remove redundant variable definitions

Author: SvenKlaassen

doubleml/irm/cvar.py

@@ -292,7 +292,6 @@ def ipw_score(theta):
         m_hat['preds'] = _trimm(m_hat['preds'], self.trimming_rule, self.trimming_threshold)
 
         # this is not done in the score to be equivalent to PQ models
-        m_hat_adj = np.full_like(m_hat['preds'], np.nan, dtype='float64')
         if self._normalize_ipw:
             m_hat_adj = _normalize_ipw(m_hat['preds'], d)
         else:

doubleml/irm/iivm.py

@@ -379,7 +379,6 @@ def _score_elements(self, y, z, d, g_hat0, g_hat1, m_hat, r_hat0, r_hat1, smpls)
         w_hat0 = d - r_hat0
         w_hat1 = d - r_hat1
 
-        m_hat_adj = np.full_like(m_hat, np.nan, dtype='float64')
         if self.normalize_ipw:
             m_hat_adj = _normalize_ipw(m_hat, d)
         else:

doubleml/irm/pq.py

@@ -379,7 +379,6 @@ def ipw_score(theta):
 
         # this is not done in the score to save computation due to multiple score evaluations
         # to be able to evaluate the raw models the m_hat['preds'] are not changed
-        m_hat_adj = np.full_like(m_hat['preds'], np.nan, dtype='float64')
         if self._normalize_ipw:
             m_hat_adj = _normalize_ipw(m_hat['preds'], d)
         else:

doubleml/irm/tests/_utils_iivm_manual.py

@@ -159,7 +159,6 @@ def iivm_dml2(y, x, d, z, g_hat0_list, g_hat1_list, m_hat_list, r_hat0_list, r_h
     u_hat0, u_hat1, w_hat0, w_hat1, g_hat0, g_hat1, m_hat, r_hat0, r_hat1 = compute_iivm_residuals(
         y, d, g_hat0_list, g_hat1_list, m_hat_list, r_hat0_list, r_hat1_list, smpls)
 
-    m_hat_adj = np.full_like(m_hat, np.nan, dtype='float64')
     if normalize_ipw:
         m_hat_adj = _normalize_ipw(m_hat, d)
     else: