Changes in / [632fda9:66acafe] in sasview
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- 11 edited
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sasview/sasview.py
rf36e01f r3b0f8cc 74 74 PLUGIN_MODEL_DIR = 'plugin_models' 75 75 APP_NAME = 'SasView' 76 77 # Set SAS_MODELPATH so sasmodels can find our custom models 78 os.environ['SAS_MODELPATH'] = os.path.join(sasdir, PLUGIN_MODEL_DIR) 76 79 77 80 from matplotlib import backend_bases -
src/sas/sasgui/perspectives/calculator/image_viewer.py
ra1b8fee r412e9e8b 59 59 _, extension = os.path.splitext(basename) 60 60 try: 61 # Note that matplotlib only reads png natively. 62 # Any other formats (tiff, jpeg, etc) are passed 63 # to PIL which seems to have a problem in version 64 # 1.1.7 that causes a close error which shows up in 65 # the log file. This does not seem to have any adverse 66 # effects. PDB --- September 17, 2017. 61 67 img = mpimg.imread(file_path) 62 68 is_png = extension.lower() == '.png' … … 89 95 if location is None: 90 96 location = os.getcwd() 91 dlg = wx.FileDialog(self.parent, "Image Viewer: Choose a image file", 92 location, "", "", style=wx.FD_OPEN | wx.FD_MULTIPLE) 97 wildcard="Images (*.bmp;*.gif;*jpeg,*jpg;*.png;*tif;*.tiff)|*bmp;\ 98 *.gif; *.jpg; *.jpeg;*png;*.png;*.tif;*.tiff|"\ 99 "Bitmap (*.bmp)|*.bmp|"\ 100 "GIF (*.gif)|*.gif|"\ 101 "JPEG (*.jpg;*.jpeg)|*.jpg;*.jpeg|"\ 102 "PNG (*.png)|*.png|"\ 103 "TIFF (*.tif;*.tiff)|*.tif;*tiff|"\ 104 "All Files (*.*)|*.*|" 105 106 dlg = wx.FileDialog(self.parent, "Image Viewer: Choose an image file", 107 location, "", wildcard, style=wx.FD_OPEN 108 | wx.FD_MULTIPLE) 93 109 if dlg.ShowModal() == wx.ID_OK: 94 110 path = dlg.GetPaths() -
src/sas/sasgui/perspectives/calculator/media/image_viewer_help.rst
rda456fb r412e9e8b 34 34 will be displayed. 35 35 36 .. image:: load_image. bmp36 .. image:: load_image.png 37 37 38 38 3) To save, print, or copy the image, or to apply a grid overlay, right-click 39 39 anywhere in the plot. 40 40 41 .. image:: pic_plot. bmp41 .. image:: pic_plot.png 42 42 43 43 4. If the image is taken from a 2D detector, SasView can attempt to convert … … 51 51 then click the OK. 52 52 53 .. image:: pic_convert. bmp53 .. image:: pic_convert.png 54 54 55 55 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ -
src/sas/sasgui/perspectives/calculator/model_editor.py
r07ec714 r23359ccb 106 106 self.model2_string = "cylinder" 107 107 self.name = 'Sum' + M_NAME 108 self.factor = 'scale_factor'109 108 self._notes = '' 110 109 self._operator = '+' … … 133 132 self.model2_name = str(self.model2.GetValue()) 134 133 self.good_name = True 135 self.fill_op rator_combox()134 self.fill_operator_combox() 136 135 137 136 def _layout_name(self): … … 491 490 a sum or multiply model then create the appropriate string 492 491 """ 493 494 492 name = '' 495 496 493 if operator == '*': 497 494 name = 'Multi' 498 factor = 'BackGround' 499 f_oper = '+' 495 factor = 'background' 500 496 else: 501 497 name = 'Sum' 502 498 factor = 'scale_factor' 503 f_oper = '*' 504 505 self.factor = factor 499 506 500 self._operator = operator 507 self.explanation = " Plugin Model = %s %s (model1 %s model2)\n" % \508 (self.factor, f_oper, self._operator)501 self.explanation = (" Plugin_model = scale_factor * (model_1 {} " 502 "model_2) + background").format(operator) 509 503 self.explanationctr.SetLabel(self.explanation) 510 504 self.name = name + M_NAME 511 505 512 506 513 def fill_op rator_combox(self):507 def fill_operator_combox(self): 514 508 """ 515 509 fill the current combobox with the operator … … 527 521 return [self.model1_name, self.model2_name] 528 522 529 def write_string(self, fname, name1, name2):523 def write_string(self, fname, model1_name, model2_name): 530 524 """ 531 525 Write and Save file … … 533 527 self.fname = fname 534 528 description = self.desc_tcl.GetValue().lstrip().rstrip() 535 if description == '': 536 description = name1 + self._operator + name2 537 text = self._operator_choice.GetValue() 538 if text.count('+') > 0: 539 factor = 'scale_factor' 540 f_oper = '*' 541 default_val = '1.0' 542 else: 543 factor = 'BackGround' 544 f_oper = '+' 545 default_val = '0.0' 546 path = self.fname 547 try: 548 out_f = open(path, 'w') 549 except: 550 raise 551 lines = SUM_TEMPLATE.split('\n') 552 for line in lines: 553 try: 554 if line.count("scale_factor"): 555 line = line.replace('scale_factor', factor) 556 #print "scale_factor", line 557 if line.count("= %s"): 558 out_f.write(line % (default_val) + "\n") 559 elif line.count("import Model as P1"): 560 if self.is_p1_custom: 561 line = line.replace('#', '') 562 out_f.write(line % name1 + "\n") 563 else: 564 out_f.write(line + "\n") 565 elif line.count("import %s as P1"): 566 if not self.is_p1_custom: 567 line = line.replace('#', '') 568 out_f.write(line % (name1) + "\n") 569 else: 570 out_f.write(line + "\n") 571 elif line.count("import Model as P2"): 572 if self.is_p2_custom: 573 line = line.replace('#', '') 574 out_f.write(line % name2 + "\n") 575 else: 576 out_f.write(line + "\n") 577 elif line.count("import %s as P2"): 578 if not self.is_p2_custom: 579 line = line.replace('#', '') 580 out_f.write(line % (name2) + "\n") 581 else: 582 out_f.write(line + "\n") 583 elif line.count("P1 = find_model"): 584 out_f.write(line % (name1) + "\n") 585 elif line.count("P2 = find_model"): 586 out_f.write(line % (name2) + "\n") 587 588 elif line.count("self.description = '%s'"): 589 out_f.write(line % description + "\n") 590 #elif line.count("run") and line.count("%s"): 591 # out_f.write(line % self._operator + "\n") 592 #elif line.count("evalDistribution") and line.count("%s"): 593 # out_f.write(line % self._operator + "\n") 594 elif line.count("return") and line.count("%s") == 2: 595 #print "line return", line 596 out_f.write(line % (f_oper, self._operator) + "\n") 597 elif line.count("out2")and line.count("%s"): 598 out_f.write(line % self._operator + "\n") 599 else: 600 out_f.write(line + "\n") 601 except: 602 raise 603 out_f.close() 604 #else: 605 # msg = "Name exists already." 529 desc_line = '' 530 if description.strip() != '': 531 # Sasmodels generates a description for us. If the user provides 532 # their own description, add a line to overwrite the sasmodels one 533 desc_line = "\nmodel_info.description = '{}'".format(description) 534 name = os.path.splitext(os.path.basename(self.fname))[0] 535 output = SUM_TEMPLATE.format(name=name, model1=model1_name, 536 model2=model2_name, operator=self._operator, desc_line=desc_line) 537 with open(self.fname, 'w') as out_f: 538 out_f.write(output) 606 539 607 540 def compile_file(self, path): … … 1278 1211 """ 1279 1212 SUM_TEMPLATE = """ 1280 # A sample of an experimental model function for Sum/Multiply(Pmodel1,Pmodel2) 1281 import os 1282 import sys 1283 import copy 1284 import collections 1285 1286 import numpy 1287 1288 from sas.sascalc.fit.pluginmodel import Model1DPlugin 1289 from sasmodels.sasview_model import find_model 1290 1291 class Model(Model1DPlugin): 1292 name = os.path.splitext(os.path.basename(__file__))[0] 1293 is_multiplicity_model = False 1294 def __init__(self, multiplicity=1): 1295 Model1DPlugin.__init__(self, name='') 1296 P1 = find_model('%s') 1297 P2 = find_model('%s') 1298 p_model1 = P1() 1299 p_model2 = P2() 1300 ## Setting model name model description 1301 self.description = '%s' 1302 if self.name.rstrip().lstrip() == '': 1303 self.name = self._get_name(p_model1.name, p_model2.name) 1304 if self.description.rstrip().lstrip() == '': 1305 self.description = p_model1.name 1306 self.description += p_model2.name 1307 self.fill_description(p_model1, p_model2) 1308 1309 ## Define parameters 1310 self.params = collections.OrderedDict() 1311 1312 ## Parameter details [units, min, max] 1313 self.details = {} 1314 ## Magnetic Panrameters 1315 self.magnetic_params = [] 1316 # non-fittable parameters 1317 self.non_fittable = p_model1.non_fittable 1318 self.non_fittable += p_model2.non_fittable 1319 1320 ##models 1321 self.p_model1= p_model1 1322 self.p_model2= p_model2 1323 1324 1325 ## dispersion 1326 self._set_dispersion() 1327 ## Define parameters 1328 self._set_params() 1329 ## New parameter:scaling_factor 1330 self.params['scale_factor'] = %s 1331 1332 ## Parameter details [units, min, max] 1333 self._set_details() 1334 self.details['scale_factor'] = ['', 0.0, numpy.inf] 1335 1336 1337 #list of parameter that can be fitted 1338 self._set_fixed_params() 1339 1340 ## parameters with orientation 1341 self.orientation_params = [] 1342 for item in self.p_model1.orientation_params: 1343 new_item = "p1_" + item 1344 if not new_item in self.orientation_params: 1345 self.orientation_params.append(new_item) 1346 1347 for item in self.p_model2.orientation_params: 1348 new_item = "p2_" + item 1349 if not new_item in self.orientation_params: 1350 self.orientation_params.append(new_item) 1351 ## magnetic params 1352 self.magnetic_params = [] 1353 for item in self.p_model1.magnetic_params: 1354 new_item = "p1_" + item 1355 if not new_item in self.magnetic_params: 1356 self.magnetic_params.append(new_item) 1357 1358 for item in self.p_model2.magnetic_params: 1359 new_item = "p2_" + item 1360 if not new_item in self.magnetic_params: 1361 self.magnetic_params.append(new_item) 1362 # get multiplicity if model provide it, else 1. 1363 try: 1364 multiplicity1 = p_model1.multiplicity 1365 try: 1366 multiplicity2 = p_model2.multiplicity 1367 except: 1368 multiplicity2 = 1 1369 except: 1370 multiplicity1 = 1 1371 multiplicity2 = 1 1372 ## functional multiplicity of the model 1373 self.multiplicity1 = multiplicity1 1374 self.multiplicity2 = multiplicity2 1375 self.multiplicity_info = [] 1376 1377 def _clone(self, obj): 1378 import copy 1379 obj.params = copy.deepcopy(self.params) 1380 obj.description = copy.deepcopy(self.description) 1381 obj.details = copy.deepcopy(self.details) 1382 obj.dispersion = copy.deepcopy(self.dispersion) 1383 obj.p_model1 = self.p_model1.clone() 1384 obj.p_model2 = self.p_model2.clone() 1385 #obj = copy.deepcopy(self) 1386 return obj 1387 1388 def _get_name(self, name1, name2): 1389 p1_name = self._get_upper_name(name1) 1390 if not p1_name: 1391 p1_name = name1 1392 name = p1_name 1393 name += "_and_" 1394 p2_name = self._get_upper_name(name2) 1395 if not p2_name: 1396 p2_name = name2 1397 name += p2_name 1398 return name 1399 1400 def _get_upper_name(self, name=None): 1401 if name is None: 1402 return "" 1403 upper_name = "" 1404 str_name = str(name) 1405 for index in range(len(str_name)): 1406 if str_name[index].isupper(): 1407 upper_name += str_name[index] 1408 return upper_name 1409 1410 def _set_dispersion(self): 1411 self.dispersion = collections.OrderedDict() 1412 ##set dispersion only from p_model 1413 for name , value in self.p_model1.dispersion.iteritems(): 1414 #if name.lower() not in self.p_model1.orientation_params: 1415 new_name = "p1_" + name 1416 self.dispersion[new_name]= value 1417 for name , value in self.p_model2.dispersion.iteritems(): 1418 #if name.lower() not in self.p_model2.orientation_params: 1419 new_name = "p2_" + name 1420 self.dispersion[new_name]= value 1421 1422 def function(self, x=0.0): 1423 return 0 1424 1425 def getProfile(self): 1426 try: 1427 x,y = self.p_model1.getProfile() 1428 except: 1429 x = None 1430 y = None 1431 1432 return x, y 1433 1434 def _set_params(self): 1435 for name , value in self.p_model1.params.iteritems(): 1436 # No 2D-supported 1437 #if name not in self.p_model1.orientation_params: 1438 new_name = "p1_" + name 1439 self.params[new_name]= value 1440 1441 for name , value in self.p_model2.params.iteritems(): 1442 # No 2D-supported 1443 #if name