Add weight propagation

src/zfitwrapper/Fitter.py

-from typing import Type, Union
+from typing import Optional, Type, Union
 import numpy as np
 import zfit
 import zfit.core
@@ -11,18 +11,25 @@ __all__ = ["Fitter", "HistFitter"]
 
 class Fitter(BaseFitter):
     def __init__(
-        self, array: np.ndarray, model: Model, retry: int = 10, *args, **kwargs
+        self,
+        array: np.ndarray,
+        model: Model,
+        weights: Optional[np.ndarray] = None,
+        retry: int = 10,
+        *args,
+        **kwargs,
     ) -> None:
         super().__init__(model=model, retry=retry, *args, **kwargs)
 
         self.array = array
+        self.weights = weights
         self.zfitresult = None
 
     @property
     def data(self) -> zfit.Data:
         assert self.model.model is not None
         obs = self.model.model.space
-        data = zfit.Data.from_numpy(obs=obs, array=self.array)
+        data = zfit.Data.from_numpy(obs=obs, array=self.array, weights=self.weights)
 
         return data
 
@@ -48,7 +55,7 @@ class Fitter(BaseFitter):
         limits = self.model.obs.limits
         low, high = np.min(limits), np.max(limits)
         bins = np.linspace(float(low), float(high), 100)
-        counts_array, edges = np.histogram(self.array, bins=bins)
+        counts_array, edges = np.histogram(self.array, bins=bins, weights=self.weights)
         bin_centers = (edges[1:] + edges[:-1]) / 2
 
         gof = self._calc_gof(counts=counts_array, centers=bin_centers)