Rename numpy functions

Author: diegoceccarelli

ranx/metrics/average_precision.py

@@ -57,7 +57,7 @@ def _average_precision_parallel_numba(qrels, run, k, rel_lvl):
     NUMBA_AVAILABLE = False
 
 
-def _average_precision_parallel_numpy(qrels, run, k, rel_lvl):
+def _average_precision_numpy(qrels, run, k, rel_lvl):
     """NumPy fallback implementation."""
     scores = np.zeros((len(qrels)), dtype=np.float64)
     for i in range(len(qrels)):
@@ -72,7 +72,7 @@ def _average_precision_parallel(qrels, run, k, rel_lvl):
     if NUMBA_AVAILABLE and use_numba():
         return _average_precision_parallel_numba(qrels, run, k, rel_lvl)
     else:
-        return _average_precision_parallel_numpy(qrels, run, k, rel_lvl)
+        return _average_precision_numpy(qrels, run, k, rel_lvl)
 
 
 # HIGH LEVEL FUNCTIONS =========================================================

ranx/metrics/f1.py

@@ -44,7 +44,7 @@ def _f1_parallel_numba(qrels, run, k, rel_lvl):
     NUMBA_AVAILABLE = False
 
 
-def _f1_parallel_numpy(qrels, run, k, rel_lvl):
+def _f1_numpy(qrels, run, k, rel_lvl):
     """NumPy fallback implementation."""
     scores = np.zeros((len(qrels)), dtype=np.float64)
     for i in range(len(qrels)):
@@ -59,7 +59,7 @@ def _f1_parallel(qrels, run, k, rel_lvl):
     if NUMBA_AVAILABLE and use_numba():
         return _f1_parallel_numba(qrels, run, k, rel_lvl)
     else:
-        return _f1_parallel_numpy(qrels, run, k, rel_lvl)
+        return _f1_numpy(qrels, run, k, rel_lvl)
 
 
 # HIGH LEVEL FUNCTIONS =========================================================

ranx/metrics/hits.py

@@ -49,7 +49,7 @@ def _hits_parallel_numba(qrels, run, k, rel_lvl):
     NUMBA_AVAILABLE = False
 
 
-def _hits_parallel_numpy(qrels, run, k, rel_lvl):
+def _hits_numpy(qrels, run, k, rel_lvl):
     """NumPy fallback implementation."""
     scores = np.zeros((len(qrels)), dtype=np.float64)
     for i in range(len(qrels)):
@@ -64,7 +64,7 @@ def _hits_parallel(qrels, run, k, rel_lvl):
     if NUMBA_AVAILABLE and use_numba():
         return _hits_parallel_numba(qrels, run, k, rel_lvl)
     else:
-        return _hits_parallel_numpy(qrels, run, k, rel_lvl)
+        return _hits_numpy(qrels, run, k, rel_lvl)
 
 
 # HIGH LEVEL FUNCTIONS =========================================================

ranx/metrics/ndcg.py

@@ -62,7 +62,7 @@ def _ndcg_parallel_numba(qrels, run, k, rel_lvl, jarvelin):
     NUMBA_AVAILABLE = False
 
 
-def _dcg_parallel_numpy(qrels, run, k, rel_lvl, jarvelin):
+def _dcg_numpy(qrels, run, k, rel_lvl, jarvelin):
     """NumPy fallback implementation."""
     scores = np.zeros((len(qrels)), dtype=np.float64)
     for i in range(len(qrels)):
@@ -77,7 +77,7 @@ def _dcg_parallel(qrels, run, k, rel_lvl, jarvelin):
     if NUMBA_AVAILABLE and use_numba():
         return _dcg_parallel_numba(qrels, run, k, rel_lvl, jarvelin)
     else:
-        return _dcg_parallel_numpy(qrels, run, k, rel_lvl, jarvelin)
+        return _dcg_numpy(qrels, run, k, rel_lvl, jarvelin)
 
