Changes in / [a235f715:c79304b] in sasview

Files:

• docs/sphinx-docs/source/user/gpu_computations.rst (added)
• docs/sphinx-docs/source/user/opencl_installation.rst (added)
• docs/sphinx-docs/source/user/sasgui/perspectives/fitting/mag_vector.bmp (modified) (previous)
• docs/sphinx-docs/source/user/sasgui/perspectives/invariant/invariant_help.rst (modified) (5 diffs)
• docs/sphinx-docs/source/user/user.rst (modified) (1 diff)
• sasview/local_config.py (modified) (1 diff)
• sasview/setup_exe.py (modified) (1 diff)
• src/sas/sasgui/guiframe/utils.py (modified) (1 diff)
• src/sas/sasgui/perspectives/fitting/basepage.py (modified) (17 diffs)
• src/sas/sasgui/perspectives/fitting/fitpage.py (modified) (2 diffs)
• src/sas/sasgui/perspectives/fitting/media/plugin.rst (modified) (31 diffs)
• src/sas/sasgui/perspectives/fitting/pagestate.py (modified) (9 diffs)

docs/sphinx-docs/source/user/sasgui/perspectives/invariant/invariant_help.rst

@@ -4 +4 @@
 .. by S King, ISIS, during SasView CodeCamp-III in Feb 2015.
 
-Invariant Calculation Perspective
-=================================
+Invariant Calculation
+=====================
 
 Description
@@ -19 +19 @@
 .. image:: image001.gif
 
-where *g = Q* for pinhole geometry (SAS) and *g = Qv* (the slit height) for  
+where *g = q* for pinhole geometry (SAS) and *g = q*\ :sub:`v` (the slit height) for  
 slit geometry (USAS).
 
@@ -45 +45 @@
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
 
-Using the perspective
----------------------
+Using invariant analysis
+------------------------
 
 1) Select *Invariant* from the *Analysis* menu on the SasView toolbar.
@@ -53 +53 @@
 
 3) Select a dataset and use the *Send To* button on the *Data Explorer* to load 
-   the dataset into the *Invariant* perspective.
+   the dataset into the *Invariant* panel.
 
-4) Use the *Customised Input* boxes on the *Invariant* perspective to subtract 
+4) Use the *Customised Input* boxes on the *Invariant* panel to subtract 
    any background, specify the contrast (i.e. difference in SLDs - this must be 
    specified for the eventual value of Q*\  to be on an absolute scale), or to 
@@ -73 +73 @@
 
 8) If the value of Q*\  calculated with the extrapolated regions is invalid, a 
-   red warning will appear at the top of the *Invariant* perspective panel.
+   red warning will appear at the top of the *Invariant* panel.
 
    The details of the calculation are available by clicking the *Details* 

docs/sphinx-docs/source/user/user.rst

@@ -14 +14 @@
          
    Working with SasView <working>
+
+   Computations with GPU <gpu_computations>

sasview/local_config.py

@@ -82 +82 @@
 _corner_image = os.path.join(icon_path, "angles_flat.png")
 _welcome_image = os.path.join(icon_path, "SVwelcome.png")
-_copyright = "(c) 2009 - 2013, UTK, UMD, NIST, ORNL, ISIS, ESS and ILL"
+_copyright = "(c) 2009 - 2016, UTK, UMD, NIST, ORNL, ISIS, ESS and ILL"
 
 

sasview/setup_exe.py

@@ -165 +165 @@
         self.version = local_config.__version__
         self.company_name = "SasView.org"
-        self.copyright = "copyright 2009 - 2013"
+        self.copyright = "copyright 2009 - 2016"
         self.name = "SasView"
         

src/sas/sasgui/guiframe/utils.py

@@ -46 +46 @@
     return flag
 
-    
+
+def check_int(item):
+    """
+    :param item: txtcrtl containing a value
+    """
+    flag = True
+    try:
+        mini = int(item.GetValue())
+        item.SetBackgroundColour(wx.WHITE)
+        item.Refresh()
+    except:
+        flag = False
+        item.SetBackgroundColour("pink")
+        item.Refresh()
+    return flag
+
+
 class PanelMenu(wx.Menu):
     """

src/sas/sasgui/perspectives/fitting/basepage.py

@@ -17 +17 @@
 from wx.lib.scrolledpanel import ScrolledPanel
 
-import sasmodels.sasview_model
+from sasmodels.weights import MODELS as POLYDISPERSITY_MODELS
+
 from sas.sasgui.guiframe.panel_base import PanelBase
-from sas.sasgui.guiframe.utils import format_number, check_float, IdList
+from sas.sasgui.guiframe.utils import format_number, check_float, IdList, check_int
 from sas.sasgui.guiframe.events import PanelOnFocusEvent
 from sas.sasgui.guiframe.events import StatusEvent
@@ -626 +627 @@
         self.disp_help_bt.Bind(wx.EVT_BUTTON, self.on_pd_help_clicked,
                                id=self.disp_help_bt.GetId())
-        self.disp_help_bt.SetToolTipString("Helps for Polydispersion.")
+        self.disp_help_bt.SetToolTipString("Help for polydispersion.")
 
