Changes in / [ae69c690:6d62b7f] in sasview

Files:

• sasview/images/dls_logo.png (added)
• sasview/sasview.py (modified) (1 diff)
• src/sas/sasgui/guiframe/images/angles.png (deleted)
• src/sas/sasgui/guiframe/images/angles_flat.png (deleted)
• src/sas/sasgui/guiframe/images/ansto_logo.png (deleted)
• src/sas/sasgui/guiframe/images/danse_logo.png (deleted)
• src/sas/sasgui/guiframe/images/dls_logo.png (deleted)
• src/sas/sasgui/guiframe/images/ess_logo.png (deleted)
• src/sas/sasgui/guiframe/images/ill_logo.png (deleted)
• src/sas/sasgui/guiframe/images/isis_logo.png (deleted)
• src/sas/sasgui/guiframe/images/nist_logo.png (deleted)
• src/sas/sasgui/guiframe/images/nsf_logo.png (deleted)
• src/sas/sasgui/guiframe/images/ornl_logo.png (deleted)
• src/sas/sasgui/guiframe/images/sns_logo.png (deleted)
• src/sas/sasgui/guiframe/images/tudelft_logo.png (deleted)
• src/sas/sasgui/guiframe/images/umd_logo.png (deleted)
• src/sas/sasgui/guiframe/images/utlogo.gif (deleted)
• src/sas/sasgui/perspectives/calculator/model_editor.py (modified) (6 diffs)
• src/sas/sasgui/perspectives/fitting/media/fitting_help.rst (modified) (2 diffs)
• src/sas/sasgui/perspectives/fitting/media/plugin.rst (modified) (1 diff)

sasview/sasview.py

@@ -74 +74 @@
 PLUGIN_MODEL_DIR = 'plugin_models'
 APP_NAME = 'SasView'
+
+# Set SAS_MODELPATH so sasmodels can find our custom models
+os.environ['SAS_MODELPATH'] = os.path.join(sasdir, PLUGIN_MODEL_DIR)
 
 from matplotlib import backend_bases

src/sas/sasgui/perspectives/calculator/model_editor.py

@@ -106 +106 @@
         self.model2_string = "cylinder"
         self.name = 'Sum' + M_NAME
-        self.factor = 'scale_factor'
         self._notes = ''
         self._operator = '+'
@@ -133 +132 @@
         self.model2_name = str(self.model2.GetValue())
         self.good_name = True
-        self.fill_oprator_combox()
+        self.fill_operator_combox()
 
     def _layout_name(self):
@@ -491 +490 @@
         a sum or multiply model then create the appropriate string
         """
-
         name = ''
-
         if operator == '*':
             name = 'Multi'
-            factor = 'BackGround'
-            f_oper = '+'
+            factor = 'background'
         else:
             name = 'Sum'
             factor = 'scale_factor'
-            f_oper = '*'
-
-        self.factor = factor
+
         self._operator = operator
-        self.explanation = "  Plugin Model = %s %s (model1 %s model2)\n" % \
-                           (self.factor, f_oper, self._operator)
+        self.explanation = ("  Plugin_model = scale_factor * (model_1 {} "
+            "model_2) + background").format(operator)
         self.explanationctr.SetLabel(self.explanation)
         self.name = name + M_NAME
 
 
-    def fill_oprator_combox(self):
+    def fill_operator_combox(self):
         """
         fill the current combobox with the operator
@@ -527 +521 @@
         return [self.model1_name, self.model2_name]
 
