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""" Matplotlib provides sophisticated date plotting capabilities, standing on the shoulders of python :mod:`datetime` and the add-on module :mod:`dateutil`.
.. _date-format:
Matplotlib date format ---------------------- Matplotlib represents dates using floating point numbers specifying the number of days since 0001-01-01 UTC, plus 1. For example, 0001-01-01, 06:00 is 1.25, not 0.25. Values < 1, i.e. dates before 0001-01-01 UTC are not supported.
There are a number of helper functions to convert between :mod:`datetime` objects and Matplotlib dates:
.. currentmodule:: matplotlib.dates
.. autosummary:: :nosignatures:
date2num num2date num2timedelta epoch2num num2epoch mx2num drange
.. note::
Like Python's datetime, mpl uses the Gregorian calendar for all conversions between dates and floating point numbers. This practice is not universal, and calendar differences can cause confusing differences between what Python and mpl give as the number of days since 0001-01-01 and what other software and databases yield. For example, the US Naval Observatory uses a calendar that switches from Julian to Gregorian in October, 1582. Hence, using their calculator, the number of days between 0001-01-01 and 2006-04-01 is 732403, whereas using the Gregorian calendar via the datetime module we find::
In [1]: date(2006, 4, 1).toordinal() - date(1, 1, 1).toordinal() Out[1]: 732401
All the Matplotlib date converters, tickers and formatters are timezone aware. If no explicit timezone is provided, the rcParam ``timezone`` is assumend. If you want to use a custom time zone, pass a :class:`datetime.tzinfo` instance with the tz keyword argument to :func:`num2date`, :func:`.plot_date`, and any custom date tickers or locators you create.
A wide range of specific and general purpose date tick locators and formatters are provided in this module. See :mod:`matplotlib.ticker` for general information on tick locators and formatters. These are described below.
The `dateutil module <https://dateutil.readthedocs.io>`_ provides additional code to handle date ticking, making it easy to place ticks on any kinds of dates. See examples below.
Date tickers ------------
Most of the date tickers can locate single or multiple values. For example::
# import constants for the days of the week from matplotlib.dates import MO, TU, WE, TH, FR, SA, SU
# tick on mondays every week loc = WeekdayLocator(byweekday=MO, tz=tz)
# tick on mondays and saturdays loc = WeekdayLocator(byweekday=(MO, SA))
In addition, most of the constructors take an interval argument::
# tick on mondays every second week loc = WeekdayLocator(byweekday=MO, interval=2)
The rrule locator allows completely general date ticking::
# tick every 5th easter rule = rrulewrapper(YEARLY, byeaster=1, interval=5) loc = RRuleLocator(rule)
Here are all the date tickers:
* :class:`MicrosecondLocator`: locate microseconds
* :class:`SecondLocator`: locate seconds
* :class:`MinuteLocator`: locate minutes
* :class:`HourLocator`: locate hours
* :class:`DayLocator`: locate specified days of the month
* :class:`WeekdayLocator`: Locate days of the week, e.g., MO, TU
* :class:`MonthLocator`: locate months, e.g., 7 for july
* :class:`YearLocator`: locate years that are multiples of base
* :class:`RRuleLocator`: locate using a :class:`matplotlib.dates.rrulewrapper`. The :class:`rrulewrapper` is a simple wrapper around a :class:`dateutil.rrule` (`dateutil <https://dateutil.readthedocs.io>`_) which allow almost arbitrary date tick specifications. See `rrule example <../gallery/ticks_and_spines/date_demo_rrule.html>`_.
* :class:`AutoDateLocator`: On autoscale, this class picks the best :class:`DateLocator` (e.g., :class:`RRuleLocator`) to set the view limits and the tick locations. If called with ``interval_multiples=True`` it will make ticks line up with sensible multiples of the tick intervals. E.g. if the interval is 4 hours, it will pick hours 0, 4, 8, etc as ticks. This behaviour is not guaranteed by default.
Date formatters ---------------
Here all all the date formatters:
* :class:`AutoDateFormatter`: attempts to figure out the best format to use. This is most useful when used with the :class:`AutoDateLocator`.
* :class:`DateFormatter`: use :func:`strftime` format strings
* :class:`IndexDateFormatter`: date plots with implicit *x* indexing. """
MONTHLY, WEEKLY, DAILY, HOURLY, MINUTELY, SECONDLY)
'num2epoch', 'mx2num', 'DateFormatter', 'IndexDateFormatter', 'AutoDateFormatter', 'DateLocator', 'RRuleLocator', 'AutoDateLocator', 'YearLocator', 'MonthLocator', 'WeekdayLocator', 'DayLocator', 'HourLocator', 'MinuteLocator', 'SecondLocator', 'MicrosecondLocator', 'rrule', 'MO', 'TU', 'WE', 'TH', 'FR', 'SA', 'SU', 'YEARLY', 'MONTHLY', 'WEEKLY', 'DAILY', 'HOURLY', 'MINUTELY', 'SECONDLY', 'MICROSECONDLY', 'relativedelta', 'seconds', 'minutes', 'hours', 'weeks')
""" Retrieve the preferred timeszone from the rcParams dictionary. """ s = matplotlib.rcParams['timezone'] if s == 'UTC': return UTC return dateutil.tz.gettz(s)
""" Time-related constants. """
MO, TU, WE, TH, FR, SA, SU)
""" Convert :mod:`datetime` or :mod:`date` to the Gregorian date as UTC float days, preserving hours, minutes, seconds and microseconds. Return value is a :func:`float`. """ # Convert to UTC tzi = getattr(dt, 'tzinfo', None) if tzi is not None: dt = dt.astimezone(UTC) tzi = UTC
base = float(dt.toordinal())
# If it's sufficiently datetime-like, it will have a `date()` method cdate = getattr(dt, 'date', lambda: None)() if cdate is not None: # Get a datetime object at midnight UTC midnight_time = datetime.time(0, tzinfo=tzi)
rdt = datetime.datetime.combine(cdate, midnight_time)
# Append the seconds as a fraction of a day base += (dt - rdt).total_seconds() / SEC_PER_DAY
return base
# a version of _to_ordinalf that can operate on numpy arrays
""" Convert `numpy.datetime64` or an ndarray of those types to Gregorian date as UTC float. Roundoff is via float64 precision. Practically: microseconds for dates between 290301 BC, 294241 AD, milliseconds for larger dates (see `numpy.datetime64`). Nanoseconds aren't possible because we do times compared to ``0001-01-01T00:00:00`` (plus one day). """
# the "extra" ensures that we at least allow the dynamic range out to # seconds. That should get out to +/-2e11 years. # NOTE: First cast truncates; second cast back is for NumPy 1.10. extra = d - d.astype('datetime64[s]').astype(d.dtype) extra = extra.astype('timedelta64[ns]') t0 = np.datetime64('0001-01-01T00:00:00').astype('datetime64[s]') dt = (d.astype('datetime64[s]') - t0).astype(np.float64) dt += extra.astype(np.float64) / 1.0e9 dt = dt / SEC_PER_DAY + 1.0
NaT_int = np.datetime64('NaT').astype(np.int64) d_int = d.astype(np.int64) try: dt[d_int == NaT_int] = np.nan except TypeError: if d_int == NaT_int: dt = np.nan return dt
""" Convert Gregorian float of the date, preserving hours, minutes, seconds and microseconds. Return value is a `.datetime`.
