Changeset 4057e06 in sasmodels

Timestamp:

Mar 4, 2019 5:17:36 PM (6 years ago)

Author:

GitHub <noreply@…>

Branches:

master, core_shell_microgels, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests

Children:

cff2939

Parents:

275511c (diff), 8064d5e (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.

git-author:

Paul Kienzle <pkienzle@…> (03/04/19 17:17:36)

git-committer:

GitHub <noreply@…> (03/04/19 17:17:36)

Message:

Merge branch 'py3' into webgl_jitter_viewer

Files:

• sasmodels/jitter.py (modified) (2 diffs)
• sasmodels/kernelcl.py (modified) (3 diffs)
• sasmodels/resolution.py (modified) (2 diffs)
• sasmodels/weights.py (modified) (1 diff)
• explore/beta/data_files/sasfit_ellipsoid_schulz_IQBD.txt (moved) (moved from explore/beta/data_files/richard_test6.txt)
• explore/beta/data_files/sasfit_ellipsoid_schulz_IQD.txt (moved) (moved from explore/beta/data_files/richard_test4.txt)
• explore/beta/data_files/sasfit_ellipsoid_schulz_IQSD.txt (moved) (moved from explore/beta/data_files/richard_test5.txt)
• explore/beta/data_files/sasfit_sphere_schulz_IQBD.txt (moved) (moved from explore/beta/data_files/richard_test3.txt)
• explore/beta/data_files/sasfit_sphere_schulz_IQD.txt (moved) (moved from explore/beta/data_files/richard_test.txt)
• explore/beta/data_files/sasfit_sphere_schulz_IQSD.txt (moved) (moved from explore/beta/data_files/richard_test2.txt)
• explore/beta/sasfit_compare.py (modified) (2 diffs)
• sasmodels/models/pearl_necklace.c (modified) (2 diffs)

sasmodels/jitter.py

@@ -964 +964 @@
 
 def mpl_plot(calculator, draw_shape, size, view, jitter, dist, mesh, projection):
+    # Note: travis-ci does not support mpl_toolkits.mplot3d, but this shouldn't be
+    # an issue since we are lazy-loading the package on a path that isn't tested.
     import mpl_toolkits.mplot3d  # Adds projection='3d' option to subplot
+    import matplotlib as mpl
     import matplotlib.pyplot as plt
     from matplotlib.widgets import Slider
-
+    
     ## create the plot window
     #plt.hold(True)
@@ -982 +985 @@
         pass
 
-    #axcolor = {'facecolor': 'lightgoldenrodyellow'}
-    axcolor = {}
+
+    # CRUFT: use axisbg instead of facecolor for matplotlib<2
+    facecolor_prop = 'facecolor' if mpl.__version__ > '2' else 'axisbg'
+    props = {facecolor_prop: 'lightgoldenrodyellow'}
 
     ## add control widgets to plot
-    axes_theta = plt.axes([0.1, 0.15, 0.45, 0.04], **axcolor)
-    axes_phi = plt.axes([0.1, 0.1, 0.45, 0.04], **axcolor)
-    axes_psi = plt.axes([0.1, 0.05, 0.45, 0.04], **axcolor)
-    stheta = Slider(axes_theta, u'Ξ', -90, 90, valinit=0)
-    sphi = Slider(axes_phi, u'φ', -180, 180, valinit=0)
-    spsi = Slider(axes_psi, u'ψ', -180, 180, valinit=0)
-
-    axes_dtheta = plt.axes([0.75, 0.15, 0.15, 0.04], **axcolor)
-    axes_dphi = plt.axes([0.75, 0.1, 0.15, 0.04], **axcolor)
-    axes_dpsi = plt.axes([0.75, 0.05, 0.15, 0.04], **axcolor)
+    axes_theta = plt.axes([0.1, 0.15, 0.45, 0.04], **props)
+    axes_phi = plt.axes([0.1, 0.1, 0.45, 0.04], **props)
+    axes_psi = plt.axes([0.1, 0.05, 0.45, 0.04], **props)
+    stheta = Slider(axes_theta, 'Theta', -90, 90, valinit=theta)
+    sphi = Slider(axes_phi, 'Phi', -180, 180, valinit=phi)
+    spsi = Slider(axes_psi, 'Psi', -180, 180, valinit=psi)
+
+    axes_dtheta = plt.axes([0.75, 0.15, 0.15, 0.04], **props)
+    axes_dphi = plt.axes([0.75, 0.1, 0.15, 0.04], **props)
+    axes_dpsi = plt.axes([0.75, 0.05, 0.15, 0.04], **props)
+
     # Note: using ridiculous definition of rectangle distribution, whose width
     # in sasmodels is sqrt(3) times the given width.  Divide by sqrt(3) to keep

sasmodels/kernelcl.py

@@ -58 +58 @@
 import time
 
+try:
+    from time import perf_counter as clock
+except ImportError: # CRUFT: python < 3.3
+    import sys
+    if sys.platform.count("darwin") > 0:
+        from time import time as clock
+    else:
+        from time import clock
+
 import numpy as np  # type: ignore
-
 
