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weather

csv_to_weather(csv_data, node_column='nodes', step_column='steps', weather_columns=None, attributes=None, weather_dir=None, weather_file_names=None)

Convert a dataframe or csv file, containing node, step and weather columns, into a weather set and corresponding weather files, if weather dir is specified.

Parameters:

Name Type Description Default
csv_data Union[str, Path, DataFrame]

Dataframe or a csv file path, containing weather data.

 required
node_column str

(Optional) Column containing node ids. The default is "nodes". The default is "nodes".

 'nodes'
step_column str

(Optional) Column containing node index for weather time series values. The default is "steps".

 'steps'
weather_columns Dict[WeatherVariable, str]

(Optional) Dictionary of weather variables (keys) and weather column names (values). Defaults are WeatherVariables values are used: "airtemp", "humidity", "rainfall", "landtemp".

 None
attributes WeatherAttributes

(Optional) Weather attribute object containing metadata for WeatherMetadata object.

 None
weather_dir Union[str, Path]

(Optional) Directory where weather files are stored. If not specified files are not created.

 None
weather_file_names Dict[WeatherVariable, str]

(Optional) Dictionary of weather variables (keys) and weather .bin file names (values).

 None

Returns:

Type Description
WeatherSet

WeatherSet object.
Source code in emodpy_malaria/weather/__init__.py 
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def csv_to_weather(csv_data: Union[str, Path, pd.DataFrame],
                   node_column: str = "nodes",
                   step_column: str = "steps",
                   weather_columns: Dict[WeatherVariable, str] = None,
                   attributes: WeatherAttributes = None,
                   weather_dir: Union[str, Path] = None,
                   weather_file_names: Dict[WeatherVariable, str] = None) -> WeatherSet:
    """
    Convert a dataframe or csv file, containing node, step and weather columns, into a weather set
    and corresponding weather files, if weather dir is specified.

    Args:
        csv_data: Dataframe or a csv file path, containing weather data.
        node_column: (Optional) Column containing node ids. The default is "nodes". The default is "nodes".
        step_column: (Optional) Column containing node index for weather time series values. The default is "steps".
        weather_columns: (Optional) Dictionary of weather variables (keys) and weather column names (values).
            Defaults are WeatherVariables values are used: "airtemp", "humidity", "rainfall", "landtemp".
        attributes: (Optional) Weather attribute object containing metadata for WeatherMetadata object.
        weather_dir: (Optional) Directory where weather files are stored. If not specified files are not created.
        weather_file_names: (Optional) Dictionary of weather variables (keys) and weather .bin file names (values).

    Returns:
        WeatherSet object.
    """

    if isinstance(csv_data, pd.DataFrame):
        ws = WeatherSet.from_dataframe(df=csv_data,
                                       node_column=node_column,
                                       step_column=step_column,
                                       weather_columns=weather_columns,
                                       attributes=attributes)

    elif isinstance(csv_data, str) or isinstance(csv_data, Path):
        ws = WeatherSet.from_csv(file_path=csv_data,
                                 node_column=node_column,
                                 step_column=step_column,
                                 weather_columns=weather_columns,
                                 attributes=attributes)
    else:
        raise TypeError("The data argument must be a file path or a pandas dataframe.")

    if weather_dir:
        ws.to_files(dir_path=weather_dir, file_names=weather_file_names)

    return ws

generate_weather(platform, site_file, start_date, end_date=None, node_column='nodes', lat_column='lat', lon_column='lon', id_reference=None, request_name='', local_dir=None, data_source=None, force=False)

Generate weather files by submitting a request and downloading generated weather files to a specified dir.

Parameters:

Name Type Description Default
platform Union[str, COMPSPlatform]

Platform name (like "Calculon") or COMPSPlatform object, where the work item will run.

 required
site_file Union[str, Path]

CSV (.csv) or demographics (.json) file containing a set of sites (points) defined with lat/lon. CSV file must contain columns for: EMOD node ids (node), latitude (lat) and longitude (lon). Demographics file must match EMOD demographics file schema.

 required
start_date int

Start date, in formats: year (2018), year and day-of-year (2018001) or date (20180101)

 required
end_date int

(Optional) End date, in formats: year (2018), year and day-of-year (2018365) or date (20181231)

 None
node_column str

(Optional) Name of a column containing EMOD node ids. The default is "nodes".

 'nodes'
lat_column str

(Optional) Name of a column containing site (point) latitude. The default is "lat".

 'lat'
lon_column str

(Optional) Name of a column containing site (point) longitude. The default is "lon".

 'lon'
id_reference str

(Optional) Value of weather metadata IdReference attribute. The default is "Default".

 None
request_name str

(Optional) Name to be used for the weather SSMT work item.

 ''
local_dir Union[str, Path]

(Optional) Local dir where files will be downloaded.

 None
data_source str

(Optional) SSMT data source to be used.

 None
force bool

(Optional) Flag ensuring a new weather request is submitted, even if weather files exist in "local_dir".

