def _test(ax):
xlim = ax.get_xlim()
ax.set_xlim(xlim[0] - 5, xlim[1] + 10)
ax.get_figure().canvas.draw()
result = ax.get_xlim()
self.assertEqual(result[0], xlim[0] - 5)
self.assertEqual(result[1], xlim[1] + 10)
# string
expected = (Period('1/1/2000',
ax.freq), Period('4/1/2000', ax.freq))
ax.set_xlim('1/1/2000', '4/1/2000')
ax.get_figure().canvas.draw()
result = ax.get_xlim()
self.assertEqual(int(result[0]), expected[0].ordinal)
self.assertEqual(int(result[1]), expected[1].ordinal)
# datetim
expected = (Period('1/1/2000',
ax.freq), Period('4/1/2000', ax.freq))
ax.set_xlim(datetime(2000, 1, 1), datetime(2000, 4, 1))
ax.get_figure().canvas.draw()
result = ax.get_xlim()
self.assertEqual(int(result[0]), expected[0].ordinal)
self.assertEqual(int(result[1]), expected[1].ordinal)
fig = ax.get_figure()
plt.close(fig)
def _test(ax):
xlim = ax.get_xlim()
ax.set_xlim(xlim[0] - 5, xlim[1] + 10)
ax.get_figure().canvas.draw()
result = ax.get_xlim()
assert result[0] == xlim[0] - 5
assert result[1] == xlim[1] + 10
# string
expected = (Period('1/1/2000',
ax.freq), Period('4/1/2000', ax.freq))
ax.set_xlim('1/1/2000', '4/1/2000')
ax.get_figure().canvas.draw()
result = ax.get_xlim()
assert int(result[0]) == expected[0].ordinal
assert int(result[1]) == expected[1].ordinal
# datetim
expected = (Period('1/1/2000',
ax.freq), Period('4/1/2000', ax.freq))
ax.set_xlim(datetime(2000, 1, 1), datetime(2000, 4, 1))
ax.get_figure().canvas.draw()
result = ax.get_xlim()
assert int(result[0]) == expected[0].ordinal
assert int(result[1]) == expected[1].ordinal
fig = ax.get_figure()
plt.close(fig)
def test_get_datevalue(self):
from pandas.plotting._converter import get_datevalue
assert get_datevalue(None, 'D') is None
assert get_datevalue(1987, 'A') == 1987
assert (get_datevalue(Period(1987, 'A'),
'M') == Period('1987-12', 'M').ordinal)
assert (get_datevalue('1/1/1987', 'D') == Period('1987-1-1',
'D').ordinal)
def test_get_datevalue(self):
from pandas.plotting._converter import get_datevalue
self.assertIsNone(get_datevalue(None, 'D'))
self.assertEqual(get_datevalue(1987, 'A'), 1987)
self.assertEqual(get_datevalue(Period(1987, 'A'), 'M'),
Period('1987-12', 'M').ordinal)
self.assertEqual(get_datevalue('1/1/1987', 'D'),
Period('1987-1-1', 'D').ordinal)
def test_get_period_range_edges(self, first, last, freq, exp_first, exp_last):
first = Period(first)
last = Period(last)
exp_first = Period(exp_first, freq=freq)
exp_last = Period(exp_last, freq=freq)
freq = pd.tseries.frequencies.to_offset(freq)
result = _get_period_range_edges(first, last, freq)
expected = (exp_first, exp_last)
assert result == expected
def __call__(self, x, pos: int = 0) -> str:
if self.formatdict is None:
return ""
else:
fmt = self.formatdict.pop(x, "")
if isinstance(fmt, np.bytes_):
fmt = fmt.decode("utf-8")
period = Period(ordinal=int(x), freq=self.freq)
assert isinstance(period, Period)
return period.strftime(fmt)
def test_resample_dup_index():
# GH 4812
# dup columns with resample raising
df = DataFrame(np.random.randn(4, 12), index=[2000, 2000, 2000, 2000],
columns=[Period(year=2000, month=i + 1, freq='M')
for i in range(12)])
df.iloc[3, :] = np.nan
result = df.resample('Q', axis=1).mean()
expected = df.groupby(lambda x: int((x.month - 1) / 3), axis=1).mean()
expected.columns = [
Period(year=2000, quarter=i + 1, freq='Q') for i in range(4)]
assert_frame_equal(result, expected)
def test_resample_basic(self):
