Get Jupyter notebook to display matplotlib figures in real-time
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I have a long running Python loop (used for machine learning), which periodically prints output and displays figures (using matplotlib). When run in Jupyter Notebook, all the text (stdout) is displayed in real-time, but the figures are all queued and not displayed until the entire loop is done.
I'd like to see the figures in real-time, on each iteration of the loop. During cell execution, not when the entire cell execution is done.
For example, if my code is:
for i in range(10):
print(i)
show_figure(FIG_i)
do_a_10_second_calculation()
I currently see:
0
1
2
...
9
FIG_0
FIG_1
...
FIG_9
What I'd like is:
0
FIG_0
1
FIG_1
2
FIG_2
...
Most importantly, I'd like to see the figures as they are calculated, as opposed to not seeing any figures on the screen until the entire loop is done.
python matplotlib jupyter-notebook real-time
asked Nov 23 '18 at 16:32
SRobertJamesSRobertJames
2,46773272
add a comment |
I have a long running Python loop (used for machine learning), which periodically prints output and displays figures (using matplotlib). When run in Jupyter Notebook, all the text (stdout) is displayed in real-time, but the figures are all queued and not displayed until the entire loop is done.
I'd like to see the figures in real-time, on each iteration of the loop. During cell execution, not when the entire cell execution is done.
For example, if my code is:
for i in range(10):
print(i)
show_figure(FIG_i)
do_a_10_second_calculation()
I currently see:
0
1
2
...
9
FIG_0
FIG_1
...
FIG_9
What I'd like is:
0
FIG_0
1
FIG_1
2
FIG_2
...
Most importantly, I'd like to see the figures as they are calculated, as opposed to not seeing any figures on the screen until the entire loop is done.
python matplotlib jupyter-notebook real-time
asked Nov 23 '18 at 16:32
SRobertJamesSRobertJames
2,46773272
add a comment |
I have a long running Python loop (used for machine learning), which periodically prints output and displays figures (using matplotlib). When run in Jupyter Notebook, all the text (stdout) is displayed in real-time, but the figures are all queued and not displayed until the entire loop is done.
I'd like to see the figures in real-time, on each iteration of the loop. During cell execution, not when the entire cell execution is done.
For example, if my code is:
for i in range(10):
print(i)
show_figure(FIG_i)
do_a_10_second_calculation()
I currently see:
0
1
2
...
9
FIG_0
FIG_1
...
FIG_9
What I'd like is:
0
FIG_0
1
FIG_1
2
FIG_2
...
Most importantly, I'd like to see the figures as they are calculated, as opposed to not seeing any figures on the screen until the entire loop is done.
python matplotlib jupyter-notebook real-time
asked Nov 23 '18 at 16:32
SRobertJamesSRobertJames
2,46773272
I have a long running Python loop (used for machine learning), which periodically prints output and displays figures (using matplotlib). When run in Jupyter Notebook, all the text (stdout) is displayed in real-time, but the figures are all queued and not displayed until the entire loop is done.
I'd like to see the figures in real-time, on each iteration of the loop. During cell execution, not when the entire cell execution is done.
For example, if my code is:
for i in range(10):
print(i)
show_figure(FIG_i)
do_a_10_second_calculation()
I currently see:
0
1
2
...
9
FIG_0
FIG_1
...
FIG_9
What I'd like is:
0
FIG_0
1
FIG_1
2
FIG_2
...
Most importantly, I'd like to see the figures as they are calculated, as opposed to not seeing any figures on the screen until the entire loop is done.
python matplotlib jupyter-notebook real-time
python matplotlib jupyter-notebook real-time
asked Nov 23 '18 at 16:32
SRobertJamesSRobertJames
2,46773272
asked Nov 23 '18 at 16:32
SRobertJamesSRobertJames
2,46773272
asked Nov 23 '18 at 16:32
SRobertJamesSRobertJames
2,46773272
asked Nov 23 '18 at 16:32
SRobertJamesSRobertJames
2,46773272
asked Nov 23 '18 at 16:32
SRobertJamesSRobertJames
2,46773272
2,46773272
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
I suppose the problem lies in the part of the code you do not show here. Because it should work as expected. Making it runnable,
%matplotlib inline
import matplotlib.pyplot as plt
def do_a_1_second_calculation():
plt.pause(1)
def show_figure(i):
plt.figure(i)
plt.plot([1,i,3])
plt.show()
for i in range(10):
print(i)
show_figure(i)
do_a_1_second_calculation()
results in the desired outcome
answered Nov 23 '18 at 17:30
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13170248
Aha! I didn't realize you need to explicitly doplt.show(). I had omitted that, and all the figures still displayed at the end, when the cell completed execution. Adding that in the loop indeed solves the problem.
