6DhASSKJrJr SSKJr SSKJr \R"S5r Sr SSjr S Sjr g) ) exceptionsoptional_importsN) graph_objsnumpycX4:a[R"S5e[U5S:Xa3USn[R"U5n[R "U5nU$X:Xa3USn[R"U5n[R "U5nU$UcX- [ XC- 5- n[US[U5S- - - 5n[R"XXS-U[U5S- -U- 5n[R"U5n[R "U5nU$X- [ XC- 5- nSn[[U5S- 5H!nX(Us=::a X(S-:aO O O US- nM# X'n X'S-n [R"XXS-Xi- X- - 5n[R"U5n[R "U5nU$)a6 Normalize facecolor values by vmin/vmax and return rgb-color strings This function takes a tuple color along with a colormap and a minimum (vmin) and maximum (vmax) range of possible mean distances for the given parametrized surface. It returns an rgb color based on the mean distance between vmin and vmax zmIncorrect relation between vmin and vmax. The vmin value cannot be bigger than or equal to the value of vmax.rg?) r PlotlyErrorlenclrsconvert_to_RGB_255 label_rgbfloatintfind_intermediate_colorrange) facecolormapscalevminvmax face_colortlow_color_indexk low_scale_valhigh_scale_vals P/var/www/html/env/lib/python3.13/site-packages/plotly/figure_factory/_trisurf.pymap_face2colorrs |$$    8}a[ ,,Z8 ^^J/  |b\ ,,Z8 ^^J/  =t{ 44A!!sc(ma.?'@"ABO55)1,-S]Q&'/9J 00*8q/5Q</1$+ "2M"Q#67N55)1,-"~'EFJ 00sVcVUcSSSS.n[R"U5 [R"USSUS9upF[UUUUUUUUUU S9 n[ U U U U S9n[ R "UUU[ RR[ RRR"S0UD6[ RRR"S0UD6[ RRR"S0UD6[ USUS US S9S 9S 9n[ R"UUS 9$)a Returns figure for a triangulated surface plot :param (array) x: data values of x in a 1D array :param (array) y: data values of y in a 1D array :param (array) z: data values of z in a 1D array :param (array) simplices: an array of shape (ntri, 3) where ntri is the number of triangles in the triangularization. Each row of the array contains the indicies of the verticies of each triangle :param (str|tuple|list) colormap: either a plotly scale name, an rgb or hex color, a color tuple or a list of colors. An rgb color is of the form 'rgb(x, y, z)' where x, y, z belong to the interval [0, 255] and a color tuple is a tuple of the form (a, b, c) where a, b and c belong to [0, 1]. If colormap is a list, it must contain the valid color types aforementioned as its members :param (bool) show_colorbar: determines if colorbar is visible :param (list|array) scale: sets the scale values to be used if a non- linearly interpolated colormap is desired. If left as None, a linear interpolation between the colors will be excecuted :param (function|list) color_func: The parameter that determines the coloring of the surface. Takes either a function with 3 arguments x, y, z or a list/array of color values the same length as simplices. If None, coloring will only depend on the z axis :param (str) title: title of the plot :param (bool) plot_edges: determines if the triangles on the trisurf are visible :param (bool) showbackground: makes background in plot visible :param (str) backgroundcolor: color of background. Takes a string of the form 'rgb(x,y,z)' x,y,z are between 0 and 255 inclusive :param (str) gridcolor: color of the gridlines besides the axes. Takes a string of the form 'rgb(x,y,z)' x,y,z are between 0 and 255 inclusive :param (str) zerolinecolor: color of the axes. Takes a string of the form 'rgb(x,y,z)' x,y,z are between 0 and 255 inclusive :param (str) edges_color: color of the edges, if plot_edges is True :param (int|float) height: the height of the plot (in pixels) :param (int|float) width: the width of the plot (in pixels) :param (dict) aspectratio: a dictionary of the aspect ratio values for the x, y and z axes. 