def plot_insert(insert_x, insert_y, width, length, circle_centre):
circle, ellipse = visual_circle_and_ellipse(insert_x, insert_y, width,
length, circle_centre)
plt.figure()
plt.plot(insert_x, insert_y)
plt.axis("equal")
plt.plot(circle["x"], circle["y"])
plt.title("Insert shape parameterisation")
plt.xlabel("x (cm)")
plt.ylabel("y (cm)")
plt.grid(True)
plt.plot(ellipse["x"], ellipse["y"])
def create_dvh(structure, dcm_struct, dcm_dose):
structure_dose_values = find_dose_within_structure(structure, dcm_struct,
dcm_dose)
hist = np.histogram(structure_dose_values, 100)
freq = hist[0]
bin_edge = hist[1]
bin_mid = (bin_edge[1::] + bin_edge[:-1:]) / 2
cumulative = np.cumsum(freq[::-1])
cumulative = cumulative[::-1]
bin_mid = np.append([0], bin_mid)
cumulative = np.append(cumulative[0], cumulative)
percent_cumulative = cumulative / cumulative[0] * 100
plt.plot(bin_mid, percent_cumulative, label=structure)
plt.title("DVH")
plt.xlabel("Dose (Gy)")
plt.ylabel("Relative Volume (%)")
def display_mu_density(
grid, mu_density, grid_resolution=None, cmap=None, vmin=None, vmax=None
):
"""Prints a colour plot of the MU Density.
Examples
--------
See `pymedphys.mudensity.calculate`_.
"""
if grid_resolution is None:
grid_resolution = grid["mlc"][1] - grid["mlc"][0]
x, y = pcolormesh_grid(grid["mlc"], grid["jaw"], grid_resolution)
plt.pcolormesh(x, y, mu_density, cmap=cmap, vmin=vmin, vmax=vmax)
plt.colorbar()
plt.title("MU density")
plt.xlabel("MLC direction (mm)")
plt.ylabel("Jaw direction (mm)")
plt.axis("equal")
plt.gca().invert_yaxis()
def plot_model(width_data, length_data, factor_data):
i, j, k = create_transformed_mesh(width_data, length_data, factor_data)
model_width, model_length, model_factor = i, j, k
# model_width_mesh, model_length_mesh = np.meshgrid(
# model_width, model_length)
vmin = np.nanmin(
np.concatenate([model_factor.ravel(),
factor_data.ravel()]))
vmax = np.nanmax(
np.concatenate([model_factor.ravel(),
factor_data.ravel()]))
# vrange = vmax - vmin
plt.scatter(
width_data,
length_data,
s=100,
c=factor_data,
cmap="viridis",
vmin=vmin,
vmax=vmax,
zorder=2,
)
plt.colorbar()
cs = plt.contour(model_width,
model_length,
model_factor,
20,
vmin=vmin,
vmax=vmax)
plt.clabel(cs, cs.levels[::2], inline=True)
plt.title("Insert model")
plt.xlabel("width (cm)")
plt.ylabel("length (cm)")
def plot_results(
grid_xx, grid_yy, logfile_mu_density, mosaiq_mu_density, diff_colour_scale=0.1
):
min_val = np.min([logfile_mu_density, mosaiq_mu_density])
max_val = np.max([logfile_mu_density, mosaiq_mu_density])
plt.figure()
plt.pcolormesh(grid_xx, grid_yy, logfile_mu_density, vmin=min_val, vmax=max_val)
plt.colorbar()
plt.title("Logfile MU density")
plt.xlabel("MLC direction (mm)")
plt.ylabel("Jaw direction (mm)")
plt.gca().invert_yaxis()
plt.figure()
plt.pcolormesh(grid_xx, grid_yy, mosaiq_mu_density, vmin=min_val, vmax=max_val)
plt.colorbar()
plt.title("Mosaiq MU density")
plt.xlabel("MLC direction (mm)")
plt.ylabel("Jaw direction (mm)")
plt.gca().invert_yaxis()
scaled_diff = (logfile_mu_density - mosaiq_mu_density) / max_val
plt.figure()
plt.pcolormesh(
grid_xx,
grid_yy,
scaled_diff,
vmin=-diff_colour_scale / 2,
vmax=diff_colour_scale / 2,
)
plt.colorbar(label="Limited colour range = {}".format(diff_colour_scale / 2))
plt.title("(Logfile - Mosaiq MU density) / Maximum MU Density")
plt.xlabel("MLC direction (mm)")
plt.ylabel("Jaw direction (mm)")
plt.gca().invert_yaxis()
plt.show()
plt.figure()
plt.pcolormesh(
grid_xx, grid_yy, scaled_diff, vmin=-diff_colour_scale, vmax=diff_colour_scale
)
plt.colorbar(label="Limited colour range = {}".format(diff_colour_scale))
plt.title("(Logfile - Mosaiq MU density) / Maximum MU Density")
plt.xlabel("MLC direction (mm)")
plt.ylabel("Jaw direction (mm)")
plt.gca().invert_yaxis()
plt.show()
absolute_range = np.max([-np.min(scaled_diff), np.max(scaled_diff)])
plt.figure()
plt.pcolormesh(
grid_xx, grid_yy, scaled_diff, vmin=-absolute_range, vmax=absolute_range
)
plt.colorbar(label="No limited colour range")
plt.title("(Logfile - Mosaiq MU density) / Maximum MU Density")
plt.xlabel("MLC direction (mm)")
plt.ylabel("Jaw direction (mm)")
plt.gca().invert_yaxis()
plt.show()