Integer to float conversion TypeError

bowpy/filter/fk.py

@@ -299,7 +299,6 @@ def fk_filter(
             slopes,
             deltaslope,
             peakpick=None,
-            mindist=dist,
             smoothing=smoothpicks,
             interactive=slopepicking,
         )
@@ -908,7 +907,7 @@ def _fk_extract_polygon(
     """
     # Shift 0|0 f-k to center, for easier handling
     dsfk = np.fft.fftshift(data.conj().transpose())
-    dsfk_tmp = dsfk[0 : dsfk.shape[0] / 2]
+    dsfk_tmp = dsfk[0 : dsfk.shape[0] // 2]
 
     # Define polygon by user-input.
     # If eval_mean is true, select area where to calculate the mean value
@@ -930,10 +929,10 @@ def _fk_extract_polygon(
     data_fk = np.zeros(dsfk.shape).astype("complex")
 
     # top half of domain.
-    data_fk[0 : dsfk.shape[0] / 2] = dsfk_tmp
+    data_fk[0 : dsfk.shape[0] // 2] = dsfk_tmp
 
     # Bottom half of domain, exploiting symmetry and shift properties.
-    data_fk[dsfk.shape[0] / 2 :] = np.roll(
+    data_fk[dsfk.shape[0] // 2 :] = np.roll(
         np.roll(np.flipud(np.fliplr(dsfk_tmp)), 1).transpose(), 1
     ).transpose()
 
@@ -960,7 +959,7 @@ def _fk_eliminate_polygon(
     """
     # Shift 0|0 f-k to center, for easier handling
     dsfk = np.fft.fftshift(data.conj().transpose())
-    dsfk_tmp = dsfk[0 : dsfk.shape[0] / 2]
+    dsfk_tmp = dsfk[0 : dsfk.shape[0] // 2]
 
     # Define polygon by user-input.
     # If eval_mean is true, select area where to calculate the mean value
@@ -982,10 +981,10 @@ def _fk_eliminate_polygon(
     data_fk = np.zeros(dsfk.shape).astype("complex")
 
     # top half of domain.
-    data_fk[0 : dsfk.shape[0] / 2] = dsfk_tmp
+    data_fk[0 : dsfk.shape[0] // 2] = dsfk_tmp
 
     # Bottom half of domain, exploiting symmetry and shift properties.
-    data_fk[dsfk.shape[0] / 2 :] = np.roll(
+    data_fk[dsfk.shape[0] // 2 :] = np.roll(
         np.roll(np.flipud(np.fliplr(dsfk_tmp)), 1).transpose(), 1
     ).transpose()
 
@@ -1023,15 +1022,15 @@ def _fk_ls_filter_eliminate_phase_sp(ArrayData, y_dist=False, radius=None, maxk=
     type snes:  int
     """
     # Define freq Array
-    freq = np.zeros((len(ArrayData), len(ArrayData[0]) / 2 + 1)) + 1j
+    freq = np.zeros((len(ArrayData), len(ArrayData[0]) // 2 + 1)) + 1j
 
     for i in range(len(ArrayData)):
         freq_new = np.fft.rfftn(ArrayData[i])
         freq[i] = freq_new
 
     # Define k Array
     freqT = freq.conj().transpose()
-    knum = np.zeros((len(freqT), len(freqT[0]) / 2 + 1))
+    knum = np.zeros((len(freqT), len(freqT[0]) // 2 + 1))
 
     # calc best range
     N = len(freqT[0])

bowpy/util/base.py

@@ -531,15 +531,15 @@ def line_cut(array, shape):
     elif name in ["butterworth", "Butterworth", "taper", "Taper"] and isinstance(
         length, int
     ):
-        fil_lh = create_filter(name, array.shape[0] / 2, length, kwarg)
+        fil_lh = create_filter(name, array.shape[0] // 2, length, kwarg)
 
     elif name in ["taper", "Taper"] and isinstance(length, int):
-        fil_lh = create_filter(name, array.shape[0] / 2, length, kwarg)
+        fil_lh = create_filter(name, array.shape[0] // 2, length, kwarg)
 
     fil_rh = np.flipud(fil_lh)[::-1][0:][::-1]
     fil = np.zeros(2 * fil_lh.size)
-    fil[: fil.size / 2] = fil_lh
-    fil[fil.size / 2 :] = fil_rh
+    fil[: fil.size // 2] = fil_lh
+    fil[fil.size // 2 :] = fil_rh
 
     new_array = array.transpose() * fil
     new_array = new_array.transpose()
@@ -582,16 +582,16 @@ def line_set_zero(array, shape):
     elif name in ["butterworth", "Butterworth", "taper", "Taper"] and isinstance(
         length, int
     ):
-        fil_lh = create_filter(name, array.shape[0] / 2, length, kwarg)
+        fil_lh = create_filter(name, array.shape[0] // 2, length, kwarg)
 
     elif name in ["taper", "Taper"] and isinstance(length, int):
-        fil_lh = create_filter(name, array.shape[0] / 2, length, kwarg)
+        fil_lh = create_filter(name, array.shape[0] // 2, length, kwarg)
         # fil_lh = -1. * fil_lh + 1.
 