-    def write_string(self, fname, name1, name2):
+    def write_string(self, fname, model1_name, model2_name):
         """
         Write and Save file
@@ -533 +527 @@
         self.fname = fname
         description = self.desc_tcl.GetValue().lstrip().rstrip()
-        if description == '':
-            description = name1 + self._operator + name2
-        text = self._operator_choice.GetValue()
-        if text.count('+') > 0:
-            factor = 'scale_factor'
-            f_oper = '*'
-            default_val = '1.0'
-        else:
-            factor = 'BackGround'
-            f_oper = '+'
-            default_val = '0.0'
-        path = self.fname
-        try:
-            out_f = open(path, 'w')
-        except:
-            raise
-        lines = SUM_TEMPLATE.split('\n')
-        for line in lines:
-            try:
-                if line.count("scale_factor"):
-                    line = line.replace('scale_factor', factor)
-                    #print "scale_factor", line
-                if line.count("= %s"):
-                    out_f.write(line % (default_val) + "\n")
-                elif line.count("import Model as P1"):
-                    if self.is_p1_custom:
-                        line = line.replace('#', '')
-                        out_f.write(line % name1 + "\n")
-                    else:
-                        out_f.write(line + "\n")
-                elif line.count("import %s as P1"):
-                    if not self.is_p1_custom:
-                        line = line.replace('#', '')
-                        out_f.write(line % (name1) + "\n")
-                    else:
-                        out_f.write(line + "\n")
-                elif line.count("import Model as P2"):
-                    if self.is_p2_custom:
-                        line = line.replace('#', '')
-                        out_f.write(line % name2 + "\n")
-                    else:
-                        out_f.write(line + "\n")
-                elif line.count("import %s as P2"):
-                    if not self.is_p2_custom:
-                        line = line.replace('#', '')
-                        out_f.write(line % (name2) + "\n")
-                    else:
-                        out_f.write(line + "\n")
-                elif line.count("P1 = find_model"):
-                    out_f.write(line % (name1) + "\n")
-                elif line.count("P2 = find_model"):
-                    out_f.write(line % (name2) + "\n")
-
-                elif line.count("self.description = '%s'"):
-                    out_f.write(line % description + "\n")
-                #elif line.count("run") and line.count("%s"):
-                #    out_f.write(line % self._operator + "\n")
-                #elif line.count("evalDistribution") and line.count("%s"):
-                #    out_f.write(line % self._operator + "\n")
-                elif line.count("return") and line.count("%s") == 2:
-                    #print "line return", line
-                    out_f.write(line % (f_oper, self._operator) + "\n")
-                elif line.count("out2")and line.count("%s"):
-                    out_f.write(line % self._operator + "\n")
-                else:
-                    out_f.write(line + "\n")
-            except:
-                raise
-        out_f.close()
-        #else:
-        #    msg = "Name exists already."
+        desc_line = ''
+        if description.strip() != '':
+            # Sasmodels generates a description for us. If the user provides
+            # their own description, add a line to overwrite the sasmodels one
+            desc_line = "\nmodel_info.description = '{}'".format(description)
+        name = os.path.splitext(os.path.basename(self.fname))[0]
+        output = SUM_TEMPLATE.format(name=name, model1=model1_name, 
+            model2=model2_name, operator=self._operator, desc_line=desc_line)
+        with open(self.fname, 'w') as out_f:
+            out_f.write(output)
 
