1301 lines
44 KiB
Python
1301 lines
44 KiB
Python
from __future__ import annotations
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import pathlib
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import re
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import uuid
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import numpy as np
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from nmreval.fit import data as fit_d
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from nmreval.fit.model import Model
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from nmreval.fit.result import FitResult
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from nmreval.fit.minimizer import FitRoutine
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from nmreval.lib.colors import available_cycles
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from nmreval.lib.logger import logger
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from nmreval.math.interpol import interpolate
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from nmreval.math.logfourier import logft
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from nmreval.math.smooth import smooth
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from nmreval.nmr.relaxation import Relaxation
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from ..Qt import QtCore, QtWidgets
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from ..lib import Relations
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from ..lib.undos import *
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from ..data.container import *
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from ..io.filereaders import QFileReader
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from ..lib.utils import busy_cursor
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class GraphSignals(QtCore.QObject):
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valueChanged = QtCore.pyqtSignal()
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class GraphDict(OrderedDict):
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def __init__(self, data):
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super().__init__()
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self._data = data
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self.signals = GraphSignals()
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self.valueChanged = self.signals.valueChanged
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def __setitem__(self, key, value):
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super().__setitem__(key, value)
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self.valueChanged.emit()
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def __delitem__(self, key):
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super().__delitem__(key)
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self.valueChanged.emit()
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def tree(self, key_only=False):
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ret_val = OrderedDict()
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for k, g in self.items():
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if key_only:
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ret_val[k] = (g.title, [(s, self._data[s].name) for s in g.sets])
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else:
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ret_val[(k, g.title)] = [(s, self._data[s].name) for s in g.sets]
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return ret_val
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def list(self):
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return [(k, v.title) for k, v in self.items()]
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def active(self, key: str, return_val: str = 'both'):
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if not key:
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return []
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else:
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if return_val == 'both':
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return [(self._data[i].id, self._data[i].name) for i in self[key]]
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elif return_val == 'id':
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return [self._data[i].id for i in self[key]]
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elif return_val == 'name':
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return [self._data[i].name for i in self[key]]
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else:
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raise ValueError(f'return_val got wrong value {return_val!r}')
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def current_sets(self, key: str):
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if key:
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return [(self._data[i].id, self._data[i].name) for i in self[key].sets]
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else:
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return []
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class UpperManagement(QtCore.QObject):
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newGraph = QtCore.pyqtSignal()
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restoreGraph = QtCore.pyqtSignal(str)
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deleteGraph = QtCore.pyqtSignal(str)
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newData = QtCore.pyqtSignal([list, str], [list, str, bool])
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deleteData = QtCore.pyqtSignal(list)
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dataChanged = QtCore.pyqtSignal(str)
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fitFinished = QtCore.pyqtSignal(list)
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stopFit = QtCore.pyqtSignal()
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properties_collected = QtCore.pyqtSignal(dict)
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unset_state = QtCore.pyqtSignal(list)
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_colors = cycle(TUColors)
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_actions = {
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'ls': (ShiftCommand, 'Left shift'),
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'cut': (CutCommand, 'Cut'),
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'ap': (ApodizationCommand, 'Apodization'),
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'zf': (ZerofillCommand, 'Zerofill'),
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'ph': (PhaseCommand, 'Phase correction'),
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'autoph': (AutophaseCommand, 'Autophase'),
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'bl': (BaselineCommand, 'Baseline'),
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'bls': (BaselineSplineCommand, 'Baseline'),
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'ft': (FourierCommand, 'Fourier'),
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'ft_pake': 'FT (de-paked)',
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'sort': (SortCommand, 'Sort'),
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'norm': (NormCommand, 'Normalize'),
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'center': (CenterCommand, 'Center on max'),
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}
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def __init__(self, window):
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super().__init__()
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self._fit_active = False
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self.fit_thread = None
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self.fit_worker = None
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self.counter = 0
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self.data = OrderedDict()
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self.window = window
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self.current_graph = None
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self.graphs = GraphDict(self.data)
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self.namespace = None
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self.undostack = QtWidgets.QUndoStack()
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self.deleteData.connect(self.plot_from_graph)
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self._filereader = None
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def __setitem__(self, key: str, value, **kwargs):
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if isinstance(value, ExperimentContainer):
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item = value
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item.id = key
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elif isinstance(value, FitResult):
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item = FitContainer(key, value, manager=self, **kwargs)
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elif isinstance(value, Signal):
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item = SignalContainer(key, value, manager=self, **kwargs)
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else:
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item = PointContainer(key, value, manager=self, **kwargs)
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item.dataChanged.connect(lambda x: self.dataChanged.emit(x))
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self.data[key] = item
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def __getitem__(self, item):
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return self.data[item]
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def __contains__(self, item):
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return item in self.data
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def __iter__(self):
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for k, v in self.data.items():
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yield k, v
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@property
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def active_sets(self):
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return self.graphs.active(self.current_graph)
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@property
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def active_id(self):
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return self.graphs.active(self.current_graph, return_val='id')
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def get_attributes(self, graph_id: str, attr: str) -> dict[str, Any]:
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return {self.data[i].id: getattr(self.data[i], attr) for i in self.graphs[graph_id].sets}
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def add(self, data, **kwargs):
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_id = str(uuid.uuid4())
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self.__setitem__(_id, data, **kwargs)
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return _id
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def load_files(self, fname: list[str], new_plot: str = None):
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if self._filereader is None:
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self._filereader = QFileReader(manager=self)
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ret_dic = self._filereader.readfiles(fname)
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self.add_new_data(ret_dic, new_plot)
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def _load_session(self, sets: dict, graphs: dict):
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sid = self._load_sets(sets)
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for g in graphs:
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_ = g.pop('id')
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graph = QGraphWindow.set_state(g)
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self.graphs[graph.id] = graph
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self.restoreGraph.emit(graph.id)
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children = [sid[c] for c in g['children']]
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active = [sid[c] for c in g['active']]
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inactive = [k for k in children if k not in active]
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self.newData.emit(children, graph.id)
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graph.active = active
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graph.listWidget.blockSignals(True)
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for i, l in enumerate(g['in_legend']):
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try:
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graph.listWidget.item(i).setCheckState(QtCore.Qt.Checked if l else QtCore.Qt.Unchecked)
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except AttributeError:
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pass
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graph.listWidget.blockSignals(False)
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# set unchecked in tree and hide/show in plot
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self.unset_state.emit(inactive)
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self.change_visibility(active, inactive)
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def _load_sets(self, sets: dict) -> dict:
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sid = {}
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for _id, (data, opts) in sets.items():
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if isinstance(data, FitResult):
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# for fits, _id belongs to the fitted data, not the fit
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src_id = data.idx
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if src_id in sid:
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new_id = self.add(data, src=sid[src_id])
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self.data[sid[src_id]]._fits.append(new_id)
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else:
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new_id = self.add(data)
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else:
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new_id = self.add(data)
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sid[_id] = new_id
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for m in ['real', 'imag']:
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if m in opts:
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self.data[new_id].setSymbol(**opts[m][0], mode=m)
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self.data[new_id].setLine(**opts[m][1], mode=m)
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return sid
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def add_new_data(self, data: list, gid: str):
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sid = []
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for d in data:
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if isinstance(d, tuple):
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if len(d) == 2:
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self._load_session(d[0], graphs=d[1])
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else:
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sid.extend(list(self._load_sets(d[0]).values()))
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else:
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sid.append(self.add(d))
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if sid:
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gid = '' if not gid else gid
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self.newData.emit(sid, gid)
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def plots_to_graph(self, plotkeys: list, gid: str):
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self.graphs[gid].add(plotkeys, [self.data[k].plots for k in plotkeys])
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for k in plotkeys:
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self.data[k].graph = gid
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@QtCore.pyqtSlot(list)
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def plot_from_graph(self, key: list[str]):
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sort_graph = {}
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for sid in key:
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v = self.data[sid].graph
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if v not in sort_graph:
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sort_graph[v] = []
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sort_graph[v].append(sid)
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for gid, sets in sort_graph.items():
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self.graphs[gid].remove(sets)
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@QtCore.pyqtSlot(list, str, str)
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def move_sets(self, sets: list, dest: str, src: (str|list), pos: int = -1):
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if isinstance(src, str):
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src = [src]*len(sets)
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for graph_id, set_id in zip(src, sets):
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# move all plots to the same graph
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if graph_id != dest:
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self.graphs[graph_id].remove(set_id)
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self.plots_to_graph([set_id], dest)
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# move to correct position
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self.graphs[dest].move_sets(sets, pos)
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def select_window(self, gid: str):
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for key, plot in self.graphs.items():
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if key == gid:
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self.window.area.setActiveSubWindow(plot.parent())
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@QtCore.pyqtSlot()
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@QtCore.pyqtSlot(list, str)
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def copy_sets(self, sets: list = None, src: str = None):
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if sets is None:
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sets = self.graphs[self.current_graph].active[:]
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if src is None:
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src = self.current_graph
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new_ids = []
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for s in sets:
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copy_of_s = self.data[s].copy(full=True)
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copy_of_s.id = str(uuid.uuid4())
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new_ids.append(copy_of_s.id)
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self.data[copy_of_s.id] = copy_of_s
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self.newData.emit(new_ids, src)
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return new_ids
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@QtCore.pyqtSlot(list)
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@QtCore.pyqtSlot(str)
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@QtCore.pyqtSlot()
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def delete_sets(self, rm_sets: list = None):
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rm_graphs = []
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if rm_sets is None:
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rm_sets = self.graphs[self.current_graph].sets + [self.current_graph]
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self.undostack.beginMacro('Delete')
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rm_set_by_graph = {}
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for k in rm_sets[::-1]:
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if k in self.data:
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parent_graph = self.data[k].graph
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if parent_graph not in rm_set_by_graph:
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rm_set_by_graph[parent_graph] = []
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rm_set_by_graph[parent_graph].append(k)
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elif k in self.graphs:
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rm_graphs.append(k)
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else:
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logger.warning(f'delete_sets: {k} is not in data or graph found')
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for gid, sid_list in rm_set_by_graph.items():
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cmd = DeleteCommand(self.data, sid_list, self.graphs, gid, self.newData, self.deleteData)
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self.undostack.push(cmd)
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for k in rm_graphs:
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cmd = DeleteGraphCommand(self.graphs, k, self.restoreGraph, self.deleteGraph)
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self.undostack.push(cmd)
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self.undostack.endMacro()
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def delete_graph(self, gid):
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self.delete_sets(self.graphs[gid].sets + [gid])
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@QtCore.pyqtSlot()
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def cat(self, src_sets=None):
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joined = None
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group_set = set()
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name_set = set()
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value_set = set()
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if src_sets is None:
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if self.current_graph:
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src_sets = self.graphs[self.current_graph].active
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else:
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return
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for sid in src_sets:
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data_i = self.data[sid]
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if joined is None:
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joined = data_i.copy()
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else:
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joined.append(data_i.data.x, data_i.data.y, y_err=data_i.data.y_err, mask=data_i.data.mask)
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name_set.add(data_i.name)
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group_set.add(data_i.group)
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value_set.add(data_i.value)
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if joined is not None:
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joined.group = '+'.join(group_set)
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joined.name = '+'.join(name_set)
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if len(value_set) == 1:
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joined.value = value_set.pop()
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else:
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joined.value = 0.0
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self.newData.emit([self.add(joined)], self.current_graph)
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def get_data(self, sid: str, xy_only: bool = False):
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"""
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Return data for a given id.
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Return value is tuple of [x, y, y_err] and mask if xy_only is False, [x, y] if true.
