def plot_colorbar(cax,
cmap,
hue_norm,
cnorm=None,
label=None,
orientation='vertical',
labelsize=4,
linewidth=0.5):
if isinstance(cmap, str):
cmap = copy.copy(get_cmap(cmap))
if cnorm is None:
cnorm = Normalize(vmin=hue_norm[0], vmax=hue_norm[1])
from .utilities import smart_number_format
colorbar = ColorbarBase(cax,
cmap=cmap,
norm=cnorm,
format=ticker.FuncFormatter(smart_number_format),
orientation=orientation,
extend='both')
colorbar.locator = ticker.MaxNLocator(nbins=3)
colorbar.update_ticks()
colorbar.set_label(label, fontsize=labelsize)
colorbar.outline.set_linewidth(linewidth)
colorbar.ax.tick_params(size=labelsize,
labelsize=labelsize,
width=linewidth)
return cax
def display_displacements(simulation_folder, lower_percentile=70, upper_percentile=99.7, save_plot = True, arrow_factor=4):
"""
show the total displacement field or the masked range of displacements by size
simulation_folder: path to simulation folder
lower_percentile and upper_percentile give range of deformationsize which is used
as a mask
save_plot: option to save the plot to the simulation folder
arrow_factor: scales the arrow length in the plot
To increase plotting speed you might increase the lower percentile (e.g 30 instead 0)
"""
# load in deformations and coordinates
r = np.genfromtxt(os.path.join(simulation_folder, "R.dat")) # positions
u = np.genfromtxt(os.path.join(simulation_folder, "Ufound.dat")) #deformations
uabs = np.sqrt(np.sum(u ** 2., axis=1)) # absolute values for filtering
# filter displacements by absolute size
mask = (uabs > np.percentile(uabs, lower_percentile)) & (uabs < np.percentile(uabs, upper_percentile))
r2 = r[mask]
u2 = u[mask]
uabs2 = uabs[mask]
# plot the masked deformation
fig = plt.figure()
ax1 = fig.gca(projection='3d', label='fitted-displ', rasterized=True)
color_bounds1 = np.array([np.percentile(uabs2, 0), np.percentile(uabs2, 99.8)]) * 10 ** 6
np.random.seed(1234)
for r2i, u2i, uabs2i in tqdm(zip(r2 * 10 ** 6, u2 * 10 ** 6, uabs2 * (10 ** 6))):
# if np.random.uniform(0, 1) < 0.2: # uabs2i/u_upper:
color = plt.cm.jet(((uabs2i - color_bounds1[0]) / (color_bounds1[1] - color_bounds1[0])))
alpha = 1. - (r2i[0] - r2i[1]) / (270. * 0.5)
if alpha > 1:
alpha = 1.
if alpha < 0:
alpha = 0.
plt.quiver(r2i[0], r2i[1], r2i[2], u2i[0], u2i[1], u2i[2], length=uabs2i * arrow_factor ,
color=color, arrow_length_ratio=0, alpha=alpha, pivot='tip', linewidth=0.5)
# plot colorbar ---------------------------------------------------------
cbaxes = fig.add_axes([0.15, 0.1, 0.125, 0.010])
cmap = plt.cm.jet
norm = plt.Normalize(vmin=color_bounds1[0], vmax=color_bounds1[1])
cb1 = ColorbarBase(cbaxes, cmap=cmap, norm=norm, orientation='horizontal')
cb1.set_label('Displacements [µm]')
tick_locator = ticker.MaxNLocator(nbins=3)
cb1.locator = tick_locator
cb1.update_ticks()
ax1.w_xaxis.set_pane_color((0.2, 0.2, 0.2, 1.0))
ax1.w_yaxis.set_pane_color((0.2, 0.2, 0.2, 1.0))
ax1.w_zaxis.set_pane_color((0.2, 0.2, 0.2, 1.0))
if save_plot:
plt.savefig( os.path.join(simulation_folder,'deformations_plot_lower_{}_upper_{}.png'.format(lower_percentile, upper_percentile)), dpi=500, bbox_inches="tight", pad_inches=0)
return
def create_colorbar(cax,
cmap_range=(0, 1),
cmap_name="jet",
colorbar_title="",
colorbar_loc="top",
ticksize=8,
num_ticks=None):
""" create colorbar
