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Log et utils pour Dataugv5

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Harle, Antoine (Contracteur) 2019-11-18 16:48:51 -05:00
parent 860d9f1bbb
commit f4bdd9bca5
6 changed files with 57 additions and 45 deletions
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37
higher/utils.py
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@ -52,28 +52,41 @@ def plot_resV2(log, fig_name='res', param_names=None):
epochs = [x["epoch"] for x in log]
fig, ax = plt.subplots(nrows=2, ncols=2, figsize=(15, 15))
fig, ax = plt.subplots(nrows=2, ncols=3, figsize=(30, 15))
ax[0, 0].set_title('Loss')
ax[0, 0].plot(epochs,[x["train_loss"] for x in log], label='Train')
ax[0, 0].plot(epochs,[x["val_loss"] for x in log], label='Val')
ax[0, 0].legend()
ax[0, 1].set_title('Acc')
ax[0, 1].plot(epochs,[x["acc"] for x in log])
ax[1, 0].set_title('Acc')
ax[1, 0].plot(epochs,[x["acc"] for x in log])
if log[0]["param"]!= None:
ax[1, 1].set_title('Prob')
if not param_names : param_names = ['P'+str(idx) for idx, _ in enumerate(log[0]["param"])]
proba=[[x["param"][idx] for x in log] for idx, _ in enumerate(log[0]["param"])]
ax[1, 1].stackplot(epochs, proba, labels=param_names)
ax[1, 1].legend(param_names, loc='center left', bbox_to_anchor=(1, 0.5))
#proba=[[x["param"][idx] for x in log] for idx, _ in enumerate(log[0]["param"])]
proba=[[x["param"][idx]['p'] for x in log] for idx, _ in enumerate(log[0]["param"])]
mag=[[x["param"][idx]['m'] for x in log] for idx, _ in enumerate(log[0]["param"])]
ax[1, 0].set_title('Mean prob')
mean = np.mean([x["param"] for x in log], axis=0)
std = np.std([x["param"] for x in log], axis=0)
ax[1, 0].bar(param_names, mean, yerr=std)
plt.sca(ax[1, 0]), plt.xticks(rotation=90)
ax[0, 1].set_title('Prob =f(epoch)')
ax[0, 1].stackplot(epochs, proba, labels=param_names)
#ax[0, 1].legend(param_names, loc='center left', bbox_to_anchor=(1, 0.5))
ax[1, 1].set_title('Prob =f(TF)')
mean = np.mean(proba, axis=1)
std = np.std(proba, axis=1)
ax[1, 1].bar(param_names, mean, yerr=std)
plt.sca(ax[1, 1]), plt.xticks(rotation=90)
ax[0, 2].set_title('Mag =f(epoch)')
ax[0, 2].stackplot(epochs, mag, labels=param_names)
ax[0, 2].legend(param_names, loc='center left', bbox_to_anchor=(1, 0.5))
ax[1, 2].set_title('Mag =f(TF)')
mean = np.mean(mag, axis=1)
std = np.std(mag, axis=1)
ax[1, 2].bar(param_names, mean, yerr=std)
plt.sca(ax[1, 2]), plt.xticks(rotation=90)
fig_name = fig_name.replace('.',',')