not in self.p_model2.orientation_params: 1444 new_name = "p2_" + name 1445 self.params[new_name]= value 1446 1447 # Set "scale" as initializing 1448 self._set_scale_factor() 1449 1450 1451 def _set_details(self): 1452 for name ,detail in self.p_model1.details.iteritems(): 1453 new_name = "p1_" + name 1454 #if new_name not in self.orientation_params: 1455 self.details[new_name]= detail 1456 1457 for name ,detail in self.p_model2.details.iteritems(): 1458 new_name = "p2_" + name 1459 #if new_name not in self.orientation_params: 1460 self.details[new_name]= detail 1461 1462 def _set_scale_factor(self): 1463 pass 1464 1465 1466 def setParam(self, name, value): 1467 # set param to this (p1, p2) model 1468 self._setParamHelper(name, value) 1469 1470 ## setParam to p model 1471 model_pre = '' 1472 new_name = '' 1473 name_split = name.split('_', 1) 1474 if len(name_split) == 2: 1475 model_pre = name.split('_', 1)[0] 1476 new_name = name.split('_', 1)[1] 1477 if model_pre == "p1": 1478 if new_name in self.p_model1.getParamList(): 1479 self.p_model1.setParam(new_name, value) 1480 elif model_pre == "p2": 1481 if new_name in self.p_model2.getParamList(): 1482 self.p_model2.setParam(new_name, value) 1483 elif name == 'scale_factor': 1484 self.params['scale_factor'] = value 1485 else: 1486 raise ValueError, "Model does not contain parameter %s" % name 1487 1488 def getParam(self, name): 1489 # Look for dispersion parameters 1490 toks = name.split('.') 1491 if len(toks)==2: 1492 for item in self.dispersion.keys(): 1493 # 2D not supported 1494 if item.lower()==toks[0].lower(): 1495 for par in self.dispersion[item]: 1496 if par.lower() == toks[1].lower(): 1497 return self.dispersion[item][par] 1498 else: 1499 # Look for standard parameter 1500 for item in self.params.keys(): 1501 if item.lower()==name.lower(): 1502 return self.params[item] 1503 return 1504 #raise ValueError, "Model does not contain parameter %s" % name 1505 1506 def _setParamHelper(self, name, value): 1507 # Look for dispersion parameters 1508 toks = name.split('.') 1509 if len(toks)== 2: 1510 for item in self.dispersion.keys(): 1511 if item.lower()== toks[0].lower(): 1512 for par in self.dispersion[item]: 1513 if par.lower() == toks[1].lower(): 1514 self.dispersion[item][par] = value 1515 return 1516 else: 1517 # Look for standard parameter 1518 for item in self.params.keys(): 1519 if item.lower()== name.lower(): 1520 self.params[item] = value 1521 return 1522 1523 raise ValueError, "Model does not contain parameter %s" % name 1524 1525 1526 def _set_fixed_params(self): 1527 self.fixed = [] 1528 for item in self.p_model1.fixed: 1529 new_item = "p1" + item 1530 self.fixed.append(new_item) 1531 for item in self.p_model2.fixed: 1532 new_item = "p2" + item 1533 self.fixed.append(new_item) 1534 1535 self.fixed.sort() 1536 1537 1538 def run(self, x = 0.0): 1539 self._set_scale_factor() 1540 return self.params['scale_factor'] %s \ 1541 (self.p_model1.run(x) %s self.p_model2.run(x)) 1542 1543 def runXY(self, x = 0.0): 1544 self._set_scale_factor() 1545 return self.params['scale_factor'] %s \ 1546 (self.p_model1.runXY(x) %s self.p_model2.runXY(x)) 1547 1548 ## Now (May27,10) directly uses the model eval function 1549 ## instead of the for-loop in Base Component. 1550 def evalDistribution(self, x = []): 1551 self._set_scale_factor() 1552 return self.params['scale_factor'] %s \ 1553 (self.p_model1.evalDistribution(x) %s \ 1554 self.p_model2.evalDistribution(x)) 1555 1556 def set_dispersion(self, parameter, dispersion): 1557 value= None 1558 new_pre = parameter.split("_", 1)[0] 1559 new_parameter = parameter.split("_", 1)[1] 1560 try: 1561 if new_pre == 'p1' and \ 1562 new_parameter in self.p_model1.dispersion.keys(): 1563 value= self.p_model1.set_dispersion(new_parameter, dispersion) 1564 if new_pre == 'p2' and \ 1565 new_parameter in self.p_model2.dispersion.keys(): 1566 