def test_plot_3d_montage(requires_pyvista, fname_raw, to_1020, ch_names):
import pyvista
pyvista.close_all()
assert len(pyvista.plotting._ALL_PLOTTERS) == 0
raw = mne.io.read_raw_nirx(fname_raw)
if to_1020:
need = set(
sum((ch_name.split()[0].split('_') for ch_name in raw.ch_names),
list()))
mon = mne.channels.make_standard_montage('standard_1020')
mon.rename_channels({h: n for h, n in zip(mon.ch_names, need)})
raw.set_montage(mon)
n_labels = len(raw.ch_names) // 2
view_map = {
'left-lat': np.arange(1, n_labels // 2),
'caudal': np.arange(n_labels // 2, n_labels + 1)
}
# We use "sample" here even though it's wrong so that we can have a head
# surface
with catch_logging() as log:
mne_nirs.viz.plot_3d_montage(raw.info,
view_map,
subject='sample',
surface='white',
subjects_dir=subjects_dir,
ch_names=ch_names,
verbose=True)
assert len(pyvista.plotting._ALL_PLOTTERS) == 0
log = log.getvalue().lower()
if to_1020:
assert 'automatically mapped' in log
else:
assert 'could not' in log
def test_closing_and_mem_cleanup():
n = 5
for i in range(n):
for j in range(n):
p = pyvista.Plotter(off_screen=OFF_SCREEN)
for k in range(n):
p.add_mesh(pyvista.Sphere(radius=k))
p.show()
pyvista.close_all()
def test_closing_and_mem_cleanup():
n = 5
for _ in range(n):
for _ in range(n):
p = pyvista.Plotter()
for k in range(n):
p.add_mesh(pyvista.Sphere(radius=k))
p.show()
pyvista.close_all()
def check_gc():
"""Ensure that all VTK objects are garbage-collected by Python."""
before = set(id(o) for o in gc.get_objects() if _is_vtk(o))
yield
pyvista.close_all()
gc.collect()
after = [o for o in gc.get_objects() if _is_vtk(o) and id(o) not in before]
assert len(after) == 0, \
'Not all objects GCed:\n' + \
'\n'.join(sorted(o.__class__.__name__ for o in after))
def render_figures(
code,
code_path,
output_dir,
output_base,
context,
function_name,
config,
):
"""Run a pyplot script and save the images in *output_dir*.
Save the images under *output_dir* with file names derived from
*output_base*
"""
# Try to determine if all images already exist
is_doctest, code_pieces = _split_code_at_show(code)
# Otherwise, we didn't find the files, so build them
results = []
ns = plot_context if context else {}
for i, code_piece in enumerate(code_pieces):
# generate the plot
_run_code(
doctest.script_from_examples(code_piece)
if is_doctest else code_piece, code_path, ns, function_name)
images = []
figures = pyvista.plotting._ALL_PLOTTERS
for j, (address, plotter) in enumerate(figures.items()):
if hasattr(plotter, '_gif_filename'):
image_file = ImageFile(output_dir,
f"{output_base}_{i:02d}_{j:02d}.gif")
shutil.move(plotter._gif_filename, image_file.filename)
else:
image_file = ImageFile(output_dir,
f"{output_base}_{i:02d}_{j:02d}.png")
plotter.screenshot(image_file.filename)
images.append(image_file)
pyvista.close_all() # close and clear all plotters
results.append((code_piece, images))
return results
def __call__(self, block, block_vars, gallery_conf): # noqa:D101
from sphinx_gallery.scrapers import figure_rst
image_names = list()
image_path_iterator = block_vars["image_path_iterator"]
figures = pyvista.plotting._ALL_PLOTTERS
seen_plotters = list()
for address, plotter in figures.items():
if plotter in seen_plotters:
continue
seen_plotters += [plotter]
fname = next(image_path_iterator)
if hasattr(plotter, '_gif_filename'):
# move gif to fname
shutil.move(plotter._gif_filename, fname)
else:
plotter.screenshot(fname)
image_names.append(fname)
pyvista.close_all() # close and clear all plotters
return figure_rst(image_names, gallery_conf["src_dir"])
def test_scraper(tmpdir):
pytest.importorskip('sphinx_gallery')
pyvista.close_all()
plotter = pyvista.Plotter(off_screen=True)
scraper = Scraper()
src_dir = str(tmpdir)
out_dir = op.join(str(tmpdir), '_build', 'html')
img_fname = op.join(src_dir, 'auto_examples', 'images', 'sg_img.png')
gallery_conf = {"src_dir": src_dir, "builder_name": "html"}
target_file = op.join(src_dir, 'auto_examples', 'sg.py')
block = None
block_vars = dict(image_path_iterator=(img for img in [img_fname]),
example_globals=dict(a=1),
target_file=target_file)
os.makedirs(op.dirname(img_fname))
assert not os.path.isfile(img_fname)
os.makedirs(out_dir)
scraper(block, block_vars, gallery_conf)
assert os.path.isfile(img_fname)
plotter.close()
def plot_prediction(index, prediction, gound_truth, labels, path, title=""):
"""Plots a picture for each class with the mesh and the labels predicted for it in red if it is wrong and green if it is correct.
