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from IPython.display import set_matplotlib_formats, display | |
import pandas as pd | |
import numpy as np | |
import matplotlib.pyplot as plt | |
import mglearn | |
from mglearn import plot_helpers | |
from cycler import cycler | |
set_matplotlib_formats('pdf', 'png') | |
plt.rcParams['savefig.dpi'] = 300 | |
plt.rcParams['figure.dpi'] = 100 | |
plt.rcParams['image.cmap'] = "viridis" | |
plt.rcParams['image.interpolation'] = "none" | |
plt.rcParams['savefig.bbox'] = "tight" | |
plt.rcParams['lines.linewidth'] = 2 | |
plt.rcParams['legend.numpoints'] = 1 | |
plt.rc('axes', prop_cycle=( | |
cycler('color', plot_helpers.cm_cycle.colors) + | |
cycler('linestyle', ['-', '-', "--", (0, (3, 3)), (0, (1.5, 1.5))]))) | |
np.set_printoptions(precision=3, suppress=True) | |
pd.set_option("display.max_columns", 8) | |
pd.set_option('display.precision', 2) | |
__all__ = ['np', 'mglearn', 'display', 'plt', 'pd'] |
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