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hub / github.com/IgaoGuru/Sequoia / plot_evolution

Function plot_evolution

utils/general.py:1217–1238  ·  view source on GitHub ↗
(yaml_file='data/hyp.finetune.yaml')

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1215
1216
1217def plot_evolution(yaml_file='data/hyp.finetune.yaml'): # from utils.general import *; plot_evolution()
1218 # Plot hyperparameter evolution results in evolve.txt
1219 with open(yaml_file) as f:
1220 hyp = yaml.load(f, Loader=yaml.FullLoader)
1221 x = np.loadtxt('evolve.txt', ndmin=2)
1222 f = fitness(x)
1223 # weights = (f - f.min()) ** 2 # for weighted results
1224 plt.figure(figsize=(10, 12), tight_layout=True)
1225 matplotlib.rc('font', **{'size': 8})
1226 for i, (k, v) in enumerate(hyp.items()):
1227 y = x[:, i + 7]
1228 # mu = (y * weights).sum() / weights.sum() # best weighted result
1229 mu = y[f.argmax()] # best single result
1230 plt.subplot(6, 5, i + 1)
1231 plt.scatter(y, f, c=hist2d(y, f, 20), cmap='viridis', alpha=.8, edgecolors='none')
1232 plt.plot(mu, f.max(), 'k+', markersize=15)
1233 plt.title('%s = %.3g' % (k, mu), fontdict={'size': 9}) # limit to 40 characters
1234 if i % 5 != 0:
1235 plt.yticks([])
1236 print('%15s: %.3g' % (k, mu))
1237 plt.savefig('evolve.png', dpi=200)
1238 print('\nPlot saved as evolve.png')
1239
1240
1241def plot_results_overlay(start=0, stop=0): # from utils.general import *; plot_results_overlay()

Callers

nothing calls this directly

Calls 2

fitnessFunction · 0.85
hist2dFunction · 0.85

Tested by

no test coverage detected