Fix deprecation warnings caused by np.int and np.float

spectral/__init__.py

@@ -4,7 +4,7 @@
 
 from __future__ import absolute_import, division, print_function, unicode_literals
 
-__version__ = '0.22.2'
+__version__ = '0.22.3'
 
 import sys
 if sys.byteorder == 'little':

spectral/config.py

@@ -157,5 +157,4 @@ class SpySettings:
                        [100, 0, 100],
                        [200, 0, 200],
                        [0, 100, 100],
-                       [0, 200, 200]], np.int)
-
+                       [0, 200, 200]], np.int8)

spectral/graphics/colorscale.py

@@ -52,13 +52,13 @@ def __init__(self, levels, colors, num_tics=0):
         if type(levels) in (list, tuple):
             levels = [float(x) for x in levels]
         elif isinstance(levels, np.ndarray):
-            levels = levels.astype(np.float)
+            levels = levels.astype(float)
 
         self.span = levels[-1] - levels[0]
         self.max = levels[-1]
         self.min = levels[0]
         self.tics = np.linspace(self.min, self.max, num_tics)
-        self.colorTics = np.zeros((len(self.tics), 3), np.int)
+        self.colorTics = np.zeros((len(self.tics), 3), int)
         self.size = len(self.tics)
         self.bgColor = np.array([0, 0, 0])
 
@@ -71,7 +71,7 @@ def __init__(self, levels, colors, num_tics=0):
                 dcolor = colors[j] - colors[j - 1]
                 dlevel = levels[j] - levels[j - 1]
             self.colorTics[i] = (colors[j - 1] + (self.tics[i] - levels[j - 1])
-                                 / dlevel * dcolor).astype(np.int)
+                                 / dlevel * dcolor).astype(int)
 
     def __call__(self, val):
         '''Returns the scale color associated with the given value.'''

spectral/graphics/graphics.py

@@ -566,7 +566,7 @@ def get_rgb_meta(source, bands=None, **kwargs):
             # Pick the first, middle, and last bands
             n = source.shape[-1]
             bands = [0, n // 2, n - 1]
-        rgb = source.read_bands(bands).astype(np.float)
+        rgb = source.read_bands(bands).astype(float)
         meta['bands'] = bands
     else:
         # It should be a numpy array
@@ -587,7 +587,7 @@ def get_rgb_meta(source, bands=None, **kwargs):
             # first, middle, & last bands.
             bands = [0, s[2] / 2, s[2] - 1]
 
-        rgb = np.take(source, bands, 2).astype(np.float)
+        rgb = np.take(source, bands, 2).astype(float)
         if rgb.ndim == 2:
             rgb = rgb[:, :, np.newaxis]
         meta['bands'] = bands
@@ -614,14 +614,14 @@ def get_rgb_meta(source, bands=None, **kwargs):
                 scale.set_range(min(rgb.ravel()), max(rgb.ravel()))
             rgb3 = np.zeros((s[0], s[1], 3), int)
             rgb3 = np.apply_along_axis(scale, 2, rgb)
-            rgb = rgb3.astype(np.float) / 255.
+            rgb = rgb3.astype(float) / 255.
             return (_fill_mask(rgb, mask, bg), meta)
         else:
             # Only one band of data to display but still need to determine how
             # to scale the data values
             meta['mode'] = 'monochrome'
             monochrome = True
-            rgb = np.repeat(rgb, 3, 2).astype(np.float)
+            rgb = np.repeat(rgb, 3, 2).astype(float)
 
     # Perform any requested color enhancements.
 

spectral/graphics/ndwindow.py

@@ -348,7 +348,7 @@ def __init__(self, data, parent, id, *args, **kwargs):
 
         self.data = data
         self.classes = kwargs.get('classes',
-                                  np.zeros(data.shape[:-1], np.int))
+                                  np.zeros(data.shape[:-1], int))
         self.features = kwargs.get('features', list(range(6)))
         self.labels = kwargs.get('labels', list(range(data.shape[-1])))
         self.max_menu_class = int(np.max(self.classes.ravel() + 1))

spectral/io/spyfile.py

@@ -550,8 +550,8 @@ def tile_image(im, nrows, ncols):
                         contains nrows lists, each of which contains
                         ncols SubImage objects.
     '''
-    x = (np.array(list(range(nrows + 1))) * float(im.nrows) / nrows).astype(np.int)
-    y = (np.array(list(range(ncols + 1))) * float(im.ncols) / ncols).astype(np.int)
+    x = (np.array(list(range(nrows + 1))) * float(im.nrows) / nrows).astype(int)
+    y = (np.array(list(range(ncols + 1))) * float(im.ncols) / ncols).astype(int)
     x[-1] = im.nrows
     y[-1] = im.ncols