Changeset 13f5656 in sasview


Ignore:
Timestamp:
Oct 10, 2016 10:59:02 AM (8 years ago)
Author:
wojciech
Branches:
master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.1.1, release-4.1.2, release-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload
Children:
ec72ceb
Parents:
131d94b (diff), afb93df (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:
wpotrzebowski <Wojciech.Potrzebowski@…> (10/10/16 10:58:46)
git-committer:
wpotrzebowski <Wojciech.Potrzebowski@…> (10/10/16 10:59:02)
Message:

Adding pyopencl requirement to check_packages and requirements txt

Files:
3 added
1 deleted
8 edited
1 moved

Legend:

Unmodified
Added
Removed

  • docs/sphinx-docs/source/dev/dev.rst

    r476d4e3 re8447d8  
    11Developer Documentation 
    22======================= 
     3 
     4.. note:: In Windows use [Alt]-[Cursor left] to return to the previous page 
    35 
    46Contents 

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

    rec860a8f re8447d8  
    66======== 
    77 
     8.. note:: In Windows use [Alt]-[Cursor left] to return to the previous page 
     9 
    810:download:`Tutorial <../../../../sasview/media/Tutorial.pdf>` 

  • src/sas/sascalc/fit/MultiplicationModel.py

    rcb4ef58 rfd62331  
    88    r""" 
    99        Use for P(Q)\*S(Q); function call must be in the order of P(Q) and then S(Q): 
    10         The model parameters are combined from both models, P(Q) and S(Q), except 1) 'effect_radius' of S(Q) 
    11         which will be calculated from P(Q) via calculate_ER(),  
    12         and 2) 'scale' in P model which is synchronized w/ volfraction in S  
     10        The model parameters are combined from both models, P(Q) and S(Q), except 1) 'radius_effective' of S(Q) 
     11        which will be calculated from P(Q) via calculate_ER(), 
     12        and 2) 'scale' in P model which is synchronized w/ volfraction in S 
    1313        then P*S is multiplied by a new parameter, 'scale_factor'. 
    1414        The polydispersion is applicable only to P(Q), not to S(Q). 
    … …  
    3434        ## Parameter details [units, min, max] 
    3535        self.details = {} 
    36          
    37         ##models  
     36 
     37        ## Define parameters to exclude from multiplication model 
     38        self.excluded_params={'radius_effective','scale','background'} 
     39 
     40        ##models 
    3841        self.p_model = p_model 
    39         self.s_model = s_model         
     42        self.s_model = s_model 
    4043        self.magnetic_params = [] 
    4144        ## dispersion 
    … …  
    4548        ## New parameter:Scaling factor 
    4649        self.params['scale_factor'] = 1 
    47          
     50        self.params['background']  = 0 
     51 
    4852        ## Parameter details [units, min, max] 
    4953        self._set_details() 
    5054        self.details['scale_factor'] = ['', 0.0, numpy.inf] 
    51          
     55        self.details['background'] = ['',-numpy.inf,numpy.inf] 
     56 
    5257        #list of parameter that can be fitted 
    53         self._set_fixed_params()   
     58        self._set_fixed_params() 
    5459        ## parameters with orientation 
    5560        for item in self.p_model.orientation_params: 
    5661            self.orientation_params.append(item) 
    57         for item in self.p_model.magnetic_params:   
    58             self.magnetic_params.append(item)  
     62        for item in self.p_model.magnetic_params: 
     63            self.magnetic_params.append(item) 
    5964        for item in self.s_model.orientation_params: 
    6065            if not item in self.orientation_params: 
    … …  
    6671            multiplicity = 1 
    6772        ## functional multiplicity of the model 
    68         self.multiplicity = multiplicity     
    69            
     73        self.multiplicity = multiplicity 
     74 
    7075        # non-fittable parameters 
    71         self.non_fittable = p_model.non_fittable   
    72         self.multiplicity_info = []  
     76        self.non_fittable = p_model.non_fittable 
     77        self.multiplicity_info = [] 
    7378        self.fun_list = {} 
    7479        if self.non_fittable > 1: 
    7580            try: 
    76                 self.multiplicity_info = p_model.multiplicity_info  
     81                self.multiplicity_info = p_model.multiplicity_info 
    7782                self.fun_list = p_model.fun_list 
    7883                self.is_multiplicity_model = True 
    … …  
    8287            self.is_multiplicity_model = False 
    8388            self.multiplicity_info = [0] 
    84              
     89 
    8590    def _clone(self, obj): 
    8691        """ 
    … …  
    96101        #obj = copy.deepcopy(self) 
    97102        return obj 
    98      
    99      
     103 
     104 
    100105    def _set_dispersion(self): 
    101106        """ 
    … …  
    103108        applied to s_model 
    104109        """ 
    105         ##set dispersion only from p_model  
     110        ##set dispersion only from p_model 
    106111        for name , value in self.p_model.dispersion.iteritems(): 