         self.Bind(wx.EVT_RADIOBUTTON, self._set_dipers_Param,
@@ -932 +933 @@
         if len(self._disp_obj_dict) > 0:
             for k, v in self._disp_obj_dict.iteritems():
-                self.state._disp_obj_dict[k] = v
+                self.state._disp_obj_dict[k] = v.type
 
             self.state.values = copy.deepcopy(self.values)
@@ -1009 +1010 @@
             if len(self._disp_obj_dict) > 0:
                 for k, v in self._disp_obj_dict.iteritems():
-                    self.state._disp_obj_dict[k] = v
+                    self.state._disp_obj_dict[k] = v.type
 
             self.state.values = copy.deepcopy(self.values)
@@ -1123 +1124 @@
                                                     state.disp_cb_dict[item])
                         # Create the dispersion objects
-                        from sas.models.dispersion_models import ArrayDispersion
-                        disp_model = ArrayDispersion()
+                        disp_model = POLYDISPERSITY_MODELS['array']()
                         if hasattr(state, "values") and \
                                  self.disp_cb_dict[item].GetValue() == True:
@@ -1379 +1379 @@
         self.weights = copy.deepcopy(state.weights)
 
-        for key, disp in state._disp_obj_dict.iteritems():
-            # From saved file, disp_model can not be sent in model obj.
-            # it will be sent as a string here, then converted to model object.
-            if disp.__class__.__name__ == 'str':
-                disp_model = None
-                com_str = "from sasmodels.weights "
-                com_str += "import %s as disp_func \ndisp_model = disp_func()"
-                exec com_str % disp
-            else:
-                disp_model = disp
+        for key, disp_type in state._disp_obj_dict.iteritems():
+            #disp_model = disp
+            disp_model = POLYDISPERSITY_MODELS[disp_type]()
             self._disp_obj_dict[key] = disp_model
             param_name = key.split('.')[0]
@@ -2281 +2274 @@
                 continue
 
-            name = str(item[1])
-            if name.endswith(".npts") or name.endswith(".nsigmas"):
+            value_ctrl = item[2]
+            if not value_ctrl.IsEnabled():
+                # ArrayDispersion disables PD, Min, Max, Npts, Nsigs
                 continue
 
-            # Check that min, max and value are floats
-            value_ctrl, min_ctrl, max_ctrl = item[2], item[5], item[6]
-            min_str = min_ctrl.GetValue().strip()
-            max_str = max_ctrl.GetValue().strip()
+            name = item[1]
             value_str = value_ctrl.GetValue().strip()
-            validity = check_float(value_ctrl)
-            if min_str != "":
-                validity = validity and check_float(min_ctrl)
-            if max_str != "":
-                validity = validity and check_float(max_ctrl)
-            if not validity:
-                continue
-
-            # Check that min is less than max
-            low = -numpy.inf if min_str == "" else float(min_str)
-            high = numpy.inf if max_str == "" else float(max_str)
-            if high < low:
-                min_ctrl.SetBackgroundColour("pink")
-                min_ctrl.Refresh()
-                max_ctrl.SetBackgroundColour("pink")
-                max_ctrl.Refresh()
-                #msg = "Invalid fit range for %s: min must be smaller than max"%name
-                #wx.PostEvent(self._manager.parent, StatusEvent(status=msg))
-                continue
-
-            # Force value between min and max
-            value = float(value_str)
-            if value < low:
-                value = low
-                value_ctrl.SetValue(format_number(value))
-            elif value > high:
-                value = high
-                value_ctrl.SetValue(format_number(value))
+            if name.endswith(".npts"):
+                validity = check_int(value_ctrl)
+                if not validity:
+                    continue
+                value = int(value_str)
+
+            elif name.endswith(".nsigmas"):
+                validity = check_float(value_ctrl)
+                if not validity:
+                    continue
+                value = float(value_str)
+
+            else:  # value or polydispersity
+
+                # Check that min, max and value are floats
+                min_ctrl, max_ctrl = item[5], item[6]
+                min_str = min_ctrl.GetValue().strip()
+                max_str = max_ctrl.GetValue().strip()
+                validity = check_float(value_ctrl)
+                if min_str != "":
+                    validity = validity and check_float(min_ctrl)
+                if max_str != "":
+                    validity = validity and check_float(max_ctrl)
+                if not validity:
+                    continue
+
+                # Check that min is less than max
+                low = -numpy.inf if min_str == "" else float(min_str)
+                high = numpy.inf if max_str == "" else float(max_str)
+                if high < low:
+                    min_ctrl.SetBackgroundColour("pink")
+                    min_ctrl.Refresh()
+                    max_ctrl.SetBackgroundColour("pink")
+                    max_ctrl.Refresh()
+                    #msg = "Invalid fit range for %s: min must be smaller than max"%name
+                    #wx.PostEvent(self._manager.parent, StatusEvent(status=msg))
+                    continue
+
+                # Force value between min and max
+                value = float(value_str)
+                if value < low:
+                    value = low
+                    value_ctrl.SetValue(format_number(value))
+                elif value > high:
+                    value = high
+                    value_ctrl.SetValue(format_number(value))
+
+                if name not in self.model.details.keys():
+                    self.model.details[name] = ["", None, None]
+                old_low, old_high = self.model.details[name][1:3]
+                if old_low != low or old_high != high:
+                    # The configuration has changed but it won't change the
+                    # computed curve so no need to set is_modified to True
+                    #is_modified = True
+                    self.model.details[name][1:3] = low, high
 
             # Update value in model if it has changed
@@ -2323 +2341 @@
                 self.model.setParam(name, value)
                 is_modified = True
-
-            if name not in self.model.details.keys():
-                self.model.details[name] = ["", None, None]
-            old_low, old_high = self.model.details[name][1:3]
-            if old_low != low or old_high != high:
-                # The configuration has changed but it won't change the
-                # computed curve so no need to set is_modified to True
-                #is_modified = True
-                self.model.details[name][1:3] = low, high
 
         return is_modified
@@ -2504 +2513 @@
                 self._disp_obj_dict[name1] = disp_model
                 self.model.set_dispersion(param_name, disp_model)
-                self.state._disp_obj_dict[name1] = disp_model
+                self.state._disp_obj_dict[name1] = disp_model.type
 
                 value1 = str(format_number(self.model.getParam(name1), True))
@@ -2527 +2536 @@
                         item[0].Enable()
                         item[2].Enable()
+                        item[3].Show(True)
+                        item[4].Show(True)
                         item[5].Enable()
                         item[6].Enable()
@@ -2619 +2630 @@
         self._disp_obj_dict[name] = disp
         self.model.set_dispersion(name.split('.')[0], disp)
-        self.state._disp_obj_dict[name] = disp
+        self.state._disp_obj_dict[name] = disp.type
         self.values[name] = values
         self.weights[name] = weights
@@ -2687 +2698 @@
         :param disp_function: dispersion distr. function
         """
-        # List of the poly_model name in the combobox
-        list = ["RectangleDispersion", "ArrayDispersion",
-                "LogNormalDispersion", "GaussianDispersion",
-                "SchulzDispersion"]
-
         # Find the selection
-        try:
-            selection = list.index(disp_func.__class__.__name__)
-            return selection
-        except:
-            return 3
+        if disp_func is not None:
+            try:
+                return POLYDISPERSITY_MODELS.values().index(disp_func.__class__)
+            except ValueError:
+                pass  # Fall through to default class
+        return POLYDISPERSITY_MODELS.keys().index('gaussian')
 
     def on_reset_clicked(self, event):
@@ -3284 +3291 @@
                     pd = content[name][1]
                     if name.count('.') > 0:
+                        # If this is parameter.width, then pd may be a floating
+                        # point value or it may be an array distribution.
+                        # Nothing to do for parameter.npts or parameter.nsigmas.
                         try:
                             float(pd)
-                        except:
+                            if name.endswith('.npts'):
+                                pd = int(pd)
+                        except Exception:
                             #continue
                             if not pd and pd != '':
@@ -3294 +3306 @@
                         # Only array func has pd == '' case.
                         item[2].Enable(False)
+                    else:
+                        item[2].Enable(True)
                     if item[2].__class__.__name__ == "ComboBox":
                         if content[name][1] in self.model.fun_list:
@@ -3320 +3334 @@
                         pd = value[0]
                         if name.count('.') > 0:
+                            # If this is parameter.width, then pd may be a floating
+                            # point value or it may be an array distribution.
+                            # Nothing to do for parameter.npts or parameter.nsigmas.
                             try:
                                 pd = float(pd)
+                                if name.endswith('.npts'):
+                                    pd = int(pd)
                             except:
                                 #continue
@@ -3330 +3349 @@
                             # Only array func has pd == '' case.
                             item[2].Enable(False)
+                        else:
+                            item[2].Enable(True)
                         if item[2].__class__.__name__ == "ComboBox":
                             if value[0] in self.model.fun_list:
@@ -3349 +3370 @@
         Helps get paste for poly function
 
