Numpy types; closes #94

empymod/kernel.py

@@ -961,7 +961,7 @@ def halfspace(off, angle, zsrc, zrec, etaH, etaV, freqtime, ab, signal,
         if signal == -1:  # Calculate DC
             time = np.r_[time[:, 0], 1e4][:, None]
             freqtime = time
-        dtype = float
+        dtype = np.float_
 
     # Other defined parameters
     rh = np.sqrt(xco**2 + yco**2)  # Horizontal distance in space
@@ -1167,7 +1167,8 @@ def airwave(sval, hp, rp, res, fab, delta):
 
             def coeff_dk(k, K):
                 r"""Return coefficients Dk for k, K."""
-                n = np.arange(int((k+1)/2), np.min([k, K/2])+.5, 1, dtype=int)
+                n = np.arange(
+                        int((k+1)/2), np.min([k, K/2])+.5, 1, dtype=np.int_)
                 Dk = n**(K/2)*fn(2*n)
                 Dk /= fn(n)*fn(n-1)*fn(k-n)*fn(2*n-k)*fn(K/2-n)
                 return Dk.sum()*(-1)**(k+K/2)

empymod/transform.py

@@ -307,8 +307,8 @@ def hankel_qwe(zsrc, zrec, lsrc, lrec, off, ang_fact, depth, ab, etaH, etaV,
         # as QWE is not designed for these intervals.
         check0 = np.log(intervals[:, :-1])
         check1 = np.log(intervals[:, 1:])
-        numerator = np.zeros((off.size, maxint), dtype=complex)
-        denominator = np.zeros((off.size, maxint), dtype=complex)
+        numerator = np.zeros((off.size, maxint), dtype=np.complex_)
+        denominator = np.zeros((off.size, maxint), dtype=np.complex_)
 
         if k_used[0]:
             numerator += sPJ0r(check0) + 1j*sPJ0i(check0)
@@ -325,7 +325,7 @@ def hankel_qwe(zsrc, zrec, lsrc, lrec, off, ang_fact, depth, ab, etaH, etaV,
         doqwe = np.all((np.abs(numerator)/np.abs(denominator) < diff_quad), 1)
 
         # Pre-allocate output array
-        fEM = np.zeros(off.size, dtype=complex)
+        fEM = np.zeros(off.size, dtype=np.complex_)
         conv = True
 
         # Carry out SciPy's Quad if required
@@ -357,7 +357,7 @@ def hankel_qwe(zsrc, zrec, lsrc, lrec, off, ang_fact, depth, ab, etaH, etaV,
                 sPJ0b = sPJ0br(np.log(lambd)) + 1j*sPJ0bi(np.log(lambd))
 
             # Carry out and return the Hankel transform for this interval
-            sEM = np.zeros_like(numerator, dtype=complex)
+            sEM = np.zeros_like(numerator, dtype=np.complex_)
             if k_used[1]:
                 sEM += np.sum(np.reshape(sPJ1*BJ1, (off.size, nquad, -1),
                               order='F'), 1)
@@ -395,7 +395,7 @@ def getkernel(i, inplambd, inpoff, inpfang):
                                                ab, xdirect, msrc, mrec)
 
             # Carry out and return the Hankel transform for this interval
-            gEM = np.zeros_like(inpoff, dtype=complex)
+            gEM = np.zeros_like(inpoff, dtype=np.complex_)
             if k_used[1]:
                 gEM += inpfang*np.dot(PJ1[0, :], BJ1[iB])
                 if ab in [11, 12, 21, 22, 14, 24, 15, 25]:  # Because of J2
@@ -481,7 +481,7 @@ def hankel_quad(zsrc, zrec, lsrc, lrec, off, ang_fact, depth, ab, etaH, etaV,
         sPJ0bi = None
 
     # Pre-allocate output array
-    fEM = np.zeros(off.size, dtype=complex)
+    fEM = np.zeros(off.size, dtype=np.complex_)
     conv = True
 
