Changes in sasmodels/compare.py [765eb0e:ced5bd2] in sasmodels

File:

• sasmodels/compare.py (modified) (10 diffs)

sasmodels/compare.py

@@ -73 +73 @@
     -res=0 sets the resolution width dQ/Q if calculating with resolution
     -lowq*/-midq/-highq/-exq use q values up to 0.05, 0.2, 1.0, 10.0
+    -q=min:max alternative specification of qrange
     -nq=128 sets the number of Q points in the data set
     -1d*/-2d computes 1d or 2d data
@@ -533 +534 @@
                 % (pd, n, nsigma, nsigma, pdtype)
     if M0 != 0.:
-        line += "  M0:%.3f  mphi:%.1f  mtheta:%.1f" % (M0, mphi, mtheta)
+        line += "  M0:%.3f  mtheta:%.1f  mphi:%.1f" % (M0, mtheta, mphi)
     return line
 
@@ -768 +769 @@
     'accuracy', 'is2d' and 'view' parsed from the command line.
     """
-    qmax, nq, res = opts['qmax'], opts['nq'], opts['res']
+    qmin, qmax, nq, res = opts['qmin'], opts['qmax'], opts['nq'], opts['res']
     if opts['is2d']:
         q = np.linspace(-qmax, qmax, nq)  # type: np.ndarray
@@ -777 +778 @@
     else:
         if opts['view'] == 'log' and not opts['zero']:
-            qmax = math.log10(qmax)
-            q = np.logspace(qmax-3, qmax, nq)
+            q = np.logspace(math.log10(qmin), math.log10(qmax), nq)
         else:
-            q = np.linspace(0.001*qmax, qmax, nq)
+            q = np.linspace(qmin, qmax, nq)
         if opts['zero']:
             q = np.hstack((0, q))
@@ -955 +955 @@
         else:
             err, errstr, errview = abs(relerr), "rel err", "log"
+            if (err == 0.).all():
+                errview = 'linear'
         if 0:  # 95% cutoff
             sorted = np.sort(err.flatten())
@@ -960 +962 @@
             err[err > cutoff] = cutoff
         #err,errstr = base/comp,"ratio"
-        plot_theory(data, None, resid=err, view=errview, use_data=use_data)
-        if view == 'linear':
-            plt.xscale('linear')
+        plot_theory(data, None, resid=err, view=view, use_data=use_data)
+        plt.yscale(errview)
         plt.title("max %s = %.3g"%(errstr, abs(err).max()))
         #cbar_title = errstr if errview=="linear" else "log "+errstr
@@ -1001 +1002 @@
 
     # Data generation
-    'data=', 'noise=', 'res=',
-    'nq=', 'lowq', 'midq', 'highq', 'exq', 'zero',
+    'data=', 'noise=', 'res=', 'nq=', 'q=',
+    'lowq', 'midq', 'highq', 'exq', 'zero',
     '2d', '1d',
 
@@ -1122 +1123 @@
         'view'      : 'log',
         'is2d'      : False,
+        'qmin'      : None,
         'qmax'      : 0.05,
         'nq'        : 128,
@@ -1159 +1161 @@
         elif arg == '-zero':    opts['zero'] = True
         elif arg.startswith('-nq='):       opts['nq'] = int(arg[4:])
+        elif arg.startswith('-q='):
+            opts['qmin'], opts['qmax'] = [float(v) for v in arg[3:].split(':')]
         elif arg.startswith('-res='):      opts['res'] = float(arg[5:])
         elif arg.startswith('-noise='):    opts['noise'] = float(arg[7:])
@@ -1207 +1211 @@
 
     # Create the computational engines
+    if opts['qmin'] is None:
+        opts['qmin'] = 0.001*opts['qmax']
     if opts['datafile'] is not None:
         data = load_data(os.path.expanduser(opts['datafile']))