The input date *x* is a float in ordinal days at UTC, and the output will be the specified `.datetime` object corresponding to that time in timezone *tz*, or if *tz* is ``None``, in the timezone specified in :rc:`timezone`. """ if tz is None: tz = _get_rc_timezone()
ix, remainder = divmod(x, 1) ix = int(ix) if ix < 1: raise ValueError('Cannot convert {} to a date. This often happens if ' 'non-datetime values are passed to an axis that ' 'expects datetime objects.'.format(ix)) dt = datetime.datetime.fromordinal(ix).replace(tzinfo=UTC)
# Since the input date `x` float is unable to preserve microsecond # precision of time representation in non-antique years, the # resulting datetime is rounded to the nearest multiple of # `musec_prec`. A value of 20 is appropriate for current dates. musec_prec = 20 remainder_musec = int(round(remainder * MUSECONDS_PER_DAY / musec_prec) * musec_prec)
# For people trying to plot with full microsecond precision, enable # an early-year workaround if x < 30 * 365: remainder_musec = int(round(remainder * MUSECONDS_PER_DAY))
# add hours, minutes, seconds, microseconds dt += datetime.timedelta(microseconds=remainder_musec)
return dt.astimezone(tz)
# a version of _from_ordinalf that can operate on numpy arrays
""" Use this class to parse date strings to matplotlib datenums when you know the date format string of the date you are parsing. """ """ fmt: any valid strptime format is supported """ self.fmt = fmt
"""s : string to be converted return value: a date2num float """ return date2num(datetime.datetime(*time.strptime(s, self.fmt)[:6]))
""" Use this class to parse date strings to matplotlib datenums when you know the date format string of the date you are parsing. See :doc:`/gallery/misc/load_converter.py`. """ """ Args: fmt: any valid strptime format is supported encoding: encoding to use on byte input (default: 'utf-8') """ super().__init__(fmt) self.encoding = encoding
""" Args: b: byte input to be converted Returns: A date2num float """ s = b.decode(self.encoding) return super().__call__(s)
# a version of dateutil.parser.parse that can operate on nump0y arrays
""" Convert a date string to a datenum using :func:`dateutil.parser.parse`.
Parameters ---------- d : string or sequence of strings The dates to convert.
default : datetime instance, optional The default date to use when fields are missing in *d*. """ if isinstance(d, str): dt = dateutil.parser.parse(d, default=default) return date2num(dt) else: if default is not None: d = [dateutil.parser.parse(s, default=default) for s in d] d = np.asarray(d) if not d.size: return d return date2num(_dateutil_parser_parse_np_vectorized(d))
""" Convert datetime objects to Matplotlib dates.
Parameters ---------- d : `datetime.datetime` or `numpy.datetime64` or sequences of these
Returns ------- float or sequence of floats Number of days (fraction part represents hours, minutes, seconds, ms) since 0001-01-01 00:00:00 UTC, plus one.
Notes ----- The addition of one here is a historical artifact. Also, note that the Gregorian calendar is assumed; this is not universal practice. For details see the module docstring. """ if hasattr(d, "values"): # this unpacks pandas series or dataframes... d = d.values if not np.iterable(d): if (isinstance(d, np.datetime64) or (isinstance(d, np.ndarray) and np.issubdtype(d.dtype, np.datetime64))): return _dt64_to_ordinalf(d) return _to_ordinalf(d)
else: d = np.asarray(d) if np.issubdtype(d.dtype, np.datetime64): return _dt64_to_ordinalf(d) if not d.size: return d return _to_ordinalf_np_vectorized(d)
""" Convert a Julian date (or sequence) to a Matplotlib date (or sequence).
Parameters ---------- j : float or sequence of floats Julian date(s)
Returns ------- float or sequence of floats Matplotlib date(s) """ if cbook.iterable(j): j = np.asarray(j) return j - JULIAN_OFFSET
""" Convert a Matplotlib date (or sequence) to a Julian date (or sequence).
Parameters ---------- n : float or sequence of floats Matplotlib date(s)
Returns ------- float or sequence of floats Julian date(s) """ if cbook.iterable(n): n = np.asarray(n) return n + JULIAN_OFFSET
""" Convert Matplotlib dates to `~datetime.datetime` objects.
Parameters ---------- x : float or sequence of floats Number of days (fraction part represents hours, minutes, seconds) since 0001-01-01 00:00:00 UTC, plus one. tz : string, optional Timezone of *x* (defaults to rcparams ``timezone``).
