Deal with new copy behaviour of np.array() in NumPy 2

madmom/evaluation/tempo.py

@@ -38,7 +38,8 @@ def sort_tempo(tempo):
         Tempi sorted according to their strength.
 
     """
-    tempo = np.array(tempo, copy=False, ndmin=1)
+    if not isinstance(tempo, np.ndarray):
+        tempo = np.array(tempo, ndmin=1)
     if tempo.ndim != 2:
         raise ValueError('`tempo` has no strength information, cannot sort '
                          'them.')

madmom/features/beats.py

@@ -1082,7 +1082,8 @@ def process_online(self, activations, reset=True, **kwargs):
         """
         # cast as 1-dimensional array
         # Note: in online mode, activations are just float values
-        activations = np.array(activations, copy=False, subok=True, ndmin=1)
+        if not isinstance(activations, np.ndarray):
+            activations = np.array(activations, ndmin=1)
         # reset to initial state
         if reset:
             self.reset()

madmom/features/onsets.py

@@ -1125,7 +1125,8 @@ def process_online(self, activations, reset=True, **kwargs):
         """
         # cast as 1-dimensional array
         # Note: in online mode, activations are just float values
-        activations = np.array(activations, copy=False, subok=True, ndmin=1)
+        if not isinstance(activations, np.ndarray):
+            activations = np.array(activations, ndmin=1)
         # buffer data
         if self.buffer is None or reset:
             # reset the processor

madmom/features/tempo.py

@@ -392,8 +392,8 @@ def process_online(self, activations, reset=True, **kwargs):
             Corresponding delays [frames].
 
         """
-
-        activations = np.array(activations, copy=False, subok=True, ndmin=1, dtype=float)
+        if not isinstance(activations, np.ndarray):
+            activations = np.array(activations, ndmin=1, dtype=float)
         # reset to initial state
         if reset:
             self.reset()
@@ -402,7 +402,7 @@ def process_online(self, activations, reset=True, **kwargs):
         # iterate over all activations
         # Note: in online mode, activations are just float values, thus cast
         #       them as 1-dimensional array
-        for act in np.array(activations, copy=False, subok=True, ndmin=1):
+        for act in activations:
             # online feed backward comb filter (y[n] = x[n] + α * y[n - τ])
             y_n = act + self.alpha * self._comb_buffer[idx]
             # shift output buffer with new value

madmom/processors.py

@@ -797,7 +797,7 @@ def process(self, data, **kwargs):
         ndmin = len(self.buffer_size)
         # cast the data to have that many dimensions
         if data.ndim < ndmin:
-            data = np.array(data, copy=False, subok=True, ndmin=ndmin)
+            data = np.array(data, ndmin=ndmin)
         # length of the data
         data_length = len(data)
         # if length of data exceeds buffer length simply replace buffer data