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()