Source code for dynamo.plot.scPotential

from ..tools.utils import update_dict
from .utils import save_fig


[docs]def show_landscape( adata, Xgrid, Ygrid, Zgrid, basis="umap", save_show_or_return="show", save_kwargs={}, ): """Plot the quasi-potential landscape. Parameters ---------- adata: :class:`~anndata.AnnData` AnnData object that contains Xgrid, Ygrid and Zgrid data for visualizing potential landscape. Xgrid: `numpy.ndarray` x-coordinates of the Grid produced from the meshgrid function. Ygrid: `numpy.ndarray` y-coordinates of the Grid produced from the meshgrid function. Zgrid: `numpy.ndarray` z-coordinates or potential at each of the x/y coordinate. basis: `str` (default: umap) The method of dimension reduction. By default it is trimap. Currently it is not checked with Xgrid and Ygrid. save_show_or_return: {'show', 'save', 'return'} (default: `show`) Whether to save, show or return the figure. save_kwargs: `dict` (default: `{}`) A dictionary that will passed to the save_fig function. By default it is an empty dictionary and the save_fig function will use the {"path": None, "prefix": 'show_landscape', "dpi": None, "ext": 'pdf', "transparent": True, "close": True, "verbose": True} as its parameters. Otherwise you can provide a dictionary that properly modify those keys according to your needs. Returns ------- A 3D plot showing the quasi-potential of each cell state. """ if "grid_Pot_" + basis in adata.uns.keys(): Xgrid_, Ygrid_, Zgrid_ = ( adata.uns["grid_Pot_" + basis]["Xgrid"], adata.uns["grid_Pot_" + basis]["Ygrid"], adata.uns["grid_Pot_" + basis]["Zgrid"], ) Xgrid = Xgrid_ if Xgrid is None else Xgrid Ygrid = Ygrid_ if Ygrid is None else Ygrid Zgrid = Zgrid_ if Zgrid is None else Zgrid from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt from matplotlib import cm from matplotlib.ticker import LinearLocator, FormatStrFormatter from matplotlib.colors import LightSource fig = plt.figure() ax = fig.gca(projection="3d") # Plot the surface. ls = LightSource(azdeg=0, altdeg=65) # Shade data, creating an rgb array. rgb = ls.shade(Zgrid, plt.cm.RdYlBu) surf = ax.plot_surface( Xgrid, Ygrid, Zgrid, cmap=cm.coolwarm, rstride=1, cstride=1, facecolors=rgb, linewidth=0, antialiased=False, ) # Customize the z axis. ax.zaxis.set_major_locator(LinearLocator(10)) ax.zaxis.set_major_formatter(FormatStrFormatter("%.02f")) # Add a color bar which maps values to colors. # fig.colorbar(surf, shrink=0.5, aspect=5) ax.set_xlabel(basis + "_1") ax.set_ylabel(basis + "_2") ax.set_zlabel("U") if save_show_or_return == "save": s_kwargs = { "path": None, "prefix": "show_landscape", "dpi": None, "ext": "pdf", "transparent": True, "close": True, "verbose": True, } s_kwargs = update_dict(s_kwargs, save_kwargs) save_fig(**s_kwargs) elif save_show_or_return == "show": plt.tight_layout() plt.show() elif save_show_or_return == "return": return ax
# show_pseudopot(Xgrid, Ygrid, Zgrid) # % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% # % % -- Plot selected paths on pot. surface -- # % path_spacing = 4; # % hold on; # % for n_path = 1:numPaths # % if ( ((mod(x_path(n_path, 1), path_spacing) == 0) && (mod(y_path(n_path, 1), path_spacing) == 0)) ... # % || ((mod(y_path(n_path, 1), path_spacing) == 0) && (mod(x_path(n_path, 1), path_spacing) == 0)) ) # % # % % % *** To generate log-log surface *** # % % x_path(n_path, :) = x_path(n_path, :) + 0.1; # % % y_path(n_path, :) = y_path(n_path, :) + 0.1; # % % % *** # % # % if (path_tag(n_path) == 1) # % plot3(x_path(n_path, :), y_path(n_path, :), pot_path(n_path, :) ... # % , '-r' , 'MarkerSize', 1) % plot paths # % elseif (path_tag(n_path) == 2) # % plot3(x_path(n_path, :), y_path(n_path, :), pot_path(n_path, :) ... # % , '-b' , 'MarkerSize', 1) % plot paths # % elseif (path_tag(n_path) == 3) # % plot3(x_path(n_path, :), y_path(n_path, :), pot_path(n_path, :) ... # % , '-g' , 'MarkerSize', 1) % plot paths # % end # % hold on; # % # % end # % end