Question

我已经阅读了许多有关在Jupyter中调整图形大小和设置图形大小限制的文章，实际上我深信3D绘图会有所不同。

这是Jupyter不断回馈给我的3D散点图，尽管尝试了许多figsize和dpi=设置（在plt.figure()或plt.rcParams()中），< / p>

这是我的数据和当前代码，

%pylab inline
pylab.rcParams['figure.figsize'] = (20, 16)
pylab.rcParams['figure.dpi'] = 200

import matplotlib.pyplot as plt
import matplotlib

from mpl_toolkits.mplot3d import Axes3D

# data1

fig = plt.figure()

ax = fig.add_subplot(111, projection='3d')

ax.scatter(data1.a_close, data1.g_close, data1.m_close)

我在做什么错了？

编辑：我正在使用Mac（10.11），如果提供了一些详细信息，这些都是我的pip安装软件包。我也尝试卸载并重新安装jupyter，但这没有帮助

alabaster==0.7.12
anaconda-client==1.6.14
anaconda-navigator==1.8.7
anaconda-project==0.8.2
appnope==0.1.0
appscript==1.0.1
argh==0.26.2
asn1crypto==0.24.0
astroid==2.0.4
astropy==3.0.5
atomicwrites==1.2.1
attrs==18.2.0
Babel==2.6.0
backcall==0.1.0
backports.shutil-get-terminal-size==1.0.0
beautifulsoup4==4.6.3
bitarray==0.8.3
bkcharts==0.2
blaze==0.11.3
bleach==3.0.2
blist==1.3.6
bokeh==1.0.0
boto==2.48.0
Bottleneck==1.2.1
certifi==2018.4.16
cffi==1.11.5
chardet==3.0.4
Click==7.0
cloudpickle==0.6.1
clyent==1.2.2
colorama==0.4.0
conda==4.5.9
conda-build==3.0.27
conda-verify==2.0.0
contextlib2==0.5.5
cryptography==2.3.1
CVXcanon==0.1.1
cvxopt==1.2.2
cvxpy==1.0.10
cycler==0.10.0
Cython==0.29
cytoolz==0.9.0.1
dash==0.28.5
dash-core-components==0.35.2
dash-html-components==0.13.2
dash-renderer==0.14.3
dash-table-experiments==0.6.0
dask==0.19.4
datashape==0.5.4
decorator==4.3.0
defusedxml==0.5.0
dill==0.2.8.2
distcan==0.0.1
distributed==1.23.3
Django==2.1.2
docutils==0.14
ecos==2.0.5
entrypoints==0.2.3
et-xmlfile==1.0.1
eventsourcing==6.3.0
fastcache==1.0.2
fastnumbers==2.1.1
feather-format==0.4.0
filelock==3.0.9
fix-yahoo-finance==0.0.22
Flask==1.0.2
Flask-Caching==1.4.0
Flask-Compress==1.4.0
Flask-Cors==3.0.6
future==0.16.0
gevent==1.3.7
glmnet==2.0.0
glmnet-py==0.1.0b2
glob2==0.6
gmpy2==2.0.8
greenlet==0.4.15
h5py==2.8.0
heapdict==1.0.0
html5lib==1.0.1
hupper==1.3.1
idna==2.7
imageio==2.4.1
imagesize==1.1.0
importlib-metadata==0.6
inflection==0.3.1
ipykernel==5.1.0
ipython==7.0.1
ipython-genutils==0.2.0
ipywidgets==7.4.2
isort==4.3.4
ItsDangerous==1.0.0
jdcal==1.4
jedi==0.13.1
Jinja2==2.10
joblib==0.12.5
jsonschema==2.6.0
jupyter==1.0.0
jupyter-client==5.2.3
jupyter-console==6.0.0
jupyter-core==4.4.0
jupyterlab==0.35.2
jupyterlab-launcher==0.13.1
jupyterlab-server==0.2.0
keyring==15.1.0
kiwisolver==1.0.1
lazy-object-proxy==1.3.1
llvmlite==0.25.0
locket==0.2.0
lxml==4.2.5
Markdown==3.0.1
MarkupSafe==1.0
matplotlib==3.0.0
mccabe==0.6.1
mistune==0.8.4
mizani==0.5.2
mlxtend==0.13.0
mock==2.0.0
more-itertools==4.3.0
mpmath==1.0.0
msgpack==0.5.6
msgpack-python==0.5.6
multipledispatch==0.6.0
multiprocess==0.70.6.1
multitasking==0.0.7
natsort==5.4.1
navigator-updater==0.2.1
nbconvert==5.4.0
nbformat==4.4.0
ndg-httpsclient==0.5.1
networkx==2.2
nltk==3.3
nose==1.3.7
notebook==5.7.0
numba==0.40.1
numexpr==2.6.8
numpy==1.15.3