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"""
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d = self.data[sid]
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if xy_only:
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return [d.x, d.y]
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return [d.data.x, d.data.y, d.data.y_err], d.data.mask.data
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def change_visibility(self, selected: list, deselected: list):
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"""Change status of list of ids after status change in datawidget"""
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for s in selected:
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self.graphs[self.data[s].graph].show_item([s])
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for d in deselected:
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self.graphs[self.data[d].graph].hide_item([d])
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@QtCore.pyqtSlot(str, str)
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def change_keys(self, identifier: str, name: str):
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if identifier in self.data:
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d = self.data[identifier]
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d.name = name
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self.graphs[d.graph].update_legend(identifier, name)
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elif identifier in self.graphs:
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self.graphs[identifier].title = name
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else:
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raise KeyError('Unknown ID ' + str(identifier))
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@QtCore.pyqtSlot(str, tuple)
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def apply(self, func: str, arguments: tuple):
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# undos, names displayed by undo action
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cmd, cmd_text = self._actions[func]
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self.undostack.beginMacro(cmd_text)
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for sid in self.graphs[self.current_graph]:
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single_undo = cmd(self.data[sid], *arguments)
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self.undostack.push(single_undo)
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self.undostack.endMacro()
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def cut(self):
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if self.current_graph:
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xlim, _ = self.graphs[self.current_graph].ranges
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self.apply('cut', xlim)
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@QtCore.pyqtSlot()
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def unmask(self):
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for d in self.data.values():
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d.mask = np.ones_like(d.mask, dtype=bool)
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def prepare_fit(self, parameter: dict, links: list, fit_options: dict) -> bool:
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if self._fit_active:
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return False
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self.__fit_options = (parameter, links, fit_options)
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self.fitter = FitRoutine()
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models = {}
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fit_limits = fit_options['limits']
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fit_mode = fit_options['fit_mode']
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we_option = fit_options['we']
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self.fitter.fitmethod = fit_mode
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# all-encompassing error catch