 # Attempt to setup opencl. This may fail if the pyopencl package is not
@@ -611 +619 @@
         #Call kernel and retrieve results
         wait_for = None
-        last_nap = time.clock()
+        last_nap = clock()
         step = 1000000//self.q_input.nq + 1
         for start in range(0, call_details.num_eval, step):
@@ -622 +630 @@
                 # Allow other processes to run
                 wait_for[0].wait()
-                current_time = time.clock()
+                current_time = clock()
                 if current_time - last_nap > 0.5:
                     time.sleep(0.001)

sasmodels/resolution.py

@@ -445 +445 @@
     q = np.sort(q)
     if q_min + 2*MINIMUM_RESOLUTION < q[0]:
-        n_low = np.ceil((q[0]-q_min) / (q[1]-q[0])) if q[1] > q[0] else 15
+        n_low = int(np.ceil((q[0]-q_min) / (q[1]-q[0]))) if q[1] > q[0] else 15
         q_low = np.linspace(q_min, q[0], n_low+1)[:-1]
     else:
         q_low = []
     if q_max - 2*MINIMUM_RESOLUTION > q[-1]:
-        n_high = np.ceil((q_max-q[-1]) / (q[-1]-q[-2])) if q[-1] > q[-2] else 15
+        n_high = int(np.ceil((q_max-q[-1]) / (q[-1]-q[-2]))) if q[-1] > q[-2] else 15
         q_high = np.linspace(q[-1], q_max, n_high+1)[1:]
     else:
@@ -499 +499 @@
             q_min = q[0]*MINIMUM_ABSOLUTE_Q
         n_low = log_delta_q * (log(q[0])-log(q_min))
-        q_low = np.logspace(log10(q_min), log10(q[0]), np.ceil(n_low)+1)[:-1]
+        q_low = np.logspace(log10(q_min), log10(q[0]), int(np.ceil(n_low))+1)[:-1]
     else:
         q_low = []
     if q_max > q[-1]:
         n_high = log_delta_q * (log(q_max)-log(q[-1]))
-        q_high = np.logspace(log10(q[-1]), log10(q_max), np.ceil(n_high)+1)[1:]
+        q_high = np.logspace(log10(q[-1]), log10(q_max), int(np.ceil(n_high))+1)[1:]
     else:
         q_high = []

sasmodels/weights.py

@@ -23 +23 @@
     default = dict(npts=35, width=0, nsigmas=3)
     def __init__(self, npts=None, width=None, nsigmas=None):
-        self.npts = self.default['npts'] if npts is None else npts
+        self.npts = self.default['npts'] if npts is None else int(npts)
         self.width = self.default['width'] if width is None else width
         self.nsigmas = self.default['nsigmas'] if nsigmas is None else nsigmas

explore/beta/sasfit_compare.py

@@ -505 +505 @@
     }
 
-    Q, IQ = load_sasfit(data_file('richard_test.txt'))
-    Q, IQSD = load_sasfit(data_file('richard_test2.txt'))
-    Q, IQBD = load_sasfit(data_file('richard_test3.txt'))
+    Q, IQ = load_sasfit(data_file('sasfit_sphere_schulz_IQD.txt'))
+    Q, IQSD = load_sasfit(data_file('sasfit_sphere_schulz_IQSD.txt'))
+    Q, IQBD = load_sasfit(data_file('sasfit_sphere_schulz_IQBD.txt'))
     target = Theory(Q=Q, F1=None, F2=None, P=IQ, S=None, I=IQSD, Seff=None, Ibeta=IQBD)
     actual = sphere_r(Q, norm="sasfit", **pars)
@@ -526 +526 @@
     }
 
-    Q, IQ = load_sasfit(data_file('richard_test4.txt'))
-    Q, IQSD = load_sasfit(data_file('richard_test5.txt'))
-    Q, IQBD = load_sasfit(data_file('richard_test6.txt'))
+    Q, IQ = load_sasfit(data_file('sasfit_ellipsoid_shulz_IQD.txt'))
+    Q, IQSD = load_sasfit(data_file('sasfit_ellipsoid_shulz_IQSD.txt'))
+    Q, IQBD = load_sasfit(data_file('sasfit_ellipsoid_shulz_IQBD.txt'))
     target = Theory(Q=Q, F1=None, F2=None, P=IQ, S=None, I=IQSD, Seff=None, Ibeta=IQBD)
     actual = ellipsoid_pe(Q, norm="sasfit", **pars)

sasmodels/models/pearl_necklace.c

@@ -40 +40 @@
     const double si = sas_sinx_x(q*A_s);
     const double omsi = 1.0 - si;
-    const double pow_si = pow(si, num_pearls);
+    const double pow_si = pown(si, num_pearls);
 
     // form factor for num_pearls
@@ -81 +81 @@
 radius_from_volume(double radius, double edge_sep, double thick_string, double fp_num_pearls)
 {
-    const int num_pearls = (int) fp_num_pearls +0.5;
     const double vol_tot = form_volume(radius, edge_sep, thick_string, fp_num_pearls);
     return cbrt(vol_tot/M_4PI_3);