# GH3609
s = Series(range(100), index=date_range(
'20130101', freq='s', periods=100, name='idx'), dtype='float')
s[10:30] = np.nan
index = PeriodIndex([
Period('2013-01-01 00:00', 'T'),
Period('2013-01-01 00:01', 'T')], name='idx')
expected = Series([34.5, 79.5], index=index)
result = s.to_period().resample('T', kind='period').mean()
assert_series_equal(result, expected)
result2 = s.resample('T', kind='period').mean()
assert_series_equal(result2, expected)
def _use_dynamic_x(ax, data):
freq = _get_index_freq(data)
ax_freq = _get_ax_freq(ax)
if freq is None: # convert irregular if axes has freq info
freq = ax_freq
else: # do not use tsplot if irregular was plotted first
if (ax_freq is None) and (len(ax.get_lines()) > 0):
return False
if freq is None:
return False
if isinstance(freq, DateOffset):
freq = freq.rule_code
else:
freq = frequencies.get_base_alias(freq)
freq = frequencies.get_period_alias(freq)
if freq is None:
return False
# hack this for 0.10.1, creating more technical debt...sigh
if isinstance(data.index, DatetimeIndex):
base = frequencies.get_freq(freq)
x = data.index
if (base <= frequencies.FreqGroup.FR_DAY):
return x[:1].is_normalized
return Period(x[0], freq).to_timestamp(tz=x.tz) == x[0]
return True
def __call__(self, x, pos=0):
if self.formatdict is None:
return ""
else:
fmt = self.formatdict.pop(x, "")
return Period(ordinal=int(x), freq=self.freq).strftime(fmt)
def test_period_index_construction_from_strings(klass):
# https://github.com/pandas-dev/pandas/issues/26109
strings = ["2020Q1", "2020Q2"] * 2
data = klass(strings)
result = PeriodIndex(data, freq="Q")
expected = PeriodIndex([Period(s) for s in strings])
tm.assert_index_equal(result, expected)
def test_finder_monthly_long(self):
rng = period_range('1988Q1', periods=24 * 12, freq='M')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
xp = Period('1989Q1', 'M').ordinal
self.assertEqual(rs, xp)
def test_resample_basic(self):
# GH3609
s = Series(
range(100),
index=date_range("20130101", freq="s", periods=100, name="idx"),
dtype="float",
)
s[10:30] = np.nan
index = PeriodIndex(
[Period("2013-01-01 00:00", "T"), Period("2013-01-01 00:01", "T")],
name="idx",
)
expected = Series([34.5, 79.5], index=index)
result = s.to_period().resample("T", kind="period").mean()
tm.assert_series_equal(result, expected)
result2 = s.resample("T", kind="period").mean()
tm.assert_series_equal(result2, expected)
def __call__(self, x, pos=0):
_check_implicitly_registered()
if self.formatdict is None:
return ''
else:
fmt = self.formatdict.pop(x, '')
return Period(ordinal=int(x), freq=self.freq).strftime(fmt)
def test_finder_hourly(self):
nhours = 23
rng = date_range('1/1/1999', freq='H', periods=nhours)
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
xp = Period('1/1/1999', freq='H').ordinal
self.assertEqual(rs, xp)
def __call__(self, x, pos=0):
if self.formatdict is None:
return ""
else:
fmt = self.formatdict.pop(x, "")
if isinstance(fmt, np.bytes_):
fmt = fmt.decode("utf-8")
return Period(ordinal=int(x), freq=self.freq).strftime(fmt)
def test_finder_minutely(self):
nminutes = 50 * 24 * 60
rng = date_range('1/1/1999', freq='Min', periods=nminutes)
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
xp = Period('1/1/1999', freq='Min').ordinal
self.assertEqual(rs, xp)
def test_finder_annual(self):
import matplotlib.pyplot as plt
xp = [1987, 1988, 1990, 1990, 1995, 2020, 2070, 2170]
for i, nyears in enumerate([5, 10, 19, 49, 99, 199, 599, 1001]):
rng = period_range('1987', periods=nyears, freq='A')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
self.assertEqual(rs, Period(xp[i], freq='A').ordinal)
plt.close(ax.get_figure())
def get_datevalue(date, freq):
if isinstance(date, Period):
return date.asfreq(freq).ordinal
elif isinstance(date,
(str, datetime, pydt.date, pydt.time, np.datetime64)):
return Period(date, freq).ordinal
elif (is_integer(date) or is_float(date)
or (isinstance(date, (np.ndarray, Index)) and (date.size == 1))):
return date
elif date is None:
return None
raise ValueError(f"Unrecognizable date '{date}'")
def get_datevalue(date, freq):
if isinstance(date, Period):
return date.asfreq(freq).ordinal
elif isinstance(date, (compat.string_types, datetime,
pydt.date, pydt.time)):
return Period(date, freq).ordinal
elif (is_integer(date) or is_float(date) or
(isinstance(date, (np.ndarray, Index)) and (date.size == 1))):
return date
elif date is None:
return None
raise ValueError("Unrecognizable date '%s'" % date)
def test_finder_quarterly(self):
import matplotlib.pyplot as plt
xp = Period('1988Q1').ordinal
yrs = [3.5, 11]
for n in yrs:
rng = period_range('1987Q2', periods=int(n * 4), freq='Q')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
assert rs == xp
(vmin, vmax) = ax.get_xlim()
ax.set_xlim(vmin + 0.9, vmax)
rs = xaxis.get_majorticklocs()[0]
assert xp == rs
plt.close(ax.get_figure())
def test_finder_daily(self):
import matplotlib.pyplot as plt
xp = Period('1999-1-1', freq='B').ordinal
day_lst = [10, 40, 252, 400, 950, 2750, 10000]
for n in day_lst:
rng = bdate_range('1999-1-1', periods=n)
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
self.assertEqual(xp, rs)
vmin, vmax = ax.get_xlim()
ax.set_xlim(vmin + 0.9, vmax)
rs = xaxis.get_majorticklocs()[0]
self.assertEqual(xp, rs)
plt.close(ax.get_figure())
def test_finder_monthly(self):
import matplotlib.pyplot as plt
xp = Period('Jan 1988').ordinal
yrs = [1.15, 2.5, 4, 11]
for n in yrs:
rng = period_range('1987Q2', periods=int(n * 12), freq='M')
ser = Series(np.random.randn(len(rng)), rng)
ax = ser.plot()
xaxis = ax.get_xaxis()
rs = xaxis.get_majorticklocs()[0]
self.assertEqual(rs, xp)
vmin, vmax = ax.get_xlim()
ax.set_xlim(vmin + 0.9, vmax)
rs = xaxis.get_majorticklocs()[0]
self.assertEqual(xp, rs)
plt.close(ax.get_figure())
def format_dateaxis(subplot, freq, index):
"""
Pretty-formats the date axis (x-axis).
Major and minor ticks are automatically set for the frequency of the
current underlying series. As the dynamic mode is activated by
default, changing the limits of the x axis will intelligently change
the positions of the ticks.
"""
# handle index specific formatting
# Note: DatetimeIndex does not use this
# interface. DatetimeIndex uses matplotlib.date directly
if isinstance(index, PeriodIndex):
majlocator = TimeSeries_DateLocator(freq,
dynamic_mode=True,
minor_locator=False,
plot_obj=subplot)
minlocator = TimeSeries_DateLocator(freq,
dynamic_mode=True,
minor_locator=True,
plot_obj=subplot)
subplot.xaxis.set_major_locator(majlocator)
subplot.xaxis.set_minor_locator(minlocator)
majformatter = TimeSeries_DateFormatter(freq,
dynamic_mode=True,
minor_locator=False,
plot_obj=subplot)
minformatter = TimeSeries_DateFormatter(freq,
dynamic_mode=True,
minor_locator=True,
plot_obj=subplot)
subplot.xaxis.set_major_formatter(majformatter)
subplot.xaxis.set_minor_formatter(minformatter)