Returns ------- `~datetime.datetime` or sequence of `~datetime.datetime` Dates are returned in timezone *tz*.
If *x* is a sequence, a sequence of :class:`datetime` objects will be returned.
Notes ----- The addition of one here is a historical artifact. Also, note that the Gregorian calendar is assumed; this is not universal practice. For details, see the module docstring. """ if tz is None: tz = _get_rc_timezone() if not cbook.iterable(x): return _from_ordinalf(x, tz) else: x = np.asarray(x) if not x.size: return x return _from_ordinalf_np_vectorized(x, tz).tolist()
return datetime.timedelta(days=x)
""" Convert number of days to a `~datetime.timedelta` object.
If *x* is a sequence, a sequence of `~datetime.timedelta` objects will be returned.
Parameters ---------- x : float, sequence of floats Number of days. The fraction part represents hours, minutes, seconds.
Returns ------- `datetime.timedelta` or list[`datetime.timedelta`]
""" if not cbook.iterable(x): return _ordinalf_to_timedelta(x) else: x = np.asarray(x) if not x.size: return x return _ordinalf_to_timedelta_np_vectorized(x).tolist()
""" Return a sequence of equally spaced Matplotlib dates.
The dates start at *dstart* and reach up to, but not including *dend*. They are spaced by *delta*.
Parameters ---------- dstart, dend : `~datetime.datetime` The date limits. delta : `datetime.timedelta` Spacing of the dates.
Returns ------- drange : `numpy.array` A list floats representing Matplotlib dates.
""" f1 = date2num(dstart) f2 = date2num(dend) step = delta.total_seconds() / SEC_PER_DAY
# calculate the difference between dend and dstart in times of delta num = int(np.ceil((f2 - f1) / step))
# calculate end of the interval which will be generated dinterval_end = dstart + num * delta
# ensure, that an half open interval will be generated [dstart, dend) if dinterval_end >= dend: # if the endpoint is greated than dend, just subtract one delta dinterval_end -= delta num -= 1
f2 = date2num(dinterval_end) # new float-endpoint return np.linspace(f1, f2, num + 1)
### date tickers and formatters ###
""" Tick location is seconds since the epoch. Use a :func:`strftime` format string.
Python only supports :mod:`datetime` :func:`strftime` formatting for years greater than 1900. Thanks to Andrew Dalke, Dalke Scientific Software who contributed the :func:`strftime` code below to include dates earlier than this year. """
""" *fmt* is a :func:`strftime` format string; *tz* is the :class:`tzinfo` instance. """ if tz is None: tz = _get_rc_timezone() self.fmt = fmt self.tz = tz
if x == 0: raise ValueError('DateFormatter found a value of x=0, which is ' 'an illegal date; this usually occurs because ' 'you have not informed the axis that it is ' 'plotting dates, e.g., with ax.xaxis_date()') return num2date(x, self.tz).strftime(self.fmt)
self.tz = tz
def _replace_common_substr(self, s1, s2, sub1, sub2, replacement): """Helper function for replacing substrings sub1 and sub2 located at the same indexes in strings s1 and s2 respectively, with the string replacement. It is expected that sub1 and sub2 have the same length. Returns the pair s1, s2 after the substitutions. """ # Find common indexes of substrings sub1 in s1 and sub2 in s2 # and make substitutions inplace. Because this is inplace, # it is okay if len(replacement) != len(sub1), len(sub2). i = 0 while True: j = s1.find(sub1, i) if j == -1: break
i = j + 1 if s2[j:j + len(sub2)] != sub2: continue
s1 = s1[:j] + replacement + s1[j + len(sub1):] s2 = s2[:j] + replacement + s2[j + len(sub2):]
return s1, s2
"""Call time.strftime for years before 1900 by rolling forward a multiple of 28 years.
*fmt* is a :func:`strftime` format string.
Dalke: I hope I did this math right. Every 28 years the calendar repeats, except through century leap years excepting the 400 year leap years. But only if you're using the Gregorian calendar. """ if fmt is None: fmt = self.fmt
# Since python's time module's strftime implementation does not # support %f microsecond (but the datetime module does), use a # regular expression substitution to replace instances of %f. # Note that this can be useful since python's floating-point # precision representation for datetime causes precision to be # more accurate closer to year 0 (around the year 2000, precision # can be at 10s of microseconds). fmt = re.sub(r'((^|[^%])(%%)*)%f', r'\g<1>{0:06d}'.format(dt.microsecond), fmt)
year = dt.year # For every non-leap year century, advance by # 6 years to get into the 28-year repeat cycle delta = 2000 - year off = 6 * (delta // 100 + delta // 400) year = year + off
# Move to between the years 1973 and 2000 year1 = year + ((2000 - year) // 28) * 28 year2 = year1 + 28 timetuple = dt.timetuple() # Generate timestamp string for year and year+28 s1 = time.strftime(fmt, (year1,) + timetuple[1:]) s2 = time.strftime(fmt, (year2,) + timetuple[1:])
# Replace instances of respective years (both 2-digit and 4-digit) # that are located at the same indexes of s1, s2 with dt's year. # Note that C++'s strftime implementation does not use padded # zeros or padded whitespace for %y or %Y for years before 100, but # uses padded zeros for %x. (For example, try the runnable examples # with .tm_year in the interval [-1900, -1800] on # http://en.cppreference.com/w/c/chrono/strftime.) For ease of # implementation, we always use padded zeros for %y, %Y, and %x. s1, s2 = self._replace_common_substr(s1, s2, "{0:04d}".format(year1), "{0:04d}".format(year2), "{0:04d}".format(dt.year)) s1, s2 = self._replace_common_substr(s1, s2, "{0:02d}".format(year1 % 100), "{0:02d}".format(year2 % 100), "{0:02d}".format(dt.year % 100)) return cbook.unicode_safe(s1)
""" Refer to documentation for :meth:`datetime.datetime.strftime`
*fmt* is a :meth:`datetime.datetime.strftime` format string.
