def register_cmap(name, colors, reverse=False): """Register a cmap given a name and either a cmap or an Nx3 or Nx4 ndarray or rgb(a) data. Calls to_linear_cmap(colors) before registering. Args: name (str, None): if None, name = colors.name; this will not play nicely with an ndarray colors (Colormap or ndarray): colors as either a matplotlib Colormap or an Nx3 or Nx4 ndarray or rgb(a) data reverse (bool): flip the lower and upper ends of the mapping """ if name is None: name = colors.name cmap = to_linear_cmap(name, colors, reverse=reverse) _register_cmap(name=name, cmap=cmap)
def register_cmap(name, colors, reverse=False): """Register a cmap given a name and either a cmap or an Nx3 or Nx4 ndarray or rgb(a) data. Calls to_linear_cmap(colors) before registering. Args: name (str, None): if None, name = colors.name; this will not play nicely with an ndarray colors (Colormap or ndarray): colors as either a matplotlib Colormap or an Nx3 or Nx4 ndarray or rgb(a) data reverse (bool): flip the lower and upper ends of the mapping """ if name is None: name = colors.name cmap = to_linear_cmap(name, colors, reverse=reverse) _register_cmap(name=name, cmap=cmap)
warnings.filterwarnings("ignore") from datascience import Table as _Table import numpy as _np import matplotlib.pyplot as _plt from matplotlib.ticker import MultipleLocator as _MultipleLocator from matplotlib.collections import PolyCollection as _PC from matplotlib.colors import LinearSegmentedColormap as _LinearSegmentedColormap from matplotlib.cm import register_cmap as _register_cmap from IPython.display import display as _display cmap = _plt.get_cmap('Dark2') cmap_4thdownbot = _LinearSegmentedColormap.from_list('4thdownbot_cmap', cmap.colors[:3], N=3) _register_cmap(name='4thdownbot_cmap', cmap=cmap_4thdownbot) def display_re_matrix(re): _display(re.unstack(level=0).sort_values(by=0)) def display_weights(w): _display(w.to_frame().transpose()) def fast_run_expectancy(retro, re): TABLE_FLAG = False if isinstance(retro, _Table): TABLE_FLAG = True retro = retro.to_df()