:param index: array[n_labels]
An array containing the index of the test meshes for each class
:param prediction: array[n_prediction]
The result of the classification
:param gound_truth: array[n_prediction]
The gound truth labels in the same order of prediction
:param labels: list
A list containing the classes
:param path: string or os.path
The path where to save the plots
:return:
"""
os.makedirs(os.path.join(path, "Qualitative"), exist_ok=True)
i_prediction = 0
err = prediction == gound_truth
for inds, l in zip(index, labels):
plotter = pv.Plotter(shape=(1, index[0].shape[0]),
off_screen=False,
window_size=[1024, 1024 // 2])
plotter.set_background("white")
j = 0
offs = glob.glob(os.path.join('.', 'Dataset', l, "*.off"))
for i in inds:
mesh = pv.read(offs[i])
plotter.subplot(0, j)
plotter.add_text(labels[prediction[i_prediction]],
color="green" if err[i_prediction] else "red",
font_size=10)
plotter.add_mesh(mesh, smooth_shading=True, color="grey")
j += 1
i_prediction += 1
plotter.save_graphic(
os.path.join(path, "Qualitative", l + title + '.pdf'))
pv.close_all()
return
def __call__(self, block, block_vars, gallery_conf):
"""
Called by sphinx-gallery to save the figures generated after running
example code.
"""
try:
from sphinx_gallery.scrapers import figure_rst
except ImportError:
raise ImportError('You must install `sphinx_gallery`')
image_names = list()
image_path_iterator = block_vars["image_path_iterator"]
figures = pyvista.plotting._ALL_PLOTTERS
for address, plotter in figures.items():
fname = next(image_path_iterator)
if hasattr(plotter, '_gif_filename'):
# move gif to fname
shutil.move(plotter._gif_filename, fname)
else:
plotter.screenshot(fname)
image_names.append(fname)
pyvista.close_all() # close and clear all plotters
return figure_rst(image_names, gallery_conf["src_dir"])
def _close_all():
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning)
close_all()
def plot_mesh(vertices,
faces=None,
input_file_name=None,
darkmode=True,
background_color='k',
text=None,
window_size=[1280, 720],
font_color='w',
cpos=[(3.77, 3.77, 3.77), (0.0069, -0.0045, 0.0),
(0.0, 0.0, 1.0)]):
'''visualize the mesh surface using vtk and return an img.
vertices is a numpy array of vertices with faces.
faces is a numpy array of indices specifying the faces of the surface of the mesh using ^those vertices.
input_file_name is a string giving the path to a file containing ^those faces (e.g. *.ply or *.stl).