    107             self.dispersion[name] = value  
    108                                        
     112            self.dispersion[name] = value 
     113 
    109114    def getProfile(self): 
    110115        """ 
    111116        Get SLD profile of p_model if exists 
    112          
     117 
    113118        :return: (r, beta) where r is a list of radius of the transition points\ 
    114119                beta is a list of the corresponding SLD values 
    … …  
    121126            x = None 
    122127            y = None 
    123              
     128 
    124129        return x, y 
    125      
     130 
    126131    def _set_params(self): 
    127132        """ 
    128133        Concatenate the parameters of the two models to create 
    129         these model parameters  
     134        these model parameters 
    130135        """ 
    131136 
    132137        for name , value in self.p_model.params.iteritems(): 
    133             if not name in self.params.keys() and name != 'scale': 
     138            if not name in self.params.keys() and name not in self.excluded_params: 
    134139                self.params[name] = value 
    135              
     140 
    136141        for name , value in self.s_model.params.iteritems(): 
    137             #Remove the effect_radius from the (P*S) model parameters. 
    138             if not name in self.params.keys() and name != 'effect_radius': 
     142            #Remove the radius_effective from the (P*S) model parameters. 
     143            if not name in self.params.keys() and name not in self.excluded_params: 
    139144                self.params[name] = value 
    140                  
     145 
    141146        # Set "scale and effec_radius to P and S model as initializing 
    142147        # since run P*S comes from P and S separately. 
     148        self._set_backgrounds() 
    143149        self._set_scale_factor() 
    144         self._set_effect_radius()        
    145              
     150        self._set_radius_effective() 
     151 
    146152    def _set_details(self): 
    147153        """ 
    148154        Concatenate details of the two models to create 
    149         this model's details  
     155        this model's details 
    150156        """ 
    151157        for name, detail in self.p_model.details.iteritems(): 
    152             if name != 'scale': 
     158            if name not in self.excluded_params: 
    153159                self.details[name] = detail 
    154              
     160 
    155161        for name , detail in self.s_model.details.iteritems(): 
    156             if not name in self.details.keys() or name != 'effect_radius': 
     162            if not name in self.details.keys() or name not in self.exluded_params: 
    157163                self.details[name] = detail 
    158      
     164 
     165    def _set_backgrounds(self): 
     166        """ 
     167        Set component backgrounds to zero 
     168        """ 
     169        self.p_model.setParam('background',0) 
     170        self.s_model.setParam('background',0) 
     171 
     172 
    159173    def _set_scale_factor(self): 
    160174        """ 
    … …  
    162176        """ 
    163177        value = self.params['volfraction'] 
    164         if value != None:  
     178        if value != None: 
    165179            factor = self.p_model.calculate_VR() 
    166180            if factor == None or factor == NotImplemented or factor == 0.0: 
    … …  
    170184            self.p_model.setParam('scale', value) 
    171185            self.s_model.setParam('volfraction', val) 
    172              
    173     def _set_effect_radius(self): 
     186 
     187    def _set_radius_effective(self): 
    174188        """ 
    175189        Set effective radius to S(Q) model 
    176190        """ 
    177         if not 'effect_radius' in self.s_model.params.keys(): 
     191        if not 'radius_effective' in self.s_model.params.keys(): 
    178192            return 
    179193        effective_radius = self.p_model.calculate_ER() 
    180194        #Reset the effective_radius of s_model just before the run 
    181195        if effective_radius != None and effective_radius != NotImplemented: 
    182             self.s_model.setParam('effect_radius', effective_radius) 
    183                  
     196            self.s_model.setParam('radius_effective', effective_radius) 
     197 
    184198    def setParam(self, name, value): 
    185         """  
     199        """ 
    186200        Set the value of a model parameter 
    187          
     201 
    188202        :param name: name of the parameter 
    189203        :param value: value of the parameter 
    … …  
    191205        # set param to P*S model 
    192206        self._setParamHelper( name, value) 
    193          
    194         ## setParam to p model  
    195         # set 'scale' in P(Q) equal to volfraction  
     207 
     208        ## setParam to p model 
     209        # set 'scale' in P(Q) equal to volfraction 
    196210        if name == 'volfraction': 
