[PYTHON] matplotlib로 numpy datetime64 플롯

matplotlib로 numpy datetime64 플롯

나는 2 개의 numpy 어레이 1D를 가지고 있는데, 하나는 datetime64 형식의 측정 시간입니다. 예를 들면 다음과 같습니다.

array([2011-11-15 01:08:11, 2011-11-16 02:08:04, ..., 2012-07-07 11:08:00], dtype=datetime64[us])

및 정수 데이터와 동일한 길이 및 치수의 다른 배열. Matplotlib 시간 대 데이터에서 플롯을 만들고 싶습니다. 데이터를 직접 입력하면 다음과 같습니다.

plot(timeSeries, data)

더 자연적인 단위로 시간을 보내는 방법이 있습니까? 예를 들어,이 경우 개월 / 년이 좋습니다. 편집하다: Gustav Larsson의 제안을 시도했지만 오류가 발생했습니다.

Out[128]:
[<matplotlib.lines.Line2D at 0x419aad0>]
---------------------------------------------------------------------------
OverflowError                             Traceback (most recent call last)
/usr/lib/python2.7/dist-packages/IPython/zmq/pylab/backend_inline.pyc in show(close)
    100     try:
    101         for figure_manager in Gcf.get_all_fig_managers():
--> 102             send_figure(figure_manager.canvas.figure)
    103     finally:
    104         show._to_draw = []

/usr/lib/python2.7/dist-packages/IPython/zmq/pylab/backend_inline.pyc in send_figure(fig)
    209     """
    210     fmt = InlineBackend.instance().figure_format
--> 211     data = print_figure(fig, fmt)
    212     # print_figure will return None if there's nothing to draw:
    213     if data is None:

/usr/lib/python2.7/dist-packages/IPython/core/pylabtools.pyc in print_figure(fig, fmt)
    102     try:
    103         bytes_io = BytesIO()
--> 104         fig.canvas.print_figure(bytes_io, format=fmt, bbox_inches='tight')
    105         data = bytes_io.getvalue()
    106     finally:

/usr/lib/pymodules/python2.7/matplotlib/backend_bases.pyc in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, **kwargs)
   1981                     orientation=orientation,
   1982                     dryrun=True,
-> 1983                     **kwargs)
   1984                 renderer = self.figure._cachedRenderer
   1985                 bbox_inches = self.figure.get_tightbbox(renderer)

/usr/lib/pymodules/python2.7/matplotlib/backends/backend_agg.pyc in print_png(self, filename_or_obj, *args, **kwargs)
    467 
    468     def print_png(self, filename_or_obj, *args, **kwargs):
--> 469         FigureCanvasAgg.draw(self)
    470         renderer = self.get_renderer()
    471         original_dpi = renderer.dpi

/usr/lib/pymodules/python2.7/matplotlib/backends/backend_agg.pyc in draw(self)
    419 
    420         try:
--> 421             self.figure.draw(self.renderer)
    422         finally:
    423             RendererAgg.lock.release()

/usr/lib/pymodules/python2.7/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
     53     def draw_wrapper(artist, renderer, *args, **kwargs):
     54         before(artist, renderer)
---> 55         draw(artist, renderer, *args, **kwargs)
     56         after(artist, renderer)
     57 

/usr/lib/pymodules/python2.7/matplotlib/figure.pyc in draw(self, renderer)
    896         dsu.sort(key=itemgetter(0))
    897         for zorder, a, func, args in dsu:
--> 898             func(*args)
    899 
    900         renderer.close_group('figure')

/usr/lib/pymodules/python2.7/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
     53     def draw_wrapper(artist, renderer, *args, **kwargs):
     54         before(artist, renderer)
---> 55         draw(artist, renderer, *args, **kwargs)
     56         after(artist, renderer)
     57 

/usr/lib/pymodules/python2.7/matplotlib/axes.pyc in draw(self, renderer, inframe)
   1995 
   1996         for zorder, a in dsu:
-> 1997             a.draw(renderer)
   1998 
   1999         renderer.close_group('axes')

/usr/lib/pymodules/python2.7/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
     53     def draw_wrapper(artist, renderer, *args, **kwargs):
     54         before(artist, renderer)
---> 55         draw(artist, renderer, *args, **kwargs)
     56         after(artist, renderer)
     57 