Warning: For years before 1900, depending upon the current locale it is possible that the year displayed with %x might be incorrect. For years before 100, %y and %Y will yield zero-padded strings. """ if fmt is None: fmt = self.fmt fmt = self.illegal_s.sub(r"\1", fmt) fmt = fmt.replace("%s", "s") if dt.year >= 1900: # Note: in python 3.3 this is okay for years >= 1000, # refer to http://bugs.python.org/issue1777412 return cbook.unicode_safe(dt.strftime(fmt))
return self.strftime_pre_1900(dt, fmt)
""" Use with :class:`~matplotlib.ticker.IndexLocator` to cycle format strings by index. """ """ *t* is a sequence of dates (floating point days). *fmt* is a :func:`strftime` format string. """ if tz is None: tz = _get_rc_timezone() self.t = t self.fmt = fmt self.tz = tz
'Return the label for time *x* at position *pos*' ind = int(np.round(x)) if ind >= len(self.t) or ind <= 0: return '' return num2date(self.t[ind], self.tz).strftime(self.fmt)
""" This class attempts to figure out the best format to use. This is most useful when used with the :class:`AutoDateLocator`.
The AutoDateFormatter has a scale dictionary that maps the scale of the tick (the distance in days between one major tick) and a format string. The default looks like this::
self.scaled = { DAYS_PER_YEAR: rcParams['date.autoformat.year'], DAYS_PER_MONTH: rcParams['date.autoformat.month'], 1.0: rcParams['date.autoformat.day'], 1. / HOURS_PER_DAY: rcParams['date.autoformat.hour'], 1. / (MINUTES_PER_DAY): rcParams['date.autoformat.minute'], 1. / (SEC_PER_DAY): rcParams['date.autoformat.second'], 1. / (MUSECONDS_PER_DAY): rcParams['date.autoformat.microsecond'], }
The algorithm picks the key in the dictionary that is >= the current scale and uses that format string. You can customize this dictionary by doing::
>>> locator = AutoDateLocator() >>> formatter = AutoDateFormatter(locator) >>> formatter.scaled[1/(24.*60.)] = '%M:%S' # only show min and sec
A custom :class:`~matplotlib.ticker.FuncFormatter` can also be used. The following example shows how to use a custom format function to strip trailing zeros from decimal seconds and adds the date to the first ticklabel::
>>> def my_format_function(x, pos=None): ... x = matplotlib.dates.num2date(x) ... if pos == 0: ... fmt = '%D %H:%M:%S.%f' ... else: ... fmt = '%H:%M:%S.%f' ... label = x.strftime(fmt) ... label = label.rstrip("0") ... label = label.rstrip(".") ... return label >>> from matplotlib.ticker import FuncFormatter >>> formatter.scaled[1/(24.*60.)] = FuncFormatter(my_format_function) """
# This can be improved by providing some user-level direction on # how to choose the best format (precedence, etc...)
# Perhaps a 'struct' that has a field for each time-type where a # zero would indicate "don't show" and a number would indicate # "show" with some sort of priority. Same priorities could mean # show all with the same priority.
# Or more simply, perhaps just a format string for each # possibility...
""" Autoformat the date labels. The default format is the one to use if none of the values in ``self.scaled`` are greater than the unit returned by ``locator._get_unit()``. """ self._locator = locator self._tz = tz self.defaultfmt = defaultfmt self._formatter = DateFormatter(self.defaultfmt, tz) self.scaled = {DAYS_PER_YEAR: rcParams['date.autoformatter.year'], DAYS_PER_MONTH: rcParams['date.autoformatter.month'], 1.0: rcParams['date.autoformatter.day'], 1. / HOURS_PER_DAY: rcParams['date.autoformatter.hour'], 1. / (MINUTES_PER_DAY): rcParams['date.autoformatter.minute'], 1. / (SEC_PER_DAY): rcParams['date.autoformatter.second'], 1. / (MUSECONDS_PER_DAY): rcParams['date.autoformatter.microsecond']}
locator_unit_scale = float(self._locator._get_unit()) # Pick the first scale which is greater than the locator unit. fmt = next((fmt for scale, fmt in sorted(self.scaled.items()) if scale >= locator_unit_scale), self.defaultfmt)
if isinstance(fmt, str): self._formatter = DateFormatter(fmt, self._tz) result = self._formatter(x, pos) elif callable(fmt): result = fmt(x, pos) else: raise TypeError('Unexpected type passed to {0!r}.'.format(self))
return result
kwargs['freq'] = freq self._base_tzinfo = tzinfo
self._update_rrule(**kwargs)
self._construct.update(kwargs)
self._update_rrule(**self._construct)
tzinfo = self._base_tzinfo
# rrule does not play nicely with time zones - especially pytz time # zones, it's best to use naive zones and attach timezones once the # datetimes are returned if 'dtstart' in kwargs: dtstart = kwargs['dtstart'] if dtstart.tzinfo is not None: if tzinfo is None: tzinfo = dtstart.tzinfo else: dtstart = dtstart.astimezone(tzinfo)
kwargs['dtstart'] = dtstart.replace(tzinfo=None)
if 'until' in kwargs: until = kwargs['until'] if until.tzinfo is not None: if tzinfo is not None: until = until.astimezone(tzinfo) else: raise ValueError('until cannot be aware if dtstart ' 'is naive and tzinfo is None')
kwargs['until'] = until.replace(tzinfo=None)
self._construct = kwargs.copy() self._tzinfo = tzinfo self._rrule = rrule(**self._construct)
# pytz zones are attached by "localizing" the datetime if hasattr(tzinfo, 'localize'): return tzinfo.localize(dt, is_dst=True)
return dt.replace(tzinfo=tzinfo)
"""Decorator function that allows rrule methods to handle tzinfo.""" # This is only necessary if we're actually attaching a tzinfo if self._tzinfo is None: return f
# All datetime arguments must be naive. If they are not naive, they are # converted to the _tzinfo zone before dropping the zone. def normalize_arg(arg): if isinstance(arg, datetime.datetime) and arg.tzinfo is not None: if arg.tzinfo is not self._tzinfo: arg = arg.astimezone(self._tzinfo)
return arg.replace(tzinfo=None)
return arg
def normalize_args(args, kwargs): args = tuple(normalize_arg(arg) for arg in args) kwargs = {kw: normalize_arg(arg) for kw, arg in kwargs.items()}
return args, kwargs
# There are two kinds of functions we care about - ones that return # dates and ones that return lists of dates. if not returns_list: def inner_func(*args, **kwargs): args, kwargs = normalize_args(args, kwargs) dt = f(*args, **kwargs) return self._attach_tzinfo(dt, self._tzinfo) else: def inner_func(*args, **kwargs): args, kwargs = normalize_args(args, kwargs) dts = f(*args, **kwargs) return [self._attach_tzinfo(dt, self._tzinfo) for dt in dts]
return functools.wraps(f)(inner_func)
if name in self.__dict__: return self.__dict__[name]
f = getattr(self._rrule, name)
if name in {'after', 'before'}: return self._aware_return_wrapper(f) elif name in {'xafter', 'xbefore', 'between'}: return self._aware_return_wrapper(f, returns_list=True) else: return f
self.__dict__.update(state)
""" Determines the tick locations when plotting dates.
