diff --git a/LICENSE b/LICENSE
index 1619c6dc0345162308e083596dc9341282001afb..b8350378e810121d96bc065a8ddaab7d2ec38308 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,6 +1,6 @@
BSD 3-Clause License
-Copyright (c) 2019,
+Copyright (c) 2019-2022, IPython Development Team.
All rights reserved.
Redistribution and use in source and binary forms, with or without
diff --git a/README.md b/README.md
index 9ef91180b175712b690469c14a44199148129392..21c64188ce2e8d30179dc10242f133b0d65b3964 100644
--- a/README.md
+++ b/README.md
@@ -1,22 +1,26 @@
# Matplotlib Inline Back-end for IPython and Jupyter
+This package provides support for matplotlib to display figures directly inline in the Jupyter notebook and related clients, as shown below.
+
## Installation
With conda:
```bash
-conda install -c conda-forge notebook matplotlib
+conda install -c conda-forge matplotlib-inline
```
With pip:
```bash
-pip install notebook matplotlib
+pip install matplotlib-inline
```
## Usage
-This package is included in IPython and can be used in a Jupyter Notebook:
+Note that in current versions of JupyterLab and Jupyter Notebook, the explicit use of the `%matplotlib inline` directive is not needed anymore, though other third-party clients may still require it.
+
+This will produce a figure immediately below:
```python
%matplotlib inline
@@ -28,3 +32,7 @@ x = np.linspace(0, 3*np.pi, 500)
plt.plot(x, np.sin(x**2))
plt.title('A simple chirp');
```
+
+## License
+
+Licensed under the terms of the BSD 3-Clause License, by the IPython Development Team (see `LICENSE` file).
diff --git a/matplotlib_inline/__init__.py b/matplotlib_inline/__init__.py
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..f7ef1dd1a5f7e2f34add0f321caaf7742841d899 100644
--- a/matplotlib_inline/__init__.py
+++ b/matplotlib_inline/__init__.py
@@ -0,0 +1,2 @@
+from . import backend_inline, config # noqa
+__version__ = "0.1.6" # noqa
diff --git a/matplotlib_inline/backend_inline.py b/matplotlib_inline/backend_inline.py
index ca2e003186d899b4ccc8d960081d44c90ed63841..6bcc1d4a013957a4015ef9d66e5fc4e29d80f201 100644
--- a/matplotlib_inline/backend_inline.py
+++ b/matplotlib_inline/backend_inline.py
@@ -4,13 +4,11 @@
# Distributed under the terms of the BSD 3-Clause License.
import matplotlib
-from matplotlib.backends.backend_agg import ( # noqa
- new_figure_manager,
- FigureCanvasAgg,
- new_figure_manager_given_figure,
-)
from matplotlib import colors
+from matplotlib.backends import backend_agg
+from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib._pylab_helpers import Gcf
+from matplotlib.figure import Figure
from IPython.core.interactiveshell import InteractiveShell
from IPython.core.getipython import get_ipython
@@ -20,6 +18,57 @@ from IPython.display import display
from .config import InlineBackend
+def new_figure_manager(num, *args, FigureClass=Figure, **kwargs):
+ """
+ Return a new figure manager for a new figure instance.
+
+ This function is part of the API expected by Matplotlib backends.
+ """
+ return new_figure_manager_given_figure(num, FigureClass(*args, **kwargs))
+
+
+def new_figure_manager_given_figure(num, figure):
+ """
+ Return a new figure manager for a given figure instance.
+
+ This function is part of the API expected by Matplotlib backends.
+ """
+ manager = backend_agg.new_figure_manager_given_figure(num, figure)
+
+ # Hack: matplotlib FigureManager objects in interacive backends (at least
+ # in some of them) monkeypatch the figure object and add a .show() method
+ # to it. This applies the same monkeypatch in order to support user code
+ # that might expect `.show()` to be part of the official API of figure
+ # objects. For further reference:
+ # https://github.com/ipython/ipython/issues/1612
+ # https://github.com/matplotlib/matplotlib/issues/835
+
+ if not hasattr(figure, 'show'):
+ # Queue up `figure` for display
+ figure.show = lambda *a: display(
+ figure, metadata=_fetch_figure_metadata(figure))
+
+ # If matplotlib was manually set to non-interactive mode, this function
+ # should be a no-op (otherwise we'll generate duplicate plots, since a user
+ # who set ioff() manually expects to make separate draw/show calls).
+ if not matplotlib.is_interactive():
+ return manager
+
+ # ensure current figure will be drawn, and each subsequent call
+ # of draw_if_interactive() moves the active figure to ensure it is
+ # drawn last
+ try:
+ show._to_draw.remove(figure)
+ except ValueError:
+ # ensure it only appears in the draw list once
+ pass
+ # Queue up the figure for drawing in next show() call
+ show._to_draw.append(figure)
+ show._draw_called = True
+
+ return manager
+
+
def show(close=None, block=None):
"""Show all figures as SVG/PNG payloads sent to the IPython clients.