-        :param item: Gui param items
-        :param value: the values for parameter ctrols
-        """
-        is_array = False
-        if len(value[1]) > 0:
-            # Only for dispersion func.s
-            try:
-                item[7].SetValue(value[1])
-                selection = item[7].GetCurrentSelection()
-                name = item[7].Name
-                param_name = name.split('.')[0]
-                dispersity = item[7].GetClientData(selection)
-                disp_model = dispersity()
-                # Only for array disp
-                try:
-                    pd_vals = numpy.array(value[2])
-                    pd_weights = numpy.array(value[3])
-                    if len(pd_vals) > 0 and len(pd_vals) > 0:
-                        if len(pd_vals) == len(pd_weights):
-                            self._set_disp_array_cb(item=item)
-                            self._set_array_disp_model(name=name,
-                                                       disp=disp_model,
-                                                       values=pd_vals,
-                                                       weights=pd_weights)
-                            is_array = True
-                except Exception:
-                    logging.error(traceback.format_exc())
-                if not is_array:
-                    self._disp_obj_dict[name] = disp_model
-                    self.model.set_dispersion(name,
-                                              disp_model)
-                    self.state._disp_obj_dict[name] = \
-                                              disp_model
-                    self.model.set_dispersion(param_name, disp_model)
-                    self.state.values = self.values
-                    self.state.weights = self.weights
-                    self.model._persistency_dict[param_name] = \
-                                            [self.state.values,
-                                             self.state.weights]
-
-            except Exception:
-                logging.error(traceback.format_exc())
-                print "Error in BasePage._paste_poly_help: %s" % \
-                                        sys.exc_info()[1]
-
-    def _set_disp_array_cb(self, item):
+        *item* is the parameter name
+
+        *value* depends on which parameter is being processed, and whether it
+        has array polydispersity.
+
+        For parameters without array polydispersity:
+
+            parameter => ['FLOAT', '']
+            parameter.width => ['FLOAT', 'DISTRIBUTION', '']
+            parameter.npts => ['FLOAT', '']
+            parameter.nsigmas => ['FLOAT', '']
+
+        For parameters with array polydispersity:
+
+            parameter => ['FLOAT', '']
+            parameter.width => ['FILENAME', 'array', [x1, ...], [w1, ...]]
+            parameter.npts => ['FLOAT', '']
+            parameter.nsigmas => ['FLOAT', '']
+        """
+        # Do nothing if not setting polydispersity
+        if len(value[1]) == 0:
+            return
+
+        try:
+            name = item[7].Name
+            param_name = name.split('.')[0]
+            item[7].SetValue(value[1])
+            selection = item[7].GetCurrentSelection()
+            dispersity = item[7].GetClientData(selection)
+            disp_model = dispersity()
+
+            if value[1] == 'array':
+                pd_vals = numpy.array(value[2])
+                pd_weights = numpy.array(value[3])
+                if len(pd_vals) == 0 or len(pd_vals) != len(pd_weights):
+                    msg = ("bad array distribution parameters for %s"
+                           % param_name)
+                    raise ValueError(msg)
+                self._set_disp_cb(True, item=item)
+                self._set_array_disp_model(name=name,
+                                           disp=disp_model,
+                                           values=pd_vals,
+                                           weights=pd_weights)
+            else:
+                self._set_disp_cb(False, item=item)
+                self._disp_obj_dict[name] = disp_model
+                self.model.set_dispersion(param_name, disp_model)
+                self.state._disp_obj_dict[name] = disp_model.type
+                # TODO: It's not an array, why update values and weights?
+                self.model._persistency_dict[param_name] = \
+                    [self.values, self.weights]
+                self.state.values = self.values
+                self.state.weights = self.weights
+
+        except Exception:
+            logging.error(traceback.format_exc())
+            print "Error in BasePage._paste_poly_help: %s" % \
+                                    sys.exc_info()[1]
+
+    def _set_disp_cb(self, isarray, item):
         """
         Set cb for array disp
         """
-        item[0].SetValue(False)
-        item[0].Enable(False)
-        item[2].Enable(False)
-        item[3].Show(False)
-        item[4].Show(False)
-        item[5].SetValue('')
-        item[5].Enable(False)
-        item[6].SetValue('')
-        item[6].Enable(False)
+        if isarray:
+            item[0].SetValue(False)
+            item[0].Enable(False)
+            item[2].Enable(False)
+            item[3].Show(False)
+            item[4].Show(False)
+            item[5].SetValue('')
+            item[5].Enable(False)
+            item[6].SetValue('')
+            item[6].Enable(False)
+        else:
+            item[0].Enable()
+            item[2].Enable()
+            item[3].Show(True)
+            item[4].Show(True)
+            item[5].Enable()
+            item[6].Enable()
 
     def update_pinhole_smear(self):

src/sas/sasgui/perspectives/fitting/fitpage.py

@@ -10 +10 @@
 import math
 import time
+import traceback
 
 from sasmodels.weights import MODELS as POLYDISPERSITY_MODELS
@@ -2058 +2059 @@
             msg = "Error: This model state has missing or outdated "
             msg += "information.\n"
-            msg += "%s" % (sys.exc_value)
+            msg += traceback.format_exc()
             wx.PostEvent(self._manager.parent,
                          StatusEvent(status=msg, info="error"))

src/sas/sasgui/perspectives/fitting/media/plugin.rst

@@ -1 +1 @@
 .. _Writing_a_Plugin:
 
-Writing a Plugin
-================
-
-Users can write their own models and save it to the the SasView
+Writing a Plugin Model
+======================
+
+Overview
+^^^^^^^^
+
+You can write your own model and save it to the the SasView
 *plugin_models* folder
 
-  *C:\\Users\\[username]\\.sasview\\plugin_models* - (on Windows)
+  *C:\\Users\\[username]\\.sasview\\plugin_models* (on Windows)
 
 The next time SasView is started it will compile the plugin and add
-it to the list of *Customized Models*.  It is recommended that an
+it to the list of *Customized Models* in a FitPage.  It is recommended that an
 existing model be used as a template.
-
-This page was originally written by our MOST experienced developers,
-but has subsequently been edited by our LEAST experienced developer who felt
-some instructions could have been clearer, and learnt one or two things that
-were missing altogether! But they succeeded in converting a model that passed
-testing, so there is no reason why you should not be able to do the same.
 