# x and y coord info
subplot.format_coord = lambda t, y: ("t = {0} y = {1:8f}".format(
Period(ordinal=int(t), freq=freq), y))
elif isinstance(index, TimedeltaIndex):
subplot.xaxis.set_major_formatter(TimeSeries_TimedeltaFormatter())
else:
raise TypeError('index type not supported')
pylab.draw_if_interactive()
def test_take_fill_valid(self, arr1d):
arr = arr1d
dti = self.index_cls(arr1d)
now = Timestamp.now().tz_localize(dti.tz)
result = arr.take([-1, 1], allow_fill=True, fill_value=now)
assert result[0] == now
msg = f"value should be a '{arr1d._scalar_type.__name__}' or 'NaT'. Got"
with pytest.raises(TypeError, match=msg):
# fill_value Timedelta invalid
arr.take([-1, 1], allow_fill=True, fill_value=now - now)
with pytest.raises(TypeError, match=msg):
# fill_value Period invalid
arr.take([-1, 1], allow_fill=True, fill_value=Period("2014Q1"))
tz = None if dti.tz is not None else "US/Eastern"
now = Timestamp.now().tz_localize(tz)
msg = "Cannot compare tz-naive and tz-aware datetime-like objects"
with pytest.raises(TypeError, match=msg):
# Timestamp with mismatched tz-awareness
arr.take([-1, 1], allow_fill=True, fill_value=now)
value = pd.NaT.value
msg = f"value should be a '{arr1d._scalar_type.__name__}' or 'NaT'. Got"
with pytest.raises(TypeError, match=msg):
# require NaT, not iNaT, as it could be confused with an integer
arr.take([-1, 1], allow_fill=True, fill_value=value)
value = np.timedelta64("NaT", "ns")
with pytest.raises(TypeError, match=msg):
# require appropriate-dtype if we have a NA value
arr.take([-1, 1], allow_fill=True, fill_value=value)
if arr.tz is not None:
# GH#37356
# Assuming here that arr1d fixture does not include Australia/Melbourne
value = Timestamp.now().tz_localize("Australia/Melbourne")
msg = "Timezones don't match. .* != 'Australia/Melbourne'"
with pytest.raises(ValueError, match=msg):
# require tz match, not just tzawareness match
arr.take([-1, 1], allow_fill=True, fill_value=value)
def test_corner_cases(simple_period_range_series, simple_date_range_series):
# miscellaneous test coverage
rng = date_range("1/1/2000", periods=12, freq="t")
ts = Series(np.random.randn(len(rng)), index=rng)
result = ts.resample("5t", closed="right", label="left").mean()
ex_index = date_range("1999-12-31 23:55", periods=4, freq="5t")
tm.assert_index_equal(result.index, ex_index)
len0pts = simple_period_range_series("2007-01", "2010-05", freq="M")[:0]
# it works
result = len0pts.resample("A-DEC").mean()
assert len(result) == 0
# resample to periods
ts = simple_date_range_series("2000-04-28", "2000-04-30 11:00", freq="h")
result = ts.resample("M", kind="period").mean()
assert len(result) == 1
assert result.index[0] == Period("2000-04", freq="M")
def test_corner_cases(simple_period_range_series, simple_date_range_series):
# miscellaneous test coverage
rng = date_range('1/1/2000', periods=12, freq='t')
ts = Series(np.random.randn(len(rng)), index=rng)
result = ts.resample('5t', closed='right', label='left').mean()
ex_index = date_range('1999-12-31 23:55', periods=4, freq='5t')
tm.assert_index_equal(result.index, ex_index)
len0pts = simple_period_range_series('2007-01', '2010-05', freq='M')[:0]
# it works
result = len0pts.resample('A-DEC').mean()
assert len(result) == 0
# resample to periods
ts = simple_date_range_series('2000-04-28', '2000-04-30 11:00', freq='h')
result = ts.resample('M', kind='period').mean()
assert len(result) == 1
