Using the qt5agg backend, I get plots that are 2 times too small unless I
use pyplot.
I just upgraded to matplotlib 2.01. I'm running on a Mac using the
Anaconda installation: 4.3.17 py36_0
This two scripts produce plots that are the same size. Why do I have to
double the figsize parameters when I do not use pyplot? Seems like a bug.
I didn't need to do this for the Qt4Agg backend.
# script 1
import matplotlib
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
fig1, ax = plt.subplots(figsize=(6, 4))
ax.plot([1, 2, 3, 2, 3, 4, 3, 4, 5])
ax.set_title('A simple plot')
ax.grid(True)
ax.set_xlabel('time')
ax.set_ylabel('volts')
plt.savefig('test1.pdf')
plt.show()
# script 2
import matplotlib
matplotlib.use('Qt5Agg')
from matplotlib.backends.backend_qt5agg \
import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
fig = Figure(figsize=(12, 8))
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.plot([1, 2, 3, 2, 3, 4, 3, 4, 5])
ax.set_title('A simple plot')
ax.grid(True)
ax.set_xlabel('time')
ax.set_ylabel('volts')
canvas.print_figure('test2.pdf')
canvas.show()
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David,
Was this fixed in 2.0.2 ?
···
On Sat, Aug 5, 2017 at 12:35 PM David J Pine <djpine at gmail.com> wrote:
Using the qt5agg backend, I get plots that are 2 times too small unless I
use pyplot.
I just upgraded to matplotlib 2.01. I'm running on a Mac using the
Anaconda installation: 4.3.17 py36_0
This two scripts produce plots that are the same size. Why do I have to
double the figsize parameters when I do not use pyplot? Seems like a bug.
I didn't need to do this for the Qt4Agg backend.
# script 1
import matplotlib
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
fig1, ax = plt.subplots(figsize=(6, 4))
ax.plot([1, 2, 3, 2, 3, 4, 3, 4, 5])
ax.set_title('A simple plot')
ax.grid(True)
ax.set_xlabel('time')
ax.set_ylabel('volts')
plt.savefig('test1.pdf')
plt.show()
# script 2
import matplotlib
matplotlib.use('Qt5Agg')
from matplotlib.backends.backend_qt5agg \
import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
fig = Figure(figsize=(12, 8))
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.plot([1, 2, 3, 2, 3, 4, 3, 4, 5])
ax.set_title('A simple plot')
ax.grid(True)
ax.set_xlabel('time')
ax.set_ylabel('volts')
canvas.print_figure('test2.pdf')
canvas.show()
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