Changeset 6da860a in sasview for src/sas/qtgui/Perspectives/Inversion/InversionLogic.py

Timestamp:

May 1, 2018 11:51:06 AM (7 years ago)

Author:

krzywon

Branches:

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

Children:

72ecbdf2

Parents:

6bd0d81

Message:

Responding to P(r) code review.

File:

• src/sas/qtgui/Perspectives/Inversion/InversionLogic.py (modified) (10 diffs)

src/sas/qtgui/Perspectives/Inversion/InversionLogic.py

@@ -1 +1 @@
 import math
-import pylab
+import logging
 import numpy as np
 
@@ -12 +12 @@
 GROUP_ID_IQ_DATA = r"$I_{obs}(q)$"
 GROUP_ID_PR_FIT = r"$P_{fit}(r)$"
+PR_PLOT_PTS = 51
+
+logger = logging.getLogger(__name__)
 
 
@@ -19 +22 @@
     No QStandardModelIndex here.
     """
-
-    # TODO: Add way to change this value
-    _pr_n_pts = 51
 
     def __init__(self, data=None):
@@ -63 +63 @@
             maxq = pr.q_max
 
-        x = pylab.arange(minq, maxq, maxq / 301.0)
+        x = np.arange(minq, maxq, maxq / 301.0)
         y = np.zeros(len(x))
         err = np.zeros(len(x))
@@ -73 +73 @@
             except:
                 err[i] = 1.0
-                print(("Error getting error", value, x[i]))
+                logger.log(("Error getting error", value, x[i]))
 
         new_plot = Data1D(x, y)
@@ -89 +89 @@
         # If we have used slit smearing, plot the smeared I(q) too
         if pr.slit_width > 0 or pr.slit_height > 0:
-            x = pylab.arange(minq, maxq, maxq / 301.0)
+            x = np.arange(minq, maxq, maxq / 301.0)
             y = np.zeros(len(x))
             err = np.zeros(len(x))
@@ -99 +99 @@
                 except:
                     err[i] = 1.0
-                    print(("Error getting error", value, x[i]))
+                    logger.log(("Error getting error", value, x[i]))
 
             new_plot = Data1D(x, y)
@@ -113 +113 @@
         return new_plot
 
-    def update1DPlot(self, plot, out, pr, q=None):
-        """
-        Create a new 1D data instance based on fitting results
-        """
-
-        qtemp = pr.x
-        if q is not None:
-            qtemp = q
-
-        # Make a plot
-        maxq = max(qtemp)
-
-        minq = min(qtemp)
-
-        # Check for user min/max
-        if pr.q_min is not None and maxq >= pr.q_min >= minq:
-            minq = pr.q_min
-        if pr.q_max is not None and maxq >= pr.q_max >= minq:
-            maxq = pr.q_max
-
-        x = pylab.arange(minq, maxq, maxq / 301.0)
-        y = np.zeros(len(x))
-        err = np.zeros(len(x))
-        for i in range(len(x)):
-            value = pr.iq(out, x[i])
-            y[i] = value
-            try:
-                err[i] = math.sqrt(math.fabs(value))
-            except:
-                err[i] = 1.0
-                print(("Error getting error", value, x[i]))
-
-        plot.x = x
-        plot.y = y
-
-        # If we have used slit smearing, plot the smeared I(q) too
-        if pr.slit_width > 0 or pr.slit_height > 0:
-            x = pylab.arange(minq, maxq, maxq / 301.0)
-            y = np.zeros(len(x))
-            err = np.zeros(len(x))
-            for i in range(len(x)):
-                value = pr.iq_smeared(pr.out, x[i])
-                y[i] = value
-                try:
-                    err[i] = math.sqrt(math.fabs(value))
-                except:
-                    err[i] = 1.0
-                    print(("Error getting error", value, x[i]))
-
-            plot.x = x
-            plot.y = y
-
-        return plot
-
     def newPRPlot(self, out, pr, cov=None):
         """
         """
         # Show P(r)
-        x = pylab.arange(0.0, pr.d_max, pr.d_max / self._pr_n_pts)
+        x = np.arange(0.0, pr.d_max, pr.d_max / PR_PLOT_PTS)
 
         y = np.zeros(len(x))
@@ -193 +139 @@
             y[i] = value
 
-        # if self._normalize_output == True:
-        #     y = y / total
-        #     dy = dy / total
-        # elif self._scale_output_unity == True:
-        #     y = y / pmax
-        #     dy = dy / pmax
-
         if cov2 is None:
             new_plot = Data1D(x, y)
@@ -213 +152 @@
 
         return new_plot
-
-    def updatePRPlot(self, plot, out, pr, cov=None):
-        x = pylab.arange(0.0, pr.d_max, pr.d_max / self._pr_n_pts)
-
-        y = np.zeros(len(x))
-        dy = np.zeros(len(x))
-
-        total = 0.0
-        pmax = 0.0
-        cov2 = np.ascontiguousarray(cov)
-
-        for i in range(len(x)):
-            if cov2 is None:
-                value = pr.pr(out, x[i])
-            else:
-                (value, dy[i]) = pr.pr_err(out, cov2, x[i])
-            total += value * pr.d_max / len(x)
-
-            # keep track of the maximum P(r) value
-            if value > pmax:
-                pmax = value
-
-            y[i] = value
-
-        # if self._normalize_output == True:
-        #     y = y / total
-        #     dy = dy / total
-        # elif self._scale_output_unity == True:
-        #     y = y / pmax
-        #     dy = dy / pmax
-        plot.x = x
-        plot.y = y
-
-        if cov2 is not None:
-            plot.dy = dy
-
-        return plot
 
     def computeDataRange(self):