[python] king's square at checkmate visualization
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- # this was originally a notebook, so its not meant to be run altogether
- import pandas as pd
- import numpy as np
- import seaborn as sns
- sns.set_theme()
- # 1.0 to heatmap all checkmates
- df = pd.read_csv(# the filepath to csv from the previous script)
- all_mates = pd.DataFrame(df.groupby('square').size())
- all_mates.reset_index(inplace=True)
- all_mates['row'] = all_mates['square']//8
- all_mates['column'] = all_mates['square'] - (all_mates['row']*8)
- all_mates['row'] = all_mates['row'] + 1
- all_mates.rename(columns={0:'n_checkmates'}, inplace=True)
- all_mates['checkmate_rate'] = (all_mates['n_checkmates']/all_mates['n_checkmates'].sum())*100
- all_mates['column'] = all_mates['column'].map({0:'A', 1:'B', 2:'C', 3:'D', 4:'E', 5:'F', 6:'G', 7:'H'})
- # 1.1 counts
- pivot_mates = all_mates.pivot(index='row', columns='column', values='n_checkmates')
- ax = sns.heatmap(pivot_mates, linewidths=1, annot=True, fmt="d", cmap='viridis', cbar=False)
- ax.invert_yaxis()
- ax.set_title('King\'s square when checkmated')
- ax.set(xlabel=None)
- ax.set(ylabel=None)
- sns.set(rc={'figure.figsize':(6,6)})
- fig = ax.get_figure()
- fig.savefig('checkmate_counts.png', dpi=800)
- # 1.2 rates
- pivot_mates_rates = all_mates.pivot(index='row', columns='column', values='checkmate_rate')
- ax = sns.heatmap(pivot_mates_rates, linewidths=.5, annot=True, cmap='viridis', cbar=False)
- ax.invert_yaxis()
- ax.set(xlabel=None)
- ax.set(ylabel=None)
- sns.set(rc={'figure.figsize':(6,6)})
- ax.set_title('King\'s square when checkmated')
- fig = ax.get_figure()
- fig.savefig('checkmate_rates.png', dpi=800)
- # 2.0 specific color
- white = df.loc[df['color'] == 'White']
- white = pd.DataFrame(white.groupby('square').size())
- white.reset_index(inplace=True)
- white['row'] = white['square']//8
- white['column'] = white['square'] - (white['row']*8)
- white['row'] = white['row'] + 1
- white.rename(columns={0:'n_checkmates'}, inplace=True)
- white['checkmate_rate'] = (white['n_checkmates']/white['n_checkmates'].sum())*100
- white['column'] = white['column'].map({0:'A', 1:'B', 2:'C', 3:'D', 4:'E', 5:'F', 6:'G', 7:'H'})
- # 2.1 counts
- pivot_mates = white.pivot(index='row', columns='column', values='n_checkmates')
- ax = sns.heatmap(pivot_mates, linewidths=1, annot=True, fmt="d", cmap='viridis', cbar=False)
- ax.invert_yaxis()
- ax.set_title('White king\'s square when checkmated')
- ax.set(xlabel=None)
- ax.set(ylabel=None)
- sns.set(rc={'figure.figsize':(6,6)})
- fig = ax.get_figure()
- fig.savefig('white_checkmate_counts.png', dpi=800)
- # 2.2 rates
- pivot_mates_rates = white.pivot(index='row', columns='column', values='checkmate_rate')
- ax = sns.heatmap(pivot_mates_rates, linewidths=.5, annot=True, cmap='viridis', cbar=False)
- ax.invert_yaxis()
- ax.set(xlabel=None)
- ax.set(ylabel=None)
- sns.set(rc={'figure.figsize':(6,6)})
- ax.set_title('White King\'s square when checkmated')
- fig = ax.get_figure()
- fig.savefig('white_checkmate_rates.png', dpi=800)
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