 
 @maybe_njit(cache=True)
@@ -97,7 +97,7 @@ def _ndcg(qrels, run, k, rel_lvl, jarvelin):
     return dcg_score / idcg_score
 
 
-def _ndcg_parallel_numpy(qrels, run, k, rel_lvl, jarvelin):
+def _ndcg_numpy(qrels, run, k, rel_lvl, jarvelin):
     """NumPy fallback implementation."""
     scores = np.zeros((len(qrels)), dtype=np.float64)
     for i in range(len(qrels)):
@@ -112,7 +112,7 @@ def _ndcg_parallel(qrels, run, k, rel_lvl, jarvelin):
     if NUMBA_AVAILABLE and use_numba():
         return _ndcg_parallel_numba(qrels, run, k, rel_lvl, jarvelin)
     else:
-        return _ndcg_parallel_numpy(qrels, run, k, rel_lvl, jarvelin)
+        return _ndcg_numpy(qrels, run, k, rel_lvl, jarvelin)
 
 
 # HIGH LEVEL FUNCTIONS =========================================================

ranx/metrics/precision.py

@@ -32,7 +32,7 @@ def _precision_parallel_numba(qrels, run, k, rel_lvl):
     NUMBA_AVAILABLE = False
 
 
-def _precision_parallel_numpy(qrels, run, k, rel_lvl):
+def _precision_numpy(qrels, run, k, rel_lvl):
     """NumPy fallback implementation."""
     scores = np.zeros((len(qrels)), dtype=np.float64)
     for i in range(len(qrels)):
@@ -47,7 +47,7 @@ def _precision_parallel(qrels, run, k, rel_lvl):
     if NUMBA_AVAILABLE and use_numba():
         return _precision_parallel_numba(qrels, run, k, rel_lvl)
     else:
-        return _precision_parallel_numpy(qrels, run, k, rel_lvl)
+        return _precision_numpy(qrels, run, k, rel_lvl)
 
 
 # HIGH LEVEL FUNCTIONS =========================================================

ranx/metrics/recall.py

@@ -37,7 +37,7 @@ def _recall_parallel_numba(qrels, run, k, rel_lvl):
     NUMBA_AVAILABLE = False
 
 
-def _recall_parallel_numpy(qrels, run, k, rel_lvl):
+def _recall_numpy(qrels, run, k, rel_lvl):
     """NumPy fallback implementation."""
     scores = np.zeros((len(qrels)), dtype=np.float64)
     for i in range(len(qrels)):
@@ -52,7 +52,7 @@ def _recall_parallel(qrels, run, k, rel_lvl):
     if NUMBA_AVAILABLE and use_numba():
         return _recall_parallel_numba(qrels, run, k, rel_lvl)
     else:
-        return _recall_parallel_numpy(qrels, run, k, rel_lvl)
+        return _recall_numpy(qrels, run, k, rel_lvl)
 
 
 # HIGH LEVEL FUNCTIONS =========================================================

ranx/metrics/reciprocal_rank.py

@@ -37,7 +37,7 @@ def _reciprocal_rank_parallel_numba(qrels, run, k, rel_lvl):
     NUMBA_AVAILABLE = False
 
 
-def _reciprocal_rank_parallel_numpy(qrels, run, k, rel_lvl):
+def _reciprocal_rank_numpy(qrels, run, k, rel_lvl):
     """NumPy fallback implementation."""
     scores = np.zeros((len(qrels)), dtype=np.float64)
     for i in range(len(qrels)):
@@ -52,7 +52,7 @@ def _reciprocal_rank_parallel(qrels, run, k, rel_lvl):
     if NUMBA_AVAILABLE and use_numba():
         return _reciprocal_rank_parallel_numba(qrels, run, k, rel_lvl)
     else:
-        return _reciprocal_rank_parallel_numpy(qrels, run, k, rel_lvl)
+        return _reciprocal_rank_numpy(qrels, run, k, rel_lvl)
 
 
 # HIGH LEVEL FUNCTIONS =========================================================