assert result.index[0] == Period('2000-04', freq='M')
def _daily_finder(vmin, vmax, freq):
periodsperday = -1
if freq >= FreqGroup.FR_HR:
if freq == FreqGroup.FR_NS:
periodsperday = 24 * 60 * 60 * 1000000000
elif freq == FreqGroup.FR_US:
periodsperday = 24 * 60 * 60 * 1000000
elif freq == FreqGroup.FR_MS:
periodsperday = 24 * 60 * 60 * 1000
elif freq == FreqGroup.FR_SEC:
periodsperday = 24 * 60 * 60
elif freq == FreqGroup.FR_MIN:
periodsperday = 24 * 60
elif freq == FreqGroup.FR_HR:
periodsperday = 24
else: # pragma: no cover
raise ValueError(f"unexpected frequency: {freq}")
periodsperyear = 365 * periodsperday
periodspermonth = 28 * periodsperday
elif freq == FreqGroup.FR_BUS:
periodsperyear = 261
periodspermonth = 19
elif freq == FreqGroup.FR_DAY:
periodsperyear = 365
periodspermonth = 28
elif resolution.get_freq_group(freq) == FreqGroup.FR_WK:
periodsperyear = 52
periodspermonth = 3
else: # pragma: no cover
raise ValueError("unexpected frequency")
# save this for later usage
vmin_orig = vmin
(vmin, vmax) = (
Period(ordinal=int(vmin), freq=freq),
Period(ordinal=int(vmax), freq=freq),
)
span = vmax.ordinal - vmin.ordinal + 1
dates_ = period_range(start=vmin, end=vmax, freq=freq)
# Initialize the output
info = np.zeros(span,
dtype=[("val", np.int64), ("maj", bool), ("min", bool),
("fmt", "|S20")])
info["val"][:] = dates_.asi8
info["fmt"][:] = ""
info["maj"][[0, -1]] = True
# .. and set some shortcuts
info_maj = info["maj"]
info_min = info["min"]
info_fmt = info["fmt"]
def first_label(label_flags):
if (label_flags[0]
== 0) and (label_flags.size > 1) and ((vmin_orig % 1) > 0.0):
return label_flags[1]
else:
return label_flags[0]
# Case 1. Less than a month
if span <= periodspermonth:
day_start = period_break(dates_, "day")
month_start = period_break(dates_, "month")
def _hour_finder(label_interval, force_year_start):
_hour = dates_.hour
_prev_hour = (dates_ - 1 * dates_.freq).hour
hour_start = (_hour - _prev_hour) != 0
info_maj[day_start] = True
info_min[hour_start & (_hour % label_interval == 0)] = True
year_start = period_break(dates_, "year")
info_fmt[hour_start & (_hour % label_interval == 0)] = "%H:%M"
info_fmt[day_start] = "%H:%M\n%d-%b"
info_fmt[year_start] = "%H:%M\n%d-%b\n%Y"
if force_year_start and not has_level_label(year_start, vmin_orig):
info_fmt[first_label(day_start)] = "%H:%M\n%d-%b\n%Y"
def _minute_finder(label_interval):
hour_start = period_break(dates_, "hour")
_minute = dates_.minute
_prev_minute = (dates_ - 1 * dates_.freq).minute
minute_start = (_minute - _prev_minute) != 0
info_maj[hour_start] = True
info_min[minute_start & (_minute % label_interval == 0)] = True
year_start = period_break(dates_, "year")
info_fmt = info["fmt"]
info_fmt[minute_start & (_minute % label_interval == 0)] = "%H:%M"
info_fmt[day_start] = "%H:%M\n%d-%b"
info_fmt[year_start] = "%H:%M\n%d-%b\n%Y"
def _second_finder(label_interval):
minute_start = period_break(dates_, "minute")
_second = dates_.second
_prev_second = (dates_ - 1 * dates_.freq).second
second_start = (_second - _prev_second) != 0
info["maj"][minute_start] = True
info["min"][second_start & (_second % label_interval == 0)] = True
year_start = period_break(dates_, "year")
info_fmt = info["fmt"]
info_fmt[second_start
& (_second % label_interval == 0)] = "%H:%M:%S"
info_fmt[day_start] = "%H:%M:%S\n%d-%b"
info_fmt[year_start] = "%H:%M:%S\n%d-%b\n%Y"
if span < periodsperday / 12000.0:
