Changeset 644430f in sasmodels

Timestamp:

Dec 23, 2015 10:02:39 AM (9 years ago)

Author:

Paul Kienzle <pkienzle@…>

Branches:

master, core_shell_microgels, costrafo411, magnetic_model, release_v0.94, release_v0.95, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests

Children:

e3a9733

Parents:

cade620

Message:

fix plots. 1D: handle all NaN. 2D: handle arbitrary detector shape. both: add x,y labels

File:

• sasmodels/data.py (modified) (7 diffs)

sasmodels/data.py

@@ -275 +275 @@
 
         #print(vmin, vmax)
-        positive = False
+        all_positive = True
+        some_present = False
         if plot_data:
-            mdata = masked_array(data.y, data.mask)
+            mdata = masked_array(data.y, data.mask.copy())
             mdata[~np.isfinite(mdata)] = masked
             if view is 'log':
                 mdata[mdata <= 0] = masked
-            plt.errorbar(data.x, scale*mdata, yerr=data.dy, fmt='.')
-            positive = positive or (mdata>0).any()
+            plt.errorbar(data.x/10, scale*mdata, yerr=data.dy, fmt='.')
+            all_positive = all_positive and (mdata>0).all()
+            some_present = some_present or (mdata.count() > 0)
+
 
         if plot_theory:
-            mtheory = masked_array(theory, data.mask)
+            mtheory = masked_array(theory, data.mask.copy())
+            mtheory[~np.isfinite(mtheory)] = masked
             if view is 'log':
-                mtheory[mtheory<= 0] = masked
-            plt.plot(data.x, scale*mtheory, '-', hold=True)
-            positive = positive or (mtheory>0).any()
-
-        plt.xscale(view)
-        plt.yscale('linear' if view == 'q4' or not positive else view)
-        plt.xlabel('Q')
-        plt.ylabel('I(Q)')
+                mtheory[mtheory<=0] = masked
+            plt.plot(data.x/10, scale*mtheory, '-', hold=True)
+            all_positive = all_positive and (mtheory>0).all()
+            some_present = some_present or (mtheory.count() > 0)
+
+        plt.xscale('linear' if not some_present else view)
+        plt.yscale('linear'
+                   if view == 'q4' or not some_present or not all_positive
+                   else view)
+        plt.xlabel("$q$/nm$^{-1}$")
+        plt.ylabel('$I(q)$')
 
     if plot_resid:
@@ -300 +307 @@
             plt.subplot(122)
 
-        mresid = masked_array(resid, data.mask)
-        plt.plot(data.x, mresid, '-')
+        mresid = masked_array(resid, data.mask.copy())
+        mresid[~np.isfinite(mresid)] = masked
+        some_present = (mresid.count() > 0)
+        plt.plot(data.x/10, mresid, '-')
+        plt.xlabel("$q$/nm$^{-1}$")
         plt.ylabel('residuals')
-        plt.xlabel('Q')
-        plt.xscale(view)
+        plt.xscale('linear' if not some_present else view)
 
 
@@ -366 +375 @@
         _plot_2d_signal(data, target, view=view, vmin=vmin, vmax=vmax)
         plt.title('data')
-        plt.colorbar()
+        h = plt.colorbar()
+        h.set_label('$I(q)$')
 
     if plot_theory:
@@ -377 +387 @@
         _plot_2d_signal(data, theory, view=view, vmin=vmin, vmax=vmax)
         plt.title('theory')
-        plt.colorbar()
+        h = plt.colorbar()
+        h.set_label('$I(q)$')
 
     #if plot_data or plot_theory:
@@ -388 +399 @@
             plt.subplot(122)
         _plot_2d_signal(data, resid, view='linear')
-        plt.colorbar()
         plt.title('residuals')
+        h = plt.colorbar()
+        h.set_label('$\Delta I(q)$')
 
 
@@ -414 +426 @@
     #plottable = Iq
     plottable = masked_array(image, ~valid | data.mask)
-    xmin, xmax = min(data.qx_data), max(data.qx_data)
-    ymin, ymax = min(data.qy_data), max(data.qy_data)
+    xmin, xmax = min(data.qx_data)/10, max(data.qx_data)/10
+    ymin, ymax = min(data.qy_data)/10, max(data.qy_data)/10
     # TODO: fix vmin, vmax so it is shared for theory/resid
     vmin = vmax = None
@@ -423 +435 @@
     except:
         vmin, vmax = 0, 1
-    plt.imshow(plottable.reshape(128, 128),
+    plt.imshow(plottable.reshape(len(data.xbins), len(data.ybins)),
                interpolation='nearest', aspect=1, origin='upper',
                extent=[xmin, xmax, ymin, ymax], vmin=vmin, vmax=vmax)
+    plt.xlabel("$q_x$/nm$^{-1}$")
+    plt.ylabel("$q_y$/nm$^{-1}$")