Applying pysynthdid, obtaining homogeneous weights and no plot

[slavakung]

I am trying to apply the code to a time series dataset I am working with. I arranged it as in the example

When I run:

'sdid = SynthDID(df_int, pre_terem, post_terem, treatment )
sdid.fit(zeta_type="base")
hat_omega_simple = sdid.estimated_params(model="sc")
hat_omega_simple'

the sc_weight is the same for all the features, at 0.027

Then when I run:

'sdid.plot(model="sc")'

I get:

---

TypeError Traceback (most recent call last)
Input In [139], in <cell line: 1>()
----> 1 sdid.plot(model="sc")

File ~/anaconda3/lib/python3.9/site-packages/synthdid/plot.py:12, in Plot.plot(self, model, figsize)
10 result = pd.DataFrame({"actual_y": self.target_y()})
11 post_actural_treat = result.loc[self.post_term[0] :, "actual_y"].mean()
---> 12 post_point = np.mean(self.Y_post_c.index)
14 if model == "sdid":
15 result["sdid"] = self.sdid_trajectory()

File <array_function internals>:5, in mean(*args, **kwargs)

File ~/anaconda3/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3438, in mean(a, axis, dtype, out, keepdims, where)
3436 pass
3437 else:
-> 3438 return mean(axis=axis, dtype=dtype, out=out, **kwargs)
3440 return _methods._mean(a, axis=axis, dtype=dtype,
3441 out=out, **kwargs)

File ~/anaconda3/lib/python3.9/site-packages/pandas/core/indexes/extension.py:95, in _inherit_from_data..method(self, *args, **kwargs)
93 if "inplace" in kwargs:
94 raise ValueError(f"cannot use inplace with {type(self).name}")
---> 95 result = attr(self._data, *args, **kwargs)
96 if wrap:
97 if isinstance(result, type(self._data)):

TypeError: mean() got an unexpected keyword argument 'dtype'