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plot_utils.py
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plot_utils.py
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import matplotlib
from matplotlib import pyplot as plt
import numpy as np
from tqdm import tqdm, trange
from scipy.spatial import Voronoi, voronoi_plot_2d
import vtk
from vtk.util import numpy_support
from matplotlib import colors as mcolors
# from scipy.stats import norm as snorm
try:
import qt_utils
except ImportError:
print('Could not import qt properly')
import vtk_utils
try:
matplotlib.rcParams.update({
"pgf.texsystem": "pdflatex",
'font.family': 'serif',
'text.usetex': True,
'pgf.rcfonts': False,
})
except:
print('Could not Latex-ify labels ')
# sudo apt-get install dvipng texlive-latex-extra texlive-fonts-recommended cm-super
print('Current backend', matplotlib.pyplot.get_backend())
conflicting_backends = ['QtAgg', 'Qt5Agg']
if matplotlib.pyplot.get_backend() in conflicting_backends:
try:
matplotlib.use('GTK3Agg')
print('backend set to GTK3Agg to avoid conflict with VTK plot')
except:
print('Tried to switch to GTK3, failed')
print('Currently using:', matplotlib.get_backend())
def plot_edge_matrix(edge_matrix):
plt.figure(figsize=(10,10))
plt.scatter(edge_matrix[:,0], edge_matrix[:,1])
plt.xlabel('Parent Node ID')
plt.ylabel('Child Node ID')
plt.gca().set_aspect(1)
plt.tight_layout()
plt.show()
def plot_level_frequency(levels):
plt.figure()
# plt.hist(levels)
levels_x, counts = np.unique(levels, return_counts=True)
plt.bar(levels_x, height=counts)
plt.xlabel('Node Level')
plt.ylabel('Frequency')
plt.show()
def plot_time_complexity(dataset_sizes, execution_times):
# execution_times_tree = execution_times_tree
plt.figure()
plt.grid()
plt.scatter(dataset_sizes, execution_times, label='Exhaustive Search')
# time_matrix = list()
# for i in range(2, 31):
# filename = 'times_taken_tree_numba-%i.npy' % i
# times = np.load(filename)
# time_matrix.append(times)
# time_matrix = np.asarray(time_matrix)
# size_matrix = np.tile(dataset_sizes, [time_matrix.shape[0],1])
# data_matrix = np.dstack((size_matrix, time_matrix))
# print(time_matrix.shape, size_matrix.shape, data_matrix.shape)
# color_range = np.linspace(0, 1, time_matrix.shape[0])
# line_colors = [cm.jet(c) for c in color_range]
# plt.scatter(dataset_sizes, times, label='Node size %i' % i)
# line_segments = LineCollection(segments=data_matrix, colors=line_colors)
# plt.gca().add_collection(line_segments)
# for t, time in enumerate(time_matrix):
# plt.scatter(dataset_sizes, time, label='Node size = %i' %(t+2), color=line_colors[t])
# plt.scatter(dataset_sizes, execution_times_tree, label='MTree-Accelerated Search')
plt.xlabel('Dataset Size')
plt.ylabel('Execution time (s)')
# x0 = dataset_sizes[0]
# t0e = execution_times_exhaustive[0]
# xn = dataset_sizes / x0
# xs = np.power(xn, 3) * 0.63
# plt.plot(dataset_sizes, xs, label='$O x^3$ Time Complexity Fit', linestyle='dashed')
# x0 = dataset_sizes[0]
# t0t = execution_times_tree[0]
# xn = dataset_sizes / x0
# xt = np.power(xn, 2) * t0t * 0.16
# plt.plot(dataset_sizes, xt, label='$O x^2$ Time Complexity Fit', linestyle='dashed')
plt.legend()
plt.show()
def plot_2D_map(vertex_dict, vertex_level=0, reference_data=None, query_data=None, query_radius=None, edges=None, colors=None, savename=None, return_figure=False, figure=None, use_legend=True, convex_hull=False):
if figure is not None:
fig = figure
else:
fig = plt.figure(figsize=(10,10))
ax = plt.gca()
# where some data has already been plotted to ax
handles, labels = ax.get_legend_handles_labels()
if reference_data is not None:
if reference_data.shape[0] > 2:
vor = Voronoi(reference_data[:,:2])
fig = voronoi_plot_2d(vor, ax=ax, show_vertices=False, line_colors='k', line_width=1, line_alpha=0.6, point_size=0.5)
if query_data is not None:
if np.ndim(query_data) == 2:
plt.scatter(query_data[:,0], query_data[:,1], c='r', zorder=0, label='Query Point', marker='x')
elif np.ndim(query_data) == 1:
if query_radius is not None:
circle1 = plt.Circle((query_data[0], query_data[1]), query_radius, color='lime', fill=True, alpha=0.2, label='Query Point')
plt.gca().add_patch(circle1)
plt.scatter(query_data[0], query_data[1], c='r', zorder=0, label='Query Point', marker='x')
if colors is not None:
circle_color = colors[vertex_level % len(colors)]
else:
circle_color = 'k'
colors = ['k']
scatter_points = list()
for vertex_ID in tqdm(vertex_dict.keys()):
vertex_data = vertex_dict[vertex_ID]
# print(vertex_data)
if vertex_data[1] is None:
print('centroid is None, presumably this is the old MTree format?')
