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Copy pathRadialPower_128s.py
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RadialPower_128s.py
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#!/usr/bin/env python
#! -*- coding:utf-8 -*-
import numpy as np; np.random.seed(0)
import seaborn as sns; sns.set()
import matplotlib.pyplot as plt
# 0 1 2 3 4 5 6 7 8 9
ctr_in =[[0.00, 0.00, 2.84, 2.84, 3.33, 3.33, 2.83, 2.83, 0.00, 0.00], # 0
[0.00, 0.00, 2.84, 2.84, 3.33, 3.33, 2.83, 2.83, 0.00, 0.00], # 1
[0.00, 3.33, 3.33, 4.37, 4.37, 4.36, 4.36, 3.31, 3.31, 0.00], # 2
[0.00, 3.33, 3.33, 4.37, 4.37, 4.36, 4.36, 3.31, 3.31, 0.00], # 3
[2.83, 2.83, 4.36, 4.36, 5.02, 5.02, 4.36, 4.36, 2.84, 2.84], # 4
[2.83, 2.83, 4.36, 4.36, 5.02, 5.02, 4.36, 4.36, 2.84, 2.84], # 5
[0.00, 3.31, 3.31, 4.35, 4.35, 4.35, 4.35, 3.31, 3.31, 0.00], # 6
[0.00, 3.31, 3.31, 4.35, 4.35, 4.35, 4.35, 3.31, 3.31, 0.00], # 7
[0.00, 0.00, 2.83, 2.83, 3.32, 3.32, 2.83, 2.83, 0.00, 0.00], # 8
[0.00, 0.00, 2.83, 2.83, 3.32, 3.32, 2.83, 2.83, 0.00, 0.00]] # 9
ctr_out=[[0.00, 0.00, 3.43, 3.43, 4.06, 4.06, 3.45, 3.45, 0.00, 0.00], # 0
[0.00, 0.00, 3.43, 3.43, 4.06, 4.06, 3.45, 3.45, 0.00, 0.00], # 1
[0.00, 4.05, 4.05, 5.44, 5.44, 5.45, 5.45, 4.06, 4.06, 0.00], # 2
[0.00, 4.05, 4.05, 5.44, 5.44, 5.45, 5.45, 4.06, 4.06, 0.00], # 3
[3.42, 3.42, 5.44, 5.44, 6.30, 6.30, 5.46, 5.46, 3.44, 3.44], # 4
[3.42, 3.42, 5.44, 5.44, 6.30, 6.30, 5.46, 5.46, 3.44, 3.44], # 5
[0.00, 4.04, 4.04, 5.43, 5.43, 5.45, 5.45, 4.07, 4.07, 0.00], # 6
[0.00, 4.04, 4.04, 5.43, 5.43, 5.45, 5.45, 4.07, 4.07, 0.00], # 7
[0.00, 0.00, 3.42, 3.42, 4.05, 4.05, 3.44, 3.44, 0.00, 0.00], # 8
[0.00, 0.00, 3.42, 3.42, 4.05, 4.05, 3.44, 3.44, 0.00, 0.00]] # 9
ner_ctc=[[0.00, 0.00, 2.84, 2.84, 4.21, 4.21, 2.83, 2.83, 0.00, 0.00], # 0
[0.00, 0.00, 2.84, 2.84, 4.21, 4.21, 2.83, 2.83, 0.00, 0.00], # 1
[0.00, 4.21, 4.21, 4.26, 4.26, 4.24, 4.24, 4.06, 4.06, 0.00], # 2
[0.00, 4.21, 4.21, 4.26, 4.26, 4.24, 4.24, 4.06, 4.06, 0.00], # 3
[2.85, 2.85, 4.26, 4.26, 6.15, 6.15, 4.23, 4.23, 2.82, 2.82], # 4
[2.85, 2.85, 4.26, 4.26, 6.15, 6.15, 4.23, 4.23, 2.82, 2.82], # 5
[0.00, 4.24, 4.24, 4.26, 4.26, 4.24, 4.24, 4.19, 4.19, 0.00], # 6
[0.00, 4.24, 4.24, 4.26, 4.26, 4.24, 4.24, 4.19, 4.19, 0.00], # 7
[0.00, 0.00, 2.85, 2.85, 4.22, 4.22, 2.83, 2.83, 0.00, 0.00], # 8
[0.00, 0.00, 2.85, 2.85, 4.22, 4.22, 2.83, 2.83, 0.00, 0.00]] # 9
ax = sns.heatmap(ner_ctc, annot=True, cmap='RdPu')
plt.axes().get_xaxis().set_visible(False)
plt.axes().get_yaxis().set_visible(False)
plt.show()