 False

Returns:

Type Description
WeatherRequest

Can be used to access asset collection id or a local dir (if not given as ) argument or a download report.
Source code in emodpy_malaria/weather/__init__.py 
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def generate_weather(platform: Union[str, COMPSPlatform],
                     site_file: Union[str, Path],
                     start_date: int,
                     end_date: int = None,
                     node_column: str = "nodes",
                     lat_column: str = "lat",
                     lon_column: str = "lon",
                     id_reference: str = None,
                     request_name: str = "",
                     local_dir: Union[str, Path] = None,
                     data_source: str = None,
                     force: bool = False) -> WeatherRequest:
    """
    Generate weather files by submitting a request and downloading generated weather files to a specified dir.

    Args:
        platform: Platform name (like "Calculon") or COMPSPlatform object, where the work item will run.
        site_file: CSV (.csv) or demographics (.json) file containing a set of sites (points) defined with lat/lon.
            CSV file must contain columns for: EMOD node ids (node), latitude (lat) and longitude (lon).
            Demographics file must match EMOD demographics file schema.
        start_date: Start date, in formats: year (2018), year and day-of-year (2018001) or date (20180101)
        end_date: (Optional) End date, in formats: year (2018), year and day-of-year (2018365) or date (20181231)
        node_column: (Optional) Name of a column containing EMOD node ids. The default is "nodes".
        lat_column: (Optional) Name of a column containing site (point) latitude. The default is "lat".
        lon_column: (Optional) Name of a column containing site (point) longitude. The default is "lon".
        id_reference: (Optional) Value of weather metadata IdReference attribute. The default is "Default".
        request_name: (Optional) Name to be used for the weather SSMT work item.
        local_dir: (Optional) Local dir where files will be downloaded.
        data_source: (Optional) SSMT data source to be used.
        force: (Optional) Flag ensuring a new weather request is submitted, even if weather files exist in "local_dir".

    Returns:
        (WeatherRequest): Can be used to access asset collection id or a local dir (if not given as ) argument or a download report.
    """
    wa = WeatherArgs(site_file=site_file,
                     start_date=start_date,
                     end_date=end_date,
                     node_column=node_column,
                     lat_column=lat_column,
                     lon_column=lon_column,
                     id_reference=id_reference)

    wr = WeatherRequest(platform=platform, local_dir=local_dir, data_source=data_source)
    wr.generate(weather_args=wa, request_name=request_name, force=force)
    wr.download(force=force)

    return wr

weather_to_csv(weather_dir, weather_file_prefix='', weather_file_names=None, csv_file=None, node_column='nodes', step_column='steps', weather_columns=None)

Convert weather files into a dataframe and a .csv file, if csv file path is specified.

Parameters:

Name Type Description Default
weather_dir Union[str, Path]

Local dir containing weather files.

 required
weather_file_prefix str

(Optional) Weather files prefix, e.g. "dtk_15arcmin"

 ''
weather_file_names Dict[WeatherVariable, str]

(Optional) Dictionary of weather variables (keys) and weather .bin file names (values).

 None
csv_file Union[str, Path]

(Optional) The path of a csv file to be generated. If not specified csv file is not created.

 None
node_column str

(Optional) Column containing node ids. The default is "nodes".

 'nodes'
step_column str

(Optional) Column containing node index for weather time series values. The default is "steps".

 'steps'
weather_columns Dict[WeatherVariable, str]

(Optional) Dictionary of weather variables (keys) and weather column names (values). Defaults are WeatherVariables values are used: "airtemp", "humidity", "rainfall", "landtemp".

 None

Returns:

Type Description
Tuple[DataFrame, WeatherAttributes]

Dataframe and weather attributes objects.
Source code in emodpy_malaria/weather/__init__.py 
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def weather_to_csv(weather_dir: Union[str, Path],
                   weather_file_prefix: str = "",
                   weather_file_names: Dict[WeatherVariable, str] = None,
                   csv_file: Union[str, Path] = None,
                   node_column: str = "nodes",
                   step_column: str = "steps",
                   weather_columns: Dict[WeatherVariable, str] = None) -> Tuple[pd.DataFrame, WeatherAttributes]:
    """
    Convert weather files into a dataframe and a .csv file, if csv file path is specified.

    Args:
        weather_dir: Local dir containing weather files.
        weather_file_prefix: (Optional) Weather files prefix, e.g. "dtk_15arcmin"
        weather_file_names: (Optional) Dictionary of weather variables (keys) and weather .bin file names (values).
        csv_file: (Optional) The path of a csv file to be generated. If not specified csv file is not created.
        node_column: (Optional) Column containing node ids. The default is "nodes".
        step_column: (Optional) Column containing node index for weather time series values. The default is "steps".
        weather_columns: (Optional) Dictionary of weather variables (keys) and weather column names (values).
            Defaults are WeatherVariables values are used: "airtemp", "humidity", "rainfall", "landtemp".

    Returns:
        Dataframe and weather attributes objects.
    """
    ws = WeatherSet.from_files(dir_path=weather_dir, prefix=weather_file_prefix, file_names=weather_file_names)
    if csv_file:
        df = ws.to_csv(file_path=csv_file,
                       node_column=node_column,
                       step_column=step_column,
                       weather_columns=weather_columns)
    else:
        df = ws.to_dataframe(node_column=node_column,
                             step_column=step_column,
                             weather_columns=weather_columns)
    wa = ws.attributes

    return df, wa