value= self.p_model2.set_dispersion(new_parameter, dispersion) 1567 self._set_dispersion() 1568 return value 1569 except: 1570 raise 1571 1572 def fill_description(self, p_model1, p_model2): 1573 description = "" 1574 description += "This model gives the summation or multiplication of" 1575 description += "%s and %s. "% ( p_model1.name, p_model2.name ) 1576 self.description += description 1577 1578 if __name__ == "__main__": 1579 m1= Model() 1580 #m1.setParam("p1_scale", 25) 1581 #m1.setParam("p1_length", 1000) 1582 #m1.setParam("p2_scale", 100) 1583 #m1.setParam("p2_rg", 100) 1584 out1 = m1.runXY(0.01) 1585 1586 m2= Model() 1587 #m2.p_model1.setParam("scale", 25) 1588 #m2.p_model1.setParam("length", 1000) 1589 #m2.p_model2.setParam("scale", 100) 1590 #m2.p_model2.setParam("rg", 100) 1591 out2 = m2.p_model1.runXY(0.01) %s m2.p_model2.runXY(0.01)\n 1592 print "My name is %s."% m1.name 1593 print out1, " = ", out2 1594 if out1 == out2: 1595 print "===> Simple Test: Passed!" 1596 else: 1597 print "===> Simple Test: Failed!" 1213 from sasmodels.core import load_model_info 1214 from sasmodels.sasview_model import make_model_from_info 1215 1216 model_info = load_model_info('{model1}{operator}{model2}') 1217 model_info.name = '{name}'{desc_line} 1218 Model = make_model_from_info(model_info) 1598 1219 """ 1599 1600 1220 if __name__ == "__main__": 1601 1221 # app = wx.PySimpleApp() -
src/sas/sasgui/perspectives/fitting/basepage.py
r33dc18f r33dc18f 2928 2928 return False 2929 2929 2930 2931 def _get_copy_params_details(self): 2932 """ 2933 Combines polydisperse parameters with self.parameters so that they can 2934 be written to the clipboard (for Excel or LaTeX). Also returns a list of 2935 the names of parameters that have been fitted 2936 2937 :returns: all_params - A list of all parameters, in the format of 2938 self.parameters 2939 :returns: fitted_par_names - A list of the names of parameters that have 2940 been fitted 2941 """ 2942 # Names of params that are being fitted 2943 fitted_par_names = [param[1] for param in self.param_toFit] 2944 # Names of params with associated polydispersity 2945 disp_params = [param[1].split('.')[0] for param in self.fittable_param] 2946 2947 # Create array of all parameters 2948 all_params = copy.copy(self.parameters) 2949 for param in self.parameters: 2950 if param[1] in disp_params: 2951 # Polydisperse params aren't in self.parameters, so need adding 2952 # to all_params 2953 name = param[1] + ".width" 2954 index = all_params.index(param) + 1 2955 to_insert = [] 2956 if name in fitted_par_names: 2957 # Param is fitted, so already has a param list in self.param_toFit 2958 to_insert = self.param_toFit[fitted_par_names.index(name)] 2959 else: 2960 # Param isn't fitted, so mockup a param list 2961 to_insert = [None, name, self.model.getParam(name), None, None] 2962 all_params.insert(index, to_insert) 2963 return all_params, fitted_par_names 2964 2930 2965 def get_copy_excel(self): 2931 2966 """ … … 2941 2976 Get the string copies of the param names and values in the tap 2942 2977 """ 2978 if not self.parameters: 2979 # Do nothing if parameters doesn't exist 2980 return False 2981 2943 2982 content = '' 2944 2945 2983 crlf = chr(13) + chr(10) 2946 2984 tab = chr(9) 2947 2985 2948 # Do it if params exist 2949 if self.parameters: 2950 2951 for param in self.parameters: 2952 content += param[1] # parameter name 2986 all_params, fitted_param_names = self._get_copy_params_details() 2987 2988 # Construct row of parameter names 2989 for param in all_params: 2990 name = param[1] # Parameter name 2991 content += name 2992 content += tab 2993 if name in fitted_param_names: 2994 # Only print errors for fitted parameters 2995 content += name + "_err" 2953 2996 content += tab 2954 content += param[1] + "_err" 2955 content += tab 2956 2957 content += crlf 2958 2959 # row of values and errors... 2960 for param in self.parameters: 2961 content += param[2].GetValue() # value 2962 content += tab 2963 content += param[4].GetValue() # error 2964 content += tab 2965 2966 return content 2967 else: 2968 return False 2997 2998 content += crlf 2999 3000 # Construct row of parameter values and errors 3001 for param in all_params: 3002 value = param[2] 3003 if hasattr(value, 'GetValue'): 3004 # param[2] is a text box 3005 value = value.GetValue() 3006 else: 3007 # param[2] is a float (from our self._get_copy_params_details) 3008 value = str(value) 3009 content += value 3010 content += tab 3011 if param[1] in fitted_param_names: 3012 # Only print errors for fitted parameters 3013 content += param[4].GetValue() 3014 content += tab 3015 3016 return content 2969 3017 2970 3018 def get_copy_latex(self): … … 2981 3029 Get the string copies of the param names and values in the tap 2982 3030 """ 3031 if not self.parameters: 3032 # Do nothing if self.parameters doesn't exist 3033 return False 3034 2983 3035 content = '\\begin{table}' 2984 3036 content += '\\begin{tabular}[h]' … … 2987 3039 tab = chr(9) 2988 3040 2989 # Do it if params exist 2990 if self.parameters: 2991 2992 content += '{|' 2993 for param in self.parameters: 2994 content += 'l|l|' 2995 content += '}\hline' 2996 content += crlf 2997 2998 for index, param in enumerate(self.parameters): 2999 content += param[1].replace('_', '\_') # parameter name 3041 all_params, fitted_param_names = self._get_copy_params_details() 3042 3043 content += '{|' 3044 for param in all_params: 3045 content += 'l|l|' 3046 content += '}\hline' 3047 content += crlf 3048 3049 # Construct row of parameter names 3050 for index, param in enumerate(all_params): 3051 name = param[1] # Parameter name 3052 content += name.replace('_', '\_') # Escape underscores 3053 if name in fitted_param_names: 3054 # Only print errors for fitted parameters 3000 3055 content += ' & ' 3001 content += param[1].replace('_', '\_') + "\_err" 3002 if index < len(self.parameters) - 1: 3003 content += ' & ' 3004 content += '\\\\ \\hline' 3005 content += crlf 3006 3007 # row of values and errors... 3008 for index, param in enumerate(self.parameters): 3009 content += param[2].GetValue() # parameter value 3056 content += name.replace('_', '\_') + "\_err" 3057 if index < len(all_params) - 1: 3010 3058 content += ' & ' 3011 content += param[4].GetValue() # parameter error 3012 if index < len(self.parameters) - 1: 3013 content += ' & ' 3014 content += '\\\\ \\hline' 3015 content += crlf 3016 3017 content += '\\end{tabular}' 3018 content += '\\end{table}' 3019 return content 3020 else: 3021 return False 3059 3060 content += '\\\\ \\hline' 3061 content += crlf 3062 3063 # Construct row of values and errors 3064 for index, param in enumerate(all_params): 3065 value = param[2] 3066 if hasattr(value, "GetValue"): 3067 # value is a text box 3068 value = value.GetValue() 3069 else: 3070 # value is a float (from self._get_copy_params_details) 3071 value = str(value) 3072 content += value 3073 if param[1] in fitted_param_names: 3074 # Only print errors for fitted params 3075 content += ' & ' 3076 content += param[4].GetValue() 3077 if index < len(all_params) - 1: 3078 content += ' & ' 3079 3080 content += '\\\\ \\hline' 3081 content += crlf 3082 content += '\\end{tabular}' 3083 content += '\\end{table}' 3084 3085 return content 3022 3086 3023 3087 def set_clipboard(self, content=None): -
src/sas/sasgui/perspectives/fitting/fitpage.py
r79e6a33 r79e6a33 289 289 self.btFitHelp.SetToolTipString("General fitting help.") 290 290 self.btFitHelp.Bind(wx.EVT_BUTTON, self._onFitHelp) 291 291 292 292 # Resolution Smearing Help button (for now use same technique as 293 293 # used for dI help to get tiniest possible button that works … … 303 303 self.btSmearHelp.SetToolTipString("Resolution smearing help.") 304 304 self.btSmearHelp.Bind(wx.EVT_BUTTON, self._onSmearHelp) 305 305 306 306 # textcntrl for custom resolution 307 307 self.smear_pinhole_percent = ModelTextCtrl(self, wx.ID_ANY, … … 564 564 sizer.Add(self.draw_button, 0, 0) 565 565 sizer.Add((-1, 5)) 566 566 567 567 sizer.Add(self.tcChi, 0, 0) 568 568 sizer.Add(self.Npts_fit, 0, 0) … … 570 570 sizer.Add(self.btFit, 0, 0) 571 571 sizer.Add(self.btFitHelp, 0, 0) 572 572 573 573 boxsizer_range.Add(sizer_chi2) 574 574 boxsizer_range.Add(sizer) … … 2188 2188 self.save_current_state() 2189 2189 2190 if not self.is_mac: 2191 self.Layout() 2192 self.Refresh() 2190 2193 # plot model ( when drawing, do not update chisqr value again) 2191 2194 self._draw_model(update_chisqr=False, source='fit') … … 2782 2785 else: 2783 2786 return cmp(a.lower(), b.lower()) 2784 2787 2785 2788 # keys obtained now from ordered dict, so commenting alphabetical 2786 2789 # ordering keys.sort(custom_compare) -
src/sas/sasgui/perspectives/fitting/fitpanel.py
r67b0a99 r6f9abd3 501 501 if data is None: 502 502 return None 503 focused_page = self.GetPage(self.GetSelection()) 503 504 for page in self.opened_pages.values(): 504 505 # check if the selected data existing in the fitpanel 505 506 pos = self.GetPageIndex(page) 506 507 if not check_data_validity(page.get_data()) and not page.batch_on: 508 if page.model is not None and page != focused_page: 509 # Page has an active theory and is in background - don't 510 # send data here. 511 continue 507 512 # make sure data get placed in 1D empty tab if data is 1D 508 513 # else data get place on 2D tab empty tab -
src/sas/sasgui/perspectives/fitting/fitting.py
r2504b5a r2504b5a 1337 1337 1338 1338 is_data2d = issubclass(data.__class__, Data2D) 1339 # check consistency of arrays1339 # Check consistency of arrays 1340 1340 if not is_data2d: 1341 1341 if len(res.theory) == len(res.index[res.index]) and \ … … 1348 1348 new_theory[res.index == False] = np.nan 1349 1349 correct_result = True 1350 # get all fittable parameters of the current model1350 # Get all fittable parameters of the current model 1351 1351 param_list = model.getParamList() 1352 1352 for param in model.getDispParamList(): 1353 if not model.is_fittable(param) and \ 1353 if '.' in param and param in param_list: 1354 # Ensure polydispersity results are displayed 1355 p1, p2 = param.split('.') 1356 if not model.is_fittable(p1) and not (p2 == 'width' and param in res.param_list)\ 1357 and param in param_list: 1358 param_list.remove(param) 1359 elif not model.is_fittable(param) and \ 1354 1360 param in param_list: 1355 1361 param_list.remove(param) … … 1372 1378 batch_outputs["Chi2"].append(ERROR) 1373 1379 for param in param_list: 1374 # save value of fixed parameters1380 # Save value of fixed parameters 1375 1381 if param not in res.param_list: 1376 1382 batch_outputs[str(param)].append(ERROR) 1377 1383 else: 1378 # save only fitted values1384 # Save only fitted values 1379 1385 batch_outputs[param].append(ERROR) 1380 1386 batch_inputs["error on %s" % str(param)].append(ERROR) -
src/sas/sasgui/perspectives/fitting/media/fitting_help.rst
r05b0bf6 rca383a0 195 195 the :ref:`Advanced_Plugin_Editor` . 196 196 197 **SasView version 4.2** made it possible to specify whether a plugin created with 198 the *New Plugin Model* dialog is actually a form factor P(Q) or a structure factor 199 S(Q). To do this, simply add one or other of the following lines under the *import* 200 statements. 201 202 For a form factor:: 203 204 form_factor = True 205 206 or for a structure factor:: 207 208 structure_factor = True 209 210 If the plugin is a structure factor it is *also* necessary to add two variables to 211 the parameter list:: 212 213 parameters = [ 214 ['radius_effective', '', 1, [0.0, numpy.inf], 'volume', ''], 215 ['volfraction', '', 1, [0.0, 1.0], '', ''], 216 [...], 217 218 and to the declarations of the functions Iq and Iqxy::: 219 220 def Iq(x , radius_effective, volfraction, ...): 221 222 def Iqxy(x, y, radius_effective, volfraction, ...): 223 224 Such a plugin should then be available in the S(Q) drop-down box on a FitPage (once 225 a P(Q) model has been selected). 226 197 227 Sum|Multi(p1,p2) 198 228 ^^^^^^^^^^^^^^^^ … … 206 236 or:: 207 237 208 Plugin Model = scale_factor * model_1 /* model_2+ background238 Plugin Model = scale_factor * (model1 * model2) + background 209 239 210 240 In the *Easy Sum/Multi Editor* give the new model a function name and brief 211 241 description (to appear under the *Details* button on the *FitPage*). Then select 212 242 two existing models, as p1 and p2, and the required operator, '+' or '*' between 213 them. Finally, click the *Apply* button to generate the model and then click *Close*. 214 215 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. 243 them. Finally, click the *Apply* button to generate and test the model and then click *Close*. 244 245 Any changes to a plugin model generated in this way only become effective *after* it is re-selected 246 from the plugin models drop-down menu on the FitPage. If the model is not listed you can force a 247 recompilation of the plugins by selecting *Fitting* > *Plugin Model Operations* > *Load Plugin Models*. 248 249 **SasView version 4.2** introduced a much simplified and more extensible structure for plugin models 250 generated through the Easy Sum/Multi Editor. For example, the code for a combination of a sphere model 251 with a power law model now looks like this:: 252 253 from sasmodels.core import load_model_info 254 from sasmodels.sasview_model import make_model_from_info 255 256 model_info = load_model_info('sphere+power_law') 257 model_info.name = 'MyPluginModel' 258 model_info.description = 'sphere + power_law' 259 Model = make_model_from_info(model_info) 260 261 To change the models or operators contributing to this plugin it is only necessary to edit the string 262 in the brackets after *load_model_info*, though it would also be a good idea to update the model name 263 and description too!!! 264 265 The model specification string can handle multiple models and combinations of operators (+ or *) which 266 are processed according to normal conventions. Thus 'model1+model2*model3' would be valid and would 267 multiply model2 by model3 before adding model1. In this example, parameters in the *FitPage* would be 268 prefixed A (for model2), B (for model3) and C (for model1). Whilst this might appear a little 269 confusing, unless you were creating a plugin model from multiple instances of the same model the parameter 270 assignments ought to be obvious when you load the plugin. 271 272 If you need to include another plugin model in the model specification string, just prefix the name of 273 that model with *custom*. For instance:: 274 275 sphere+custom.MyPluginModel 276 277 To create a P(Q)*\S(Q) model use the @ symbol instead of * like this:: 278 279 sphere@hardsphere 280 281 This streamlined approach to building complex plugin models from existing library models, or models 282 available on the *Model Marketplace*, also permits the creation of P(Q)*\S(Q) plugin models, something 283 that was not possible in earlier versions of SasView. 216 284 217 285 .. _Advanced_Plugin_Editor: -
src/sas/sasgui/perspectives/fitting/media/plugin.rst
r72100ee re081946 18 18 * By writing a model from scratch outside of SasView (only recommended for 19 19 code monkeys!) 20 21 **What follows below is quite technical. If you just want a helping hand to get 22 started creating your own models see** :ref:`Adding_your_own_models`. 20 23 21 24 Overview -
test/corfunc/test/utest_corfunc.py
r253eb6c6 r968d67e 17 17 upperq=(0.15, 0.24)) 18 18 self.extrapolation = None 19 self.transformation = None 19 20 20 21 def extrapolate(self):
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