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try:
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for model_id, model_p in parameter.items():
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m = Model(model_p['func'])
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models[model_id] = m
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m_complex = model_p['complex']
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# sets are not in active order but in order they first appeared in fit dialog
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# iterate over order of set id in active order and access parameter inside loop
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# instead of directly looping
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list_ids = list(model_p['parameter'].keys())
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set_order = [self.active_id.index(i) for i in list_ids]
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for pos in set_order:
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set_id = list_ids[pos]
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data_i = self.data[set_id]
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set_params = model_p['parameter'][set_id]
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if we_option.lower() == 'deltay':
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we = data_i.y_err**2
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else:
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we = we_option
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if m_complex is None or m_complex == 1:
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_y = data_i.y.real
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elif m_complex == 2 and np.iscomplexobj(data_i.y):
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_y = data_i.y.imag
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else:
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_y = data_i.y
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_x = data_i.x
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if fit_limits == 'none':
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inside = slice(None)
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elif fit_limits == 'x':
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x_lim, _ = self.graphs[self.current_graph].ranges
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inside = np.where((_x >= x_lim[0]) & (_x <= x_lim[1]))
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else:
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inside = np.where((_x >= fit_limits[0]) & (_x <= fit_limits[1]))
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if isinstance(we, str):
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d = fit_d.Data(_x[inside], _y[inside], we=we, idx=set_id)
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else:
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d = fit_d.Data(_x[inside], _y[inside], we=we[inside], idx=set_id)
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d.set_model(m)
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d.set_parameter(set_params[0], var=model_p['var'],
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lb=model_p['lb'], ub=model_p['ub'],
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fun_kwargs=set_params[1])
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self.fitter.add_data(d)
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model_globs = model_p['glob']
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if model_globs:
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m.set_global_parameter(**model_p['glob'])
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for links_i in links:
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self.fitter.set_link_parameter((models[links_i[0]], links_i[1]),
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(models[links_i[2]], links_i[3]))
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return True
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except Exception as e:
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logger.error('Fit preparation failed', *e.args)
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QtWidgets.QMessageBox.warning(QtWidgets.QWidget(),
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'Fit prep failed',
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f'Fit preparation failed with message\n{e.args}')
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return False
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def start_fit(self):
|
|
with busy_cursor():
|
|
self.fit_worker = FitWorker(self.fitter)
|
|
self.fit_thread = QtCore.QThread()
|
|
self.fit_worker.moveToThread(self.fit_thread)
|
|
|
|
self.fit_thread.started.connect(self.fit_worker.run)
|
|
self.fit_worker.finished.connect(self.end_fit)
|
|
self.fit_worker.finished.connect(self.fit_thread.quit)
|
|
self.fit_worker.finished.connect(self.fit_worker.deleteLater)
|
|
self.fit_thread.finished.connect(self.fit_thread.deleteLater)
|
|
|
|
self.stopFit.connect(lambda: self.fit_worker.fitter.abort())
|
|
|
|
self.fit_thread.start()
|
|
|
|
@QtCore.pyqtSlot(list, bool)
|
|
def end_fit(self, result: list, success: bool):
|
|
if success:
|
|
logger.info('Successful fit')
|
|
self.fitFinished.emit(result)
|
|
else:
|
|
e = result[0]
|
|
logger.exception(e, exc_info=True)
|
|
QtWidgets.QMessageBox.warning(QtWidgets.QWidget(), 'Fit failed',
|
|
f'Fit kaput with exception: \n\n{e!r}')
|
|
self.fitFinished.emit([])
|
|
self._fit_active = False
|
|
|
|
@QtCore.pyqtSlot(dict)
|
|
def redo_fits(self, res: dict):
|
|
models = self.__fit_options[0]
|
|
for single_model, model_args in models.items():
|
|
parameter = model_args['parameter']
|
|
|
|
for set_id, set_parameter in parameter.items():
|
|
new_values = [v.value for v in res[set_id].parameter.values()]
|
|
parameter[set_id] = (new_values, set_parameter[1])
|
|
if self.prepare_fit(*self.__fit_options):
|
|
self.start_fit()
|
|
|
|
def make_fits(self, res: dict, opts: list, param_graph: str, show_fit: bool, parts: bool, extrapolate: list) -> None:
|
|
"""
|
|
|
|
Args:
|
|
res: key is that of original data, value is FitResult
|
|
opts: (ignore this fits, delete previous fits)
|
|
param_graph: None if no parameter to plot, '' for new graph, or id of existig graph
|
|
show_fit: plot fit curve?
|
|
parts: key is that of original data, value is list of subplots
|
|
extrapolate:
|
|
|
|
"""
|
|
f_id_list = []
|
|
gid = ''
|
|
|
|
tobedeleted = []
|
|
accepted = []
|
|
for i, (k, fit) in enumerate(res.items()):
|
|
reject, delete_prev = opts[i]
|
|
if reject:
|
|
continue
|
|
|
|
if not all(e is None for e in extrapolate):
|
|
spacefunc = np.geomspace if fit.islog else np.linspace
|
|
|
|
xmin = fit.x.min()
|
|
xmax = fit.x.max()
|
|
|
|
len_data = len(fit.x_data)
|
|
num_pts = 20*len_data-9 if len_data < 51 else 3*len_data
|
|
|
|
if extrapolate[0] is not None:
|
|
xmin = extrapolate[0]
|
|
if extrapolate[1] is not None:
|
|
xmax = extrapolate[1]
|
|
if extrapolate[2] is not None:
|
|
num_pts = extrapolate[2]
|
|
|
|
_x = spacefunc(xmin, xmax, num=num_pts)
|
|
|
|
fit = fit.with_new_x(_x)
|
|
|
|
data_k = self.data[k]
|
|
if delete_prev:
|
|
tobedeleted.extend([f.id for f in data_k.get_fits()])
|
|
data_k.set_fits([])
|
|
|
|
syms = data_k.plot_real.symbol
|
|
if syms == SymbolStyle.No:
|
|
color = data_k.plot_real.linecolor
|
|
else:
|
|
color = data_k.plot_real.symbolcolor
|
|
|
|
fit.value = data_k.value
|
|
fit.group = data_k.group
|
|
|
|
accepted.append(fit)
|
|
|
|
data_name = f' ({data_k.name})'
|
|
if show_fit:
|
|
fit.name += data_name
|
|
f_id = self.add(fit, color=color, src=k)
|
|
|
|
f_id_list.append(f_id)
|
|
data_k.set_fits(f_id)
|
|
|
|
if parts:
|
|
color_scheme = available_cycles['colorblind']
|
|
for subfunc, col in zip(fit.sub(fit.x), cycle(color_scheme)):
|
|
subfunc.value = data_k.value
|
|
subfunc.group = data_k.group
|
|
subfunc.name += data_name
|
|
sub_f_id = self.add(subfunc, color=col, linestyle=LineStyle.Dashed, symbol=SymbolStyle.No)
|
|
|
|
self[sub_f_id].add_relation(Relations.isFitPartOf, f_id)
|
|
self[f_id].add_relation(Relations.hasFitPart, sub_f_id)
|
|
|
|
f_id_list.append(sub_f_id)
|
|
gid = data_k.graph
|
|
self.delete_sets(tobedeleted)
|
