Changeset 9a5097c in sasview for src/sas/sascalc/data_util/qsmearing.py

Timestamp:

Mar 26, 2017 11:33:16 PM (7 years ago)

Author:

andyfaff

Branches:

master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

ed2276f

Parents:

9146ed9

Message:

MAINT: import numpy as np

File:

• src/sas/sascalc/data_util/qsmearing.py (modified) (5 diffs)

src/sas/sascalc/data_util/qsmearing.py

@@ -9 +9 @@
 #copyright 2008, University of Tennessee
 ######################################################################
-import numpy
 import math
 import logging
@@ -60 +59 @@
     if data.dx is not None and data.isSesans:
         #if data.dx[0] > 0.0:
-        if numpy.size(data.dx[data.dx <= 0]) == 0:
+        if np.size(data.dx[data.dx <= 0]) == 0:
             _found_sesans = True
         # if data.dx[0] <= 0.0:
-        if numpy.size(data.dx[data.dx <= 0]) > 0:
+        if np.size(data.dx[data.dx <= 0]) > 0:
             raise ValueError('one or more of your dx values are negative, please check the data file!')
 
@@ -121 +120 @@
         self.resolution = resolution
         if offset is None:
-            offset = numpy.searchsorted(self.resolution.q_calc, self.resolution.q[0])
+            offset = np.searchsorted(self.resolution.q_calc, self.resolution.q[0])
         self.offset = offset
 
@@ -137 +136 @@
         start, end = first_bin + self.offset, last_bin + self.offset
         q_calc = self.resolution.q_calc
-        iq_calc = numpy.empty_like(q_calc)
+        iq_calc = np.empty_like(q_calc)
         if start > 0:
             iq_calc[:start] = self.model.evalDistribution(q_calc[:start])
@@ -157 +156 @@
         """
         q = self.resolution.q
-        first = numpy.searchsorted(q, q_min)
-        last = numpy.searchsorted(q, q_max)
+        first = np.searchsorted(q, q_min)
+        last = np.searchsorted(q, q_max)
         return first, min(last,len(q)-1)