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Description
Bug report
hist2d interprets dates differently than doplot,scatter, etc. In the example, manually applyingdate2num before callinghist2d makes the output work as expected, but is not necessary forplot.
Code for reproduction
importmatplotlibimportnumpyasnpimportmatplotlib.pyplotaspltprint(matplotlib.__version__)t=np.array(['2020-04-02T23:00:00.749079563','2020-04-02T23:00:00.749083039','2020-04-02T23:00:01.792519894','2020-04-02T23:00:01.793246307','2020-04-02T23:00:01.793248355','2020-04-02T23:00:01.795347666','2020-04-02T23:00:01.796964828','2020-04-02T23:00:01.798717183','2020-04-02T23:00:01.800349212','2020-04-02T23:00:01.801143192'],dtype='datetime64[ns]')tlim=np.array(['2020-04-02T23:00:00','2020-04-02T23:00:02'],dtype='datetime64[ns]')z=np.arange(t.shape[0],dtype=float)fig,ax=plt.subplots(3,2,figsize=(12,12))# plot with no axis controlax[0,0].plot(t,z,'.')ax[0,1].hist2d(t,z,bins=[5,5])# set axes to expected range with default time handling# plot works, hist2d doesnt.ax[1,0].plot(t,z,'.')ax[1,0].set_xlim(tlim[0],tlim[1])ax[1,1].hist2d(t,z,bins=[5,5])ax[1,1].plot(t,z,'.')ax[1,1].set_xlim(tlim[0],tlim[1])# manually converting dates fixes hist2dax[2,0].plot(t,z,'.')ax[2,0].set_xlim(tlim[0],tlim[1])ax[2,1].hist2d(matplotlib.dates.date2num(t),z,bins=[5,5])ax[2,1].plot(t,z,'.')ax[2,1].set_xlim(tlim[0],tlim[1])
Actual outcome
(737517.9583333334, 737517.9583564815) # output of set_xlim call
Note that the times are O(10^18) in the firsthist2d plot (upper right), unlike O(10^5) in the x-limits.
Expected outcome
hist2d should interpret time as withplot.
Matplotlib version
- Operating system: MacOS Catalina
- Matplotlib version: 3.2.1 (conda-forge)
- Matplotlib backend (
print(matplotlib.get_backend())): module://ipykernel.pylab.backend_inline - Python version: 3.6.7
- Jupyter version (if applicable): 6.1.3 (client)