centroid = [0, 0]
radius = 200
else:
# return fig
centroid = vertex_data[1]
radius = vertex_data[2]
scatter_points.append(centroid[:2])
circle1 = plt.Circle((centroid[0], centroid[1]), radius, color=circle_color, fill=False, alpha=0.8, linestyle='dashed')
plt.gca().add_patch(circle1)
if edges is not None:
for edge in edges:
# print(edge)
if edge[0] is None:
edge[0] = [0,0]
if edge[1] is None:
continue
movement_vector = edge[1] - edge[0]
plt.arrow(edge[0][0], edge[0][1], movement_vector[0], movement_vector[1], zorder=10, head_width=0.5, length_includes_head=True, color=colors[vertex_level % len(colors)])
# plt.plot([edge[0][0], edge[1][0]], [edge[0][1], edge[1][1]], color=colors[vertex_level % len(colors)])
scatter_points = np.asarray(scatter_points)
plt.scatter(scatter_points[:,0], scatter_points[:,1], color=colors[vertex_level % len(colors)], label='Level %i' % vertex_level)
if vertex_level is not None:
plt.title('Node depth %i' % vertex_level)
plt.gca().set_aspect('equal')
plt.tight_layout()
plt.legend()
if savename is not None:
plt.savefig(savename, dpi=600)
plt.close()
elif return_figure:
fig = plt.gcf()
return fig
else:
plt.show()
def plot_2D_map_flattened(vertex_dict, reference_data=None, children=None, save_name=None, colors=None):
levelled_vertices = dict()
if children is not None:
levelled_edges = dict()
for dict_key in tqdm(vertex_dict.keys()):
vertex_data = vertex_dict[dict_key]
vertex_level = vertex_data[3]
if children is not None:
if vertex_level not in levelled_edges.keys():
sublist = list()
levelled_edges.update({vertex_level:sublist})
edge_data = children.get(dict_key)
# print(edge_data.shape)
if edge_data is not None:
origin = vertex_data[1]
for edge in edge_data:
# print(edge)
terminus = vertex_dict.get(edge[0])[1]
# print(origin, terminus)
levelled_edges[vertex_level].append([origin, terminus])
if vertex_level not in levelled_vertices.keys():
print('Adding %i level' % vertex_level)
subdict = dict()
subdict.update({dict_key:vertex_data})
levelled_vertices.update({vertex_level:subdict})
else:
levelled_vertices[vertex_level].update({dict_key:vertex_data})
if reference_data is not None:
if reference_data.shape[0] > 2:
vor = Voronoi(reference_data[:,:2])
flat_figure = voronoi_plot_2d(vor, show_vertices=False, line_colors='k', line_width=1, line_alpha=0.6, point_size=0.5)
else:
flat_figure = plt.figure()
for vertex_level in levelled_vertices.keys():
subdict = levelled_vertices[vertex_level]
if children is not None:
edge_data = levelled_edges[vertex_level]
flat_figure = plot_2D_map(subdict, vertex_level=vertex_level, reference_data=None, edges=edge_data, figure=flat_figure, return_figure=True, colors=colors)
plt.show()
def plot_2D_map_levelled(vertex_dict, reference_data=None, save_name=None, colors=None):
levelled_vertices = dict()
for dict_key in tqdm(vertex_dict.keys()):
vertex_data = vertex_dict[dict_key]
vertex_level = vertex_data[3]
if vertex_level not in levelled_vertices.keys():
print('Adding %i level' % vertex_level)
subdict = dict()
subdict.update({dict_key:vertex_data})
levelled_vertices.update({vertex_level:subdict})
else:
levelled_vertices[vertex_level].update({dict_key:vertex_data})
for vertex_level in levelled_vertices.keys():
subdict = levelled_vertices[vertex_level]
plot_2D_map(subdict, vertex_level=vertex_level, reference_data=reference_data)
def plot_dataset_variance(dataset):
np.seterr(under='ignore')
print(dataset.shape)
# Create a figure instance
fig = plt.figure()
# Create an axes instance
ax = fig.add_axes([0,0,1,1])
# Create the boxplot
violin_axes = list()
for dim in tqdm(range(50)):
# for dim in tqdm(range(dataset.shape[1])):
dim_data = dataset[:,dim].astype(float)
violin_axes.append(dim_data)
bp = ax.violinplot(violin_axes)
plt.grid()
# print(bp)
plt.show()