|
|
|
if accepted and (param_graph != '-1'):
|
|
self.make_fit_parameter(accepted, graph_id=param_graph)
|
|
|
|
self.newData.emit(f_id_list, gid)
|
|
|
|
def extend_fits(self, set_id: list, x_range: np.ndarray):
|
|
graphs = {}
|
|
for sid in set_id:
|
|
data = self[sid]
|
|
fit = data.copy(full=True, keep_color=True)
|
|
fit.data = fit.data.with_new_x(x_range)
|
|
|
|
graph_id = data.graph
|
|
if graph_id not in graphs:
|
|
graphs[graph_id] = []
|
|
graphs[graph_id].append(self.add(fit))
|
|
|
|
color_scheme = available_cycles['colorblind']
|
|
for subfunc, col in zip(fit.data.sub(fit.x), cycle(color_scheme)):
|
|
subfunc.value = fit.value
|
|
subfunc.group = fit.group
|
|
graphs[graph_id].append(self.add(subfunc, color=col, linestyle=LineStyle.Dashed, symbol=SymbolStyle.No))
|
|
|
|
for k, v in graphs.items():
|
|
self.newData.emit(v, k)
|
|
|
|
def make_fit_parameter(self, fit_sets: list[str | FitResult], graph_id: str = None):
|
|
fit_dict = self._collect_fit_parameter(fit_sets)
|
|
|
|
if fit_dict:
|
|
p_id_list = []
|
|
for v in fit_dict.values():
|
|
xy = np.array(v[0]).T
|
|
p_id_list.append(self.add(Points(x=xy[0], y=xy[1], y_err=xy[2], name=v[1])))
|
|
|
|
if not graph_id:
|
|
graph_id = ''
|
|
|
|
self.newData[list, str, bool].emit(p_id_list, graph_id, True)
|
|
|
|
def save_fit_parameter(self, fname: str | pathlib.Path, fit_sets: list[str] = None):
|
|
if fit_sets is None:
|
|
fit_sets = [s for s in self.active_id]
|
|
|
|
for set_id in fit_sets:
|
|
data = self.data[set_id]
|
|
if data.mode != 'fit':
|
|
continue
|
|
|
|
data.data.save_parameter(fname)
|
|
|
|
def _collect_fit_parameter(self, fit_sets: list[str | FitResult]) -> dict:
|
|
fit_dict = {}
|
|
|
|
for set_id in fit_sets:
|
|
if isinstance(set_id, str):
|
|
data = self.data[set_id]
|
|
if data.mode != 'fit':
|
|
continue
|
|
elif isinstance(set_id, FitResult):
|
|
data = set_id
|
|
else:
|
|
continue
|
|
|
|
for fit_key, pvalue in data.parameter.items():
|
|
|
|
if fit_key not in fit_dict:
|
|
fit_dict[fit_key] = [[], fit_key]
|
|
|
|
err = 0 if pvalue.error is None else pvalue.error
|
|
|
|
fit_dict[fit_key][0].append([data.value, pvalue.value, err])
|
|
|
|
return fit_dict
|
|
|
|
@QtCore.pyqtSlot(dict, str)
|
|
def extract_points(self, params: dict, gid: str):
|
|
xy_mode = params.pop('xy')
|
|
_active = self.graphs[self.current_graph].active
|
|
|
|
new_datasets = {}
|
|
for sid in _active:
|
|
data_i = self.data[sid]
|
|
if data_i.group not in new_datasets:
|
|
new_datasets[data_i.group] = [], []
|
|
new_x_axis, _temp = new_datasets[data_i.group]
|
|
|
|
new_x_axis.append(data_i.value)
|
|
_temp.append(data_i.points(params))
|
|
|
|
key_list = []
|
|
for label, (new_x_axis, _temp) in new_datasets.items():
|
|
_temp = np.array(_temp) # (number of sets, number of picks, (x, y, y_err))
|
|
num_pts = _temp.shape[1]
|
|
|
|
for i in range(num_pts):
|
|
if xy_mode[0]:
|
|
key = self.add(Points(x=new_x_axis, y=_temp[:, i, 0], name=label))
|
|
key_list.append(key)
|
|
|
|
if xy_mode[1]:
|
|
key = self.add(Points(x=new_x_axis, y=_temp[:, i, 1], y_err=_temp[:, i, 2], name=label))
|
|
key_list.append(key)
|
|
|
|
self.newData[list, str, bool].emit(key_list, gid, True)
|
|
|
|
@QtCore.pyqtSlot(list)
|
|
def get_properties(self, sid: list) -> dict:
|
|
props = {}
|
|
for key in sid:
|
|
if key not in self.data:
|
|
continue
|
|
|
|
props = self.data[key].get_properties()
|
|
|
|
self.properties_collected.emit(props)
|
|
|
|
return props
|
|
|
|
@QtCore.pyqtSlot(list, str, str, object)
|
|
def update_property(self, sid: list, key1: str, key2: str, value: Any):
|
|
for s in sid:
|
|
self.data[s].update_property(key1, key2, value)
|
|
|
|
def create_empty(self):
|
|
import numpy.random as random
|
|
dat = Points(x=np.arange(10), y=np.arange(10) + random.rand(10)-0.5, y_err=random.rand(10),
|
|
name='Das Sein und das Nichts')
|
|
idd = self.add(dat)
|
|
self.newData.emit([idd], self.current_graph)
|
|
|
|
@QtCore.pyqtSlot(tuple, dict, str)
|
|
def calc_mean(self, dist_params, conversion, graph):
|
|
dist, args = dist_params
|
|
parameter = []
|
|
|
|
x = None
|
|
name = 'tau (%s)' % {conversion["to_"]}
|
|
value = 0.
|
|
for i, p in enumerate(args):
|
|