     def compile_file(self, path):
@@ -1278 +1211 @@
 """
 SUM_TEMPLATE = """
-# A sample of an experimental model function for Sum/Multiply(Pmodel1,Pmodel2)
-import os
-import sys
-import copy
-import collections
-
-import numpy
-
-from sas.sascalc.fit.pluginmodel import Model1DPlugin
-from sasmodels.sasview_model import find_model
-
-class Model(Model1DPlugin):
-    name = os.path.splitext(os.path.basename(__file__))[0]
-    is_multiplicity_model = False
-    def __init__(self, multiplicity=1):
-        Model1DPlugin.__init__(self, name='')
-        P1 = find_model('%s')
-        P2 = find_model('%s')
-        p_model1 = P1()
-        p_model2 = P2()
-        ## Setting  model name model description
-        self.description = '%s'
-        if self.name.rstrip().lstrip() == '':
-            self.name = self._get_name(p_model1.name, p_model2.name)
-        if self.description.rstrip().lstrip() == '':
-            self.description = p_model1.name
-            self.description += p_model2.name
-            self.fill_description(p_model1, p_model2)
-
-        ## Define parameters
-        self.params = collections.OrderedDict()
-
-        ## Parameter details [units, min, max]
-        self.details = {}
-        ## Magnetic Panrameters
-        self.magnetic_params = []
-        # non-fittable parameters
-        self.non_fittable = p_model1.non_fittable
-        self.non_fittable += p_model2.non_fittable
-
-        ##models
-        self.p_model1= p_model1
-        self.p_model2= p_model2
-
-
-        ## dispersion
-        self._set_dispersion()
-        ## Define parameters
-        self._set_params()
-        ## New parameter:scaling_factor
-        self.params['scale_factor'] = %s
-
-        ## Parameter details [units, min, max]
-        self._set_details()
-        self.details['scale_factor'] = ['', 0.0, numpy.inf]
-
-
-        #list of parameter that can be fitted
-        self._set_fixed_params()
-
-        ## parameters with orientation
-        self.orientation_params = []
-        for item in self.p_model1.orientation_params:
-            new_item = "p1_" + item
-            if not new_item in self.orientation_params:
-                self.orientation_params.append(new_item)
-
-        for item in self.p_model2.orientation_params:
-            new_item = "p2_" + item
-            if not new_item in self.orientation_params:
-                self.orientation_params.append(new_item)
-        ## magnetic params
-        self.magnetic_params = []
-        for item in self.p_model1.magnetic_params:
-            new_item = "p1_" + item
-            if not new_item in self.magnetic_params:
-                self.magnetic_params.append(new_item)
-
-        for item in self.p_model2.magnetic_params:
-            new_item = "p2_" + item
-            if not new_item in self.magnetic_params:
-                self.magnetic_params.append(new_item)
-        # get multiplicity if model provide it, else 1.
-        try:
-            multiplicity1 = p_model1.multiplicity
-            try:
-                multiplicity2 = p_model2.multiplicity
-            except:
-                multiplicity2 = 1
-        except:
-            multiplicity1 = 1
-            multiplicity2 = 1
-        ## functional multiplicity of the model
-        self.multiplicity1 = multiplicity1
-        self.multiplicity2 = multiplicity2
-        self.multiplicity_info = []
-
-    def _clone(self, obj):
-        import copy
-        obj.params     = copy.deepcopy(self.params)
-        obj.description     = copy.deepcopy(self.description)
-        obj.details    = copy.deepcopy(self.details)
-        obj.dispersion = copy.deepcopy(self.dispersion)
-        obj.p_model1  = self.p_model1.clone()
-        obj.p_model2  = self.p_model2.clone()
-        #obj = copy.deepcopy(self)
-        return obj
-
-    def _get_name(self, name1, name2):
-        p1_name = self._get_upper_name(name1)
-        if not p1_name:
-            p1_name = name1
-        name = p1_name
-        name += "_and_"
-        p2_name = self._get_upper_name(name2)
-        if not p2_name:
-            p2_name = name2
-        name += p2_name
-        return name
-
-    def _get_upper_name(self, name=None):
-        if name is None:
-            return ""
-        upper_name = ""
-        str_name = str(name)
-        for index in range(len(str_name)):
-            if str_name[index].isupper():
-                upper_name += str_name[index]
-        return upper_name
-
-    def _set_dispersion(self):
-        self.dispersion = collections.OrderedDict()
-        ##set dispersion only from p_model
-        for name , value in self.p_model1.dispersion.iteritems():
-            #if name.lower() not in self.p_model1.orientation_params:
-            new_name = "p1_" + name
-            self.dispersion[new_name]= value
-        for name , value in self.p_model2.dispersion.iteritems():
-            #if name.lower() not in self.p_model2.orientation_params:
-            new_name = "p2_" + name
-            self.dispersion[new_name]= value
-
-    def function(self, x=0.0):
-        return 0
-
-    def getProfile(self):
-        try:
-            x,y = self.p_model1.getProfile()
-        except:
-            x = None
-            y = None
-
-        return x, y
-
-    def _set_params(self):
-        for name , value in self.p_model1.params.iteritems():
-            # No 2D-supported
-            #if name not in self.p_model1.orientation_params:
-            new_name = "p1_" + name
-            self.params[new_name]= value
-
-        for name , value in self.p_model2.params.iteritems():
-            # No 2D-supported
-            #if name not in self.p_model2.orientation_params:
-            new_name = "p2_" + name
-            self.params[new_name]= value