def plot_vtk(locations=None, scalars=None, actor_dict=None, scalar_name='Values', title=None, glyph_scale=1, glyph_type='cube', colormap='viridis', show_scalar_bar=True, show_axes=True, use_qt=False):
if actor_dict is None:
actor_dict = dict()
if locations is not None:
if locations.shape[1] == 2:
third = np.zeros([locations.shape[0],1])
locations = np.hstack([locations, third])
if scalars is None:
scalars = np.ones(locations.shape[0])
if type(scalars) is not dict:
scalar_dict = {scalar_name:scalars}
else:
scalar_dict = scalars
if show_scalar_bar:
if show_axes:
actor_dict.update({'<[polydata': vtk_utils.add_polydata(locations=locations, scalar_dict=scalar_dict, glyph_scale=glyph_scale, glyph_type=glyph_type, colormap=colormap)})
else:
actor_dict.update({'[polydata': vtk_utils.add_polydata(locations=locations, scalar_dict=scalar_dict, glyph_scale=glyph_scale, glyph_type=glyph_type, colormap=colormap)})
elif show_axes:
actor_dict.update({'<polydata': vtk_utils.add_polydata(locations=locations, scalar_dict=scalar_dict, glyph_scale=glyph_scale, glyph_type=glyph_type, colormap=colormap)})
if use_qt:
qt_utils.render_data(actor_dict=actor_dict)
else:
create_renderer(actors=actor_dict)
else:
if use_qt:
qt_utils.render_data(actor_dict=actor_dict)
else:
create_renderer(actors=actor_dict)
def create_renderer(actors=None,
title='field',
background_color='White',
add_skybox=False,
window_size=(600, 600),
display=True):
renderer = vtk.vtkRenderer()
# try:
# cube_path = 'data/cubemap/lab'
# cubemap = ReadCubeMap(cube_path, '/', '.png', 2)
# if add_skybox:
# skybox = ReadCubeMap(cube_path, '/', '.png', 2)
# # skybox = ReadCubeMap(cube_path, '/skybox', '.jpg', 2)
# skybox.InterpolateOn()
# skybox.RepeatOff()
# skybox.EdgeClampOn()
# skyboxActor = vtk.vtkSkybox()
# skyboxActor.SetTexture(skybox)
# renderer.AddActor(skyboxActor)
# renderer.UseImageBasedLightingOn()
# renderer.SetEnvironmentTexture(cubemap)
# except:
# print('raytracing failed to initialise, are you on VTK 9.0?')
render_camera = renderer.GetActiveCamera()
renderWindow = vtk.vtkRenderWindow()
renderWindow.SetSize(window_size)
renderWindow.AddRenderer(renderer)
renderWindow.PolygonSmoothingOn()
renderWindowInteractor = vtk.vtkRenderWindowInteractor()
renderWindowInteractor.SetRenderWindow(renderWindow)
renderWindowInteractor.SetInteractorStyle(vtk_utils.MyInteractorStyle(renderWindowInteractor, render_camera, renderWindow))
renderer.SetBackground(vtk.vtkNamedColors().GetColor3d(background_color))
renderer.SetUseDepthPeeling(1)
renderer.SetMaximumNumberOfPeels(10)
# print(dir(renderer))
# renderer.SetStereoTypeToSplitViewportHorizontal()
scalarbar_dict = dict()
if actors is not None:
if isinstance(actors, list):
print('List of actors supplied, adding list')
for actor in actors:
renderer.AddActor(actor)
elif isinstance(actors, dict):
print('List of actors supplied, adding list')
for key_name in actors:
if key_name[0] == '<':
axes_actor = vtk_utils.add_axes(actors[key_name], renderer, axes_type='cartesian', axes_placement='outer')
axes_key = '%s-axes' % (key_name)
renderer.AddActor(axes_actor)
if key_name[0] == '(':
axes_actor = vtk_utils.add_axes(actors[key_name], renderer, axes_type='polar', axes_placement='outer')
axes_key = '%s-axes' % (key_name)
renderer.AddActor(axes_actor)
if key_name[0] == '[':
try:
bar_actor = vtk_utils.add_colorbar(actors[key_name], title=key_name, return_widget=False, interactor=renderWindowInteractor)
bar_name = 'colorbar_' + key_name
scalarbar_dict.update({bar_name: bar_actor})
except AttributeError:
pass
if key_name[1] == '[':
print('adding scalar bar')
bar_actor = vtk_utils.add_colorbar(actors[key_name], title=key_name, return_widget=True, interactor=renderWindowInteractor)
bar_name = 'colorbar_' + key_name
scalarbar_dict.update({bar_name: bar_actor})