    197211            self._set_scale_factor() 
    198         elif name in self.p_model.getParamList(): 
     212        elif name in self.p_model.getParamList() and name not in self.excluded_params: 
    199213            self.p_model.setParam( name, value) 
    200          
    201         ## setParam to s model  
    202         # This is a little bit abundant: Todo: find better way          
    203         self._set_effect_radius() 
    204         if name in self.s_model.getParamList(): 
     214 
     215        ## setParam to s model 
     216        # This is a little bit abundant: Todo: find better way 
     217        self._set_radius_effective() 
     218        if name in self.s_model.getParamList() and name not in self.excluded_params: 
    205219            if name != 'volfraction': 
    206220                self.s_model.setParam( name, value) 
    207              
     221 
    208222 
    209223        #self._setParamHelper( name, value) 
    210          
     224 
    211225    def _setParamHelper(self, name, value): 
    212226        """ 
    … …  
    228242                    self.params[item] = value 
    229243                    return 
    230              
     244 
    231245        raise ValueError, "Model does not contain parameter %s" % name 
    232               
    233     
     246 
     247 
    234248    def _set_fixed_params(self): 
    235249        """ 
    … …  
    240254 
    241255        self.fixed.sort() 
    242                  
    243                  
     256 
     257 
    244258    def run(self, x = 0.0): 
    245         """  
     259        """ 
    246260        Evaluate the model 
    247          
     261 
    248262        :param x: input q-value (float or [float, float] as [r, theta]) 
    249263        :return: (scattering function value) 
    250264        """ 
    251265        # set effective radius and scaling factor before run 
    252         self._set_effect_radius() 
     266        self._set_radius_effective() 
    253267        self._set_scale_factor() 
    254268        return self.params['scale_factor'] * self.p_model.run(x) * \ 
    255                             self.s_model.run(x) 
     269                            self.s_model.run(x) + self.params['background'] 
    256270 
    257271    def runXY(self, x = 0.0): 
    258         """  
     272        """ 
    259273        Evaluate the model 
    260          
     274 
    261275        :param x: input q-value (float or [float, float] as [qx, qy]) 
    262276        :return: scattering function value 
    263         """   
     277        """ 
    264278        # set effective radius and scaling factor before run 
    265         self._set_effect_radius() 
     279        self._set_radius_effective() 
    266280        self._set_scale_factor() 
    267281        out = self.params['scale_factor'] * self.p_model.runXY(x) * \ 
    268                         self.s_model.runXY(x) 
     282                        self.s_model.runXY(x) + self.params['background'] 
    269283        return out 
    270      
    271     ## Now (May27,10) directly uses the model eval function  
     284 
     285    ## Now (May27,10) directly uses the model eval function 
    272286    ## instead of the for-loop in Base Component. 
    273287    def evalDistribution(self, x = []): 
    274         """  
     288        """ 
    275289        Evaluate the model in cartesian coordinates 
    276          
     290 
    277291        :param x: input q[], or [qx[], qy[]] 
    278292        :return: scattering function P(q[]) 
    279293        """ 
    280294        # set effective radius and scaling factor before run 
    281         self._set_effect_radius() 
     295        self._set_radius_effective() 
    282296        self._set_scale_factor() 
    283297        out = self.params['scale_factor'] * self.p_model.evalDistribution(x) * \ 
    284                         self.s_model.evalDistribution(x) 
     298                        self.s_model.evalDistribution(x) + self.params['background'] 
    285299        return out 
    286300 
    … …  
    288302        """ 
    289303        Set the dispersion object for a model parameter 
    290          
     304 
    291305        :param parameter: name of the parameter [string] 
    292306        :dispersion: dispersion object of type DispersionModel 
    … …  
    299313            return value 
    300314        except: 
    301             raise  
     315            raise 
    302316 
    303317    def fill_description(self, p_model, s_model): 
    … …  
    306320        """ 
    307321        description = "" 
    308         description += "Note:1) The effect_radius (effective radius) of %s \n"%\ 
     322        description += "Note:1) The radius_effective (effective radius) of %s \n"%\ 
    309323                                                                (s_model.name) 
    310324        description += "             is automatically calculated " 
    … …  
    318332        description += "        for details of individual models." 
    319333        self.description += description 
    320      