– SRobertJames
Nov 23 '18 at 17:38
add a comment |
The display function from IPython.display can be used to immediately flush a figure to cell output. Assuming that FIG_i in your code is an actual Matplotlib figure object, you can just replace show_figure(FIG_i) with display(FIG_i) and the figures will output in real time.
Here's a complete example of display in action:
from matplotlib import pyplot as plt
import numpy as np
from IPython.display import display
from time import sleep
for eps in range(0, 11, 5):
data = np.random.randint(eps, eps+10, size=(2,10))
fig = plt.figure()
ax = fig.gca()
ax.plot(*data)
print('eps %f' % eps)
display(fig)
plt.close() # .close prevents the normal figure display at end of cell execution
sleep(2)
print('slept 2 sec')
Here's a screenshot of the output:
answered Nov 23 '18 at 16:46
teltel
7,52921433
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
I suppose the problem lies in the part of the code you do not show here. Because it should work as expected. Making it runnable,
%matplotlib inline
import matplotlib.pyplot as plt
def do_a_1_second_calculation():
plt.pause(1)
def show_figure(i):
plt.figure(i)
plt.plot([1,i,3])
plt.show()
for i in range(10):
print(i)
show_figure(i)
do_a_1_second_calculation()
results in the desired outcome
answered Nov 23 '18 at 17:30
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13170248
Aha! I didn't realize you need to explicitly doplt.show(). I had omitted that, and all the figures still displayed at the end, when the cell completed execution. Adding that in the loop indeed solves the problem.
– SRobertJames
Nov 23 '18 at 17:38
add a comment |
I suppose the problem lies in the part of the code you do not show here. Because it should work as expected. Making it runnable,
%matplotlib inline
import matplotlib.pyplot as plt
def do_a_1_second_calculation():
plt.pause(1)
def show_figure(i):
plt.figure(i)
plt.plot([1,i,3])
plt.show()
for i in range(10):
print(i)
show_figure(i)
do_a_1_second_calculation()
results in the desired outcome
answered Nov 23 '18 at 17:30
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13170248
Aha! I didn't realize you need to explicitly doplt.show(). I had omitted that, and all the figures still displayed at the end, when the cell completed execution. Adding that in the loop indeed solves the problem.
– SRobertJames
Nov 23 '18 at 17:38
add a comment |
I suppose the problem lies in the part of the code you do not show here. Because it should work as expected. Making it runnable,
%matplotlib inline
import matplotlib.pyplot as plt
def do_a_1_second_calculation():
plt.pause(1)
def show_figure(i):
plt.figure(i)
plt.plot([1,i,3])
plt.show()
for i in range(10):
print(i)
show_figure(i)
do_a_1_second_calculation()
results in the desired outcome
answered Nov 23 '18 at 17:30
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13170248
I suppose the problem lies in the part of the code you do not show here. Because it should work as expected. Making it runnable,
%matplotlib inline
import matplotlib.pyplot as plt
def do_a_1_second_calculation():
plt.pause(1)
def show_figure(i):
plt.figure(i)
plt.plot([1,i,3])
plt.show()
for i in range(10):
print(i)
show_figure(i)
do_a_1_second_calculation()
results in the desired outcome
answered Nov 23 '18 at 17:30
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13170248
answered Nov 23 '18 at 17:30
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13170248
answered Nov 23 '18 at 17:30
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13170248
answered Nov 23 '18 at 17:30
ImportanceOfBeingErnestImportanceOfBeingErnest
142k13170248
142k13170248
Aha! I didn't realize you need to explicitly doplt.show(). I had omitted that, and all the figures still displayed at the end, when the cell completed execution. Adding that in the loop indeed solves the problem.