numpydoc==0.8.0
odo==0.5.1
olefile==0.46
openpyxl==2.5.9
osqp==0.4.1
packaging==18.0
palettable==3.1.1
pandas==0.23.4
pandas-datareader==0.7.0
pandocfilters==1.4.2
parso==0.3.1
partd==0.3.9
PasteDeploy==1.5.2
path.py==11.5.0
pathlib2==2.3.2
patsy==0.5.0
pbr==5.1.0
pep8==1.7.1
pexpect==4.6.0
pickleshare==0.7.5
Pillow==5.3.0
pkginfo==1.4.2
plaster==1.0
plaster-pastedeploy==0.6
plotly==3.3.0
pluggy==0.8.0
ply==3.11
prometheus-client==0.4.2
prompt-toolkit==2.0.6
psutil==5.4.7
ptyprocess==0.5.2
py==1.7.0
pyarrow==0.11.1
pyasn1==0.4.4
pycodestyle==2.4.0
pycosat==0.6.3
pycparser==2.19
pycrypto==2.6.1
pycryptodome==3.6.6
pycurl==7.43.0.2
pyflakes==2.0.0
Pygments==2.2.0
pylint==2.1.1
pymc3==3.5
pyodbc==4.0.24
pyOpenSSL==18.0.0
pyparsing==2.2.2
PyQt5==5.11.3
PyQt5-sip==4.19.13
pyramid-arima==0.8.1
PySocks==1.6.8
pystan==2.18.0.0
pytest==3.9.2
python-dateutil==2.7.3
pytz==2018.6
PyWavelets==1.0.1
PyYAML==3.12
pyzmq==17.1.2
qfrm==0.2.0.27
QtAwesome==0.5.1
qtconsole==4.3.1
QtPy==1.5.2
Quandl==3.4.3
redis==2.10.6
repoze.lru==0.7
requests==2.20.0
requests-file==1.4.3
requests-ftp==0.3.1
retrying==1.3.3
rope==0.11.0
rpy2==2.9.4
ruamel-yaml==0.11.14
scikit-image==0.14.1
scikit-learn==0.19.0
scipy==1.1.0
scs==2.0.2
seaborn==0.9.0
Send2Trash==1.5.0
simplegeneric==0.8.1
simplejson==3.16.0
singledispatch==3.4.0.3
sip==4.19.8
six==1.11.0
snowballstemmer==1.2.1
sortedcollections==1.0.1
sortedcontainers==2.0.5
Sphinx==1.8.1
sphinxcontrib-websupport==1.1.0
spyder==3.3.1
spyder-kernels==1.1.0
SQLAlchemy==1.2.12
statistics==1.0.3.5
statsmodels==0.9.0
sympy==1.1.1
tables==3.4.4
tblib==1.3.2
terminado==0.8.1
testpath==0.4.2
Theano==1.0.3
toolz==0.9.0
tornado==5.1.1
tqdm==4.28.1
traitlets==4.3.2
translationstring==1.3
typed-ast==1.1.0
typing==3.6.6
tzlocal==1.5.1
unicodecsv==0.14.1
urllib3==1.24
venusian==1.1.0
wcwidth==0.1.7
webencodings==0.5.1
WebOb==1.8.3
Werkzeug==0.14.1
widgetsnbextension==3.4.2
wrapt==1.10.11
xlrd==1.1.0
XlsxWriter==1.1.2
xlwings==0.13.0
xlwt==1.3.0
yahoo-finance==1.4.0
zict==0.1.3
zope.deprecation==4.3.0
zope.interface==4.6.0

Answer 1

这是由于matplotlib 3.0.0中的错误所致。在matplotlib 3.0.1中不应出现该错误。

您拥有的选项：

更新到matplotlib 3.0.1

在绘制之前，请在jupyter笔记本中设置以下选项

%config InlineBackend.print_figure_kwargs = {'bbox_inches':None}

使用%matplotlib notebook后端而不是%matplotlib inline后端。

Answer 2

尝试更换

%pylab inline
pylab.rcParams['figure.figsize'] = (20, 16)
pylab.rcParams['figure.dpi'] = 200

import matplotlib.pyplot as plt
import matplotlib

使用

%matplotlib inline

import matplotlib.pyplot as plt
import matplotlib

matplotlib.rcParams['figure.figsize'] = (20, 16)
matplotlib.rcParams['figure.dpi'] = 200

Answer 3

有时在Mac上也会发生这种情况。

首先使用此功能：

import matplotlib.pyplot as plt
import matplotlib
%matplotlib inline

matplotlib.rcParams['figure.figsize'] = (20, 16)
matplotlib.rcParams['figure.dpi'] = 200

我的案例的窍门： ：首先导入，然后使用%matplotlib inline命令。但是，似乎是个错误。

Jupyter使3D matplotlib图变得非常小

3 个答案: