Changes in / [2746eab:f80b416e] in sasview
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docs/sphinx-docs/source/conf.py
r96f00a0 r96f00a0 80 80 version = '4.1' 81 81 # The full version, including alpha/beta/rc tags. 82 release = '4.1. 0'82 release = '4.1.2' 83 83 84 84 # The language for content autogenerated by Sphinx. Refer to documentation -
sasview/README.txt
r311d00a r6394851 4 4 1- Features 5 5 =========== 6 - New in Version 4.1.2 7 -------------------- 8 This point release is a bug-fix release addressing: 9 10 - Fixes #984: PDF Reports Generate Empty PDFs 11 - Fixes a path typo 12 - 64 bit and 32 bit Windows executables now available 13 14 It is recommended that all users upgrade to this version 15 16 - New in Version 4.1.1 17 -------------------- 18 This point release is a bug-fix release addressing: 19 20 - Fixes #948: Mathjax CDN is going away 21 - Fixes #938: Cannot read canSAS1D file output by SasView 22 - Fixes #960: Save project throws error if empty fit page 23 - Fixes #929: Problem deleting data in first fit page 24 - Fixes #918: Test folders not bundled with release 25 - Fixes an issue with the live discovery of plugin models 26 - Fixes an issue with the NXcanSAS data loader 27 - Updated tutorials for SasView 4.x.y 28 6 29 - New in Version 4.1.0 7 30 ------------------ -
sasview/__init__.py
r463e7ffc r6394851 1 __version__ = "4.1 "1 __version__ = "4.1.2" 2 2 __build__ = "GIT_COMMIT" 3 3 -
sasview/local_config.py
ra1b8fee rd908932 47 47 '''This work benefited from the use of the SasView application, originally developed under NSF Award DMR-0520547. SasView also contains code developed with funding from the EU Horizon 2020 programme under the SINE2020 project Grant No 654000.''' 48 48 _acknowledgement_citation = \ 49 '''M. Doucet et al. SasView Version 4.1 , Zenodo, 10.5281/zenodo.438138'''49 '''M. Doucet et al. SasView Version 4.1.2, Zenodo, 10.5281/zenodo.825675''' 50 50 51 51 _acknowledgement = \ -
sasview/sasview.spec
re42c8e9d r945f45d 138 138 'sasmodels.core', 139 139 'pyopencl', 140 'tinycc' 140 'tinycc', 141 'xhtml2pdf' 141 142 ] 142 143 -
sasview/setup_exe.py
ra1b8fee r3563e06 179 179 test_1d_dir = os.path.join(path, "test\\1d_data") 180 180 test_2d_dir = os.path.join(path, "test\\2d_data") 181 test_sesans_dir = os.path.join(path, "test\\sesans_data") 182 test_convertible_dir = os.path.join(path, "test\\convertible_files") 181 183 test_save_dir = os.path.join(path, "test\\save_states") 182 test_upcoming_dir = os.path.join(path, "test\\upcoming_formats") 184 test_coord_dir = os.path.join(path, "test\\coordinate_data") 185 test_image_dir = os.path.join(path, "test\\image_data") 186 test_other_dir = os.path.join(path, "test\\other_files") 183 187 184 188 matplotlibdatadir = matplotlib.get_data_path() … … 269 273 # Copying the images directory to the distribution directory. 270 274 for f in findall(images_dir): 271 if not ".svn" in f: 272 data_files.append(("images", [f])) 275 data_files.append(("images", [f])) 273 276 274 277 # Copying the HTML help docs 275 278 for f in findall(media_dir): 276 if not ".svn" in f: 277 data_files.append(("media", [f])) 279 data_files.append(("media", [f])) 278 280 279 281 # Copying the sample data user data 280 282 for f in findall(test_1d_dir): 281 if not ".svn" in f: 282 data_files.append(("test\\1d_data", [f])) 283 284 # Copying the sample data user data 283 data_files.append(("test\\1d_data", [f])) 285 284 for f in findall(test_2d_dir): 286 if not ".svn" in f: 287 data_files.append(("test\\2d_data", [f])) 288 289 # Copying the sample data user data 285 data_files.append(("test\\2d_data", [f])) 290 286 for f in findall(test_save_dir): 291 if not ".svn" in f: 292 data_files.append(("test\\save_states", [f])) 293 294 # Copying the sample data user data 295 for f in findall(test_upcoming_dir): 296 if not ".svn" in f: 297 data_files.append(("test\\upcoming_formats", [f])) 287 data_files.append(("test\\save_states", [f])) 288 for f in findall(test_sesans_dir): 289 data_files.append(("test\\sesans_data", [f])) 290 for f in findall(test_convertible_dir): 291 data_files.append(("test\\convertible_files", [f])) 292 for f in findall(test_coord_dir): 293 data_files.append(("test\\coordinate_data", [f])) 294 for f in findall(test_image_dir): 295 data_files.append(("test\\image_data", [f])) 296 for f in findall(test_other_dir): 297 data_files.append(("test\\other_files", [f])) 298 298 299 299 # Copying opencl include files -
src/sas/sascalc/corfunc/corfunc_calculator.py
rff11b21 ra859f99 34 34 35 35 def __call__(self, x): 36 if self._lastx == [] or x.tolist() != self._lastx.tolist(): 36 # If input is a single number, evaluate the function at that number 37 # and return a single number 38 if type(x) == float or type(x) == int: 39 return self._smoothed_function(np.array([x]))[0] 40 # If input is a list, and is different to the last input, evaluate 41 # the function at each point. If the input is the same as last time 42 # the function was called, return the result that was calculated 43 # last time instead of explicity evaluating the function again. 44 elif self._lastx == [] or x.tolist() != self._lastx.tolist(): 37 45 self._lasty = self._smoothed_function(x) 38 46 self._lastx = x … … 121 129 extrapolation = Data1D(qs, iqs) 122 130 123 return params, extrapolation 131 return params, extrapolation, s2 124 132 125 133 def compute_transform(self, extrapolation, trans_type, background=None, … … 131 139 :param background: The background value (if not provided, previously 132 140 calculated value will be used) 141 :param extrap_fn: A callable function representing the extraoplated data 133 142 :param completefn: The function to call when the transform calculation 134 is complete `143 is complete 135 144 :param updatefn: The function to call to update the GUI with the status 136 145 of the transform calculation … … 144 153 if trans_type == 'fourier': 145 154 self._transform_thread = FourierThread(self._data, extrapolation, 146 background, completefn=completefn, updatefn=updatefn) 155 background, completefn=completefn, 156 updatefn=updatefn) 147 157 elif trans_type == 'hilbert': 148 158 self._transform_thread = HilbertThread(self._data, extrapolation, -
src/sas/sascalc/corfunc/transform_thread.py
rd03228e ra859f99 2 2 from sas.sascalc.dataloader.data_info import Data1D 3 3 from scipy.fftpack import dct 4 from scipy.integrate import trapz, cumtrapz 4 5 import numpy as np 5 6 from time import sleep … … 13 14 self.extrapolation = extrapolated_data 14 15 16 def check_if_cancelled(self): 17 if self.isquit(): 18 self.update("Fourier transform cancelled.") 19 self.complete(transforms=None) 20 return True 21 return False 22 15 23 def compute(self): 16 24 qs = self.extrapolation.x … … 19 27 background = self.background 20 28 29 xs = np.pi*np.arange(len(qs),dtype=np.float32)/(q[1]-q[0])/len(qs) 30 21 31 self.ready(delay=0.0) 22 self.update(msg=" Starting Fourier transform.")32 self.update(msg="Fourier transform in progress.") 23 33 self.ready(delay=0.0) 24 if self.isquit(): 25 34 35 if self.check_if_cancelled(): return 26 36 try: 27 gamma = dct((iqs-background)*qs**2) 28 gamma = gamma / gamma.max() 29 except: 37 # ----- 1D Correlation Function ----- 38 gamma1 = dct((iqs-background)*qs**2) 39 Q = gamma1.max() 40 gamma1 /= Q 41 42 if self.check_if_cancelled(): return 43 44 # ----- 3D Correlation Function ----- 45 # gamma3(R) = 1/R int_{0}^{R} gamma1(x) dx 46 # trapz uses the trapezium rule to calculate the integral 47 mask = xs <= 200.0 # Only calculate gamma3 up to x=200 (as this is all that's plotted) 48 # gamma3 = [trapz(gamma1[:n], xs[:n])/xs[n-1] for n in range(2, len(xs[mask]) + 1)]j 49 # gamma3.insert(0, 1.0) # Gamma_3(0) is defined as 1 50 n = len(xs[mask]) 51 gamma3 = cumtrapz(gamma1[:n], xs[:n])/xs[1:n] 52 gamma3 = np.hstack((1.0, gamma3)) # Gamma_3(0) is defined as 1 53 54 if self.check_if_cancelled(): return 55 56 # ----- Interface Distribution function ----- 57 idf = dct(-qs**4 * (iqs-background)) 58 59 if self.check_if_cancelled(): return 60 61 # Manually calculate IDF(0.0), since scipy DCT tends to give us a 62 # very large negative value. 63 # IDF(x) = int_0^inf q^4 * I(q) * cos(q*x) * dq 64 # => IDF(0) = int_0^inf q^4 * I(q) * dq 65 idf[0] = trapz(-qs**4 * (iqs-background), qs) 66 idf /= Q # Normalise using scattering invariant 67 68 except Exception as e: 69 import logging 70 logger = logging.getLogger(__name__) 71 logger.error(e) 72 30 73 self.update(msg="Fourier transform failed.") 31 self.complete(transform =None)74 self.complete(transforms=None) 32 75 return 33 76 if self.isquit(): … … 35 78 self.update(msg="Fourier transform completed.") 36 79 37 xs = np.pi*np.arange(len(qs),dtype=np.float32)/(q[1]-q[0])/len(qs) 38 transform = Data1D(xs, gamma) 80 transform1 = Data1D(xs, gamma1) 81 transform3 = Data1D(xs[xs <= 200], gamma3) 82 idf = Data1D(xs, idf) 39 83 40 self.complete(transform=transform) 84 transforms = (transform1, transform3, idf) 85 86 self.complete(transforms=transforms) 41 87 42 88 class HilbertThread(CalcThread): … … 64 110 self.update(msg="Hilbert transform completed.") 65 111 66 self.complete(transform =None)112 self.complete(transforms=None) -
src/sas/sascalc/dataloader/file_reader_base_class.py
ra78a02f rae69c690 115 115 data.y = np.asarray([data.y[i] for i in ind]).astype(np.float64) 116 116 if data.dx is not None: 117 if len(data.dx) == 0: 118 data.dx = None 119 continue 117 120 data.dx = np.asarray([data.dx[i] for i in ind]).astype(np.float64) 118 121 if data.dxl is not None: … … 121 124 data.dxw = np.asarray([data.dxw[i] for i in ind]).astype(np.float64) 122 125 if data.dy is not None: 126 if len(data.dy) == 0: 127 data.dy = None 128 continue 123 129 data.dy = np.asarray([data.dy[i] for i in ind]).astype(np.float64) 124 130 if data.lam is not None: … … 185 191 self.output = [] 186 192 187 def remove_empty_q_values(self, has_error_dx=False, has_error_dy=False): 193 def remove_empty_q_values(self, has_error_dx=False, has_error_dy=False, 194 has_error_dxl=False, has_error_dxw=False): 188 195 """ 189 196 Remove any point where Q == 0 … … 192 199 self.current_dataset.x = self.current_dataset.x[x != 0] 193 200 self.current_dataset.y = self.current_dataset.y[x != 0] 194 self.current_dataset.dy = self.current_dataset.dy[x != 0] if \ 195 has_error_dy else np.zeros(len(self.current_dataset.y)) 196 self.current_dataset.dx = self.current_dataset.dx[x != 0] if \ 197 has_error_dx else np.zeros(len(self.current_dataset.x)) 201 if has_error_dy: 202 self.current_dataset.dy = self.current_dataset.dy[x != 0] 203 if has_error_dx: 204 self.current_dataset.dx = self.current_dataset.dx[x != 0] 205 if has_error_dxl: 206 self.current_dataset.dxl = self.current_dataset.dxl[x != 0] 207 if has_error_dxw: 208 self.current_dataset.dxw = self.current_dataset.dxw[x != 0] 198 209 199 210 def reset_data_list(self, no_lines=0): … … 204 215 x = np.zeros(no_lines) 205 216 y = np.zeros(no_lines) 217 dx = np.zeros(no_lines) 206 218 dy = np.zeros(no_lines) 207 dx = np.zeros(no_lines)208 219 self.current_dataset = plottable_1D(x, y, dx, dy) 209 220 -
src/sas/sascalc/dataloader/readers/cansas_reader.py
ra78a02f rae69c690 130 130 self.current_datainfo.meta_data[PREPROCESS] = self.processing_instructions 131 131 self._parse_entry(entry) 132 has_error_dx = self.current_dataset.dx is not None 133 has_error_dy = self.current_dataset.dy is not None 134 self.remove_empty_q_values(has_error_dx=has_error_dx, 135 has_error_dy=has_error_dy) 136 self.send_to_output() # Combine datasets with DataInfo 137 self.current_datainfo = DataInfo() # Reset DataInfo 132 self.data_cleanup() 138 133 except FileContentsException as fc_exc: 139 134 # File doesn't meet schema - try loading with a less strict schema … … 154 149 self.load_file_and_schema(xml_file) # Reload strict schema so we can find where error are in file 155 150 invalid_xml = self.find_invalid_xml() 156 invalid_xml = INVALID_XML.format(basename + self.extension) + invalid_xml 157 raise DataReaderException(invalid_xml) # Handled by base class 151 if invalid_xml != "": 152 invalid_xml = INVALID_XML.format(basename + self.extension) + invalid_xml 153 raise DataReaderException(invalid_xml) # Handled by base class 158 154 except FileContentsException as fc_exc: 159 155 msg = "CanSAS Reader could not load the file {}".format(xml_file) … … 279 275 # I and Q points 280 276 elif tagname == 'I' and isinstance(self.current_dataset, plottable_1D): 281 unit_list = unit.split("|") 282 if len(unit_list) > 1: 283 self.current_dataset.yaxis(unit_list[0].strip(), 284 unit_list[1].strip()) 285 else: 286 self.current_dataset.yaxis("Intensity", unit) 277 self.current_dataset.yaxis("Intensity", unit) 287 278 self.current_dataset.y = np.append(self.current_dataset.y, data_point) 288 279 elif tagname == 'Idev' and isinstance(self.current_dataset, plottable_1D): 289 280 self.current_dataset.dy = np.append(self.current_dataset.dy, data_point) 290 281 elif tagname == 'Q': 291 unit_list = unit.split("|") 292 if len(unit_list) > 1: 293 self.current_dataset.xaxis(unit_list[0].strip(), 294 unit_list[1].strip()) 295 else: 296 self.current_dataset.xaxis("Q", unit) 282 self.current_dataset.xaxis("Q", unit) 297 283 self.current_dataset.x = np.append(self.current_dataset.x, data_point) 298 284 elif tagname == 'Qdev': 299 285 self.current_dataset.dx = np.append(self.current_dataset.dx, data_point) 300 286 elif tagname == 'dQw': 301 if self.current_dataset.dxw is None: 302 self.current_dataset.dxw = np.empty(0) 303 self.current_dataset.dxw = np.append(self.current_dataset.dxw, data_point) 287 self.current_dataset.dxw = np.append(self.current_dataset.dxw, data_point) 304 288 elif tagname == 'dQl': 305 if self.current_dataset.dxl is None:306 self.current_dataset.dxl = np.empty(0)307 289 self.current_dataset.dxl = np.append(self.current_dataset.dxl, data_point) 308 290 elif tagname == 'Qmean': … … 312 294 elif tagname == 'Sesans': 313 295 self.current_datainfo.isSesans = bool(data_point) 296 self.current_dataset.xaxis(attr.get('x_axis'), 297 attr.get('x_unit')) 298 self.current_dataset.yaxis(attr.get('y_axis'), 299 attr.get('y_unit')) 314 300 elif tagname == 'yacceptance': 315 301 self.current_datainfo.sample.yacceptance = (data_point, unit) … … 512 498 for error in self.errors: 513 499 self.current_datainfo.errors.add(error) 514 self.errors.clear() 515 self.send_to_output() 500 self.data_cleanup() 501 self.sort_one_d_data() 502 self.sort_two_d_data() 503 self.reset_data_list() 516 504 empty = None 517 505 return self.output[0], empty 506 507 def data_cleanup(self): 508 """ 509 Clean up the data sets and refresh everything 510 :return: None 511 """ 512 has_error_dx = self.current_dataset.dx is not None 513 has_error_dxl = self.current_dataset.dxl is not None 514 has_error_dxw = self.current_dataset.dxw is not None 515 has_error_dy = self.current_dataset.dy is not None 516 self.remove_empty_q_values(has_error_dx=has_error_dx, 517 has_error_dxl=has_error_dxl, 518 has_error_dxw=has_error_dxw, 519 has_error_dy=has_error_dy) 520 self.send_to_output() # Combine datasets with DataInfo 521 self.current_datainfo = DataInfo() # Reset DataInfo 518 522 519 523 def _is_call_local(self): … … 642 646 value_unit = local_unit 643 647 except KeyError: 644 err_msg = "CanSAS reader: unexpected " 645 err_msg += "\"{0}\" unit [{1}]; " 646 err_msg = err_msg.format(tagname, local_unit) 647 err_msg += "expecting [{0}]".format(default_unit) 648 # Do not throw an error for loading Sesans data in cansas xml 649 # This is a temporary fix. 650 if local_unit != "A" and local_unit != 'pol': 651 err_msg = "CanSAS reader: unexpected " 652 err_msg += "\"{0}\" unit [{1}]; " 653 err_msg = err_msg.format(tagname, local_unit) 654 err_msg += "expecting [{0}]".format(default_unit) 648 655 value_unit = local_unit 649 656 except: … … 675 682 di_exists = True 676 683 if dqw_exists and not dql_exists: 677 array_size = self.current_dataset.dxw.size - 1 678 self.current_dataset.dxl = np.append(self.current_dataset.dxl, 679 np.zeros([array_size])) 684 array_size = self.current_dataset.dxw.size 685 self.current_dataset.dxl = np.zeros(array_size) 680 686 elif dql_exists and not dqw_exists: 681 array_size = self.current_dataset.dxl.size - 1 682 self.current_dataset.dxw = np.append(self.current_dataset.dxw, 683 np.zeros([array_size])) 687 array_size = self.current_dataset.dxl.size 688 self.current_dataset.dxw = np.zeros(array_size) 684 689 elif not dql_exists and not dqw_exists and not dq_exists: 685 array_size = self.current_dataset.x.size - 1690 array_size = self.current_dataset.x.size 686 691 self.current_dataset.dx = np.append(self.current_dataset.dx, 687 692 np.zeros([array_size])) 688 693 if not di_exists: 689 array_size = self.current_dataset.y.size - 1694 array_size = self.current_dataset.y.size 690 695 self.current_dataset.dy = np.append(self.current_dataset.dy, 691 696 np.zeros([array_size])) … … 857 862 node.append(point) 858 863 self.write_node(point, "Q", datainfo.x[i], 859 {'unit': datainfo. _xaxis + " | " + datainfo._xunit})864 {'unit': datainfo.x_unit}) 860 865 if len(datainfo.y) >= i: 861 866 self.write_node(point, "I", datainfo.y[i], 862 {'unit': datainfo. _yaxis + " | " + datainfo._yunit})867 {'unit': datainfo.y_unit}) 863 868 if datainfo.dy is not None and len(datainfo.dy) > i: 864 869 self.write_node(point, "Idev", datainfo.dy[i], 865 {'unit': datainfo. _yaxis + " | " + datainfo._yunit})870 {'unit': datainfo.y_unit}) 866 871 if datainfo.dx is not None and len(datainfo.dx) > i: 867 872 self.write_node(point, "Qdev", datainfo.dx[i], 868 {'unit': datainfo. _xaxis + " | " + datainfo._xunit})873 {'unit': datainfo.x_unit}) 869 874 if datainfo.dxw is not None and len(datainfo.dxw) > i: 870 875 self.write_node(point, "dQw", datainfo.dxw[i], 871 {'unit': datainfo. _xaxis + " | " + datainfo._xunit})876 {'unit': datainfo.x_unit}) 872 877 if datainfo.dxl is not None and len(datainfo.dxl) > i: 873 878 self.write_node(point, "dQl", datainfo.dxl[i], 874 {'unit': datainfo. _xaxis + " | " + datainfo._xunit})879 {'unit': datainfo.x_unit}) 875 880 if datainfo.isSesans: 876 sesans = self.create_element("Sesans") 881 sesans_attrib = {'x_axis': datainfo._xaxis, 882 'y_axis': datainfo._yaxis, 883 'x_unit': datainfo.x_unit, 884 'y_unit': datainfo.y_unit} 885 sesans = self.create_element("Sesans", attrib=sesans_attrib) 877 886 sesans.text = str(datainfo.isSesans) 878 node.append(sesans)879 self.write_node( node, "yacceptance", datainfo.sample.yacceptance[0],887 entry_node.append(sesans) 888 self.write_node(entry_node, "yacceptance", datainfo.sample.yacceptance[0], 880 889 {'unit': datainfo.sample.yacceptance[1]}) 881 self.write_node( node, "zacceptance", datainfo.sample.zacceptance[0],890 self.write_node(entry_node, "zacceptance", datainfo.sample.zacceptance[0], 882 891 {'unit': datainfo.sample.zacceptance[1]}) 883 892 -
src/sas/sascalc/dataloader/readers/cansas_reader_HDF5.py
rdcb91cf rc9ecd1b 140 140 141 141 if isinstance(value, h5py.Group): 142 # Set parent class before recursion 142 143 self.parent_class = class_name 143 144 parent_list.append(key) … … 150 151 # Recursion step to access data within the group 151 152 self.read_children(value, parent_list) 153 # Reset parent class when returning from recursive method 154 self.parent_class = class_name 152 155 self.add_intermediate() 153 156 parent_list.remove(key) -
src/sas/sascalc/dataloader/readers/xml_reader.py
rfafe52a rfafe52a 134 134 first_error = schema.assertValid(self.xmldoc) 135 135 except etree.DocumentInvalid as err: 136 # Suppress errors for <'any'> elements 137 if "##other" in str(err): 138 return first_error 136 139 first_error = str(err) 137 140 return first_error -
src/sas/sascalc/invariant/invariant.py
r7432acb rb1f20d1 610 610 # Data boundaries for fitting 611 611 qmin = self._data.x[0] 612 qmax = self._data.x[ self._low_extrapolation_npts - 1]612 qmax = self._data.x[int(self._low_extrapolation_npts - 1)] 613 613 614 614 # Extrapolate the low-Q data … … 649 649 # Data boundaries for fitting 650 650 x_len = len(self._data.x) - 1 651 qmin = self._data.x[ x_len - (self._high_extrapolation_npts - 1)]652 qmax = self._data.x[ x_len]651 qmin = self._data.x[int(x_len - (self._high_extrapolation_npts - 1))] 652 qmax = self._data.x[int(x_len)] 653 653 654 654 # fit the data with a model to get the appropriate parameters … … 688 688 if npts_in is None: 689 689 npts_in = self._low_extrapolation_npts 690 q_end = self._data.x[max(0, npts_in - 1)]690 q_end = self._data.x[max(0, int(npts_in - 1))] 691 691 692 692 if q_start >= q_end: … … 714 714 # Get extrapolation range 715 715 if npts_in is None: 716 npts_in = self._high_extrapolation_npts716 npts_in = int(self._high_extrapolation_npts) 717 717 _npts = len(self._data.x) 718 q_start = self._data.x[min(_npts, _npts - npts_in)]718 q_start = self._data.x[min(_npts, int(_npts - npts_in))] 719 719 720 720 if q_start >= q_end: -
src/sas/sasgui/guiframe/config.py
ra1b8fee rd908932 48 48 '''This work benefited from the use of the SasView application, originally developed under NSF Award DMR-0520547. SasView also contains code developed with funding from the EU Horizon 2020 programme under the SINE2020 project Grant No 654000.''' 49 49 _acknowledgement_citation = \ 50 '''M. Doucet et al. SasView Version 4.1 , Zenodo, 10.5281/zenodo.438138'''50 '''M. Doucet et al. SasView Version 4.1.2, Zenodo, 10.5281/zenodo.825675''' 51 51 52 52 _acknowledgement = \ -