This class is subclassed by other Locators and is not meant to be used on its own. """
""" *tz* is a :class:`tzinfo` instance. """ if tz is None: tz = _get_rc_timezone() self.tz = tz
""" Set time zone info. """ self.tz = tz
""" Convert axis data interval to datetime objects. """ dmin, dmax = self.axis.get_data_interval() if dmin > dmax: dmin, dmax = dmax, dmin if dmin < 1: raise ValueError('datalim minimum {} is less than 1 and ' 'is an invalid Matplotlib date value. This often ' 'happens if you pass a non-datetime ' 'value to an axis that has datetime units' .format(dmin)) return num2date(dmin, self.tz), num2date(dmax, self.tz)
""" Converts the view interval to datetime objects. """ vmin, vmax = self.axis.get_view_interval() if vmin > vmax: vmin, vmax = vmax, vmin if vmin < 1: raise ValueError('view limit minimum {} is less than 1 and ' 'is an invalid Matplotlib date value. This ' 'often happens if you pass a non-datetime ' 'value to an axis that has datetime units' .format(vmin)) return num2date(vmin, self.tz), num2date(vmax, self.tz)
""" Return how many days a unit of the locator is; used for intelligent autoscaling. """ return 1
""" Return the number of units for each tick. """ return 1
""" Given the proposed upper and lower extent, adjust the range if it is too close to being singular (i.e. a range of ~0).
""" unit = self._get_unit() interval = self._get_interval() if abs(vmax - vmin) < 1e-6: vmin -= 2 * unit * interval vmax += 2 * unit * interval return vmin, vmax
# use the dateutil rrule instance
DateLocator.__init__(self, tz) self.rule = o
# if no data have been set, this will tank with a ValueError try: dmin, dmax = self.viewlim_to_dt() except ValueError: return []
return self.tick_values(dmin, dmax)
delta = relativedelta(vmax, vmin)
# We need to cap at the endpoints of valid datetime try: start = vmin - delta except (ValueError, OverflowError): start = _from_ordinalf(1.0)
try: stop = vmax + delta except (ValueError, OverflowError): # The magic number! stop = _from_ordinalf(3652059.9999999)
self.rule.set(dtstart=start, until=stop)
dates = self.rule.between(vmin, vmax, True) if len(dates) == 0: return date2num([vmin, vmax]) return self.raise_if_exceeds(date2num(dates))
""" Return how many days a unit of the locator is; used for intelligent autoscaling. """ freq = self.rule._rrule._freq return self.get_unit_generic(freq)
def get_unit_generic(freq): if freq == YEARLY: return DAYS_PER_YEAR elif freq == MONTHLY: return DAYS_PER_MONTH elif freq == WEEKLY: return DAYS_PER_WEEK elif freq == DAILY: return 1.0 elif freq == HOURLY: return 1.0 / HOURS_PER_DAY elif freq == MINUTELY: return 1.0 / MINUTES_PER_DAY elif freq == SECONDLY: return 1.0 / SEC_PER_DAY else: # error return -1 # or should this just return '1'?
return self.rule._rrule._interval
""" Set the view limits to include the data range. """ dmin, dmax = self.datalim_to_dt() delta = relativedelta(dmax, dmin)
# We need to cap at the endpoints of valid datetime try: start = dmin - delta except ValueError: start = _from_ordinalf(1.0)
try: stop = dmax + delta except ValueError: # The magic number! stop = _from_ordinalf(3652059.9999999)
self.rule.set(dtstart=start, until=stop) dmin, dmax = self.datalim_to_dt()
vmin = self.rule.before(dmin, True) if not vmin: vmin = dmin
vmax = self.rule.after(dmax, True) if not vmax: vmax = dmax
vmin = date2num(vmin) vmax = date2num(vmax)
return self.nonsingular(vmin, vmax)
""" On autoscale, this class picks the best :class:`DateLocator` to set the view limits and the tick locations. """ interval_multiples=True): """ *minticks* is the minimum number of ticks desired, which is used to select the type of ticking (yearly, monthly, etc.).
*maxticks* is the maximum number of ticks desired, which controls any interval between ticks (ticking every other, every 3, etc.). For really fine-grained control, this can be a dictionary mapping individual rrule frequency constants (YEARLY, MONTHLY, etc.) to their own maximum number of ticks. This can be used to keep the number of ticks appropriate to the format chosen in :class:`AutoDateFormatter`. Any frequency not specified in this dictionary is given a default value.
*tz* is a :class:`tzinfo` instance.
*interval_multiples* is a boolean that indicates whether ticks should be chosen to be multiple of the interval. This will lock ticks to 'nicer' locations. For example, this will force the ticks to be at hours 0,6,12,18 when hourly ticking is done at 6 hour intervals.