_second_finder(1)
elif span < periodsperday / 6000.0:
_second_finder(2)
elif span < periodsperday / 2400.0:
_second_finder(5)
elif span < periodsperday / 1200.0:
_second_finder(10)
elif span < periodsperday / 800.0:
_second_finder(15)
elif span < periodsperday / 400.0:
_second_finder(30)
elif span < periodsperday / 150.0:
_minute_finder(1)
elif span < periodsperday / 70.0:
_minute_finder(2)
elif span < periodsperday / 24.0:
_minute_finder(5)
elif span < periodsperday / 12.0:
_minute_finder(15)
elif span < periodsperday / 6.0:
_minute_finder(30)
elif span < periodsperday / 2.5:
_hour_finder(1, False)
elif span < periodsperday / 1.5:
_hour_finder(2, False)
elif span < periodsperday * 1.25:
_hour_finder(3, False)
elif span < periodsperday * 2.5:
_hour_finder(6, True)
elif span < periodsperday * 4:
_hour_finder(12, True)
else:
info_maj[month_start] = True
info_min[day_start] = True
year_start = period_break(dates_, "year")
info_fmt = info["fmt"]
info_fmt[day_start] = "%d"
info_fmt[month_start] = "%d\n%b"
info_fmt[year_start] = "%d\n%b\n%Y"
if not has_level_label(year_start, vmin_orig):
if not has_level_label(month_start, vmin_orig):
info_fmt[first_label(day_start)] = "%d\n%b\n%Y"
else:
info_fmt[first_label(month_start)] = "%d\n%b\n%Y"
# Case 2. Less than three months
elif span <= periodsperyear // 4:
month_start = period_break(dates_, "month")
info_maj[month_start] = True
if freq < FreqGroup.FR_HR:
info["min"] = True
else:
day_start = period_break(dates_, "day")
info["min"][day_start] = True
week_start = period_break(dates_, "week")
year_start = period_break(dates_, "year")
info_fmt[week_start] = "%d"
info_fmt[month_start] = "\n\n%b"
info_fmt[year_start] = "\n\n%b\n%Y"
if not has_level_label(year_start, vmin_orig):
if not has_level_label(month_start, vmin_orig):
info_fmt[first_label(week_start)] = "\n\n%b\n%Y"
else:
info_fmt[first_label(month_start)] = "\n\n%b\n%Y"
# Case 3. Less than 14 months ...............
elif span <= 1.15 * periodsperyear:
year_start = period_break(dates_, "year")
month_start = period_break(dates_, "month")
week_start = period_break(dates_, "week")
info_maj[month_start] = True
info_min[week_start] = True
info_min[year_start] = False
info_min[month_start] = False
info_fmt[month_start] = "%b"
info_fmt[year_start] = "%b\n%Y"
if not has_level_label(year_start, vmin_orig):
info_fmt[first_label(month_start)] = "%b\n%Y"
# Case 4. Less than 2.5 years ...............
elif span <= 2.5 * periodsperyear:
year_start = period_break(dates_, "year")
quarter_start = period_break(dates_, "quarter")
month_start = period_break(dates_, "month")
info_maj[quarter_start] = True
info_min[month_start] = True
info_fmt[quarter_start] = "%b"
info_fmt[year_start] = "%b\n%Y"
# Case 4. Less than 4 years .................
elif span <= 4 * periodsperyear:
year_start = period_break(dates_, "year")
month_start = period_break(dates_, "month")
info_maj[year_start] = True
info_min[month_start] = True
info_min[year_start] = False
month_break = dates_[month_start].month
jan_or_jul = month_start[(month_break == 1) | (month_break == 7)]
info_fmt[jan_or_jul] = "%b"
info_fmt[year_start] = "%b\n%Y"
# Case 5. Less than 11 years ................
elif span <= 11 * periodsperyear:
year_start = period_break(dates_, "year")
quarter_start = period_break(dates_, "quarter")
info_maj[year_start] = True
info_min[quarter_start] = True
info_min[year_start] = False
info_fmt[year_start] = "%Y"