src/sas/sasgui/guiframe/documentation_window.py
r2746eab r2746eab 99 99 elif not os.path.exists(file_path): 100 100 url = "index.html" 101 logger.error("Could not find Sphinx documentation at %s \102 -- has it been built?",file_path)101 logger.error("Could not find Sphinx documentation at %s -- has it been built?", 102 file_path) 103 103 elif False: 104 104 start_documentation_server(docs_path, port=7999) … … 107 107 url = "file:///" + urllib.quote(file_path, r'/\:')+ url_instruction 108 108 109 logger.info("showing url " + url)109 #logger.info("showing url " + url) 110 110 if WX_SUPPORTS_HTML2: 111 111 # Complete HTML/CSS support! -
src/sas/sasgui/perspectives/corfunc/corfunc.py
r463e7ffc r9b90bf8 189 189 # Show the transformation as a curve instead of points 190 190 new_plot.symbol = GUIFRAME_ID.CURVE_SYMBOL_NUM 191 elif label == IDF_LABEL: 192 new_plot.xaxis("{x}", 'A') 193 new_plot.yaxis("{g_1}", '') 194 # Linear scale 195 new_plot.xtransform = 'x' 196 new_plot.ytransform = 'y' 197 group_id = GROUP_ID_IDF 198 # Show IDF as a curve instead of points 199 new_plot.symbol = GUIFRAME_ID.CURVE_SYMBOL_NUM 191 200 new_plot.id = label 192 201 new_plot.name = label -
src/sas/sasgui/perspectives/corfunc/corfunc_panel.py
r7432acb r2a399ca 20 20 21 21 OUTPUT_STRINGS = { 22 'max': "Long Period (A): ",22 'max': "Long Period / 2 (A): ", 23 23 'Lc': "Average Hard Block Thickness (A): ", 24 24 'dtr': "Average Interface Thickness (A): ", … … 55 55 self._data = data # The data to be analysed (corrected fr background) 56 56 self._extrapolated_data = None # The extrapolated data set 57 # Callable object of class CorfuncCalculator._Interpolator representing 58 # the extrapolated and interpolated data 59 self._extrapolated_fn = None 57 60 self._transformed_data = None # Fourier trans. of the extrapolated data 58 61 self._calculator = CorfuncCalculator() … … 218 221 219 222 try: 220 params, self._extrapolated_data = self._calculator.compute_extrapolation() 223 params, self._extrapolated_data, self._extrapolated_fn = \ 224 self._calculator.compute_extrapolation() 221 225 except Exception as e: 222 226 msg = "Error extrapolating data:\n" … … 257 261 StatusEvent(status=msg)) 258 262 259 def transform_complete(self, transform =None):263 def transform_complete(self, transforms=None): 260 264 """ 261 265 Called from FourierThread when calculation has completed 262 266 """ 263 267 self._transform_btn.SetLabel("Transform") 264 if transform is None:268 if transforms is None: 265 269 msg = "Error calculating Transform." 266 270 if self.transform_type == 'hilbert': … … 270 274 self._extract_btn.Disable() 271 275 return 272 self._transformed_data = transform 273 import numpy as np 274 plot_x = transform.x[np.where(transform.x <= 200)] 275 plot_y = transform.y[np.where(transform.x <= 200)] 276 277 self._transformed_data = transforms 278 (transform1, transform3, idf) = transforms 279 plot_x = transform1.x[transform1.x <= 200] 280 plot_y = transform1.y[transform1.x <= 200] 276 281 self._manager.show_data(Data1D(plot_x, plot_y), TRANSFORM_LABEL1) 282 # No need to shorten gamma3 as it's only calculated up to x=200 283 self._manager.show_data(transform3, TRANSFORM_LABEL3) 284 285 plot_x = idf.x[idf.x <= 200] 286 plot_y = idf.y[idf.x <= 200] 287 self._manager.show_data(Data1D(plot_x, plot_y), IDF_LABEL) 288 277 289 # Only enable extract params button if a fourier trans. has been done 278 290 if self.transform_type == 'fourier': … … 286 298 """ 287 299 try: 288 params = self._calculator.extract_parameters(self._transformed_data )300 params = self._calculator.extract_parameters(self._transformed_data[0]) 289 301 except: 290 302 params = None -
src/sas/sasgui/perspectives/corfunc/corfunc_state.py
r7432acb r2a399ca 28 28 # List of output parameters, used by __str__ 29 29 output_list = [ 30 ['max', "Long Period (A): "],30 ['max', "Long Period / 2 (A): "], 31 31 ['Lc', "Average Hard Block Thickness (A): "], 32 32 ['dtr', "Average Interface Thickness (A): "], … … 59 59 self.q = None 60 60 self.iq = None 61 # TODO: Add extrapolated data and transformed data (when implemented)62 61 63 62 def __str__(self): -
src/sas/sasgui/perspectives/corfunc/media/corfunc_help.rst
r6aad2e8 rd78b5cb 10 10 11 11 This performs a correlation function analysis of one-dimensional 12 SAXS/SANS data, or generates a model-independent volume fraction 12 SAXS/SANS data, or generates a model-independent volume fraction 13 13 profile from the SANS from an adsorbed polymer/surfactant layer. 