The AutoDateLocator has an interval dictionary that maps the frequency of the tick (a constant from dateutil.rrule) and a multiple allowed for that ticking. The default looks like this::
self.intervald = { YEARLY : [1, 2, 4, 5, 10, 20, 40, 50, 100, 200, 400, 500, 1000, 2000, 4000, 5000, 10000], MONTHLY : [1, 2, 3, 4, 6], DAILY : [1, 2, 3, 7, 14], HOURLY : [1, 2, 3, 4, 6, 12], MINUTELY: [1, 5, 10, 15, 30], SECONDLY: [1, 5, 10, 15, 30], MICROSECONDLY: [1, 2, 5, 10, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000, 200000, 500000, 1000000], }
The interval is used to specify multiples that are appropriate for the frequency of ticking. For instance, every 7 days is sensible for daily ticks, but for minutes/seconds, 15 or 30 make sense. You can customize this dictionary by doing::
locator = AutoDateLocator() locator.intervald[HOURLY] = [3] # only show every 3 hours """ DateLocator.__init__(self, tz) self._locator = YearLocator() self._freq = YEARLY self._freqs = [YEARLY, MONTHLY, DAILY, HOURLY, MINUTELY, SECONDLY, MICROSECONDLY] self.minticks = minticks
self.maxticks = {YEARLY: 11, MONTHLY: 12, DAILY: 11, HOURLY: 12, MINUTELY: 11, SECONDLY: 11, MICROSECONDLY: 8} if maxticks is not None: try: self.maxticks.update(maxticks) except TypeError: # Assume we were given an integer. Use this as the maximum # number of ticks for every frequency and create a # dictionary for this self.maxticks = dict.fromkeys(self._freqs, maxticks) self.interval_multiples = interval_multiples self.intervald = { YEARLY: [1, 2, 4, 5, 10, 20, 40, 50, 100, 200, 400, 500, 1000, 2000, 4000, 5000, 10000], MONTHLY: [1, 2, 3, 4, 6], DAILY: [1, 2, 3, 7, 14, 21], HOURLY: [1, 2, 3, 4, 6, 12], MINUTELY: [1, 5, 10, 15, 30], SECONDLY: [1, 5, 10, 15, 30], MICROSECONDLY: [1, 2, 5, 10, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000, 200000, 500000, 1000000]} if interval_multiples: # Swap "3" for "4" in the DAILY list; If we use 3 we get bad # tick loc for months w/ 31 days: 1, 4,..., 28, 31, 1 # If we use 4 then we get: 1, 5, ... 25, 29, 1 self.intervald[DAILY] = [1, 2, 4, 7, 14, 21]
self._byranges = [None, range(1, 13), range(1, 32), range(0, 24), range(0, 60), range(0, 60), None]
'Return the locations of the ticks' self.refresh() return self._locator()
return self.get_locator(vmin, vmax).tick_values(vmin, vmax)
# whatever is thrown at us, we can scale the unit. # But default nonsingular date plots at an ~4 year period. if vmin == vmax: vmin = vmin - DAYS_PER_YEAR * 2 vmax = vmax + DAYS_PER_YEAR * 2 return vmin, vmax
DateLocator.set_axis(self, axis) self._locator.set_axis(axis)
'Refresh internal information based on current limits.' dmin, dmax = self.viewlim_to_dt() self._locator = self.get_locator(dmin, dmax)
if self._freq in [MICROSECONDLY]: return 1. / MUSECONDS_PER_DAY else: return RRuleLocator.get_unit_generic(self._freq)
'Try to choose the view limits intelligently.' dmin, dmax = self.datalim_to_dt() self._locator = self.get_locator(dmin, dmax) return self._locator.autoscale()
'Pick the best locator based on a distance.' delta = relativedelta(dmax, dmin) tdelta = dmax - dmin
# take absolute difference if dmin > dmax: delta = -delta tdelta = -tdelta
# The following uses a mix of calls to relativedelta and timedelta # methods because there is incomplete overlap in the functionality of # these similar functions, and it's best to avoid doing our own math # whenever possible. numYears = float(delta.years) numMonths = numYears * MONTHS_PER_YEAR + delta.months numDays = tdelta.days # Avoids estimates of days/month, days/year numHours = numDays * HOURS_PER_DAY + delta.hours numMinutes = numHours * MIN_PER_HOUR + delta.minutes numSeconds = np.floor(tdelta.total_seconds()) numMicroseconds = np.floor(tdelta.total_seconds() * 1e6)
nums = [numYears, numMonths, numDays, numHours, numMinutes, numSeconds, numMicroseconds]
use_rrule_locator = [True] * 6 + [False]
# Default setting of bymonth, etc. to pass to rrule # [unused (for year), bymonth, bymonthday, byhour, byminute, # bysecond, unused (for microseconds)] byranges = [None, 1, 1, 0, 0, 0, None]
# Loop over all the frequencies and try to find one that gives at # least a minticks tick positions. Once this is found, look for # an interval from an list specific to that frequency that gives no # more than maxticks tick positions. Also, set up some ranges # (bymonth, etc.) as appropriate to be passed to rrulewrapper. for i, (freq, num) in enumerate(zip(self._freqs, nums)): # If this particular frequency doesn't give enough ticks, continue if num < self.minticks: # Since we're not using this particular frequency, set # the corresponding by_ to None so the rrule can act as # appropriate byranges[i] = None continue
# Find the first available interval that doesn't give too many # ticks for interval in self.intervald[freq]: if num <= interval * (self.maxticks[freq] - 1): break else: # We went through the whole loop without breaking, default to # the last interval in the list and raise a warning warnings.warn('AutoDateLocator was unable to pick an ' 'appropriate interval for this date range. ' 'It may be necessary to add an interval value ' "to the AutoDateLocator's intervald dictionary." ' Defaulting to {0}.'.format(interval))
# Set some parameters as appropriate self._freq = freq
if self._byranges[i] and self.interval_multiples: if i == DAILY and interval == 14: # just make first and 15th. Avoids 30th. byranges[i] = [1, 15] else: byranges[i] = self._byranges[i][::interval] interval = 1 else: byranges[i] = self._byranges[i]
break else: raise ValueError('No sensible date limit could be found in the ' 'AutoDateLocator.')