see https://matplotlib.org/devdocs/tutorials/colors/colorbar_only.html
Parameters
----------
cax: matplotlib.axes.Axes
cmap_name: str
cmap_range: tuple
colorbar_title: str
colorbar_loc: str
'top' or 'bottom'
ticksize: int
"""
assert colorbar_loc == "top" or colorbar_loc == "bottom"
norm = Normalize(vmin=cmap_range[0], vmax=cmap_range[1])
cmap = get_cmap(cmap_name)
cbar = ColorbarBase(cax,
cmap=cmap,
norm=norm,
orientation="horizontal",
label=colorbar_title,
ticklocation=colorbar_loc,
extend="both")
#tick_locator = ticker.MaxNLocator(nbins=5)
if num_ticks is not None:
tick_locator = ticker.LinearLocator(numticks=num_ticks)
cbar.locator = tick_locator
cbar.update_ticks()
cax.tick_params(labelsize=ticksize)
return cbar
def display_forces(simulation_folder, lower_percentile=97.5, upper_percentile=99, save_plot = True, arrow_factor=5):
"""
show the force density field of the masked force components
simulation_folder: path to simulation folder
lower_percentile and upper_percentile give range of forces which is used
as a mask
save_plot: option to save the plot to the simulation folder
arrow_factor: scales the arrow length in the plot
"""
# load in forces and coordinates
r = np.genfromtxt(os.path.join(simulation_folder, "R.dat")) # positions
f = np.genfromtxt(os.path.join(simulation_folder, "Fden.dat")) # force densities
fabs = np.sqrt(np.sum(f ** 2., axis=1)) # absolute values for filtering
# filter
mask = (fabs > np.percentile(fabs, lower_percentile)) & (fabs < np.percentile(fabs, upper_percentile))
r2 = r[mask]
f2 = f[mask]
fabs2 = fabs[mask]
# Force
fig2 = plt.figure()
ax2 = fig2.gca(projection='3d', label='fitted-forces', rasterized=True)
color_bounds2 = np.array([np.percentile(fabs2, 0.1), np.percentile(fabs2, 99.9)]) * 10 ** -6
for r2i, f2i, fabs2i in tqdm(zip(r2 * 10 ** 6, f2 * 10 ** -6, fabs2 * (10 ** -6))): #*f_scale
color = plt.cm.hot(((fabs2i - color_bounds2[0]) / (color_bounds2[1] - color_bounds2[0])))
# alpha = 1. - (r2i[0] - r2i[1]) / (270. * 1.25)
# if alpha > 1:
# alpha = 1.
alpha = 1.
ax2.quiver(r2i[0], r2i[1], r2i[2], f2i[0], f2i[1], f2i[2], length=fabs2i * arrow_factor ,
color=color, arrow_length_ratio=0, alpha=alpha, pivot='tip', linewidth=0.5)
# plot colorbar ---------------------------------------------------------
cbaxes = fig2.add_axes([0.15, 0.1, 0.125, 0.010])
cmap = plt.cm.hot
norm = plt.Normalize(vmin=color_bounds2[0], vmax=color_bounds2[1])
cb1 = ColorbarBase(cbaxes, cmap=cmap, norm=norm, orientation='horizontal')
cb1.set_label('Force Den. [pN/µm³]')
tick_locator = ticker.MaxNLocator(nbins=3)
cb1.locator = tick_locator
cb1.update_ticks()
# -------------------------------------------------------------------------
#ax2.set_xlim([-150, 150]) can be used to make an individual plot
#ax2.set_ylim([-150, 150])
#ax2.set_zlim([-150, 150])
#ax2.set_xticks([-100, -50, 0, 50, 100])
#ax2.set_yticks([-100, -50, 0, 50, 100])
#ax2.set_zticks([-100, -50, 0, 50, 100])
# ax2.set_xticklabels(['']*5)
# ax2.set_yticklabels(['']*5)
# ax2.set_zticklabels(['']*5)
ax2.w_xaxis.set_pane_color((0.2, 0.2, 0.2, 1.0))
ax2.w_yaxis.set_pane_color((0.2, 0.2, 0.2, 1.0))
ax2.w_zaxis.set_pane_color((0.2, 0.2, 0.2, 1.0))
if save_plot:
plt.savefig( os.path.join(simulation_folder,'force_density_plot_lower_{}_upper_{}.png'.format(lower_percentile, upper_percentile)), dpi=500 , bbox_inches="tight", pad_inches=0)
return