# renderer.AddActor(bar_actor)
if isinstance(actors[key_name], list):
for sub_actor in actors[key_name]:
renderer.AddActor(sub_actor)
elif type(actors[key_name]) is list:
for sub_actor in actors[key_name]:
renderer.AddActor(sub_actor)
elif isinstance(actors[key_name], dict):
for sub_actor in actors[key_name].values():
renderer.AddActor(sub_actor)
elif isinstance(actors[key_name], tuple):
for sub_actor in actors[key_name]:
renderer.AddActor(sub_actor)
else:
renderer.AddActor(actors[key_name])
else:
renderer.AddActor(actors)
renderer.ResetCamera()
# exporter = vtk.vtkJSONRenderWindowExporter()
# exporter.GetArchiver().SetArchiveName('/home/fraser/Videos/LiverView/vtk_only_2.js')
# exporter.SetRenderWindow(renderWindow)
# exporter.Write()
# exporter.Update()
# add_camera_widget(renderer, renderWindowInteractor)
if display:
renderWindow.Render()
renderWindowInteractor.Start()
return renderer, renderWindow, renderWindowInteractor
else:
return renderer, renderWindow, renderWindowInteractor
def test_3D_plot(ref_points=None, query_point=None, optimum=None, r_points=None):
actor_dict = dict()
sphere_res = 24
sphere_scale = 0.01
if ref_points is not None:
ref_vtk = vtk_utils.add_polydata(ref_points, glyph_scale=sphere_scale, glyph_type='sphere', resolution=sphere_res, colors='maroon')
actor_dict.update({'<Reference_points': ref_vtk})
if query_point is not None:
query_vtk = vtk_utils.add_polydata(query_point, glyph_scale=sphere_scale, glyph_type='sphere', resolution=sphere_res, colors='purple')
actor_dict.update({'query_point': query_vtk})
startpoints = np.tile(query_point,(3,1))
print(startpoints)
distances_vtk = vtk_utils.add_lines(np.hstack((ref_points, startpoints)), render_type='tube', tube_radius=0.002)
actor_dict.update({'distances_point': distances_vtk})
if optimum is not None:
optimum_vtk = vtk_utils.add_polydata(optimum, glyph_scale=sphere_scale, glyph_type='sphere', resolution=sphere_res, colors='purple')
actor_dict.update({'optimum_point': optimum_vtk})
if query_point is not None:
vector_vtk = vtk_utils.add_line(startPoint=query_point, endPoint=optimum, linewidth=2)
actor_dict.update({'vector': vector_vtk})
tri_1 = vtk_utils.add_polygon(vertices=np.asarray([ref_points[0], ref_points[1], optimum]))
actor_dict.update({'tri_1': tri_1})
tri_2 = vtk_utils.add_polygon(vertices=np.asarray([ref_points[0], ref_points[2], optimum]), mesh_color='Green')
actor_dict.update({'tri_2': tri_2})
tri_3 = vtk_utils.add_polygon(vertices=np.asarray([ref_points[1], ref_points[2], optimum]), mesh_color='Blue')
actor_dict.update({'tri_3': tri_3})
else:
if ref_points is not None:
del_actor = vtk_utils.generate_delaunay_space(ref_vtk, opacity=0.5)
actor_dict.update({'del space': del_actor})
if r_points is not None:
r_vtk = vtk_utils.add_polydata(r_points, glyph_scale=sphere_scale, glyph_type='sphere', resolution=sphere_res, colors='purple')
actor_dict.update({'r_points': r_vtk})
# tri_points = np.zeros([3,3])
# tri_points[0,:] = [1,0,0]
# tri_points[1,:] = [0,1,0]
# tri_points[2,:] = [0,0,1]
# tri = add_polygon(vertices=tri_points, mesh_color='blue', opacity=0.2)
# actor_dict.update({'111': tri})
# outline = vtk_utils.add_outline(corner_vtk)
# actor_dict.update({'outine': outline})
plot_vtk(actor_dict=actor_dict, use_qt=True)
def plot_3D_scatter(points, glyph_scale=0.5, scalars=None, colors=None, labels=None):
point_actor = vtk_utils.add_polydata(points, scalar_dict=scalars, colors=colors, glyph_type='sphere', resolution=12, glyph_scale=glyph_scale)
# axes_actor = add_axes(point_actor)
actor_dict = dict()
actor_dict.update({'<locs': point_actor})
# actor_dict.update({'axes': axes_actor})
if labels is not None:
label_actor = vtk_utils.add_labels(points, labels)
actor_dict.update({'labels': label_actor})
plot_vtk(actor_dict=actor_dict)