 SasView has three ways of writing models:
@@ -29 +26 @@
   `cylinder.c <https://github.com/SasView/sasmodels/blob/master/sasmodels/models/cylinder.c>`_
 
-Many models are available for download from the
-`model marketplace <http://marketplace.sasview.org/>`_.
-
-The builtin modules are available in the *sasmodels-data/models* subdirectory
-of the sasview distribution.  On Windows, this will be something like
-*C:\Program Files (x86)\SasView\models*.  On MacOSX, these will be within
+The built-in modules are available in the *sasmodels-data\\models* subdirectory
+of your SasView installation folder.  On Windows, this will be something like
+*C:\\Program Files (x86)\\SasView\\sasmodels-data\\models*.  On Mac OSX, these will be within
 the application bundle as
 */Applications/SasView 4.0.app/Contents/Resources/sasmodels-data/models*.
 
+Other models are available for download from our
+`Model Marketplace <http://marketplace.sasview.org/>`_. You can contribute your own models to the 
+Marketplace aswell.
+
 Create New Model Files
 ^^^^^^^^^^^^^^^^^^^^^^
 
-In the *~/.sasview/plugin_models* directory, copy the appropriate files
+In the *~\\.sasview\\plugin_models* directory, copy the appropriate files
 (using the examples above as templates) to mymodel.py (and mymodel.c, etc)
 as required, where "mymodel" is the name for the model you are creating.
@@ -47 +45 @@
 *Please follow these naming rules:*
 
-- No capitalization and thus no CamelCase.
-- If necessary use underscore to separate (i.e. barbell not BarBell or
+- No capitalization and thus no CamelCase
+- If necessary use underscore to separate words (i.e. barbell not BarBell or
   broad_peak not BroadPeak)
-- Don't include “model” in the name (i.e. barbell not BarBellModel)
+- Do not include “model” in the name (i.e. barbell not BarBellModel)
 
 
 Edit New Model Files
 ^^^^^^^^^^^^^^^^^^^^
+
+Model Contents
+..............
 
 The model interface definition is in the .py file.  This file contains:
@@ -65 +66 @@
     - without spaces (use underscores to separate words instead)
     - without any capitalization or CamelCase
-    - without incorporating the word 'model'
+    - without incorporating the word "model"
     - examples: *barbell* **not** *BarBell*; *broad_peak* **not** *BroadPeak*; 
       *barbell* **not** *BarBellModel*
@@ -72 +73 @@
    - this is the **title** string in the *.py* file
    - this is a one or two line description of the model, which will appear
-     at the start of the model documentation and as a tooltip in the GUI
+     at the start of the model documentation and as a tooltip in the SasView GUI
 
 - a **short discription**:
    - this is the **description** string in the *.py* file
    - this is a medium length description which appears when you click
-     *Description* on the model fit page
+     *Description* on the model FitPage
 
 - a **parameter table**:
@@ -85 +86 @@
    - this is ReStructuredText enclosed between the r""" and """ delimiters
      at the top of the *.py* file
+   - what you write here is abstracted into the SasView help documentation
+   - this is what other users will refer to when they want to know what your model does; 
+     so please be helpful!
 
 - a **definition** of the model:
@@ -97 +101 @@
 
 - a **plot** of the function, with a **figure caption**:
-   - this is automatically generated from the default parameters
+   - this is automatically generated from your default parameters
 
 - at least one **reference**:
@@ -107 +111 @@
    - the *.py* file should also contain a comment identifying *who*
      converted/created the model file
+
+Models that do not conform to these requirements will *never* be incorporated 
+into the built-in library.
 
 More complete documentation for the sasmodels package can be found at
@@ -170 +177 @@
 
 The model should include a **formula** written using LaTeX markup.
-The above example uses the *math* command to make a displayed equation.  You
+The example above uses the *math* command to make a displayed equation.  You
 can also use *\$formula\$* for an inline formula. This is handy for defining
 the relationship between the model parameters and formula variables, such
 as the phrase "\$r\$ is the radius" used above.  The live demo MathJax
 page `<http://www.mathjax.org/>`_ is handy for checking that the equations
-will look like you expect.
+will look like you intend.
 
 Math layout uses the `amsmath <http://www.ams.org/publications/authors/tex/amslatex>`_
@@ -207 +214 @@
 
     name = "sphere"  # optional: defaults to the filename without .py
+
     title = "Spheres with uniform scattering length density"
+
     description = """\
     P(q)=(scale/V)*[3V(sld-sld_solvent)*(sin(qr)-qr cos(qr))
@@ -216 +225 @@
         sld_solvent: the SLD of the solvent
     """
+
     category = "shape:sphere"
+
     single = True   # optional: defaults to True
+
     opencl = False  # optional: defaults to False
+
     structure_factor = False  # optional: defaults to False
 
@@ -229 +242 @@
 **title = "short description"** is short description of the model which
 is included after the model name in the automatically generated documentation.
-The title can also be used for a tooltip, for example.
+The title can also be used for a tooltip.
 
