Basic Examples

For more comprehensive examples, go check out Usage Examples

Calculate saturation vapor pressure from Numpy Data:

>>> import numpy as np
>>> from geocat.comp import saturation_vapor_pressure
>>> temp = np.array([50, 60, 70])
>>> saturation_vapor_pressure(temp)

array([1.22796262, 1.76730647, 2.50402976])

Calculate daily climate averages from NetCDF Data:

>>> import xarray as xr
>>> from geocat.comp import calendar_average
>>> import geocat.datafiles as gdf

>>> # get data from geocat.datafiles repo or use your own data
>>> file = gdf.get('netcdf_files/atm.20C.hourly6-1990-1995-TS.nc')
>>> ds = xr.open_dataset(file)  # open NetCDF file using xarray
>>> temp = ds.TS
>>> temp

<xarray.DataArray 'TS' (member_id: 40, time: 8761)>
[350440 values with dtype=float32]
Coordinates:
    lat        float64 ...
    lon        float64 ...
  * member_id  (member_id) int64 1 2 3 4 5 6 7 8 ... 34 35 101 102 103 104 105
  * time       (time) object 1990-01-01 00:00:00 ... 1996-01-01 00:00:00
Attributes:
    long_name:  Surface temperature (radiative)
    units:      K

>>> calendar_average(temp, 'day')
<xarray.DataArray 'TS' (member_id: 40, time: 2191)>
array([[301.88226, 301.9291 , 302.0053 , ..., 302.24304, 302.31415,
        302.33292],
       [300.3797 , 300.3421 , 300.28976, ..., 299.82782, 299.83026,
        299.8336 ],
       [300.31702, 300.29077, 300.28403, ..., 300.08377, 300.02185,
        300.0073 ],
       ...,
       [302.60565, 302.48895, 302.3853 , ..., 300.181  , 300.16293,
        300.15826],
       [299.1427 , 299.12122, 299.06543, ..., 302.36343, 302.35126,
        302.35077],
       [297.99374, 298.0177 , 298.03265, ..., 300.71463, 300.68396,
        300.67422]], dtype=float32)
Coordinates:
    lat        float64 ...
    lon        float64 ...
  * member_id  (member_id) int64 1 2 3 4 5 6 7 8 ... 34 35 101 102 103 104 105
  * time       (time) object 1990-01-01 12:00:00 ... 1996-01-01 12:00:00
Attributes:
    long_name:  Surface temperature (radiative)
    units:      K