.xlabel('azimuth')
if False:
pylab.gca().xaxis.set_label_coords(0.5, -0.02)
pylab.gca().yaxis.set_label_coords(-0.02, 0.5)
report.last().add_to(f, caption)
