Changeset e2592f0 in sasmodels

Timestamp:

Oct 9, 2018 5:23:53 PM (6 years ago)

Author:

Paul Kienzle <pkienzle@…>

Branches:

master, core_shell_microgels, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests

Children:

7d97437

Parents:

353e899

Message:

fix test warnings from py3 and numpy

Location:

sasmodels

Files:

• kernelcl.py (modified) (3 diffs)
• resolution.py (modified) (2 diffs)
• weights.py (modified) (1 diff)

sasmodels/kernelcl.py

@@ -56 +56 @@
 import time
 
+try:
+    from time import perf_counter as clock
+except ImportError: # CRUFT: python < 3.3
+    if sys.platform.count("darwin") > 0:
+        from time import time as clock
+    else:
+        from time import clock
+
 import numpy as np  # type: ignore
-
 
 # Attempt to setup opencl. This may fail if the opencl package is not
@@ -575 +582 @@
         # Call kernel and retrieve results
         wait_for = None
-        last_nap = time.clock()
+        last_nap = clock()
         step = 1000000//self.q_input.nq + 1
         for start in range(0, call_details.num_eval, step):
@@ -586 +593 @@
                 # Allow other processes to run
                 wait_for[0].wait()
-                current_time = time.clock()
+                current_time = clock()
                 if current_time - last_nap > 0.5:
                     time.sleep(0.05)

sasmodels/resolution.py

@@ -445 +445 @@
     q = np.sort(q)
     if q_min + 2*MINIMUM_RESOLUTION < q[0]:
-        n_low = np.ceil((q[0]-q_min) / (q[1]-q[0])) if q[1] > q[0] else 15
+        n_low = int(np.ceil((q[0]-q_min) / (q[1]-q[0]))) if q[1] > q[0] else 15
         q_low = np.linspace(q_min, q[0], n_low+1)[:-1]
     else:
         q_low = []
     if q_max - 2*MINIMUM_RESOLUTION > q[-1]:
-        n_high = np.ceil((q_max-q[-1]) / (q[-1]-q[-2])) if q[-1] > q[-2] else 15
+        n_high = int(np.ceil((q_max-q[-1]) / (q[-1]-q[-2]))) if q[-1] > q[-2] else 15
         q_high = np.linspace(q[-1], q_max, n_high+1)[1:]
     else:
@@ -499 +499 @@
             q_min = q[0]*MINIMUM_ABSOLUTE_Q
         n_low = log_delta_q * (log(q[0])-log(q_min))
-        q_low = np.logspace(log10(q_min), log10(q[0]), np.ceil(n_low)+1)[:-1]
+        q_low = np.logspace(log10(q_min), log10(q[0]), int(np.ceil(n_low))+1)[:-1]
     else:
         q_low = []
     if q_max > q[-1]:
         n_high = log_delta_q * (log(q_max)-log(q[-1]))
-        q_high = np.logspace(log10(q[-1]), log10(q_max), np.ceil(n_high)+1)[1:]
+        q_high = np.logspace(log10(q[-1]), log10(q_max), int(np.ceil(n_high))+1)[1:]
     else:
         q_high = []

sasmodels/weights.py

@@ -23 +23 @@
     default = dict(npts=35, width=0, nsigmas=3)
     def __init__(self, npts=None, width=None, nsigmas=None):
-        self.npts = self.default['npts'] if npts is None else npts
+        self.npts = self.default['npts'] if npts is None else int(npts)
         self.width = self.default['width'] if width is None else width
         self.nsigmas = self.default['nsigmas'] if nsigmas is None else nsigmas