     fil_rh = np.flipud(fil_lh)[::-1][1:][::-1]
     fil = np.zeros(2 * fil_lh.size)
-    fil[: fil.size / 2] = fil_lh
-    fil[fil.size / 2 + 1 :] = fil_rh
+    fil[: fil.size // 2] = fil_lh
+    fil[fil.size // 2 + 1 :] = fil_rh
     newfil = np.ones(fil.shape)
     newfil = newfil - fil
 

bowpy/util/fkutil.py

@@ -468,9 +468,9 @@ def makeMask(fkdata, slope, shape, rth=0.4, expl_cutoff=False):
     pnorm = 1 / 2.0 * (float(M.shape[0] + 1) / float(2.0 * M.shape[1]))
 
     prange = slope * pnorm
-    Mask = np.zeros((M.shape[0], 2.0 * M.shape[1]))
-    maskshape = np.zeros((M.shape[0], 2.0 * M.shape[1]))
-    W = np.zeros((M.shape[0], 2.0 * M.shape[1]))
+    Mask = np.zeros((M.shape[0], 2 * M.shape[1]))
+    maskshape = np.zeros((M.shape[0], 2 * M.shape[1]))
+    W = np.zeros((M.shape[0], 2 * M.shape[1]))
     name = shape[0]
     arg = shape[1]
 
@@ -482,16 +482,16 @@ def makeMask(fkdata, slope, shape, rth=0.4, expl_cutoff=False):
 
         if cutoff < 1:
             cutoff = 1
-        maskshape_tmp = create_filter(name, Mask.shape[0] / 2, cutoff, arg)
+        maskshape_tmp = create_filter(name, Mask.shape[0] // 2, cutoff, arg)
         maskshape_lh = (
             np.tile(maskshape_tmp, Mask.shape[1])
             .reshape(Mask.shape[1], maskshape_tmp.size)
             .transpose()
         )
         maskshape_rh = np.flipud(maskshape_lh)
 
-        maskshape[: maskshape.shape[0] / 2, :] = maskshape_lh
-        maskshape[maskshape.shape[0] / 2 :, :] = maskshape_rh
+        maskshape[: maskshape.shape[0] // 2, :] = maskshape_lh
+        maskshape[maskshape.shape[0] // 2 :, :] = maskshape_rh
 
     for m in prange:
         if m == 0.0:
@@ -511,7 +511,7 @@ def makeMask(fkdata, slope, shape, rth=0.4, expl_cutoff=False):
             Mask[:, f] = np.roll(Mask[:, f], int(f * m))
 
         W += Mask
-        Mask = np.zeros((M.shape[0], 2.0 * M.shape[1]))
+        Mask = np.zeros((M.shape[0], 2 * M.shape[1]))
 
     # Convolving each frequency slice of the mask with a boxcar
     # of size L. Widens the the maskfunction along k-axis.
@@ -535,12 +535,12 @@ def makeMask(fkdata, slope, shape, rth=0.4, expl_cutoff=False):
         Wr[np.where(Wr > rth)] = 1.0
         Wr[np.where(Wr < rth)] = 0.0
 
-    Wlhs = np.roll(Wr[:, 0 : Wr.shape[1] / 2 - 1], shift=1, axis=0)
-    Wrhs = Wr[:, 1 : Wr.shape[1] / 2 + 1]
+    Wlhs = np.roll(Wr[:, 0 : Wr.shape[1] // 2 - 1], shift=1, axis=0)
+    Wrhs = Wr[:, 1 : Wr.shape[1] // 2 + 1]
     Wrhs = np.roll(np.flipud(np.fliplr(Wrhs)), shift=0, axis=0)
 
-    Wr[:, 0 : Wr.shape[1] / 2 - 1] = Wlhs
-    Wr[:, Wr.shape[1] / 2 :] = Wrhs
+    Wr[:, 0 : Wr.shape[1] // 2 - 1] = Wlhs
+    Wr[:, Wr.shape[1] // 2 :] = Wrhs
     return Wr
 
 
@@ -1276,7 +1276,7 @@ def plotfk(
                 np.log(
                     abs(
                         np.fft.fftshift(
-                            data[:, : data.shape[1] / 2].transpose(), axes=1
+                            data[:, : data.shape[1] // 2].transpose(), axes=1
                         )
                     )
                 )
@@ -1289,7 +1289,7 @@ def plotfk(
     else:
         im = ax.imshow(
             np.flipud(
-                abs(np.fft.fftshift(data[:, : data.shape[1] / 2].transpose(), axes=1))
+                abs(np.fft.fftshift(data[:, : data.shape[1] // 2].transpose(), axes=1))
             ),
             aspect="auto",
             extent=(-0.5, 0.5, 0, 0.5),
@@ -1637,7 +1637,7 @@ def slope_distribution(
 
     pmin = prange[0]
     pmax = prange[1]
-    N = abs(pmax - pmin) / pdelta + 1
+    N = int(abs(pmax - pmin) / pdelta + 1)
     MD = np.zeros(N)
     srange = np.linspace(pmin, pmax, N)
 

bowpy/util/picker.py

@@ -230,7 +230,7 @@ def get_polygon(
         else:
             xs.append(xmin)
 
-    ys = np.linspace(ymin, ymax, no_of_vert / 2)
+    ys = np.linspace(ymin, ymax, no_of_vert // 2)
     ys = np.append(ys, ys[::-1]).tolist()
 
     poly = Polygon(list(zip(xs, ys)), animated=True, closed=False, fill=False)