def __common_plotting(self,
fermi_surface,
plotter: pv.Plotter,
mode:str,
text:str,
spin_texture:bool=False,
camera_pos:List[float]=[1, 1, 1],
background_color:str or Tuple[float,float,float,float]="white",
perspective:bool=True,
show:bool=False,
save_2d:bool=None,
save_gif:str=None,
save_mp4:str=None,
save_3d:str=None):
if mode != "plain" or spin_texture:
plotter.add_scalar_bar(
title=text,
n_labels=6,
italic=False,
bold=False,
title_font_size=None,
label_font_size=None,
position_x=0.4,
position_y=0.01,
color="black",)
plotter.add_axes(
xlabel="Kx",
ylabel="Ky",
zlabel="Kz",
line_width=6,
labels_off=False)
if not perspective:
plotter.enable_parallel_projection()
plotter.set_background(background_color)
if not show:
plotter.show(cpos=camera_pos, screenshot=save_2d)
if save_gif is not None:
path = plotter.generate_orbital_path(n_points=36)
plotter.open_gif(save_gif)
plotter.orbit_on_path(path)
if save_mp4:
path = plotter.generate_orbital_path(n_points=36)
plotter.open_movie(save_mp4)
plotter.orbit_on_path(path)
if save_3d is not None:
plotter.save_meshio(save_3d, fermi_surface)
def plot_boreholes_3d(df: pd.DataFrame,
plotter: pv.Plotter,
min_length: Union[float, int],
color_dict: dict,
show_labels=False,
labels=None,
ve=1,
**kwargs):
"""
Plot boreholes in 3D
df: pd.DataFrame containing the extracted borehole data
min_length: float/int defining the minimum depth of boreholes to be plotted
color_dict: dict containing the surface colors of the model
labels: PyVista polydata object containing the name and coordinates of cities
show_labels: bool for showing city labels
Kwargs:
radius: float/int of the radius of the boreholes plotted with PyVista, default = 10
"""
# Checking if df is of a pandas DataFrame
if not isinstance(df, pd.DataFrame):
raise TypeError('Borehole data must be provided as Pandas DataFrame')
# Checking that all necessary columns are present in the DataFrame
if not pd.Series([
'Index', 'Name', 'X', 'Y', 'Z', 'Altitude', 'Depth', 'formation'
]).isin(df.columns).all():
raise ValueError(
'[%s, %s, %s, %s, %s, %s, %s, %s] need to be columns in the provided DataFrame'
%
('Index', 'Name', 'X', 'Y', 'Z', 'Altitude', 'Depth', 'formation'))
# Checking that the min_limit is of type float or int
if not isinstance(min_length, (float, int)):
raise TypeError(
'Minimum length for boreholes must be of type float or int')
# Checking that the color_dict is of type dict
if not isinstance(color_dict, dict):
raise TypeError('Surface color dictionary must be of type dict')
# Getting the radius for the tubes
radius = kwargs.get('radius', 10)
# Checking that the radius is of type int or float
if not isinstance(radius, (int, float)):
raise TypeError('The radius must be provided as int or float')
# Checking if show_labels is of type bool
if not isinstance(show_labels, bool):
raise TypeError('Show_label must be of type bool')
# Creating tubes for later plotting
tubes, df_groups = create_borehole_tubes(df,
min_length,
color_dict,
radius=radius)
# Plotting labels
if show_labels:
tubes["Labels"] = labels
plotter.add_point_labels(tubes, "Labels", point_size=5, font_size=10)
# Plotting the borehole data
for j in tqdm(range(len(tubes))):
df_groups[j] = df_groups[j][1:]
plotter.add_mesh(
mesh=tubes[j],
cmap=[color_dict[i] for i in df_groups[j]['formation'].unique()])
# Setting plotting parameters
plotter.set_scale(1, 1, ve)
plotter.set_background(color='white')
plotter.remove_scalar_bar()
plotter.add_bounding_box(color='black')
plotter.show_grid(color='black')