if (freq == YEARLY) and self.interval_multiples: locator = YearLocator(interval) elif use_rrule_locator[i]: _, bymonth, bymonthday, byhour, byminute, bysecond, _ = byranges rrule = rrulewrapper(self._freq, interval=interval, dtstart=dmin, until=dmax, bymonth=bymonth, bymonthday=bymonthday, byhour=byhour, byminute=byminute, bysecond=bysecond)
locator = RRuleLocator(rrule, self.tz) else: locator = MicrosecondLocator(interval, tz=self.tz) if dmin.year > 20 and interval < 1000: _log.warn('Plotting microsecond time intervals is not' ' well supported. Please see the' ' MicrosecondLocator documentation' ' for details.')
locator.set_axis(self.axis)
if self.axis is not None: locator.set_view_interval(*self.axis.get_view_interval()) locator.set_data_interval(*self.axis.get_data_interval()) return locator
""" Make ticks on a given day of each year that is a multiple of base.
Examples::
# Tick every year on Jan 1st locator = YearLocator()
# Tick every 5 years on July 4th locator = YearLocator(5, month=7, day=4) """ """ Mark years that are multiple of base on a given month and day (default jan 1). """ DateLocator.__init__(self, tz) self.base = ticker._Edge_integer(base, 0) self.replaced = {'month': month, 'day': day, 'hour': 0, 'minute': 0, 'second': 0, 'tzinfo': tz }
# if no data have been set, this will tank with a ValueError try: dmin, dmax = self.viewlim_to_dt() except ValueError: return []
return self.tick_values(dmin, dmax)
ymin = self.base.le(vmin.year) * self.base.step ymax = self.base.ge(vmax.year) * self.base.step
ticks = [vmin.replace(year=ymin, **self.replaced)] while True: dt = ticks[-1] if dt.year >= ymax: return date2num(ticks) year = dt.year + self.base.step ticks.append(dt.replace(year=year, **self.replaced))
""" Set the view limits to include the data range. """ dmin, dmax = self.datalim_to_dt()
ymin = self.base.le(dmin.year) ymax = self.base.ge(dmax.year) vmin = dmin.replace(year=ymin, **self.replaced) vmax = dmax.replace(year=ymax, **self.replaced)
vmin = date2num(vmin) vmax = date2num(vmax) return self.nonsingular(vmin, vmax)
""" Make ticks on occurrences of each month, e.g., 1, 3, 12. """ """ Mark every month in *bymonth*; *bymonth* can be an int or sequence. Default is ``range(1,13)``, i.e. every month.
*interval* is the interval between each iteration. For example, if ``interval=2``, mark every second occurrence. """ if bymonth is None: bymonth = range(1, 13) elif isinstance(bymonth, np.ndarray): # This fixes a bug in dateutil <= 2.3 which prevents the use of # numpy arrays in (among other things) the bymonthday, byweekday # and bymonth parameters. bymonth = [x.item() for x in bymonth.astype(int)]
rule = rrulewrapper(MONTHLY, bymonth=bymonth, bymonthday=bymonthday, interval=interval, **self.hms0d) RRuleLocator.__init__(self, rule, tz)
""" Make ticks on occurrences of each weekday. """
""" Mark every weekday in *byweekday*; *byweekday* can be a number or sequence.
Elements of *byweekday* must be one of MO, TU, WE, TH, FR, SA, SU, the constants from :mod:`dateutil.rrule`, which have been imported into the :mod:`matplotlib.dates` namespace.
*interval* specifies the number of weeks to skip. For example, ``interval=2`` plots every second week. """ if isinstance(byweekday, np.ndarray): # This fixes a bug in dateutil <= 2.3 which prevents the use of # numpy arrays in (among other things) the bymonthday, byweekday # and bymonth parameters. [x.item() for x in byweekday.astype(int)]
rule = rrulewrapper(DAILY, byweekday=byweekday, interval=interval, **self.hms0d) RRuleLocator.__init__(self, rule, tz)
""" Make ticks on occurrences of each day of the month. For example, 1, 15, 30. """ """ Mark every day in *bymonthday*; *bymonthday* can be an int or sequence.
Default is to tick every day of the month: ``bymonthday=range(1,32)`` """ if not interval == int(interval) or interval < 1: raise ValueError("interval must be an integer greater than 0") if bymonthday is None: bymonthday = range(1, 32) elif isinstance(bymonthday, np.ndarray): # This fixes a bug in dateutil <= 2.3 which prevents the use of # numpy arrays in (among other things) the bymonthday, byweekday # and bymonth parameters. bymonthday = [x.item() for x in bymonthday.astype(int)]
rule = rrulewrapper(DAILY, bymonthday=bymonthday, interval=interval, **self.hms0d) RRuleLocator.__init__(self, rule, tz)
""" Make ticks on occurrences of each hour. """ """ Mark every hour in *byhour*; *byhour* can be an int or sequence. Default is to tick every hour: ``byhour=range(24)``
*interval* is the interval between each iteration. For example, if ``interval=2``, mark every second occurrence. """ if byhour is None: byhour = range(24)
rule = rrulewrapper(HOURLY, byhour=byhour, interval=interval, byminute=0, bysecond=0) RRuleLocator.__init__(self, rule, tz)
""" Make ticks on occurrences of each minute. """ """ Mark every minute in *byminute*; *byminute* can be an int or sequence. Default is to tick every minute: ``byminute=range(60)``
*interval* is the interval between each iteration. For example, if ``interval=2``, mark every second occurrence. """ if byminute is None: byminute = range(60)
rule = rrulewrapper(MINUTELY, byminute=byminute, interval=interval, bysecond=0) RRuleLocator.__init__(self, rule, tz)
""" Make ticks on occurrences of each second. """ """ Mark every second in *bysecond*; *bysecond* can be an int or sequence. Default is to tick every second: ``bysecond = range(60)``
*interval* is the interval between each iteration. For example, if ``interval=2``, mark every second occurrence.