  • src/sas/sasgui/perspectives/calculator/media/python_shell_help.rst

    rd85c194 rafb93df  
    33.. This is a port of the original SasView html help file to ReSTructured text 
    44.. by S King, ISIS, during SasView CodeCamp-III in Feb 2015. 
     5.. Text revised during Code Camp V in Oct 2016. 
    56 
    6 Python Shell Tool 
    7 ================= 
     7.. _Python_shell: 
     8 
     9Python Shell-Editor Tool 
     10======================== 
    811 
    912Description  
    1013----------- 
    1114 
    12 This is a Python shell/editor (PyCrust) provided with WxPython. An editing  
    13 notebook will show up when a Python file is created/loaded with the *New* or  
    14 *Open* options on the menu.  
     15This is a Python shell/editor provided with WxPython. 
    1516 
    16 *Run* enables the editor to compile and run the Python code. 
     17For the help about Python, visit the website http://docs.python.org/tutorial/ 
    1718 
    18 For the details about the Python, visit the website http://docs.python.org/tutorial/ 
     19.. note:: This shell/editor has its own help, but the Help() and Credits() calls do not work on Macs. 
    1920 
    20 The NumPy, SciPy, and Matplotlib, etc, libraries are shipped with SasView.  
    21 However, some functionality may not work. 
     21The NumPy, SciPy, and Matplotlib, etc, libraries are shipped with SasView and so functions from these can be imported into the shell/editor, however, some functionality may not work. 
    2222 
    23 PyCrust has its own Help. 
     23.. image:: new_pycrust_example.png 
     24   :align: center 
    2425 
    25 *NOTE! The Help() and Credits() calls do not work on Macs.* 
     26When a Python file, for example a fitting model, is created or loaded with the *New* or *Open* options from the menu, a new tab opens with an editing notebook. 
    2627 
    27 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ 
     28.. image:: new_pycrust_example_2.png 
     29   :align: center 
    2830 
    29 Example 
    30 ------- 
     31If a Python (.py) model has a linked C (.c) subroutine *in the same folder* then the shell/editor will open both! However input focus is usually transferred to the tab with the .c file. 
    3132 
    32 An example calling the Matplotlib plotting gallery: 
    33  
    34 .. image:: pycrust_example.png 
     33To compile a model, select *Run* > *Check Model* from the shell/editor menu. If the model contains a unit test (which it should!!!) then this will also run and a popup window will report the success/failure of the test. 
    3534 
    3635.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ 
    3736 
    38 .. note::  This help document was last changed by Steve King, 19Feb2015 
     37.. note::  This help document was last changed by Steve King, 10Oct2015 

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

    r2a6d757 re8447d8  
    33Fitting Documentation 
    44===================== 
     5 
     6.. note:: In Windows use [Alt]-[Cursor left] to return to the previous page 
    57 
    68.. toctree:: 

