[Question] how to set data range with `Dynamics()` and `Dynamics.from_data()`

[shik-design]

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Question

dyn_act = cs.Dynamics.from_data(model=cs.SIRModel, data=actual_df, name="None")
dyn_act.register().tail()

where will I run the above codes with date_range=("01Jan2022", "30Jun2022")

What tried

import covsirphy as cs
print(cs.__version__)


dyn_act = cs.Dynamics.from_data(model=cs.SIRModel, date_range=("01Jan2022", "30Jun2022"), data=actual_df, name="None")
dyn_act.register().tail()

### Additional Context

_No response_

[Hirokazu Takaya]

We have two solutions.

1. Subset actual_df with pandas.DatetimeIndex

dyn_act = cs.Dynamics.from_data(model=cs.SIRModel, data=actual_df["2022-01-01":"2022-06-30"], name=None)
dyn_act.register().tail()

2. Initialize Dynamics instance without .from_data() class method

dyn_act = cs.Dynamics(model=cs.SIRModel, date_range=("01Jan2022", "30Jun2022"), name=None)
dyn_act.register(data=actual_df).tail()

Note that Dynamics.from_data() calls Dynamics(...) and Dynamics.register(...), setting the min/max dates of actual_df as the date range automaticallly.

covid19-sir/covsirphy/dynamics/dynamics.py

Lines 115 to 142 in dfbac35

     @classmethod 
     def from_data(cls, model: ODEModel, data: pd.DataFrame, tau: int | None = 1440, name: str | None = None) -> Self: 
         """Initialize model with data. 
  
         Args: 
             data: new data to overwrite the current information 
                 Index 
                     Date (pandas.Timestamp): Observation dates 
                 Columns 
                     Susceptible (int): the number of susceptible cases 
                     Infected (int): the number of currently infected cases 
                     Fatal (int): the number of fatal cases 
                     Recovered (int): the number of recovered cases 
                     (numpy.float64): ODE parameter values defined with the ODE model (optional) 
             tau: tau value [min] or None (un-set) 
             name: name of dynamics to show in figures (e.g. "baseline") or None (un-set) 
  
         Returns: 
             initialized model 
  
         Note: 
             Regarding @date_range, refer to covsirphy.ODEModel.from_sample(). 
         """ 
         Validator(model, "model", accept_none=False).subclass(ODEModel) 
         Validator(data, "data").dataframe(time_index=True) 
         instance = cls(model=model, date_range=(data.index.min(), data.index.max()), tau=tau, name=name) 
         instance.register(data=data) 
         return instance 

[shik-design]

Thanks a lot