FIX: Drop deprecated numpy aliases to builtin types

Author: effigies

nitime/algorithms/cohere.py

@@ -1005,7 +1005,7 @@ def cache_fft(time_series, ij, lb=0, ub=None,
     FFT_conj_slices = {}
 
     for i_channel in all_channels:
-        Slices = np.zeros((n_slices, n_freqs), dtype=np.complex)
+        Slices = np.zeros((n_slices, n_freqs), dtype=complex)
         for iSlice in range(n_slices):
             thisSlice = time_series[i_channel,
                                     i_times[iSlice]:i_times[iSlice] + NFFT]
@@ -1161,7 +1161,7 @@ def cache_to_relative_phase(cache, ij):
     channels_i = max(1, max(ij_array[:, 0]) + 1)
     channels_j = max(1, max(ij_array[:, 1]) + 1)
     # Pre-allocate for speed:
-    Phi_xy = np.zeros((channels_i, channels_j, freqs), dtype=np.complex)
+    Phi_xy = np.zeros((channels_i, channels_j, freqs), dtype=complex)
 
     # These checks take time, so do them up front, not in every iteration:
     if list(FFT_slices.items())[0][1].shape[0] > 1:
@@ -1221,7 +1221,7 @@ def cache_to_coherency(cache, ij):
 
     channels_i = max(1, max(ij_array[:, 0]) + 1)
     channels_j = max(1, max(ij_array[:, 1]) + 1)
-    Cxy = np.zeros((channels_i, channels_j, freqs), dtype=np.complex)
+    Cxy = np.zeros((channels_i, channels_j, freqs), dtype=complex)
 
     #These checks take time, so do them up front, not in every iteration:
     if list(FFT_slices.items())[0][1].shape[0] > 1:

nitime/analysis/coherence.py

@@ -653,10 +653,10 @@ def coherency(self):
         if len(self.seed.shape) > 1:
             Cxy = np.empty((self.seed.data.shape[0],
                             self.target.data.shape[0],
-                            self.frequencies.shape[0]), dtype=np.complex)
+                            self.frequencies.shape[0]), dtype=complex)
         else:
             Cxy = np.empty((self.target.data.shape[0],
-                            self.frequencies.shape[0]), dtype=np.complex)
+                            self.frequencies.shape[0]), dtype=complex)
 
         #Get the fft window cache for the target time-series:
         cache = self.target_cache

nitime/analysis/correlation.py

@@ -147,7 +147,7 @@ def corrcoef(self):
 
             # Preallocate results
             Cxy = np.empty((self.seed.data.shape[0],
-                            self.target.data.shape[0]), dtype=np.float)
+                            self.target.data.shape[0]), dtype=float)
 
             for seed_idx, this_seed in enumerate(self.seed.data):
 

nitime/tests/test_algorithms.py

@@ -145,7 +145,7 @@ def test_psd_matlab():
     ts = np.loadtxt(os.path.join(test_dir_path, 'tseries12.txt'))
 
     #Complex signal!
-    ts0 = ts[1] + ts[0] * np.complex(0, 1)
+    ts0 = ts[1] + ts[0] * complex(0, 1)
 
     NFFT = 256
     Fs = 1.0