""" if bysecond is None: bysecond = range(60)
rule = rrulewrapper(SECONDLY, bysecond=bysecond, interval=interval) RRuleLocator.__init__(self, rule, tz)
""" Make ticks on regular intervals of one or more microsecond(s).
.. note::
Due to the floating point representation of time in days since 0001-01-01 UTC (plus 1), plotting data with microsecond time resolution does not work well with current dates.
If you want microsecond resolution time plots, it is strongly recommended to use floating point seconds, not datetime-like time representation.
If you really must use datetime.datetime() or similar and still need microsecond precision, your only chance is to use very early years; using year 0001 is recommended.
""" """ *interval* is the interval between each iteration. For example, if ``interval=2``, mark every second microsecond.
""" self._interval = interval self._wrapped_locator = ticker.MultipleLocator(interval) self.tz = tz
self._wrapped_locator.set_axis(axis) return DateLocator.set_axis(self, axis)
self._wrapped_locator.set_view_interval(vmin, vmax) return DateLocator.set_view_interval(self, vmin, vmax)
self._wrapped_locator.set_data_interval(vmin, vmax) return DateLocator.set_data_interval(self, vmin, vmax)
# if no data have been set, this will tank with a ValueError try: dmin, dmax = self.viewlim_to_dt() except ValueError: return []
return self.tick_values(dmin, dmax)
nmin, nmax = date2num((vmin, vmax)) nmin *= MUSECONDS_PER_DAY nmax *= MUSECONDS_PER_DAY ticks = self._wrapped_locator.tick_values(nmin, nmax) ticks = [tick / MUSECONDS_PER_DAY for tick in ticks] return ticks
""" Return how many days a unit of the locator is; used for intelligent autoscaling. """ return 1. / MUSECONDS_PER_DAY
""" Return the number of units for each tick. """ return self._interval
""" Assert that datetimes *d1* and *d2* are within *epsilon* microseconds. """ delta = d2 - d1 mus = abs(delta.total_seconds() * 1e6) assert mus < epsilon
""" Assert that float ordinals *o1* and *o2* are within *epsilon* microseconds. """ delta = abs((o2 - o1) * MUSECONDS_PER_DAY) assert delta < epsilon
""" Convert an epoch or sequence of epochs to the new date format, that is days since 0001. """ return EPOCH_OFFSET + np.asarray(e) / SEC_PER_DAY
""" Convert days since 0001 to epoch. *d* can be a number or sequence. """ return (np.asarray(d) - EPOCH_OFFSET) * SEC_PER_DAY
""" Convert mx :class:`datetime` instance (or sequence of mx instances) to the new date format. """ scalar = False if not cbook.iterable(mxdates): scalar = True mxdates = [mxdates] ret = epoch2num([m.ticks() for m in mxdates]) if scalar: return ret[0] else: return ret
""" Create a date locator with *numticks* (approx) and a date formatter for *span* in days. Return value is (locator, formatter). """
if span == 0: span = 1 / HOURS_PER_DAY
mins = span * MINUTES_PER_DAY hrs = span * HOURS_PER_DAY days = span wks = span / DAYS_PER_WEEK months = span / DAYS_PER_MONTH # Approx years = span / DAYS_PER_YEAR # Approx
if years > numticks: locator = YearLocator(int(years / numticks), tz=tz) # define fmt = '%Y' elif months > numticks: locator = MonthLocator(tz=tz) fmt = '%b %Y' elif wks > numticks: locator = WeekdayLocator(tz=tz) fmt = '%a, %b %d' elif days > numticks: locator = DayLocator(interval=int(math.ceil(days / numticks)), tz=tz) fmt = '%b %d' elif hrs > numticks: locator = HourLocator(interval=int(math.ceil(hrs / numticks)), tz=tz) fmt = '%H:%M\n%b %d' elif mins > numticks: locator = MinuteLocator(interval=int(math.ceil(mins / numticks)), tz=tz) fmt = '%H:%M:%S' else: locator = MinuteLocator(tz=tz) fmt = '%H:%M:%S'
formatter = DateFormatter(fmt, tz=tz) return locator, formatter
""" Return seconds as days. """ return s / SEC_PER_DAY
""" Return minutes as days. """ return m / MINUTES_PER_DAY
""" Return hours as days. """ return h / HOURS_PER_DAY
""" Return weeks as days. """ return w * DAYS_PER_WEEK
""" Converter for datetime.date and datetime.datetime data, or for date/time data represented as it would be converted by :func:`date2num`.
The 'unit' tag for such data is None or a tzinfo instance. """
def axisinfo(unit, axis): """ Return the :class:`~matplotlib.units.AxisInfo` for *unit*.
*unit* is a tzinfo instance or None. The *axis* argument is required but not used. """ tz = unit
majloc = AutoDateLocator(tz=tz) majfmt = AutoDateFormatter(majloc, tz=tz) datemin = datetime.date(2000, 1, 1) datemax = datetime.date(2010, 1, 1)
return units.AxisInfo(majloc=majloc, majfmt=majfmt, label='', default_limits=(datemin, datemax))
def convert(value, unit, axis): """ If *value* is not already a number or sequence of numbers, convert it with :func:`date2num`.
The *unit* and *axis* arguments are not used. """ return date2num(value)
def default_units(x, axis): """ Return the tzinfo instance of *x* or of its first element, or None """ if isinstance(x, np.ndarray): x = x.ravel()
try: x = cbook.safe_first_element(x) except (TypeError, StopIteration): pass
try: return x.tzinfo except AttributeError: pass return None
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