# Case 6. More than 12 years ................
else:
year_start = period_break(dates_, "year")
year_break = dates_[year_start].year
nyears = span / periodsperyear
(min_anndef, maj_anndef) = _get_default_annual_spacing(nyears)
major_idx = year_start[(year_break % maj_anndef == 0)]
info_maj[major_idx] = True
minor_idx = year_start[(year_break % min_anndef == 0)]
info_min[minor_idx] = True
info_fmt[major_idx] = "%Y"
return info
def _format_coord(freq, t, y):
return "t = {0} y = {1:8f}".format(Period(ordinal=int(t), freq=freq), y)
def _daily_finder(vmin, vmax, freq):
periodsperday = -1
if freq >= FreqGroup.FR_HR:
if freq == FreqGroup.FR_NS:
periodsperday = 24 * 60 * 60 * 1000000000
elif freq == FreqGroup.FR_US:
periodsperday = 24 * 60 * 60 * 1000000
elif freq == FreqGroup.FR_MS:
periodsperday = 24 * 60 * 60 * 1000
elif freq == FreqGroup.FR_SEC:
periodsperday = 24 * 60 * 60
elif freq == FreqGroup.FR_MIN:
periodsperday = 24 * 60
elif freq == FreqGroup.FR_HR:
periodsperday = 24
else: # pragma: no cover
raise ValueError("unexpected frequency: %s" % freq)
periodsperyear = 365 * periodsperday
periodspermonth = 28 * periodsperday
elif freq == FreqGroup.FR_BUS:
periodsperyear = 261
periodspermonth = 19
elif freq == FreqGroup.FR_DAY:
periodsperyear = 365
periodspermonth = 28
elif frequencies.get_freq_group(freq) == FreqGroup.FR_WK:
periodsperyear = 52
periodspermonth = 3
else: # pragma: no cover
raise ValueError("unexpected frequency")
# save this for later usage
vmin_orig = vmin
(vmin, vmax) = (Period(ordinal=int(vmin), freq=freq),
Period(ordinal=int(vmax), freq=freq))
span = vmax.ordinal - vmin.ordinal + 1
dates_ = PeriodIndex(start=vmin, end=vmax, freq=freq)
# Initialize the output
info = np.zeros(span,
dtype=[('val', np.int64), ('maj', bool),
('min', bool), ('fmt', '|S20')])
info['val'][:] = dates_._values
info['fmt'][:] = ''
info['maj'][[0, -1]] = True
# .. and set some shortcuts
info_maj = info['maj']
info_min = info['min']
info_fmt = info['fmt']
def first_label(label_flags):
if (label_flags[0] == 0) and (label_flags.size > 1) and \
((vmin_orig % 1) > 0.0):
return label_flags[1]
else:
return label_flags[0]
# Case 1. Less than a month
if span <= periodspermonth:
day_start = period_break(dates_, 'day')
month_start = period_break(dates_, 'month')
def _hour_finder(label_interval, force_year_start):
_hour = dates_.hour
_prev_hour = (dates_ - 1).hour
hour_start = (_hour - _prev_hour) != 0
info_maj[day_start] = True
info_min[hour_start & (_hour % label_interval == 0)] = True
year_start = period_break(dates_, 'year')
info_fmt[hour_start & (_hour % label_interval == 0)] = '%H:%M'
info_fmt[day_start] = '%H:%M\n%d-%b'
info_fmt[year_start] = '%H:%M\n%d-%b\n%Y'
if force_year_start and not has_level_label(year_start, vmin_orig):
info_fmt[first_label(day_start)] = '%H:%M\n%d-%b\n%Y'
def _minute_finder(label_interval):
hour_start = period_break(dates_, 'hour')
_minute = dates_.minute
_prev_minute = (dates_ - 1).minute
minute_start = (_minute - _prev_minute) != 0
info_maj[hour_start] = True
info_min[minute_start & (_minute % label_interval == 0)] = True
year_start = period_break(dates_, 'year')
info_fmt = info['fmt']
info_fmt[minute_start & (_minute % label_interval == 0)] = '%H:%M'
info_fmt[day_start] = '%H:%M\n%d-%b'
info_fmt[year_start] = '%H:%M\n%d-%b\n%Y'
def _second_finder(label_interval):
minute_start = period_break(dates_, 'minute')
_second = dates_.second
_prev_second = (dates_ - 1).second
second_start = (_second - _prev_second) != 0
info['maj'][minute_start] = True
info['min'][second_start & (_second % label_interval == 0)] = True
year_start = period_break(dates_, 'year')
info_fmt = info['fmt']
info_fmt[second_start & (_second %
label_interval == 0)] = '%H:%M:%S'
info_fmt[day_start] = '%H:%M:%S\n%d-%b'
info_fmt[year_start] = '%H:%M:%S\n%d-%b\n%Y'
if span < periodsperday / 12000.0:
