Closed aprotopopov closed 7 years ago
I'm working on releasing code for the turbofan
dataset using Keras. I've added the plots/heatmaps with 7fea00eb4da5fe54d39b72e39c673f69b4e56f00
Try
from wtte.plots.plot_heatmap import plot_heatmap
a = predicted[batch_indx,:,0]
b = predicted[batch_indx,:,1]
this_x_train = x_train[batch_indx,:,:].mean(axis=1)
this_x_test = x_test[batch_indx,:,:].mean(axis=1)
this_tte_train = y_train[batch_indx,:,0]
this_tte_test = y_test[batch_indx,:,0]
t= np.array(xrange(n_timesteps))
fig, ax = plt.subplots(1)
plot_heatmap(
fig,ax,
t,
a,
b,
max_horizon = every_nth,
time_to_event=this_tte_train,
true_time_to_event=this_tte_test,
censoring_indicator = None,
title='predicted Weibull pmf $p(t,s)$',
lw=1.0,
is_discrete=True,
resolution=None,
xax_nbins=10,
yax_nbins=4
)
plt.show()
I never got around to release turbofan
, but @gm-spacagna did it so much better than the original experiment anyway. Check out https://github.com/gm-spacagna/deep-ttf
In your blog post you have a nice visualization and good predictive results for Predicting the destruction of jet-engines.
Could you attach python code or jupyter notebook to examples directory to reproduce visualizations and prediction results?