14 14 15 A correlation function may be interpreted in terms of an imaginary rod moving 16 through the structure of the material. Î\ :sub:`1D`\ (R) is the probability that 17 a rod of length R moving through the material has equal electron/neutron scattering 18 length density at either end. Hence a frequently occurring spacing within a structure 15 A correlation function may be interpreted in terms of an imaginary rod moving 16 through the structure of the material. Î\ :sub:`1D`\ (R) is the probability that 17 a rod of length R moving through the material has equal electron/neutron scattering 18 length density at either end. Hence a frequently occurring spacing within a structure 19 19 manifests itself as a peak. 20 20 … … 30 30 * Fourier / Hilbert Transform of the smoothed data to give the correlation 31 31 function / volume fraction profile, respectively 32 * (Optional) Interpretation of the 1D correlation function based on an ideal 32 * (Optional) Interpretation of the 1D correlation function based on an ideal 33 33 lamellar morphology 34 34 … … 74 74 :align: center 75 75 76 76 77 77 Smoothing 78 78 --------- 79 79 80 The extrapolated data set consists of the Guinier back-extrapolation from Q~0 80 The extrapolated data set consists of the Guinier back-extrapolation from Q~0 81 81 up to the lowest Q value in the original data, then the original scattering data, and the Porod tail-fit beyond this. The joins between the original data and the Guinier/Porod fits are smoothed using the algorithm below to avoid the formation of ripples in the transformed data. 82 82 … … 93 93 h_i = \frac{1}{1 + \frac{(x_i-b)^2}{(x_i-a)^2}} 94 94 95 95 96 96 Transform 97 97 --------- … … 102 102 If "Fourier" is selected for the transform type, the analysis will perform a 103 103 discrete cosine transform on the extrapolated data in order to calculate the 104 correlation function 104 1D correlation function: 105 105 106 106 .. math:: … … 115 115 \left(n + \frac{1}{2} \right) k \right] } \text{ for } k = 0, 1, \ldots, 116 116 N-1, N 117 118 The 3D correlation function is also calculated: 119 120 .. math:: 121 \Gamma _{3D}(R) = \frac{1}{Q^{*}} \int_{0}^{\infty}I(q) q^{2} 122 \frac{sin(qR)}{qR} dq 117 123 118 124 Hilbert … … 165 171 .. figure:: profile1.png 166 172 :align: center 167 173 168 174 .. figure:: profile2.png 169 175 :align: center 170 176 171 177 172 178 References … … 191 197 ----- 192 198 Upon sending data for correlation function analysis, it will be plotted (minus 193 the background value), along with a *red* bar indicating the *upper end of the 199 the background value), along with a *red* bar indicating the *upper end of the 194 200 low-Q range* (used for back-extrapolation), and 2 *purple* bars indicating the range to be used for forward-extrapolation. These bars may be moved my clicking and 195 201 dragging, or by entering appropriate values in the Q range input boxes. … … 221 227 :align: center 222 228 223 229 224 230 .. note:: 225 231 This help document was last changed by Steve King, 08Oct2016 -
src/sas/sasgui/perspectives/corfunc/plot_labels.py
r1dc8ec9 r7dda833 4 4 5 5 GROUP_ID_TRANSFORM = r"$\Gamma(x)$" 6 TRANSFORM_LABEL1 = r"$\Gamma1(x)$" 7 TRANSFORM_LABEL3 = r"$\Gamma3(x)$" 6 TRANSFORM_LABEL1 = r"$\Gamma_1(x)$" 7 TRANSFORM_LABEL3 = r"$\Gamma_3(x)$" 8 9 GROUP_ID_IDF = r"$g_1(x)$" 10 IDF_LABEL = r"$g_1(x)$" -
src/sas/sasgui/perspectives/fitting/basepage.py
rb76e65a r33dc18f 1841 1841 if models.name != "NoStructure": 1842 1842 mlist.append((models.name, models)) 1843 1844 1843 # Sort the models 1845 1844 mlist_sorted = sorted(mlist) -
src/sas/sasgui/perspectives/fitting/fitpage.py
r0b6f83c r79e6a33 1156 1156 copy_flag = self.get_copy_params() 1157 1157 is_poly_enabled = self.enable_disp.GetValue() 1158 1159 self._on_select_model_helper() 1158 try: 1159 self._on_select_model_helper() 1160 except Exception as e: 1161 evt = StatusEvent(status=e.message, info="error") 1162 wx.PostEvent(self._manager.parent, evt) 1163 # Set S(Q) to None 1164 self.structurebox.SetSelection(0) 1165 self._on_select_model() 1166 return 1160 1167 self.set_model_param_sizer(self.model) 1161 1168 if self.model is None: … … 1236 1243 wx.PostEvent(self.parent, new_event) 1237 1244 # update list of plugins if new plugin is available 1238 custom_model = CUSTOM_MODEL1239 1245 mod_cat = self.categorybox.GetStringSelection() 1240 if mod_cat == custom_model: 1246 if mod_cat == CUSTOM_MODEL: 1247 temp_id = self.model.id 1241 1248 temp = self.parent.update_model_list() 1249 for v in self.parent.model_dictionary.values(): 1250 if v.id == temp_id: 1251 self.model = v() 1252 break 1242 1253 if temp: 1243 1254 self.model_list_box = temp -
src/sas/sasgui/perspectives/fitting/fitpanel.py
r6f9abd3 rc9ecd1b 92 92 # state must be cloned 93 93 state = page.get_state().clone() 94 if data is not None or page.model is not None: 94 # data_list only populated with real data 95 # Fake object in data from page.get_data() if model is selected 96 if len(page.data_list) is not 0 and page.model is not None: 95 97 new_doc = self._manager.state_reader.write_toXML(data, 96 98 state, 97 99 batch_state) 100 # Fit #2 through #n are append to first fit 98 101 if doc is not None and hasattr(doc, "firstChild"): 99 child = new_doc.firstChild.firstChild 100 doc.firstChild.appendChild(child) 102 # Only append if properly formed new_doc 103 if new_doc is not None and hasattr(new_doc, "firstChild"): 104 child = new_doc.firstChild.firstChild 105 doc.firstChild.appendChild(child) 106 # First fit defines the main document 101 107 else: 102 108 doc = new_doc … … 395 401 temp_data = page.get_data() 396 402 if temp_data is not None and temp_data.id in data: 397 self.SetSelection(pos) 398 self.on_close_page(event=None) 399 temp = self.GetSelection() 400 self.DeletePage(temp) 403 self.close_page_with_data(temp_data) 401 404 if self.sim_page is not None: 402 405 if len(self.sim_page.model_list) == 0: … … 404 407 self.SetSelection(pos) 405 408 self.on_close_page(event=None) 406 temp = self.GetSelection() 407 self.DeletePage(temp) 409 self.DeletePage(pos) 408 410 self.sim_page = None 409 411 self.batch_on = False -
