Estadísticas y predicciones de Canadian Premier League Final Stage

Jugadores Clave

Opciones Internacionales:

Varios países podrían ofrecer cobertura internacional dependiendo acuerdos preexistentes con cadenas televisivas globales; sin embargo,
cabe verificar disponibilidad específica según cada región.

Diferencias Horarias:

Asegúrate siempre tener acceso al horario local correcto ajustado según tu ubicación geográfica; esto garantizará no perderte ningún momento crucial.

Sitios Web Confiables:
.[0]: # -*- coding: utf-8 -*- [1]: # Copyright (C) British Crown Copyright 2017-2019 Met Office. [2]: # Licensed under the Apache License, Version 2.0 (the "License"); [3]: # you may not use this file except in compliance with the License. [4]: # You may obtain a copy of the License at [5]: # [6]: # http://www.apache.org/licenses/LICENSE-2.0 [7]: # [8]: # Unless required by applicable law or agreed to in writing, software [9]: # distributed under the License is distributed on an "AS IS" BASIS, [10]: # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. [11]: # See the License for the specific language governing permissions and [12]: # limitations under the License. [13]: """Contains base class for all climate indices.""" [14]: import abc [15]: import datetime [16]: import iris [17]: from iris.cube import CubeList [18]: from improver import PostProcessor [19]: from improver.synthetic_data.set_up_test_cubes import set_up_variable_cube [20]: class BaseIndex(PostProcessor): [21]: """ [22]: Abstract base class for climate indices. [23]: This class is used as the parent class for all indices which are calculated from one or more cubes. [24]: The sub-classes are responsible for specifying the following properties: [25]: - The ``data_dtype`` attribute specifies the data type that will be returned by ``process``. [26]: - The ``name`` attribute specifies the name to give to any cubes returned by ``process``. [27]: - The ``long_name`` attribute specifies the long_name to give to any cubes returned by ``process``. [28]: - The ``var_name`` attribute specifies the var_name to give to any cubes returned by ``process``. [29]: - The ``units`` attribute specifies the units to give to any cubes returned by ``process``. [30]: """ [31]: __metaclass__ = abc.ABCMeta [32]: @abc.abstractproperty [33]: def data_dtype(self): [34]: """Data type of output.""" [35]: pass [36]: @abc.abstractproperty [37]: def name(self): [38]: """Name of index.""" [39]: pass [40]: @abc.abstractproperty [41]: def long_name(self): [42]: """Long name of index.""" [43]: pass [44]: @abc.abstractproperty [45]: def var_name(self): [46]: """Variable name of index.""" [47]: pass [48]: @abc.abstractproperty [49]: def units(self): [50]: """Units of index.""" [51]: pass [52]: @abc.abstractclassmethod [53]: def _calculate_index(cls): [54]: """Calculate climate index.""" [55]: pass [56]: @staticmethod [57]: def _create_time_range(start_date=None): [58]: """ [59]: Create time range coordinate. [60]: If start_date is not provided then use current date and time. [61]: Args: [62]: start_date (datetime.datetime): Start date. [63]: Returns: [64]: tuple: Tuple containing datetime.datetime objects representing start and end times. [65]: """ [66]: if start_date is None: [67]: start_date = datetime.datetime.now() end_date = start_date + datetime.timedelta(hours=1) time_range = iris.coords.DimCoord([start_date, end_date], standard_name='time', var_name='time', long_name='time', units=iris.unit.Unit('hours since 1970-01-01')) return time_range.points return iris.cube.Cube(0