/usr/lib/pymodules/python2.7/matplotlib/axis.pyc in draw(self, renderer, *args, **kwargs)
   1039         renderer.open_group(__name__)
   1040 
-> 1041         ticks_to_draw = self._update_ticks(renderer)
   1042         ticklabelBoxes, ticklabelBoxes2 = self._get_tick_bboxes(ticks_to_draw, renderer)
   1043 

/usr/lib/pymodules/python2.7/matplotlib/axis.pyc in _update_ticks(self, renderer)
    929 
    930         interval = self.get_view_interval()
--> 931         tick_tups = [ t for t in self.iter_ticks()]
    932         if self._smart_bounds:
    933             # handle inverted limits

/usr/lib/pymodules/python2.7/matplotlib/axis.pyc in iter_ticks(self)
    876         Iterate through all of the major and minor ticks.
    877         """
--> 878         majorLocs = self.major.locator()
    879         majorTicks = self.get_major_ticks(len(majorLocs))
    880         self.major.formatter.set_locs(majorLocs)

/usr/lib/pymodules/python2.7/matplotlib/dates.pyc in __call__(self)
    747     def __call__(self):
    748         'Return the locations of the ticks'
--> 749         self.refresh()
    750         return self._locator()
    751 

/usr/lib/pymodules/python2.7/matplotlib/dates.pyc in refresh(self)
    756     def refresh(self):
    757         'Refresh internal information based on current limits.'
--> 758         dmin, dmax = self.viewlim_to_dt()
    759         self._locator = self.get_locator(dmin, dmax)
    760 

/usr/lib/pymodules/python2.7/matplotlib/dates.pyc in viewlim_to_dt(self)
    528     def viewlim_to_dt(self):
    529         vmin, vmax = self.axis.get_view_interval()
--> 530         return num2date(vmin, self.tz), num2date(vmax, self.tz)
    531 
    532     def _get_unit(self):

/usr/lib/pymodules/python2.7/matplotlib/dates.pyc in num2date(x, tz)
    287     """
    288     if tz is None: tz = _get_rc_timezone()
--> 289     if not cbook.iterable(x): return _from_ordinalf(x, tz)
    290     else: return [_from_ordinalf(val, tz) for val in x]
    291 

/usr/lib/pymodules/python2.7/matplotlib/dates.pyc in _from_ordinalf(x, tz)
    201     if tz is None: tz = _get_rc_timezone()
    202     ix = int(x)
--> 203     dt = datetime.datetime.fromordinal(ix)
    204     remainder = float(x) - ix
    205     hour, remainder = divmod(24*remainder, 1)

OverflowError: signed integer is greater than maximum

이것이 버그일까요? 또는 나는 뭔가를 놓친다. 나는 또한 간단한 것을 시도했다.

import matplotlib.pyplot as plt
import numpy as np
dates=np.array(["2011-11-13", "2011-11-14", "2011-11-15", "2011-11-16", "2011-11-19"], dtype='datetime64[us]')
data=np.array([1, 2, 3, 4, 5])
plt.plot_date(dates, data)
plt.show()

나는 아직도이 오류가 발생한다 :

OverflowError: signed integer is greater than maximum

나는 내가 뭘 잘못하고 있는지 이해하지 못합니다. ipython 0.13, matplotlib 1.1, 우분투 12.04 x64. 최종 편집 : matplotlib는 dtype = datetime64를 지원하지 않으므로 timeSeries를 datetime에서 일반 datetime.datetime으로 변환해야했습니다.

해결법

1. ==============================

   1.

   from datetime import datetime
   a=np.datetime64('2002-06-28').astype(datetime)
   plot_date(a,2)
   

2. ==============================

   2.다음을 시도해 볼 수 있습니다.

   다음을 시도해 볼 수 있습니다.

   plot_date(timeSeries, data)
   

   기본적으로 x 축은 날짜 축으로 간주되고 y 축은 일정 축으로 간주됩니다. 이것은 사용자 정의 할 수 있습니다.

from https://stackoverflow.com/questions/11376080/plot-numpy-datetime64-with-matplotlib by cc-by-sa and MIT license