     # Input-dictionary for quad
@@ -746,7 +746,7 @@ def fourier_fftlog(fEM, time, freq, ftarg):
     a = fftpack.rfft(a)
 
     # 4.b
-    m = np.arange(1, n//2, dtype=int)  # index variable
+    m = np.arange(1, n//2, dtype=np.int_)  # index variable
     if q == 0:  # unbiased (q = 0) transform
         # multiply by (kr)^[- i 2 m pi/(n dlnr)] U_mu[i 2 m pi/(n dlnr)]
         ar = a[2*m-1]
@@ -918,7 +918,7 @@ def dlf(signal, points, out_pts, filt, pts_per_dec, kind=None, ang_fact=None,
     def spline(values, points, int_pts):
         r"""Return `values` at `points` interpolated in log at `int_pts`."""
         out = iuSpline(np.log(points), values.real)(np.log(int_pts))
-        if values.dtype == complex:
+        if values.dtype == np.complex_:
             out = out+1j*iuSpline(np.log(points), values.imag)(np.log(int_pts))
         return out
 
@@ -1067,7 +1067,7 @@ def getweights(i, inpint):
 
     # 2. Pre-allocate arrays and initialize
     EM = np.zeros(EM0.size, dtype=EM0.dtype)                # EM array
-    om = np.ones(EM0.size, dtype=bool)                      # Convergence array
+    om = np.ones(EM0.size, dtype=np.bool_)                  # Convergence array
     S = np.zeros((EM0.size, maxint), dtype=EM0.dtype)  # Working arr. 4 recurs.
     relErr = np.zeros((EM0.size, maxint))                   # Relative error
     extrap = np.zeros((EM0.size, maxint), dtype=EM0.dtype)  # extrap. result

empymod/utils.py

@@ -1115,7 +1115,7 @@ def check_time(time, signal, ft, ftarg, verb):
         # Calculate minimum and maximum required frequency
         minf = np.log10(1/time.max()) + targ['add_dec'][0]
         maxf = np.log10(1/time.min()) + targ['add_dec'][1]
-        n = np.int(maxf - minf)*targ['pts_per_dec']
+        n = np.int_(maxf - minf)*targ['pts_per_dec']
 
         # Initialize FFTLog, get required parameters
         freq, tcalc, dlnr, kr, rk = transform.get_fftlog_input(
@@ -1329,7 +1329,7 @@ def get_abs(msrc, mrec, srcazm, srcdip, recazm, recdip, verb):
             ab_calc = ab_calc % 10*10 + ab_calc // 10  # Swap alpha/beta
 
     # Remove unnecessary ab's
-    bab = np.asarray(ab_calc*0+1, dtype=bool)
+    bab = np.asarray(ab_calc*0+1, dtype=np.bool_)
 
     # Remove if source is x- or y-directed
     check = np.atleast_1d(srcazm)
@@ -1468,7 +1468,7 @@ def get_layer_nr(inp, depth):
         inp[2] (depths).
 
     """
-    zinp = np.array(inp[2], dtype=float)
+    zinp = np.array(inp[2], dtype=np.float_)
 
     #  depth = [-infty : last interface]; create additional depth-array
     # pdepth = [fist interface : +infty]

tests/test_model.py

@@ -489,7 +489,7 @@ def test_multisrc_multirec(self):
         out0t = bipole(src=src0, rec=rec0, signal=0, **model)
 
         # Calculate the single-src/single-rec correspondents
-        out1f = np.zeros((2, 2), dtype=complex)
+        out1f = np.zeros((2, 2), dtype=np.complex_)
         out1t = np.zeros((2, 2))
         for i, rec in enumerate([rec1, rec2]):
             for ii, src in enumerate([src1, src2]):
@@ -941,8 +941,8 @@ def test_dipole_k():
     # Check that ab=36 returns zeros
     res['inp']['ab'] = 36
     w_res0, w_res1 = dipole_k(**res['inp'])
-    assert_allclose(w_res0, np.zeros(res['PJ0'].shape, dtype=complex))
-    assert_allclose(w_res1, np.zeros(res['PJ1'].shape, dtype=complex))
+    assert_allclose(w_res0, np.zeros(res['PJ0'].shape, dtype=np.complex_))
+    assert_allclose(w_res1, np.zeros(res['PJ1'].shape, dtype=np.complex_))
 
 
 def test_fem():