src/sas/sasgui/perspectives/fitting/fitting.py
r2d9526d r2504b5a 357 357 else: 358 358 page.formfactorbox.SetLabel(current_val) 359 if hasattr(page, 'structurebox'): 360 selected_name = page.structurebox.GetStringSelection() 361 362 page.structurebox.Clear() 363 page.initialize_combox() 364 365 index = page.structurebox.FindString(selected_name) 366 if index == -1: 367 index = 0 368 page.structurebox.SetSelection(index) 369 page._on_select_model() 359 370 except: 360 371 logger.error("update_custom_combo: %s", sys.exc_value) -
src/sas/sasgui/perspectives/fitting/models.py
rb1c2011 r632fda9 14 14 import py_compile 15 15 import shutil 16 from copy import copy 16 17 # Explicitly import from the pluginmodel module so that py2exe 17 18 # places it in the distribution. The Model1DPlugin class is used … … 20 21 from sas.sasgui.guiframe.CategoryInstaller import CategoryInstaller 21 22 from sasmodels.sasview_model import load_custom_model, load_standard_models 23 from sas.sasgui.perspectives.fitting.fitpage import CUSTOM_MODEL 22 24 23 25 logger = logging.getLogger(__name__) … … 265 267 temp = {} 266 268 if self.is_changed(): 267 return _find_models() 269 temp = _find_models() 270 self.last_time_dir_modified = time.time() 271 return temp 268 272 logger.info("plugin model : %s" % str(temp)) 269 273 return temp … … 278 282 """ 279 283 280 # regular model names only284 # Regular model names only 281 285 self.model_name_list = [] 282 286 283 # Build list automagically from sasmodels package287 # Build list automagically from sasmodels package 284 288 for model in load_standard_models(): 285 289 self.model_dictionary[model.name] = model … … 293 297 self.model_name_list.append(model.name) 294 298 295 # Looking for plugins299 # Looking for plugins 296 300 self.stored_plugins = self.findModels() 297 301 self.plugins = self.stored_plugins.values() 298 302 for name, plug in self.stored_plugins.iteritems(): 299 303 self.model_dictionary[name] = plug 304 # TODO: Remove 'hasattr' statements when old style plugin models 305 # are no longer supported. All sasmodels models will have 306 # the required attributes. 307 if hasattr(plug, 'is_structure_factor') and plug.is_structure_factor: 308 self.struct_list.append(plug) 309 self.plugins.remove(plug) 310 elif hasattr(plug, 'is_form_factor') and plug.is_form_factor: 311 self.multiplication_factor.append(plug) 312 if hasattr(plug, 'is_multiplicity_model') and plug.is_multiplicity_model: 313 self.multi_func_list.append(plug) 300 314 301 315 self._get_multifunc_models() … … 312 326 if os.path.isdir(plugin_dir): 313 327 temp = os.path.getmtime(plugin_dir) 314 if self.last_time_dir_modified !=temp:328 if self.last_time_dir_modified < temp: 315 329 is_modified = True 316 330 self.last_time_dir_modified = temp … … 323 337 new models were added else return empty dictionary 324 338 """ 339 self.plugins = [] 325 340 new_plugins = self.findModels() 326 if len(new_plugins) > 0: 327 for name, plug in new_plugins.iteritems(): 328 if name not in self.stored_plugins.keys(): 329 self.stored_plugins[name] = plug 330 self.plugins.append(plug) 331 self.model_dictionary[name] = plug 332 self.model_combobox.set_list("Plugin Models", self.plugins) 341 if new_plugins: 342 for name, plug in new_plugins.items(): 343 self.stored_plugins[name] = plug 344 self.plugins.append(plug) 345 self.model_dictionary[name] = plug 346 self.model_combobox.set_list(CUSTOM_MODEL, self.plugins) 333 347 return self.model_combobox.get_list() 334 348 else: … … 340 354 """ 341 355 self.plugins = [] 342 new_plugins = _find_models() 343 for name, plug in new_plugins.iteritems(): 344 for stored_name, stored_plug in self.stored_plugins.iteritems(): 345 if name == stored_name: 346 del self.stored_plugins[name] 347 del self.model_dictionary[name] 348 break 356 self.stored_plugins = _find_models() 357 structure_names = [model.name for model in self.struct_list] 358 form_names = [model.name for model in self.multiplication_factor] 359 360 # Remove all plugin structure factors and form factors 361 for name in copy(structure_names): 362 if '[plug-in]' in name: 363 i = structure_names.index(name) 364 del self.struct_list[i] 365 structure_names.remove(name) 366 for name in copy(form_names): 367 if '[plug-in]' in name: 368 i = form_names.index(name) 369 del self.multiplication_factor[i] 370 form_names.remove(name) 371 372 # Add new plugin structure factors and form factors 373 for name, plug in self.stored_plugins.iteritems(): 374 if plug.is_structure_factor: 375 if name in structure_names: 376 # Delete the old model from self.struct list 377 i = structure_names.index(name) 378 del self.struct_list[i] 379 # Add the new model to self.struct_list 380 self.struct_list.append(plug) 381 elif plug.is_form_factor: 382 if name in form_names: 383 # Delete the old model from self.multiplication_factor 384 i = form_names.index(name) 385 del self.multiplication_factor[i] 386 # Add the new model to self.multiplication_factor 387 self.multiplication_factor.append(plug) 388 389 # Add references to the updated model 349 390 self.stored_plugins[name] = plug 350 self.plugins.append(plug) 391 if not plug.is_structure_factor: 392 # Don't show S(Q) models in the 'Plugin Models' dropdown 393 self.plugins.append(plug) 351 394 self.model_dictionary[name] = plug 352 395 353 396 self.model_combobox.reset_list("Plugin Models", self.plugins) 397 self.model_combobox.reset_list("Structure Factors", self.struct_list) 398 self.model_combobox.reset_list("P(Q)*S(Q)", self.multiplication_factor) 399 354 400 return self.model_combobox.get_list() 355 401 -