 **description = """doc string"""** is a longer description of the model. It
-shows up when you press the "Description" button of the SasView fit page.
+shows up when you press the "Description" button of the SasView FitPage.
 It should give a brief description of the equation and the parameters
 without the need to read the entire model documentation. The triple quotes
 allow you to write the description over multiple lines. Keep the lines
 short since the GUI will wrap each one separately if they are too long.
-**Make sure the parameter names in the description match the model definition.**
+**Make sure the parameter names in the description match the model definition!**
 
 **category = "shape:sphere"** defines where the model will appear in the
 model documentation.  In this example, the model will appear alphabetically
-in the list of spheroid models.
+in the list of spheroid models in the *Shape* category.
 
 **single = True** indicates that the model can be run using single
@@ -275 +288 @@
         ["radius",      "Ang",        50, [0, inf],    "volume", "Sphere radius"],
     ]
-    # pylint: disable=bad-whitespace, line-too-long
+    # pylint: enable=bad-whitespace, line-too-long
 
 **parameters = [["name", "units", default, [min,max], "type", "tooltip"],...]**
-defines the parameters form the model.
-
-- **the order of the parameters in the definition will be the order of
-  the parameters in the user interface and the order of the parameters
-  in Iq(), Iqxy() and form_volume().**
-
-- **scale and background parameters are implicit to all models, so
-  they do not need to be included in the parameter table**
-
-- **"name"** is the name of the parameter shown on the fit screen
+defines the parameters that form the model.
+
+**Note: The order of the parameters in the definition will be the order of the 
+parameters in the user interface and the order of the parameters in Iq(), 
+Iqxy() and form_volume(). And** *scale* **and** *background* **parameters are 
+implicit to all models, so they do not need to be included in the parameter table.**
+
+- **"name"** is the name of the parameter shown on the FitPage.
 
   - parameter names should follow the mathematical convention; e.g.,
-    *radius_core* not *core_radius*, or *sld_solvent* not *solvent_sld*
+    *radius_core* not *core_radius*, or *sld_solvent* not *solvent_sld*.
+
   - model parameter names should be consistent between different models,
     so *sld_solvent*, for example, should have exactly the same name
-    in every model
+    in every model.
+
   - to see all the parameter names currently in use, type the following in the
     python shell/editor under the Tools menu::
@@ -301 +314 @@
 
     *re-use* as many as possible!!!
+
   - use "name[n]" for multiplicity parameters, where *n* is the name of
     the parameter defining the number of shells/layers/segments, etc.
@@ -306 +320 @@
 - **"units"** are displayed along with the parameter name
 
-  - every parameter should have units; use "None" if there are no units
+  - every parameter should have units; use "None" if there are no units.
+
   - **sld's should be given in units of 1e-6/Ang^2, and not simply
     1/Ang^2 to be consistent with the builtin models.  Adjust your formulas
     appropriately.**
+
   - fancy units markup is available for some units, including::
 
@@ -322 +338 @@
       and using negative exponents instead of the / operator, though
       the unit name should use the / operator for consistency.
-    - post a message to the sasview developers list with the changes
-
-- **default** is the initial value for the parameter
+    - please post a message to the SasView developers mailing list with your changes.
+
+- **default** is the initial value for the parameter.
 
   - **the parameter default values are used to auto-generate a plot of
     the model function in the documentation.**
 
-- **[min, max]** are the lower and upper limits on the parameter
-
-  - lower and upper limits can be any number, or -inf or inf.
+- **[min, max]** are the lower and upper limits on the parameter.
+
+  - lower and upper limits can be any number, or *-inf* or *inf*.
+
   - the limits will show up as the default limits for the fit making it easy,
     for example, to force the radius to always be greater than zero.
 
-- **"type"** can be one of: "", "sld", "volume", or "orientation"
+- **"type"** can be one of: "", "sld", "volume", or "orientation".
 
   - "sld" parameters can have magnetic moments when fitting magnetic models;
     depending on the spin polarization of the beam and the $q$ value being
     examined, the effective sld for that material will be used to compute the
-    scattered intensity
+    scattered intensity.
+
   - "volume" parameters are passed to Iq(), Iqxy(), and form_volume(), and
     have polydispersity loops generated automatically.
+
   - "orientation" parameters are only passed to Iqxy(), and have angular
     dispersion.
@@ -380 +399 @@
 .............
 
-For pure python models, define the Iq funtion::
+For pure python models, define the *Iq* function::
 
       import numpy as np
@@ -391 +410 @@
 The parameters *par1, par2, ...* are the list of non-orientation parameters
 to the model in the order that they appear in the parameter table.
-**Note that the autogenerated model file uses *x* rather than *q*.**
+**Note that the autogenerated model file uses** *x* **rather than** *q*.
 
 The *.py* file should import trigonometric and exponential functions from
-numpy rather that from math.  This lets us evaluate the model for the whole
+numpy rather than from math.  This lets us evaluate the model for the whole
 range of $q$ values at once rather than looping over each $q$ separately in
 python.  With $q$ as a vector, you cannot use if statements, but must instead
@@ -430 +449 @@
 list includes the *volume* parameters in order.  This is used for a weighted
 volume normalization so that scattering is on an absolute scale.  If
-*form_volume* is not definded, then the default *form_volume = 1.0* will be
+*form_volume* is not defined, then the default *form_volume = 1.0* will be
 used.
 
