Changeset 9a5097c in sasview for src/sas/sascalc/dataloader/readers/red2d_reader.py

Timestamp:

Mar 26, 2017 11:33:16 PM (8 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/dataloader/readers/red2d_reader.py (modified) (9 diffs)

src/sas/sascalc/dataloader/readers/red2d_reader.py

@@ -10 +10 @@
 ######################################################################
 import os
-import numpy
+import numpy as np
 import math
 from sas.sascalc.dataloader.data_info import Data2D, Detector
@@ -198 +198 @@
                 break
         # Make numpy array to remove header lines using index
-        lines_array = numpy.array(lines)
+        lines_array = np.array(lines)
 
         # index for lines_array
-        lines_index = numpy.arange(len(lines))
+        lines_index = np.arange(len(lines))
         
         # get the data lines
@@ -225 +225 @@
 
         # numpy array form
-        data_array = numpy.array(data_list1)
+        data_array = np.array(data_list1)
         # Redimesion based on the row_num and col_num,
         #otherwise raise an error.
@@ -235 +235 @@
         ## Get the all data: Let's HARDcoding; Todo find better way
         # Defaults
-        dqx_data = numpy.zeros(0)
-        dqy_data = numpy.zeros(0)
-        err_data = numpy.ones(row_num)
-        qz_data = numpy.zeros(row_num)
-        mask = numpy.ones(row_num, dtype=bool)
+        dqx_data = np.zeros(0)
+        dqy_data = np.zeros(0)
+        err_data = np.ones(row_num)
+        qz_data = np.zeros(row_num)
+        mask = np.ones(row_num, dtype=bool)
         # Get from the array
         qx_data = data_point[0]
@@ -254 +254 @@
             dqy_data = data_point[(5 + ver)]
         #if col_num > (6 + ver): mask[data_point[(6 + ver)] < 1] = False
-        q_data = numpy.sqrt(qx_data*qx_data+qy_data*qy_data+qz_data*qz_data)
+        q_data = np.sqrt(qx_data*qx_data+qy_data*qy_data+qz_data*qz_data)
            
         # Extra protection(it is needed for some data files): 
@@ -262 +262 @@
   
         # Store limits of the image in q space
-        xmin = numpy.min(qx_data)
-        xmax = numpy.max(qx_data)
-        ymin = numpy.min(qy_data)
-        ymax = numpy.max(qy_data)
+        xmin = np.min(qx_data)
+        xmax = np.max(qx_data)
+        ymin = np.min(qy_data)
+        ymax = np.max(qy_data)
 
         # units
@@ -287 +287 @@
         
         # store x and y axis bin centers in q space
-        x_bins = numpy.arange(xmin, xmax + xstep, xstep)
-        y_bins = numpy.arange(ymin, ymax + ystep, ystep)
+        x_bins = np.arange(xmin, xmax + xstep, xstep)
+        y_bins = np.arange(ymin, ymax + ystep, ystep)
        
         # get the limits of q values
@@ -300 +300 @@
         output.data = data
         if (err_data == 1).all():
-            output.err_data = numpy.sqrt(numpy.abs(data))
+            output.err_data = np.sqrt(np.abs(data))
             output.err_data[output.err_data == 0.0] = 1.0
         else:
@@ -335 +335 @@
                 # tranfer the comp. to cartesian coord. for newer version.
                 if ver != 1:
-                    diag = numpy.sqrt(qx_data * qx_data + qy_data * qy_data)
+                    diag = np.sqrt(qx_data * qx_data + qy_data * qy_data)
                     cos_th = qx_data / diag
                     sin_th = qy_data / diag
-                    output.dqx_data = numpy.sqrt((dqx_data * cos_th) * \
+                    output.dqx_data = np.sqrt((dqx_data * cos_th) * \
                                                  (dqx_data * cos_th) \
                                                  + (dqy_data * sin_th) * \
                                                   (dqy_data * sin_th))
-                    output.dqy_data = numpy.sqrt((dqx_data * sin_th) * \
+                    output.dqy_data = np.sqrt((dqx_data * sin_th) * \
                                                  (dqx_data * sin_th) \
                                                  + (dqy_data * cos_th) * \