src/sas/sasgui/perspectives/fitting/pagestate.py
r959eb01 rda9b239 617 617 value = "" 618 618 content = line.split(":") 619 if line == '' or len(content) == 1: 620 continue 619 621 name = content[0] 620 622 try: -
test/corfunc/test/utest_corfunc.py
r968d67e r86ba9d6 2 2 Unit Tests for CorfuncCalculator class 3 3 """ 4 from __future__ import division, print_function 4 5 5 6 import unittest 6 7 import time 8 7 9 import numpy as np 10 8 11 from sas.sascalc.corfunc.corfunc_calculator import CorfuncCalculator 9 12 from sas.sascalc.dataloader.data_info import Data1D … … 14 17 def setUp(self): 15 18 self.data = load_data() 19 # Note: to generate target values from the GUI: 20 # * load the data from test/corfunc/test/98929.txt 21 # * set qrange to (0, 0.013), (0.15, 0.24) 22 # * select fourier transform type 23 # * click Calculate Bg 24 # * click Extrapolate 25 # * click Compute Parameters 26 # * copy the Guinier and Porod values to the extrapolate function 27 # * for each graph, grab the data from DataInfo and store it in _out.txt 16 28 self.calculator = CorfuncCalculator(data=self.data, lowerq=0.013, 17 29 upperq=(0.15, 0.24)) 30 self.calculator.background = 0.3 18 31 self.extrapolation = None 19 32 self.transformation = None 33 self.results = [np.loadtxt(filename+"_out.txt").T[2] 34 for filename in ("gamma1", "gamma3", "idf")] 20 35 21 36 def extrapolate(self): 22 params, extrapolation = self.calculator.compute_extrapolation() 23 37 params, extrapolation, s2 = self.calculator.compute_extrapolation() 24 38 # Check the extrapolation parameters 25 self.assertAlmostEqual(params['A'], 4.1 9, places=2)26 self.assertAlmostEqual(params['B'], -254 70, places=0)27 self.assertAlmostEqual(params['K'], 4. 5e-5, places=2)28 self.assertAlmostEqual(params['sigma'], 2.2e-10, places=2)39 self.assertAlmostEqual(params['A'], 4.18970, places=5) 40 self.assertAlmostEqual(params['B'], -25469.9, places=1) 41 self.assertAlmostEqual(params['K'], 4.44660e-5, places=10) 42 #self.assertAlmostEqual(params['sigma'], 1.70181e-10, places=15) 29 43 30 44 # Ensure the extraplation tends to the background value … … 58 72 break 59 73 60 def transform_callback(self, transform): 61 self.assertIsNotNone(transform) 62 self.assertAlmostEqual(transform.y[0], 1) 63 self.assertAlmostEqual(transform.y[-1], 0, 5) 64 self.transformation = transform 74 def transform_callback(self, transforms): 75 transform1, transform3, idf = transforms 76 self.assertIsNotNone(transform1) 77 self.assertAlmostEqual(transform1.y[0], 1) 78 self.assertAlmostEqual(transform1.y[-1], 0, 5) 79 self.transformation = transforms 65 80 66 81 def extract_params(self): 67 params = self.calculator.extract_parameters(self.transformation )82 params = self.calculator.extract_parameters(self.transformation[0]) 68 83 self.assertIsNotNone(params) 69 84 self.assertEqual(len(params), 6) 70 85 self.assertLess(abs(params['max']-75), 2.5) # L_p ~= 75 71 86 87 def check_transforms(self): 88 gamma1, gamma3, idf = self.transformation 89 gamma1_out, gamma3_out, idf_out = self.results 90 def compare(a, b): 91 return max(abs((a-b)/b)) 92 #print("gamma1 diff", compare(gamma1.y[gamma1.x<=200.], gamma1_out)) 93 #print("gamma3 diff", compare(gamma3.y[gamma3.x<=200.], gamma3_out)) 94 #print("idf diff", compare(idf.y[idf.x<=200.], idf_out)) 95 #self.assertLess(compare(gamma1.y[gamma1.x<=200.], gamma1_out), 1e-10) 96 #self.assertLess(compare(gamma3.y[gamma3.x<=200.], gamma3_out), 1e-10) 97 #self.assertLess(compare(idf.y[idf.x<=200.], idf_out), 1e-10) 98 72 99 # Ensure tests are ran in correct order; 73 100 # Each test depends on the one before it 74 101 def test_calculator(self): 75 steps = [self.extrapolate, self.transform, self.extract_params ]102 steps = [self.extrapolate, self.transform, self.extract_params, self.check_transforms] 76 103 for test in steps: 77 104 try: 78 105 test() 79 106 except Exception as e: 107 raise 80 108 self.fail("{} failed ({}: {})".format(test, type(e), e)) 81 109 82 110 83 111 def load_data(filename="98929.txt"): 84 data = np.loadtxt(filename, dtype=np.float 32)112 data = np.loadtxt(filename, dtype=np.float64) 85 113 q = data[:,0] 86 114 iq = data[:,1] -
test/sasdataloader/test/utest_abs_reader.py
ra78a02f rae69c690 333 333 self.assertEqual(self.data.x[1], 0.03) 334 334 self.assertAlmostEquals(self.data.y[1], 1001.0) 335 self.assertEqual(self.data.dx[0], 0.0)336 335 self.assertEqual(self.data.dxl[1], 0.005) 337 336 self.assertEqual(self.data.dxw[1], 0.001) -
test/utest_sasview.py
rb54440d rbe51cf6 62 62 proc = subprocess.Popen(code, shell=True, stdout=subprocess.PIPE, stderr = subprocess.STDOUT) 63 63 std_out, std_err = proc.communicate() 64 #print std_out64 #print(">>>>>> standard out", file_path, "\n", std_out, "\n>>>>>>>>> end stdout", file_path) 65 65 #sys.exit() 66 66 m = re.search("Ran ([0-9]+) test", std_out) … … 82 82 failed += 1 83 83 print("Result for %s (%s): FAILED" % (module_name, module_dir)) 84 print(std_out)84 #print(std_out) 85 85 else: 86 86 passed += 1
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