-
-        # Set "scale" as initializing
-        self._set_scale_factor()
-
-
-    def _set_details(self):
-        for name ,detail in self.p_model1.details.iteritems():
-            new_name = "p1_" + name
-            #if new_name not in self.orientation_params:
-            self.details[new_name]= detail
-
-        for name ,detail in self.p_model2.details.iteritems():
-            new_name = "p2_" + name
-            #if new_name not in self.orientation_params:
-            self.details[new_name]= detail
-
-    def _set_scale_factor(self):
-        pass
-
-
-    def setParam(self, name, value):
-        # set param to this (p1, p2) model
-        self._setParamHelper(name, value)
-
-        ## setParam to p model
-        model_pre = ''
-        new_name = ''
-        name_split = name.split('_', 1)
-        if len(name_split) == 2:
-            model_pre = name.split('_', 1)[0]
-            new_name = name.split('_', 1)[1]
-        if model_pre == "p1":
-            if new_name in self.p_model1.getParamList():
-                self.p_model1.setParam(new_name, value)
-        elif model_pre == "p2":
-             if new_name in self.p_model2.getParamList():
-                self.p_model2.setParam(new_name, value)
-        elif name == 'scale_factor':
-            self.params['scale_factor'] = value
-        else:
-            raise ValueError, "Model does not contain parameter %s" % name
-
-    def getParam(self, name):
-        # Look for dispersion parameters
-        toks = name.split('.')
-        if len(toks)==2:
-            for item in self.dispersion.keys():
-                # 2D not supported
-                if item.lower()==toks[0].lower():
-                    for par in self.dispersion[item]:
-                        if par.lower() == toks[1].lower():
-                            return self.dispersion[item][par]
-        else:
-            # Look for standard parameter
-            for item in self.params.keys():
-                if item.lower()==name.lower():
-                    return self.params[item]
-        return
-        #raise ValueError, "Model does not contain parameter %s" % name
-
-    def _setParamHelper(self, name, value):
-        # Look for dispersion parameters
-        toks = name.split('.')
-        if len(toks)== 2:
-            for item in self.dispersion.keys():
-                if item.lower()== toks[0].lower():
-                    for par in self.dispersion[item]:
-                        if par.lower() == toks[1].lower():
-                            self.dispersion[item][par] = value
-                            return
-        else:
-            # Look for standard parameter
-            for item in self.params.keys():
-                if item.lower()== name.lower():
-                    self.params[item] = value
-                    return
-
-        raise ValueError, "Model does not contain parameter %s" % name
-
-
-    def _set_fixed_params(self):
-        self.fixed = []
-        for item in self.p_model1.fixed:
-            new_item = "p1" + item
-            self.fixed.append(new_item)
-        for item in self.p_model2.fixed:
-            new_item = "p2" + item
-            self.fixed.append(new_item)
-
-        self.fixed.sort()
-
-
-    def run(self, x = 0.0):
-        self._set_scale_factor()
-        return self.params['scale_factor'] %s \
-(self.p_model1.run(x) %s self.p_model2.run(x))
-
-    def runXY(self, x = 0.0):
-        self._set_scale_factor()
-        return self.params['scale_factor'] %s \
-(self.p_model1.runXY(x) %s self.p_model2.runXY(x))
-
-    ## Now (May27,10) directly uses the model eval function
-    ## instead of the for-loop in Base Component.
-    def evalDistribution(self, x = []):
-        self._set_scale_factor()
-        return self.params['scale_factor'] %s \
-(self.p_model1.evalDistribution(x) %s \
-self.p_model2.evalDistribution(x))
-
-    def set_dispersion(self, parameter, dispersion):
-        value= None
-        new_pre = parameter.split("_", 1)[0]
-        new_parameter = parameter.split("_", 1)[1]
-        try:
-            if new_pre == 'p1' and \
-new_parameter in self.p_model1.dispersion.keys():
-                value= self.p_model1.set_dispersion(new_parameter, dispersion)
-            if new_pre == 'p2' and \
-new_parameter in self.p_model2.dispersion.keys():
-                value= self.p_model2.set_dispersion(new_parameter, dispersion)
-            self._set_dispersion()
-            return value
-        except:
-            raise
-
-    def fill_description(self, p_model1, p_model2):
-        description = ""
-        description += "This model gives the summation or multiplication of"
-        description += "%s and %s. "% ( p_model1.name, p_model2.name )
-        self.description += description
-
-if __name__ == "__main__":
-    m1= Model()
-    #m1.setParam("p1_scale", 25)
-    #m1.setParam("p1_length", 1000)
-    #m1.setParam("p2_scale", 100)
-    #m1.setParam("p2_rg", 100)
-    out1 = m1.runXY(0.01)
-
-    m2= Model()
-    #m2.p_model1.setParam("scale", 25)
-    #m2.p_model1.setParam("length", 1000)
-    #m2.p_model2.setParam("scale", 100)
-    #m2.p_model2.setParam("rg", 100)
-    out2 = m2.p_model1.runXY(0.01) %s m2.p_model2.runXY(0.01)\n
-    print "My name is %s."% m1.name
-    print out1, " = ", out2
-    if out1 == out2:
-        print "===> Simple Test: Passed!"
-    else:
-        print "===> Simple Test: Failed!"
+from sasmodels.core import load_model_info
+from sasmodels.sasview_model import make_model_from_info
+
+model_info = load_model_info('{model1}{operator}{model2}')
+model_info.name = '{name}'{desc_line}
+Model = make_model_from_info(model_info)
 """
-
 if __name__ == "__main__":
 #    app = wx.PySimpleApp()