an example text=f'time={tme:.1f}'
window_size = [1280,720] is the standard aspect ratio for youtube,
'''
#visualize the mesh surface
pv.set_plot_theme('document')
#get the vtk object (wrapped by pyvista from withing tetgen. Faces recorded by trimesh))
if faces is None:
if input_file_name is None:
Exception('either faces or input_file_name must be specified')
mesh_trimesh = trimesh.load(input_file_name)
faces = mesh_trimesh.faces
tet = tetgen.TetGen(vertices, faces)
# #fault tolerant tetrahedralization
vertices_tet, elements_tet = tet.tetrahedralize(order=1,
mindihedral=0.,
minratio=10.,
nobisect=False,
steinerleft=100000) #
tet.make_manifold()
grid = tet.grid
# advanced plotting
plotter = pv.Plotter()
if darkmode:
plotter.set_background(background_color)
plotter.add_mesh(grid, 'lightgrey', lighting=True)
#looks like tron plotter.add_mesh(grid, 'r', 'wireframe')
else:
plotter.add_mesh(grid, 'lightgrey', lighting=True)
font_color = 'k'
if text is not None:
plotter.add_text(text,
position='upper_left',
font_size=24,
color=font_color,
font='times')
#font options
# FONT_KEYS = {'arial': vtk.VTK_ARIAL,
# 'courier': vtk.VTK_COURIER,
# 'times': vtk.VTK_TIMES}
#cpos is (camera position, focal point, and view up)
#for movies, just set the camera position to some constant value.
_cpos, img = plotter.show(title=None,
return_img=True,
cpos=cpos,
window_size=window_size,
use_ipyvtk=False,
interactive=False,
auto_close=True)
plotter.deep_clean()
del plotter
pv.close_all()
return img
def _close_all():
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning)
from pyvista import close_all
close_all()
def _close_all():
pyvista.close_all()
def plot2D(file,
field,
bounds,
ax=None,
contours=False,
colorbar=False,
cfields=['crust_upper', 'crust_lower', 'mantle_lithosphere'],
null_field='asthenosphere',
**kwargs):
"""
Plot 2D ASPECT results using Pyvista.
Parameters
----------
file : VTU or PVTU file to plot
field : Field to use for color.
bounds : List of bounds (km) by which to clip the plot.
contours : Boolean for whether to add temperature contours.
The default is False.
cfields : Names of compositional fields to use if field is 'comp_field.'
The default is ['crust_upper','crust_lower','mantle_lithosphere'].
null_field : Null field if field is 'comp_field.'
The default is 'asthenosphere'.
Returns
-------
"""
mesh = pv.read(file)
km2m = 1000
bounds_m = [bound * km2m for bound in bounds] # Convert bounds to m
bounds_3D = bounds_m + [0, 0]
mesh = mesh.clip_box(bounds=bounds_3D, invert=False)
if field == 'comp_field':
mesh = comp_field_vtk(mesh, fields=cfields, null_field=null_field)
if contours == True:
cntrs = add_contours(mesh)
pv.set_plot_theme("document")
plotter = pv.Plotter(off_screen=True)
sargs = dict(width=0.6,
fmt='%.1e',
height=0.2,
label_font_size=32,
position_x=0.1)
plotter.add_mesh(mesh, scalars=field, scalar_bar_args=sargs, **kwargs)
if contours == True:
plotter.add_mesh(cntrs, color='black', line_width=5)
plotter.view_xy()
if colorbar == False:
plotter.remove_scalar_bar()
plotter.enable_depth_peeling(10)
# Calculate Camera Position from Bounds
bounds_array = np.array(bounds_m)
xmag = float(abs(bounds_array[1] - bounds_array[0]))
ymag = float(abs(bounds_array[3] - bounds_array[2]))
aspect_ratio = ymag / xmag
plotter.window_size = (1024, int(1024 * aspect_ratio))
xmid = xmag / 2 + bounds_array[0] # X midpoint
ymid = ymag / 2 + bounds_array[2] # Y midpoint
zoom = xmag * aspect_ratio * 1.875 # Zoom level - not sure why 1.875 works
position = (xmid, ymid, zoom)
focal_point = (xmid, ymid, 0)
viewup = (0, 1, 0)
camera = [position, focal_point, viewup]
# print(camera)
plotter.camera_position = camera
plotter.camera_set = True
# Create image
img = plotter.screenshot(transparent_background=True, return_img=True)
# Plot using imshow
if ax is None:
ax = plt.gca()
ax.imshow(img, aspect='equal', extent=bounds)
plotter.clear()
pv.close_all()
return (ax)