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

    r05829fb rafb93df  
    141141From the *Fitting* option in the menu bar, select *Edit Custom Model*. 
    142142 
    143 .. image:: edit_model_menu.bmp 
     143.. image:: edit_model_menu.png 
    144144 
    145145and then one of the options 
    146146 
    147 *  *New* - to create a new custom model template 
    148 *  *Sum|Multi(p1,p2)* - to create a new model by summing/multiplying existing models in the model library 
    149 *  *Advanced* - to edit a new custom model 
     147*  *New* - to create a custom model template with a help dialog 
     148*  *Sum|Multi(p1,p2)* - to create a custom model by summing/multiplying *existing models* in the model library 
     149*  *Advanced* - to create/edit a custom model in a Python shell 
    150150*  *Delete* - to delete a custom model 
     151*  *Load* - to (re-)load custom models 
    151152 
    152153New 
    … …  
    184185^^^^^^^^ 
    185186 
    186 Selecting this option shows all the custom models in the plugin model folder 
    187  
    188   *C:\\Users\\[username]\\.sasview\\plugin_models* - (on Windows) 
     187Selecting this option shows all the custom models in the plugin model folder, on Windows this is 
     188 
     189  *C:\\Users\\{username}\\.sasview\\plugin_models* 
    189190 
    190191You can edit, modify, and save the Python code in any of these models using the 
    191 *Advanced Custom Model Editor*. 
    192  
    193 See :ref:`Writing_a_Plugin` for details on the plugin format. 
    194  
    195 *NB: Sum/Product models are still using the SasView 3.x model format.  Unless 
    196 you are confident about what you are doing, it is recommended that you 
    197 only modify lines denoted with the ## <----- comments!* 
    198  
    199 When editing is complete, select *Run -> Compile* from the *Model Editor* menu bar. An 
    200 *Info* box will appear with the results of the compilation and model unit tests. The 
    201 model will only be usable if the tests 'pass'. 
     192*Advanced Custom Model Editor*. Note that this is actually the same tool as the :ref:`Python_shell` . 
     193 
     194For details of the SasView plugin model format see :ref:`Writing_a_Plugin` . 
     195 
     196.. note:: Model files generated with the Sum/Multi option are still using the SasView 3.x model format. Unless you are confident about what you are doing, it is recommended that you only modify lines denoted with the ## <----- comments! 
     197 
     198When editing is complete, select *Run* > *Check Model* from the *Advanced Custom Model Editor* menu bar. An *Info* box will appear with the results of the compilation and model unit tests. The model will only be usable if the tests 'pass'. 
    202199 
    203200To use the model, go to the relevant *Fit Page*, select the *Customized Models* 
    204201category and then select the model from the drop-down menu. 
    205202 
    206 *NB: Any changes to a custom model generated in this way only become effective after* 
    207 *it is re-selected from the model drop-down menu on the Fit Page.* 
     203Any changes to a custom model generated in this way only become effective *after* it is re-selected from the model drop-down menu on the FitPage. 
    208204 
    209205Delete 
    … …  
    213209 
    214210*NB: Custom models shipped with SasView cannot be removed in this way.* 
     211 
     212Load 
     213^^^^ 
     214 
     215This option loads (or re-loads) all models present in the plugin model folder. 
    215216 
    216217.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ 

  • build_tools/requirements.txt

    r0ff9e1f r131d94b  
    1717sphinx==1.2.1 
    1818h5py==2.5 
     19pyopencl==2015.1 

  • check_packages.py

    r68aa210 r131d94b  
    2626    'periodictable':{'version':'1.3.0','import_name':'periodictable','test':'__version__'}, 
    2727    'bumps':{'version':'0.7.5.9','import_name':'bumps','test':'__version__'}, 
    28     'numpy':{'version':'1.6.1','import_name':'numpy','test':'__version__'}, 
    29     'scipy':{'version':'0.10.1','import_name':'scipy','test':'__version__'}, 
     28    'numpy':{'version':'1.7.1','import_name':'numpy','test':'__version__'}, 
     29    'scipy':{'version':'0.18.0','import_name':'scipy','test':'__version__'}, 
    3030    'wx':{'version':'2.8.12.1','import_name':'wx','test':'__version__'}, 
    3131    'matplotlib':{'version':'1.1.0','import_name':'matplotlib','test':'__version__'}, 
    … …  
    3333    'sphinx':{'version':'1.2.1','import_name':'sphinx','test':'__version__'}, 
    3434    'unittest-xml-reporting':{'version':'1.10.0','import_name':'xmlrunner','test':'__version__'}, 
     35    'pyopencl':{'version':'2015.1','import_name':'pyopencl','test':'VERSION_TEXT'}, 
    3536} 
    3637win_required_package_list = { 
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