def from_year_month_day(year, month, day, validate=True):
"""Creates DateTensor from tensors of years, months and days.
Args:
year: Tensor of int32 type. Elements should be positive.
month: Tensor of int32 type of same shape as `year`. Elements should be in
range `[1, 12]`.
day: Tensor of int32 type of same shape as `year`. Elements should be in
range `[1, 31]` and represent valid dates together with corresponding
elements of `month` and `year` Tensors.
validate: Whether to validate the dates.
Returns:
DateTensor object.
#### Example
```python
year = tf.constant([2015, 2017], dtype=tf.int32)
month = tf.constant([4, 12], dtype=tf.int32)
day = tf.constant([15, 30], dtype=tf.int32)
date_tensor = tff.datetime.dates_from_year_month_day(year, month, day)
```
"""
year = tf.convert_to_tensor(year, tf.int32)
month = tf.convert_to_tensor(month, tf.int32)
day = tf.convert_to_tensor(day, tf.int32)
control_deps = []
if validate:
control_deps.append(
tf.debugging.assert_positive(year, message="Year must be positive."))
control_deps.append(
tf.debugging.assert_greater_equal(
month,
constants.Month.JANUARY.value,
message=f"Month must be >= {constants.Month.JANUARY.value}"))
control_deps.append(
tf.debugging.assert_less_equal(
month,
constants.Month.DECEMBER.value,
message="Month must be <= {constants.Month.JANUARY.value}"))
control_deps.append(
tf.debugging.assert_positive(day, message="Day must be positive."))
is_leap = date_utils.is_leap_year(year)
days_in_months = tf.constant(_DAYS_IN_MONTHS_COMBINED, tf.int32)
max_days = tf.gather(days_in_months,
month + 12 * tf.dtypes.cast(is_leap, np.int32))
control_deps.append(
tf.debugging.assert_less_equal(
day, max_days, message="Invalid day-month pairing."))
with tf.compat.v1.control_dependencies(control_deps):
# Ensure years, months, days themselves are under control_deps.
year = tf.identity(year)
month = tf.identity(month)
day = tf.identity(day)
with tf.compat.v1.control_dependencies(control_deps):
ordinal = date_utils.year_month_day_to_ordinal(year, month, day)
return DateTensor(ordinal, year, month, day)
def day_of_year(self):
"""Calculates the number of days since the beginning of the year.
Returns:
Tensor of int32 type with elements in range [1, 366]. January 1st yields
"1".
#### Example
```python
dt = tff.datetime.dates_from_tuples([(2019, 1, 25), (2020, 3, 2)])
dt.day_of_year() # [25, 62]
```
"""
if self._day_of_year is None:
cumul_days_in_month_nonleap = tf.math.cumsum(
_DAYS_IN_MONTHS_NON_LEAP, exclusive=True)
cumul_days_in_month_leap = tf.math.cumsum(
_DAYS_IN_MONTHS_LEAP, exclusive=True)
days_before_month_non_leap = tf.gather(cumul_days_in_month_nonleap,
self.month() - 1)
days_before_month_leap = tf.gather(cumul_days_in_month_leap,
self.month() - 1)
days_before_month = tf.where(
date_utils.is_leap_year(self.year()), days_before_month_leap,
days_before_month_non_leap)
self._day_of_year = days_before_month + self.day()
return self._day_of_year
def test_is_leap_year(self):
years = np.array([
1600, 1700, 1800, 1900, 1901, 1903, 1904, 1953, 2000, 2020, 2025,
2100
])
expected = np.array([
True, False, False, False, False, False, True, False, True, True,
False, False
])
self.assertAllEqual(expected, date_utils.is_leap_year(years))
def _num_days_in_month(month, year):
"""Returns number of days in a given month of a given year."""
days_in_months = tf.constant(_DAYS_IN_MONTHS_COMBINED, tf.int32)
is_leap = date_utils.is_leap_year(year)
return tf.gather(days_in_months,
month + 12 * tf.dtypes.cast(is_leap, tf.int32))