@@ -56,51 +105,6 @@ show._draw_called = False
show._to_draw = []
-def draw_if_interactive():
- """
- Is called after every pylab drawing command
- """
- # signal that the current active figure should be sent at the end of
- # execution. Also sets the _draw_called flag, signaling that there will be
- # something to send. At the end of the code execution, a separate call to
- # flush_figures() will act upon these values
- manager = Gcf.get_active()
- if manager is None:
- return
- fig = manager.canvas.figure
-
- # Hack: matplotlib FigureManager objects in interacive backends (at least
- # in some of them) monkeypatch the figure object and add a .show() method
- # to it. This applies the same monkeypatch in order to support user code
- # that might expect `.show()` to be part of the official API of figure
- # objects.
- # For further reference:
- # https://github.com/ipython/ipython/issues/1612
- # https://github.com/matplotlib/matplotlib/issues/835
-
- if not hasattr(fig, 'show'):
- # Queue up `fig` for display
- fig.show = lambda *a: display(fig, metadata=_fetch_figure_metadata(fig))
-
- # If matplotlib was manually set to non-interactive mode, this function
- # should be a no-op (otherwise we'll generate duplicate plots, since a user
- # who set ioff() manually expects to make separate draw/show calls).
- if not matplotlib.is_interactive():
- return
-
- # ensure current figure will be drawn, and each subsequent call
- # of draw_if_interactive() moves the active figure to ensure it is
- # drawn last
- try:
- show._to_draw.remove(fig)
- except ValueError:
- # ensure it only appears in the draw list once
- pass
- # Queue up the figure for drawing in next show() call
- show._to_draw.append(fig)
- show._draw_called = True
-
-
def flush_figures():
"""Send all figures that changed
@@ -115,19 +119,20 @@ def flush_figures():
if not show._draw_called:
return
- if InlineBackend.instance().close_figures:
- # ignore the tracking, just draw and close all figures
- try:
- return show(True)
- except Exception as e:
- # safely show traceback if in IPython, else raise
- ip = get_ipython()
- if ip is None:
- raise e
- else:
- ip.showtraceback()
- return
try:
+ if InlineBackend.instance().close_figures:
+ # ignore the tracking, just draw and close all figures
+ try:
+ return show(True)
+ except Exception as e:
+ # safely show traceback if in IPython, else raise
+ ip = get_ipython()
+ if ip is None:
+ raise e
+ else:
+ ip.showtraceback()
+ return
+
# exclude any figures that were closed:
active = set([fm.canvas.figure for fm in Gcf.get_all_fig_managers()])
for fig in [fig for fig in show._to_draw if fig in active]:
diff --git a/matplotlib_inline/config.py b/matplotlib_inline/config.py
index c0f398069e089118c8bcb4ed5378e4a1eb991c2d..8718babad92c77a141535a5f675316d5c3a5e7ff 100644
--- a/matplotlib_inline/config.py
+++ b/matplotlib_inline/config.py
@@ -32,26 +32,19 @@ class InlineBackendConfig(SingletonConfigurable):
class InlineBackend(InlineBackendConfig):
"""An object to store configuration of the inline backend."""
- # The typical default figure size is too large for inline use,
- # so we shrink the figure size to 6x4, and tweak fonts to
- # make that fit.
+ # While we are deprecating overriding matplotlib defaults out of the
+ # box, this structure should remain here (empty) for API compatibility
+ # and the use of other tools that may need it. Specifically Spyder takes
+ # advantage of it.
+ # See https://github.com/ipython/ipython/issues/10383 for details.
rc = Dict(
- {
- 'figure.figsize': (6.0, 4.0),
- # play nicely with white background in the Qt and notebook frontend
- 'figure.facecolor': (1, 1, 1, 0),
- 'figure.edgecolor': (1, 1, 1, 0),
- # 12pt labels get cutoff on 6x4 logplots, so use 10pt.
- 'font.size': 10,
- # 72 dpi matches SVG/qtconsole
- # this only affects PNG export, as SVG has no dpi setting
- 'figure.dpi': 72,
- # 10pt still needs a little more room on the xlabel:
- 'figure.subplot.bottom': .125
- },
- help="""Subset of matplotlib rcParams that should be different for the
- inline backend."""
- ).tag(config=True)
+ {},
+ help="""Dict to manage matplotlib configuration defaults in the inline
+ backend. As of v0.1.4 IPython/Jupyter do not override defaults out of
+ the box, but third-party tools may use it to manage rc data. To change
+ personal defaults for matplotlib, use matplotlib's configuration
+ tools, or customize this class in your `ipython_config.py` file for
+ IPython/Jupyter-specific usage.""").tag(config=True)
figure_formats = Set(
{'png'},
diff --git a/setup.cfg b/setup.cfg
index 97bee13299b62f5259b380a4e03301c11df2ea77..e999fd19540ebbcb6bfdc2425068c2364fa9e876 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,7 +1,9 @@
[metadata]
name = matplotlib-inline
-version = 0.1.3
+version = attr: matplotlib_inline.__version__
description = Inline Matplotlib backend for Jupyter
+long_description = file: README.md, LICENSE
+long_description_content_type = text/markdown
author = IPython Development Team
author_email = ipython-dev@scipy.org
url = https://github.com/ipython/matplotlib-inline
@@ -27,3 +29,4 @@ classifiers =
Programming Language :: Python :: 3.7
Programming Language :: Python :: 3.8
Programming Language :: Python :: 3.9
+ Programming Language :: Python :: 3.10