– SRobertJames
Nov 23 '18 at 17:38
add a comment |
Aha! I didn't realize you need to explicitly doplt.show(). I had omitted that, and all the figures still displayed at the end, when the cell completed execution. Adding that in the loop indeed solves the problem.
– SRobertJames
Nov 23 '18 at 17:38
Aha! I didn't realize you need to explicitly do
plt.show(). I had omitted that, and all the figures still displayed at the end, when the cell completed execution. Adding that in the loop indeed solves the problem.– SRobertJames
Nov 23 '18 at 17:38
Aha! I didn't realize you need to explicitly do
plt.show(). I had omitted that, and all the figures still displayed at the end, when the cell completed execution. Adding that in the loop indeed solves the problem.– SRobertJames
Nov 23 '18 at 17:38
add a comment |
The display function from IPython.display can be used to immediately flush a figure to cell output. Assuming that FIG_i in your code is an actual Matplotlib figure object, you can just replace show_figure(FIG_i) with display(FIG_i) and the figures will output in real time.
Here's a complete example of display in action:
from matplotlib import pyplot as plt
import numpy as np
from IPython.display import display
from time import sleep
for eps in range(0, 11, 5):
data = np.random.randint(eps, eps+10, size=(2,10))
fig = plt.figure()
ax = fig.gca()
ax.plot(*data)
print('eps %f' % eps)
display(fig)
plt.close() # .close prevents the normal figure display at end of cell execution
sleep(2)
print('slept 2 sec')
Here's a screenshot of the output:
answered Nov 23 '18 at 16:46
teltel
7,52921433
add a comment |
The display function from IPython.display can be used to immediately flush a figure to cell output. Assuming that FIG_i in your code is an actual Matplotlib figure object, you can just replace show_figure(FIG_i) with display(FIG_i) and the figures will output in real time.
Here's a complete example of display in action:
from matplotlib import pyplot as plt
import numpy as np
from IPython.display import display
from time import sleep
for eps in range(0, 11, 5):
data = np.random.randint(eps, eps+10, size=(2,10))
fig = plt.figure()
ax = fig.gca()
ax.plot(*data)
print('eps %f' % eps)
display(fig)
plt.close() # .close prevents the normal figure display at end of cell execution
sleep(2)
print('slept 2 sec')
Here's a screenshot of the output:
answered Nov 23 '18 at 16:46
teltel
7,52921433
add a comment |
The display function from IPython.display can be used to immediately flush a figure to cell output. Assuming that FIG_i in your code is an actual Matplotlib figure object, you can just replace show_figure(FIG_i) with display(FIG_i) and the figures will output in real time.
Here's a complete example of display in action:
from matplotlib import pyplot as plt
import numpy as np
from IPython.display import display
from time import sleep
for eps in range(0, 11, 5):
data = np.random.randint(eps, eps+10, size=(2,10))
fig = plt.figure()
ax = fig.gca()
ax.plot(*data)
print('eps %f' % eps)
display(fig)
plt.close() # .close prevents the normal figure display at end of cell execution
sleep(2)
print('slept 2 sec')
Here's a screenshot of the output:
answered Nov 23 '18 at 16:46
teltel
7,52921433
The display function from IPython.display can be used to immediately flush a figure to cell output. Assuming that FIG_i in your code is an actual Matplotlib figure object, you can just replace show_figure(FIG_i) with display(FIG_i) and the figures will output in real time.
Here's a complete example of display in action:
from matplotlib import pyplot as plt
import numpy as np
from IPython.display import display
from time import sleep
for eps in range(0, 11, 5):
data = np.random.randint(eps, eps+10, size=(2,10))
fig = plt.figure()
ax = fig.gca()
ax.plot(*data)
print('eps %f' % eps)
display(fig)
plt.close() # .close prevents the normal figure display at end of cell execution
sleep(2)
print('slept 2 sec')
Here's a screenshot of the output:
answered Nov 23 '18 at 16:46
teltel
7,52921433
edited Nov 23 '18 at 17:05
answered Nov 23 '18 at 16:46
teltel
7,52921433
answered Nov 23 '18 at 16:46
teltel
7,52921433
answered Nov 23 '18 at 16:46
teltel
7,52921433
7,52921433
add a comment |
add a comment |
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