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Utilities API Reference

This section documents the utility functions available in canyonbpy.

Some functions are not fully implemented in the current release. Please consult the log history of the version provided on pip.

canyonbpy.utils

adjust_arctic_latitude(lat, lon)

Adjust latitude for Arctic basin calculations.

Args: lat: Latitudes to be adjusted lon: Corresponding longitudes

Returns: np.ndarray: Ajusted latitudes

Source code in canyonbpy/utils.py 
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def adjust_arctic_latitude(lat: np.ndarray, lon: np.ndarray) -> np.ndarray:
    """
    Adjust latitude for Arctic basin calculations.

    Args:
        lat: Latitudes to be adjusted
        lon: Corresponding longitudes 

    Returns:
        np.ndarray: Ajusted latitudes 
    """
    # Points for Arctic basin 'West' of Lomonossov ridge
    plon = np.array([-180, -170, -85, -80, -37, -37, 143, 143, 180, 180, -180, -180])
    plat = np.array([68, 66.5, 66.5, 80, 80, 90, 90, 68, 68, 90, 90, 68])

    # Convert longitude to -180 to 180 range
    lon = np.where(lon > 180, lon - 360, lon)

    # Create masks for points inside the polygon
    polygon = Path(np.column_stack((plon, plat)))
    points = np.column_stack((lon.flatten(), lat.flatten()))
    mask = polygon.contains_points(points)
    mask = mask.reshape(lat.shape)

    # Adjust latitude
    adjusted_lat = lat.copy()
    adjusted_lat[mask] = lat[mask] - np.sin(np.radians(lon[mask] + 37)) * (90 - lat[mask]) * 0.5

    return adjusted_lat

calculate_decimal_year(gtime)

Convert datetime to decimal year. If gtime is already a float, return it as it is, assuming it is in decimal year.

Args: gtime: Time to convert to decimal year

Returns: np.ndarray: Time converted in decimal year

Source code in canyonbpy/utils.py 
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def calculate_decimal_year(gtime: np.ndarray) -> np.ndarray:
    """
    Convert datetime to decimal year. If gtime is already a float, return it as it is, assuming it is in decimal year. 

    Args:
        gtime: Time to convert to decimal year

    Returns:
        np.ndarray: Time converted in decimal year
    """
    if isinstance(gtime[0], (float, np.float64)):
        # Assuming input is already in decimal years
        return gtime

    years = np.array([d.year + (d.dayofyear - 1 + d.hour/24 + d.minute/1440) / 366 
                      if hasattr(d, 'dayofyear') 
                      else d.year + (d - datetime(d.year, 1, 1)).total_seconds()/(366*86400)
                      for d in gtime])
    return years

calculate_pco2_corrections(ct_pred, temp, psal)

Calculate pCO2 corrections using PyCO2SYS.

Source code in canyonbpy/utils.py 
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def calculate_pco2_corrections(ct_pred: np.ndarray, temp: np.ndarray, 
                             psal: np.ndarray) -> np.ndarray:
    """Calculate pCO2 corrections using PyCO2SYS."""
    # Implementation
    pass

create_output_array(data, coords)

Create xarray DataArray with proper coordinates.

Source code in canyonbpy/utils.py 
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def create_output_array(data: np.ndarray, coords: Dict) -> xr.DataArray:
    """Create xarray DataArray with proper coordinates."""
    # Implementation
    pass

load_weight_file(weights_dir, param_name)

Load neural network weights from file.

Args: weights_dir: Optional custom directory path for weights. If None, uses package's data directory param_name: Name of the parameter whose weights to load

Returns: np.ndarray: Loaded weights

Source code in canyonbpy/utils.py 
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def load_weight_file(weights_dir: Union[str, None], param_name: str) -> np.ndarray:
    """
    Load neural network weights from file.

    Args:
        weights_dir: Optional custom directory path for weights. If None, uses package's data directory
        param_name: Name of the parameter whose weights to load

    Returns:
        np.ndarray: Loaded weights
    """
    # Implementation
    if weights_dir is not None:
        # If custom directory provided, use it directly
        filepath = f"{weights_dir}wgts_{param_name}.txt"
        return np.loadtxt(filepath)
        # If no custom directory, use package data
    with resources.open_text('canyonbpy.data.weights', f'wgts_{param_name}.txt') as f:
            return np.loadtxt(f)