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

@@ -195 +195 @@
 the :ref:`Advanced_Plugin_Editor` .
 
+**SasView version 4.2** made it possible to specify whether a plugin created with 
+the *New Plugin Model* dialog is actually a form factor P(Q) or a structure factor 
+S(Q). To do this, simply add one or other of the following lines under the *import* 
+statements.
+
+For a form factor::
+
+     form_factor = True
+         
+or for a structure factor::
+
+     structure_factor = True
+         
+If the plugin is a structure factor it is *also* necessary to add two variables to 
+the parameter list::
+
+     parameters = [ 
+                     ['radius_effective', '', 1, [0.0, numpy.inf], 'volume', ''],
+                     ['volfraction', '', 1, [0.0, 1.0], '', ''],
+                     [...],
+
+and to the declarations of the functions Iq and Iqxy:::
+
+     def Iq(x , radius_effective, volfraction, ...):
+
+     def Iqxy(x, y, radius_effective, volfraction, ...):
+
+Such a plugin should then be available in the S(Q) drop-down box on a FitPage (once 
+a P(Q) model has been selected).
+
 Sum|Multi(p1,p2)
 ^^^^^^^^^^^^^^^^
@@ -206 +236 @@
 or::
 
-     Plugin Model = scale_factor * model_1 /* model_2 + background
+     Plugin Model = scale_factor * (model1 * model2) + background
 
 In the *Easy Sum/Multi Editor* give the new model a function name and brief
 description (to appear under the *Details* button on the *FitPage*). Then select
 two existing models, as p1 and p2, and the required operator, '+' or '*' between
-them. Finally, click the *Apply* button to generate the model and then click *Close*.
-
-Any changes to a plugin model generated in this way only become effective *after* it is re-selected from the model drop-down menu on the FitPage.
+them. Finally, click the *Apply* button to generate and test the model and then click *Close*.
+
+Any changes to a plugin model generated in this way only become effective *after* it is re-selected 
+from the plugin models drop-down menu on the FitPage. If the model is not listed you can force a 
+recompilation of the plugins by selecting *Fitting* > *Plugin Model Operations* > *Load Plugin Models*.
+
+**SasView version 4.2** introduced a much simplified and more extensible structure for plugin models 
+generated through the Easy Sum/Multi Editor. For example, the code for a combination of a sphere model 
+with a power law model now looks like this::
+
+     from sasmodels.core import load_model_info
+     from sasmodels.sasview_model import make_model_from_info
+     
+     model_info = load_model_info('sphere+power_law')
+     model_info.name = 'MyPluginModel'
+     model_info.description = 'sphere + power_law'
+     Model = make_model_from_info(model_info)
+
+To change the models or operators contributing to this plugin it is only necessary to edit the string 
+in the brackets after *load_model_info*, though it would also be a good idea to update the model name 
+and description too!!!
+
+The model specification string can handle multiple models and combinations of operators (+ or *) which 
+are processed according to normal conventions. Thus 'model1+model2*model3' would be valid and would 
+multiply model2 by model3 before adding model1. In this example, parameters in the *FitPage* would be 
+prefixed A (for model2), B (for model3) and C (for model1). Whilst this might appear a little 
+confusing, unless you were creating a plugin model from multiple instances of the same model the parameter 
+assignments ought to be obvious when you load the plugin.
+
+If you need to include another plugin model in the model specification string, just prefix the name of 
+that model with *custom*. For instance::
+
+     sphere+custom.MyPluginModel
+
+To create a P(Q)*\S(Q) model use the @ symbol instead of * like this::
+
+     sphere@hardsphere
+     
+This streamlined approach to building complex plugin models from existing library models, or models 
+available on the *Model Marketplace*, also permits the creation of P(Q)*\S(Q) plugin models, something 
+that was not possible in earlier versions of SasView. 
 
 .. _Advanced_Plugin_Editor:

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

@@ -18 +18 @@
 * By writing a model from scratch outside of SasView (only recommended for
   code monkeys!)
+
+**What follows below is quite technical. If you just want a helping hand to get 
+started creating your own models see** :ref:`Adding_your_own_models`.
 
 Overview