_second_finder(1)
elif span < periodsperday / 6000.0:
_second_finder(2)
elif span < periodsperday / 2400.0:
_second_finder(5)
elif span < periodsperday / 1200.0:
_second_finder(10)
elif span < periodsperday / 800.0:
_second_finder(15)
elif span < periodsperday / 400.0:
_second_finder(30)
elif span < periodsperday / 150.0:
_minute_finder(1)
elif span < periodsperday / 70.0:
_minute_finder(2)
elif span < periodsperday / 24.0:
_minute_finder(5)
elif span < periodsperday / 12.0:
_minute_finder(15)
elif span < periodsperday / 6.0:
_minute_finder(30)
elif span < periodsperday / 2.5:
_hour_finder(1, False)
elif span < periodsperday / 1.5:
_hour_finder(2, False)
elif span < periodsperday * 1.25:
_hour_finder(3, False)
elif span < periodsperday * 2.5:
_hour_finder(6, True)
elif span < periodsperday * 4:
_hour_finder(12, True)
else:
info_maj[month_start] = True
info_min[day_start] = True
year_start = period_break(dates_, 'year')
info_fmt = info['fmt']
info_fmt[day_start] = '%d'
info_fmt[month_start] = '%d\n%b'
info_fmt[year_start] = '%d\n%b\n%Y'
if not has_level_label(year_start, vmin_orig):
if not has_level_label(month_start, vmin_orig):
info_fmt[first_label(day_start)] = '%d\n%b\n%Y'
else:
info_fmt[first_label(month_start)] = '%d\n%b\n%Y'
# Case 2. Less than three months
elif span <= periodsperyear // 4:
month_start = period_break(dates_, 'month')
info_maj[month_start] = True
if freq < FreqGroup.FR_HR:
info['min'] = True
else:
day_start = period_break(dates_, 'day')
info['min'][day_start] = True
week_start = period_break(dates_, 'week')
year_start = period_break(dates_, 'year')
info_fmt[week_start] = '%d'
info_fmt[month_start] = '\n\n%b'
info_fmt[year_start] = '\n\n%b\n%Y'
if not has_level_label(year_start, vmin_orig):
if not has_level_label(month_start, vmin_orig):
info_fmt[first_label(week_start)] = '\n\n%b\n%Y'
else:
info_fmt[first_label(month_start)] = '\n\n%b\n%Y'
# Case 3. Less than 14 months ...............
elif span <= 1.15 * periodsperyear:
year_start = period_break(dates_, 'year')
month_start = period_break(dates_, 'month')
week_start = period_break(dates_, 'week')
info_maj[month_start] = True
info_min[week_start] = True
info_min[year_start] = False
info_min[month_start] = False
info_fmt[month_start] = '%b'
info_fmt[year_start] = '%b\n%Y'
if not has_level_label(year_start, vmin_orig):
info_fmt[first_label(month_start)] = '%b\n%Y'
# Case 4. Less than 2.5 years ...............
elif span <= 2.5 * periodsperyear:
year_start = period_break(dates_, 'year')
quarter_start = period_break(dates_, 'quarter')
month_start = period_break(dates_, 'month')
info_maj[quarter_start] = True
info_min[month_start] = True
info_fmt[quarter_start] = '%b'
info_fmt[year_start] = '%b\n%Y'
# Case 4. Less than 4 years .................
elif span <= 4 * periodsperyear:
year_start = period_break(dates_, 'year')
month_start = period_break(dates_, 'month')
info_maj[year_start] = True
info_min[month_start] = True
info_min[year_start] = False
month_break = dates_[month_start].month
jan_or_jul = month_start[(month_break == 1) | (month_break == 7)]
info_fmt[jan_or_jul] = '%b'
info_fmt[year_start] = '%b\n%Y'
# Case 5. Less than 11 years ................
elif span <= 11 * periodsperyear:
year_start = period_break(dates_, 'year')
quarter_start = period_break(dates_, 'quarter')
info_maj[year_start] = True
info_min[quarter_start] = True
info_min[year_start] = False
info_fmt[year_start] = '%Y'
# Case 6. More than 12 years ................
else:
year_start = period_break(dates_, 'year')
year_break = dates_[year_start].year
nyears = span / periodsperyear
(min_anndef, maj_anndef) = _get_default_annual_spacing(nyears)
major_idx = year_start[(year_break % maj_anndef == 0)]
info_maj[major_idx] = True
minor_idx = year_start[(year_break % min_anndef == 0)]
info_min[minor_idx] = True
info_fmt[major_idx] = '%Y'
return info
