update matplotlib figure after running model in Jupyter notebook
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I am trying out some tsne code where upon cluster updates, I like to refresh the displayed image.
As of now, it seems the display refresh command is blocked until all the model iteration is finished. So, I only get one display after n iterations of the model.
ax = plt.gca()
for itr in range(4):
wrap.fit(pij, i, j)
# Visualize the results
embed = model.logits.weight.cpu().data.numpy()
# Visualize with ellipses
var = np.sqrt(model.logits_lv.weight.clone().exp_().cpu().data.numpy())
ax.clear()
for xy, (w, h), c in zip(embed, var, y):
e = Ellipse(xy=xy, width=w, height=h, ec=None, lw=0.0)
e.set_facecolor(plt.cm.Paired(c * 1.0 / y.max()))
e.set_alpha(0.5)
ax.add_artist(e)
ax.set_xlim(-9, 9)
ax.set_ylim(-9, 9)
plt.axis('off')
Do I need to send the display refresh call to a different thread?
matplotlib refresh visualization
asked Nov 22 at 16:58
bhomass
1,23512240
add a comment |
up vote
0
down vote
favorite
I am trying out some tsne code where upon cluster updates, I like to refresh the displayed image.
As of now, it seems the display refresh command is blocked until all the model iteration is finished. So, I only get one display after n iterations of the model.
ax = plt.gca()
for itr in range(4):
wrap.fit(pij, i, j)
# Visualize the results
embed = model.logits.weight.cpu().data.numpy()
# Visualize with ellipses
var = np.sqrt(model.logits_lv.weight.clone().exp_().cpu().data.numpy())
ax.clear()
for xy, (w, h), c in zip(embed, var, y):
e = Ellipse(xy=xy, width=w, height=h, ec=None, lw=0.0)
e.set_facecolor(plt.cm.Paired(c * 1.0 / y.max()))
e.set_alpha(0.5)
ax.add_artist(e)
ax.set_xlim(-9, 9)
ax.set_ylim(-9, 9)
plt.axis('off')
Do I need to send the display refresh call to a different thread?
matplotlib refresh visualization
asked Nov 22 at 16:58
bhomass
1,23512240
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I am trying out some tsne code where upon cluster updates, I like to refresh the displayed image.
As of now, it seems the display refresh command is blocked until all the model iteration is finished. So, I only get one display after n iterations of the model.
ax = plt.gca()
for itr in range(4):
wrap.fit(pij, i, j)
# Visualize the results
embed = model.logits.weight.cpu().data.numpy()
# Visualize with ellipses
var = np.sqrt(model.logits_lv.weight.clone().exp_().cpu().data.numpy())
ax.clear()
for xy, (w, h), c in zip(embed, var, y):
e = Ellipse(xy=xy, width=w, height=h, ec=None, lw=0.0)
e.set_facecolor(plt.cm.Paired(c * 1.0 / y.max()))
e.set_alpha(0.5)
ax.add_artist(e)
ax.set_xlim(-9, 9)
ax.set_ylim(-9, 9)
plt.axis('off')
Do I need to send the display refresh call to a different thread?
matplotlib refresh visualization
asked Nov 22 at 16:58
bhomass
1,23512240
I am trying out some tsne code where upon cluster updates, I like to refresh the displayed image.
As of now, it seems the display refresh command is blocked until all the model iteration is finished. So, I only get one display after n iterations of the model.
ax = plt.gca()
for itr in range(4):
wrap.fit(pij, i, j)
# Visualize the results
embed = model.logits.weight.cpu().data.numpy()
# Visualize with ellipses
var = np.sqrt(model.logits_lv.weight.clone().exp_().cpu().data.numpy())
ax.clear()
for xy, (w, h), c in zip(embed, var, y):
e = Ellipse(xy=xy, width=w, height=h, ec=None, lw=0.0)
e.set_facecolor(plt.cm.Paired(c * 1.0 / y.max()))
e.set_alpha(0.5)
ax.add_artist(e)
ax.set_xlim(-9, 9)
ax.set_ylim(-9, 9)
plt.axis('off')
Do I need to send the display refresh call to a different thread?
matplotlib refresh visualization
matplotlib refresh visualization
asked Nov 22 at 16:58
bhomass
1,23512240
asked Nov 22 at 16:58
bhomass
1,23512240
edited Nov 22 at 17:10
asked Nov 22 at 16:58
bhomass
1,23512240
asked Nov 22 at 16:58
bhomass
1,23512240
asked Nov 22 at 16:58
bhomass
1,23512240
1,23512240
add a comment |
add a comment |
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