@@ -436 +455 @@
 .................
 
-Like pure python models, inline C models need define an *Iq* function::
+Like pure python models, inline C models need to define an *Iq* function::
 
     Iq = """
@@ -516 +535 @@
 These functions have been tuned to be fast and numerically stable down
 to $q=0$ even in single precision.  In some cases they work around bugs
-which appear on some platforms but not others.
+which appear on some platforms but not others. So use them where needed!!!
 
 Models are defined using double precision declarations for the
 parameters and return values.  Declarations and constants will be converted
 to float or long double depending on the precision requested.
+
 **Floating point constants must include the decimal point.**  This allows us
 to convert values such as 1.0 (double precision) to 1.0f (single precision)
@@ -540 +560 @@
 
 A value defined as SAS_DOUBLE will stay double precision; this should
-not be used since some graphics card don't support double precision.
+not be used since some graphics cards do not support double precision.
 
 
@@ -557 +577 @@
 Form Factors
 ............
-
-::
-
-    def ER(radius, thickness):
-        """Effective radius of a core-shell sphere."""
-        return radius + thickness
 
 Away from the dilute limit you can estimate scattering including
@@ -572 +586 @@
 form averaged over all the polydispersity values.
 
-Consider the *core_shell_sphere*, which has a simple effective radius
+::
+
+    def ER(radius, thickness):
+        """Effective radius of a core-shell sphere."""
+        return radius + thickness
+
+Now consider the *core_shell_sphere*, which has a simple effective radius
 equal to the radius of the core plus the thickness of the shell, as
 shown above. Given polydispersity over *(r1, r2, ..., rm)* in radius and
@@ -597 +617 @@
 one return value for each point in the mesh grid.
 
-*NOTE: we may be removing or modifying this feature soon.*  As of this
-writing, core-shell sphere returns (1., 1.) for *VR*, giving a volume
-ratio of 1.0.
+*NOTE: we may be removing or modifying this feature soon. As of the 
+time of writing, core-shell sphere returns (1., 1.) for VR, giving a volume
+ratio of 1.0.*
 
 Unit Tests
@@ -640 +660 @@
 ^^^^^^^^^^^^^^^^^^^
 
+Installed SasView
+.................
+
 If you are editing your model from the SasView GUI, you can test it
-by selecting *Run -> Compile* from the *Model Editor* menu bar. An
+by selecting *Run > Compile* from the *Model Editor* menu bar. An
 *Info* box will appear with the results of the compilation and a
 check that the model runs.
 
+
+Built SasView
+.............
+
 If the model compiles and runs, you can next run the unit tests that
-you have added using the **test=** values. Switch to the *Shell* tab
+you have added using the **test =** values. Switch to the *Shell* tab
 and type the following::
 
@@ -686 +713 @@
 For the random models,
 
-- sld will be in(-0.5,10.5),
-- angles (theta, phi, psi) will be in (-180,180),
-- angular dispersion will be in (0,45),
-- polydispersity will be in (0,1)
-- other values will be in (0, 2*v) where v is the value of the parameter in demo.
-
-Dispersion parameters n, sigma and type will be unchanged from demo so that
+- *sld* will be in the range (-0.5,10.5),
+- angles (*theta, phi, psi*) will be in the range (-180,180),
+- angular dispersion will be in the range (0,45),
+- polydispersity will be in the range (0,1)
+- other values will be in the range (0, 2\ *v*), where *v* is the value of the parameter in demo.
+
+Dispersion parameters *n*\, *sigma* and *type* will be unchanged from demo so that
 run times are predictable.
 
@@ -701 +728 @@
 
 
-Clean Lint
-^^^^^^^^^^
-
-**NB: For now we are not providing pylint with SasView; unless you have a
-SasView development environment available, you can ignore this section.**
+Clean Lint - (Developer Version Only)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+**NB: For now we are not providing pylint with the installer version of SasView; 
+so unless you have a SasView build environment available, you can ignore this section!**
 
 Run the lint check with::
@@ -717 +744 @@
 for standard model functions *Iq*, *Iqxy*, etc.
 
-We will have delinting sessions at the SasView code camps, where we can
+We will have delinting sessions at the SasView Code Camps, where we can
 decide on standards for model files, parameter names, etc.
 
-For now, you can tell pylint to ignore things.  For example, to align you
+For now, you can tell pylint to ignore things.  For example, to align your
 parameters in blocks::
 
@@ -738 +765 @@
 Don't put in too many pylint statements, though, since they make the code ugly.
 
