cgeniepy.model#

Classes#

GenieModel is the interface to cGENIE output

Module Contents#

class cgeniepy.model.GenieModel(model_path: str | List | Tuple, gemflag=None)#

Bases: object

GenieModel is the interface to cGENIE output

model_path#

ncvar_dict#

tsvar_list#

__repr__()#

get_var(var: str | List | Tuple, attrs=None)#

Get the data of target variable. A list of variables is supported as well.

Parameters:

var – the name of target variable
unit – the unit of target variable, usually provided in the model output

Example#

>>> from cgeniepy.model import GenieModel
>>> model = GenieModel("path_to_GENIE_output")
>>> po4 = model.get_var("ocn_PO4")

get_config(config_name='BIOGEM')#

get_ts(var: str, to_ScatterData=False)#

read in time series output of GENIE

Parameters:: var – the name of the target variable
Returns:: a pandas DataFrame

get_diag_avg(target_year, is_index=False, pattern_year='\\d+', pattern_year_digit='\\d{3}')#

read the diagnostic file of cGENIE

Parameters:

target_year – the target year of the diagnostic file
is_index – if True, target_year is the index of the sorted years
pattern – the pattern of the diagnostic file name

Returns:

a pandas DataFrame

Example#

>>> from cgeniepy.model import GenieModel
>>> model = GenieModel("path_to_GENIE_output")
>>> model.get_diag_avg(9999)

grid_mask()#: cGENIE continent mask array (by setting zero values), either calculated from existing data or using biogem.grid_mask

grid_category()#: an alogirthm to define surface grid catogories depending on the land-sea mask 0: coastal sea 1: land 2: open ocean

grid_area()#: return the grid area array in used in this model experiment, unit: m2

grid_mask_3d()#: return the 3d mask of the grid used in this model experiment

grid_topo()#: return the topography of the grid used in this model experiment

grid_zt_edges()#: return the depth edges of the grid used in this model experiment

grid_lat_edges()#: return the latitude edges of the grid used in this model experiment

grid_lon_edges()#: return the longitude edges of the grid used in this model experiment

grid_zt_depths()#: return the depth of the grid used in this model experiment

grid_volume()#: return the grid volume array (3d) in m3