'x', 'y' and 'z' take (int|float) values Example 1: Sphere >>> # Necessary Imports for Trisurf >>> import numpy as np >>> from scipy.spatial import Delaunay >>> from plotly.figure_factory import create_trisurf >>> from plotly.graph_objs import graph_objs >>> # Make data for plot >>> u = np.linspace(0, 2*np.pi, 20) >>> v = np.linspace(0, np.pi, 20) >>> u,v = np.meshgrid(u,v) >>> u = u.flatten() >>> v = v.flatten() >>> x = np.sin(v)*np.cos(u) >>> y = np.sin(v)*np.sin(u) >>> z = np.cos(v) >>> points2D = np.vstack([u,v]).T >>> tri = Delaunay(points2D) >>> simplices = tri.simplices >>> # Create a figure >>> fig1 = create_trisurf(x=x, y=y, z=z, colormap="Rainbow", ... simplices=simplices) Example 2: Torus >>> # Necessary Imports for Trisurf >>> import numpy as np >>> from scipy.spatial import Delaunay >>> from plotly.figure_factory import create_trisurf >>> from plotly.graph_objs import graph_objs >>> # Make data for plot >>> u = np.linspace(0, 2*np.pi, 20) >>> v = np.linspace(0, 2*np.pi, 20) >>> u,v = np.meshgrid(u,v) >>> u = u.flatten() >>> v = v.flatten() >>> x = (3 + (np.cos(v)))*np.cos(u) >>> y = (3 + (np.cos(v)))*np.sin(u) >>> z = np.sin(v) >>> points2D = np.vstack([u,v]).T >>> tri = Delaunay(points2D) >>> simplices = tri.simplices >>> # Create a figure >>> fig1 = create_trisurf(x=x, y=y, z=z, colormap="Viridis", ... simplices=simplices) Example 3: Mobius Band >>> # Necessary Imports for Trisurf >>> import numpy as np >>> from scipy.spatial import Delaunay >>> from plotly.figure_factory import create_trisurf >>> from plotly.graph_objs import graph_objs >>> # Make data for plot >>> u = np.linspace(0, 2*np.pi, 24) >>> v = np.linspace(-1, 1, 8) >>> u,v = np.meshgrid(u,v) >>> u = u.flatten() >>> v = v.flatten() >>> tp = 1 + 0.5*v*np.cos(u/2.) >>> x = tp*np.cos(u) >>> y = tp*np.sin(u) >>> z = 0.5*v*np.sin(u/2.) >>> points2D = np.vstack([u,v]).T >>> tri = Delaunay(points2D) >>> simplices = tri.simplices >>> # Create a figure >>> fig1 = create_trisurf(x=x, y=y, z=z, colormap=[(0.2, 0.4, 0.6), (1, 1, 1)], ... simplices=simplices) Example 4: Using a Custom Colormap Function with Light Cone >>> # Necessary Imports for Trisurf >>> import numpy as np >>> from scipy.spatial import Delaunay >>> from plotly.figure_factory import create_trisurf >>> from plotly.graph_objs import graph_objs >>> # Make data for plot >>> u=np.linspace(-np.pi, np.pi, 30) >>> v=np.linspace(-np.pi, np.pi, 30) >>> u,v=np.meshgrid(u,v) >>> u=u.flatten() >>> v=v.flatten() >>> x = u >>> y = u*np.cos(v) >>> z = u*np.sin(v) >>> points2D = np.vstack([u,v]).T >>> tri = Delaunay(points2D) >>> simplices = tri.simplices >>> # Define distance function >>> def dist_origin(x, y, z): ... return np.sqrt((1.0 * x)**2 + (1.0 * y)**2 + (1.0 * z)**2) >>> # Create a figure >>> fig1 = create_trisurf(x=x, y=y, z=z, ... colormap=['#FFFFFF', '#E4FFFE', ... '#A4F6F9', '#FF99FE', ... '#BA52ED'], ... scale=[0, 0.6, 0.71, 0.89, 1], ... simplices=simplices, ... color_func=dist_origin) Example 5: Enter color_func as a list of colors >>> # Necessary Imports for Trisurf >>> import numpy as np >>> from scipy.spatial import Delaunay >>> import random >>> from plotly.figure_factory import create_trisurf >>> from plotly.graph_objs import graph_objs >>> # Make data for plot >>> u=np.linspace(-np.pi, np.pi, 30) >>> v=np.linspace(-np.pi, np.pi, 30) >>> u,v=np.meshgrid(u,v) >>> u=u.flatten() >>> v=v.flatten() >>> x = u >>> y = u*np.cos(v) >>> z = u*np.sin(v) >>> points2D = np.vstack([u,v]).T >>> tri = Delaunay(points2D) >>> simplices = tri.simplices >>> colors = [] >>> color_choices = ['rgb(0, 0, 0)', '#6c4774', '#d6c7dd'] >>> for index in range(len(simplices)): ... colors.append(random.choice(color_choices)) >>> fig = create_trisurf( ... x, y, z, simplices, ... color_func=colors, ... show_colorbar=True, ... edges_color='rgb(2, 85, 180)', ... title=' Modern Art' ... ) r)r%r&r'rET) colortypereturn_default_colorsr)rXrZrrrYr[)showbackgroundbackgroundcolor gridcolor zerolinecolorr%r&r')xaxisyaxiszaxis aspectratio)titler7heightscene)datalayout)r validate_colorsconvert_colors_to_same_typervrNrLayoutrScenerXAxisYAxisZAxisFigure)r%r&r'rWrrXrrZrr[rzr{r|r}rYrr7rdata1axisrs rcreate_trisurfrsB|AA.  "66G4uOH    # E %'#  D   %%##))//7$7##))//7$7##))//7$7c"k#&6+c:J & F   % 77r )NNFNNNN)NTNNz Trisurf PlotTTzrgb(230, 230, 230)rgb(255, 255, 255)rzrgb(50, 50, 50) rN) plotlyrr plotly.colorscolorsr plotly.graph_objsr get_moduler9rrvrrr rrsu/(  )AX   f"\  ("&!  %H8r