def get_3d_data(data, field_x, field_y, field_z):
x_set, z_av_tab, z_std_tab, y_set = analysis.get_graph_data(
data, field_x, field_y, field_z)
x = []
y = []
z = []
for i, xs in enumerate(x_set):
for j, ys in enumerate(y_set):
x.append(xs)
y.append(ys)
z.append(z_av_tab[i, j])
return x, y, z
def plot(ax, data, field_x, field_y, field_z):
data = analysis.get_graph_data(data, field_x, field_y, field_z)
for j in range(len(data[3])):
ax.plot(data[0],
data[1][:, j],
linestyle=analysis.get_lines(j),
linewidth=2,
color=analysis.get_cols(j),
label=str(field_z).replace("_", " ") + " = " + str(data[3][j]))
ax.fill_between(data[0],
data[1][:, j] - data[2][:, j] / 5.0,
data[1][:, j] + data[2][:, j] / 5.0,
alpha=0.1,
edgecolor=analysis.get_cols(j),
facecolor=analysis.get_cols(j))
ax.set_title(str(field_y))
def scatter_x_y(ax, data, field_x, field_y, field_z):
x_set, z_av_tab, z_std_tab, y_set = analysis.get_graph_data(
data, field_x, field_y, field_z)
print x_set, y_set
if "grf_max" in field_y:
im = ax.pcolormesh(x_set,
y_set,
z_av_tab.T,
norm=cols.LogNorm(vmin=max(0.0001,
np.nanmin(z_av_tab)),
vmax=np.nanmax(z_av_tab)))
else:
im = ax.pcolormesh(x_set, y_set, z_av_tab.T)
# x, y, z = get_3d_data(data, field_x, field_y, field_z)
# logx = np.log10(x)
# logy = np.log10(y)
# logz = np.log10(z)
# f = interp2d(logx, logy, logz, kind="linear")
# xi = np.linspace(min(logx), max(logx), 100)
# yi = np.linspace(min(logy), max(logy), 100)
# zi = np.power(10, f(xi, yi))
# xi = np.power(10, xi)
# yi = np.power(10, yi)
# im = ax.pcolormesh(xi, yi, zi)
ks = np.logspace(np.log10(min(x_set)), np.log10(max(x_set)), 100)
for j, kappa in enumerate(
[0.000001, 0.00001, 0.0001, 0.001, 0.01, 0.1, 1, 10, 100, 1000,
10000]):
ax.plot(ks,
kappa * np.sqrt(ks),
linestyle="--",
linewidth=1,
color="k",
label="Kappa = " + str(kappa))
ax.set_yscale('log')
ax.set_xscale('log')
ax.set_xlim([min(x_set), max(x_set)])
ax.set_ylim([min(y_set), max(y_set)])
ax.set_xlabel('Stiffness [N.m/rad]')
ax.set_ylabel('Damping [N.m.s/rad]')
ax.set_title(field_y.replace("_", " ").capitalize())
return im
def get_fall_data(data, field_x, field_y, field_z):
data = analysis.get_graph_data(data, field_x, field_y, field_z)
fall_x = []
fall_y = []
not_fall_x = []
not_fall_y = []
for i, x in enumerate(data[0]):
for j, y in enumerate(data[3]):
if data[1][i, j] > 0.2:
fall_x.append(x)
fall_y.append(y)
else:
not_fall_x.append(x)
not_fall_y.append(y)
return fall_x, fall_y, not_fall_x, not_fall_y
def get_data(data, field):
x_set, z_av_tab, z_std_tab, y_set = analysis.get_graph_data(
data, 'force_delay_line_n', field, 'force_elm_n')
x = []
y = []
z_av = []
z_std = []
for i, xs in enumerate(x_set):
for j, ys in enumerate(y_set):
x.append(xs)
y.append(ys)
if 'x_speed' in field:
z_av_tab[i, j] = 1 - abs(0.25 - z_av_tab[i, j]) / 0.25
if z_av_tab[i, j] < 0:
z_av_tab[i, j] = 0
if 'y_speed' in field:
z_av_tab[i, j] = abs(z_av_tab[i, j])
z_av.append(z_av_tab[i, j])
z_std.append(z_std_tab[i, j])
return x, y, z_av, z_std