-Check The Docs
-^^^^^^^^^^^^^^
+Check The Docs - (Developer Version Only)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 You can get a rough idea of how the documentation will look using the
@@ -756 +783 @@
 - `amsmath <http://www.ams.org/publications/authors/tex/amslatex>`_
 
-Finally
-^^^^^^^
+There is also a neat online WYSIWYG ReStructuredText editor at http://rst.ninjs.org\ .
+
+Share Your Model!
+^^^^^^^^^^^^^^^^^
 
 Once compare and the unit test(s) pass properly and everything is done,
 consider adding your model to the
-`model marketplace <http://marketplace.sasview.org/>`_.
-
+`Model Marketplace <http://marketplace.sasview.org/>`_ so that others may use it!

src/sas/sasgui/perspectives/fitting/pagestate.py

@@ -24 +24 @@
 from xml.dom.minidom import parseString
 from lxml import etree
+
+import sasmodels.weights
 
 import sas.sascalc.dataloader
@@ -474 +476 @@
                 value = content[1]
             except Exception:
-                logging.error(traceback.format_exc())
+                msg = "Report string expected 'name: value' but got %r"%line
+                logging.error(msg)
             if name.count("State created"):
                 repo_time = "" + value
@@ -516 +519 @@
                         title_name = HEADER % title
                 except Exception:
-                    logging.error(traceback.format_exc())
+                    msg = "While parsing 'data: ...'\n"
+                    logging.error(msg + traceback.format_exc())
             if name == "model name ":
                 try:
@@ -531 +535 @@
                     q_range = CENTRE % q_name
                 except Exception:
-                    logging.error(traceback.format_exc())
+                    msg = "While parsing 'Plotting Range: ...'\n"
+                    logging.error(msg + traceback.format_exc())
         paramval = ""
         for lines in param_string.split(":"):
@@ -711 +716 @@
         # For self.values ={ disp_param_name: [vals,...],...}
         # and for self.weights ={ disp_param_name: [weights,...],...}
-        value_list = {}
         for item in LIST_OF_MODEL_ATTRIBUTES:
             element = newdoc.createElement(item[0])
@@ -725 +729 @@
 
         # Create doc for the dictionary of self._disp_obj_dic
-        for item in DISPERSION_LIST:
-            element = newdoc.createElement(item[0])
-            value_list = getattr(self, item[1])
-            for key, val in value_list.iteritems():
-                value = repr(val)
+        for tagname, varname, tagtype in DISPERSION_LIST:
+            element = newdoc.createElement(tagname)
+            value_list = getattr(self, varname)
+            for key, value in value_list.iteritems():
                 sub_element = newdoc.createElement(key)
                 sub_element.setAttribute('name', str(key))
@@ -847 +850 @@
                 # Recover _disp_obj_dict from xml file
                 self._disp_obj_dict = {}
-                for item in DISPERSION_LIST:
-                    # Get node
-                    node = get_content("ns:%s" % item[0], entry)
+                for tagname, varname, tagtype in DISPERSION_LIST:
+                    node = get_content("ns:%s" % tagname, entry)
                     for attr in node:
-                        name = str(attr.get('name'))
-                        val = attr.get('value')
-                        value = val.split(" instance")[0]
-                        disp_name = value.split("<")[1]
-                        try:
-                            # Try to recover disp_model object from strings
-                            com = "from sas.models.dispersion_models "
-                            com += "import %s as disp"
-                            com_name = disp_name.split(".")[3]
-                            exec com % com_name
-                            disp_model = disp()
-                            attribute = getattr(self, item[1])
-                            attribute[name] = com_name
-                        except Exception:
-                            logging.error(traceback.format_exc())
+                        parameter = str(attr.get('name'))
+                        value = attr.get('value')
+                        if value.startswith("<"):
+                            try:
+                                # <path.to.NamedDistribution object/instance...>
+                                cls_name = value[1:].split()[0].split('.')[-1]
+                                cls = getattr(sasmodels.weights, cls_name)
+                                value = cls.type
+                            except Exception:
+                                logging.error("unable to load distribution %r for %s"
+                                              % (value, parameter))
+                                continue
+                        _disp_obj_dict = getattr(self, varname)
+                        _disp_obj_dict[parameter] = value
 
                 # get self.values and self.weights dic. if exists
-                for item in LIST_OF_MODEL_ATTRIBUTES:
-                    node = get_content("ns:%s" % item[0], entry)
+                for tagname, varname in LIST_OF_MODEL_ATTRIBUTES:
+                    node = get_content("ns:%s" % tagname, entry)
                     dic = {}
                     value_list = []
                     for par in node:
                         name = par.get('name')
-                        values = par.text.split('\n')
+                        values = par.text.split()
                         # Get lines only with numbers
                         for line in values:
@@ -882 +883 @@
                             except Exception:
                                 # pass if line is empty (it happens)
-                                logging.error(traceback.format_exc())
+                                msg = ("Error reading %r from %s %s\n"
+                                       % (line, tagname, name))
+                                logging.error(msg + traceback.format_exc())
                         dic[name] = numpy.array(value_list)
-                    setattr(self, item[1], dic)
+                    setattr(self, varname, dic)
 
     def set_plot_state(self, figs, canvases):
@@ -1231 +1234 @@
 
         except:
-            logging.info("XML document does not contain fitting information.\n %s" % sys.exc_value)
+            logging.info("XML document does not contain fitting information.\n"
+                         + traceback.format_exc())
 
         return state