if isinstance(p, float):
|
|
parameter.append(p)
|
|
else:
|
|
if x is None:
|
|
x = self.data[p].x
|
|
if i == 0:
|
|
name = self.data[p].name
|
|
value = self.data[p].value
|
|
parameter.append(self.data[p].y)
|
|
|
|
if x is None:
|
|
x = 0
|
|
|
|
key = self.add(Points(x, dist.convert(*parameter, **conversion), name=name, value=value))
|
|
self.newData.emit([key], graph)
|
|
self.sender().update_graphs(self.graphs.tree(key_only=True))
|
|
|
|
@QtCore.pyqtSlot(list, str, bool, bool, tuple, str)
|
|
def interpolate_data(self, data_ids, mode, xlog, ylog, new_axis, dest_graph):
|
|
if len(new_axis) == 4:
|
|
start, end, steps, loggy = new_axis
|
|
if loggy:
|
|
new_x = np.logspace(np.log10(start), np.log10(end), steps)
|
|
else:
|
|
new_x = np.linspace(start, end, steps)
|
|
else:
|
|
new_x = self.data[new_axis[0]].x
|
|
|
|
new_key = []
|
|
for ids in data_ids:
|
|
k = self.add(interpolate(self.data[ids], new_x, xlog=xlog, ylog=ylog, kind=mode, extrapolate=True))
|
|
new_key.append(k)
|
|
|
|
self.newData.emit(new_key, dest_graph)
|
|
|
|
def binning(self, digits: float):
|
|
_active = self.graphs[self.current_graph].active
|
|
new_data = []
|
|
for sid in _active:
|
|
key = self.add(self.data[sid].binning(digits=digits))
|
|
new_data.append(key)
|
|
|
|
self.newData.emit(new_data, self.current_graph)
|
|
|
|
@QtCore.pyqtSlot(dict, str)
|
|
def addTg(self, dic: dict, dtype: str):
|
|
graph_id = self.current_graph if dtype == 'tg' else dic.pop('graph')
|
|
|
|
set_id_list = []
|
|
|
|
if dtype == 'hodge':
|
|
for v in dic.values():
|
|
set_id_list.append(self.add(v))
|
|
|
|
else:
|
|
for k, (data, lines) in dic.items():
|
|
p: ExperimentContainer = self[k]
|
|
col = p.plot_real.linecolor
|
|
|
|
if data is not None:
|
|
set_id_list.append(self.add(data, color=col))
|
|
|
|
if dtype == 'tnmh':
|
|
if lines is not None:
|
|
lines = [lines]
|
|
else:
|
|
lines = []
|
|
|
|
for line in lines:
|
|
set_id = self.add(line, color=col)
|
|
self[set_id].setLine(style=LineStyle.Dashed)
|
|
self[set_id].setSymbol(symbol=SymbolStyle.No)
|
|
set_id_list.append(set_id)
|
|
|
|
self.newData.emit(set_id_list, graph_id)
|
|
|
|
@QtCore.pyqtSlot(int, dict)
|
|
def smooth_data(self, npoints, param_kwargs):
|
|
_active = self.graphs[self.current_graph].active
|
|
new_data = []
|
|
for sid in _active:
|
|
try:
|
|
key = self.add(smooth(self.data[sid], npoints, **param_kwargs))
|
|
new_data.append(key)
|
|
except Exception as e:
|
|
QtWidgets.QMessageBox().warning(self.window,
|
|
'Smoothing failed!',
|
|
f'Smoothing failed for {self.data[sid].name} with exception:\n{e.args}')
|
|
if new_data:
|
|
self.newData.emit(new_data, self.current_graph)
|
|
|
|
@QtCore.pyqtSlot()
|
|
def set_cycle(self, set_idx: list, cycle_name: str):
|
|
col = cycle(available_cycles[cycle_name])
|
|
for s_id in set_idx:
|
|
self.data[s_id].setColor(next(col), symbol=True, line=True, mode='all')
|
|
|
|
@QtCore.pyqtSlot(dict, tuple)
|
|
def shift_scale(self, values: dict, options: tuple):
|
|
copy_data, value_plot = options
|
|
|
|
sid_list = []
|
|
shift_y = []
|
|
shift_x = []
|
|
for k, v in values.items():
|
|
d_k = self.data[k]
|
|
|
|
if copy_data is None:
|
|
d_k.shift_scale(v[0], v[1])
|
|
else:
|
|
new_data = d_k.copy(full=True)
|
|
new_data.shift_scale(v[0], v[1])
|
|
|
|
sid = self.add(new_data)
|
|
sid_list.append(sid)
|
|
|
|
shift_x.append(d_k.value)
|
|
shift_y.append(v[0]+v[1])
|
|
|
|
self.newData.emit(sid_list, copy_data)
|
|
|
|
if value_plot is not None:
|
|
sid_list = []
|
|
shift_y = np.array(shift_y)
|
|
for i, (mode, default) in enumerate([('x shift', 0.), ('y shift', 0.),
|
|
('x scale', 1.), ('y scale', 1.), ]):
|
|
if np.all(shift_y[:, i] == default):
|
|
continue
|
|
data = Points(shift_x, shift_y[:, i], name=mode)
|
|
sid_list.append(self.add(data))
|
|
|
|
self.newData.emit(sid_list, value_plot)
|
|
|
|
@QtCore.pyqtSlot(list)
|
|
def convert_sets(self, src: list):
|
|
new_graph = {}
|
|
|
|
error_list = []
|
|
|
|
for sets in src:
|
|
# merge: sets (real, imag, graph, type)
|
|
# normal: sets (source set, graph, type)
|
|
|
|
graph_id = sets[-2]
|
|
new_type = [Points, FID, Spectrum, BDS][sets[-1]]
|
|
|
|
if len(sets) == 4:
|
|
real_set, imag_set = sets[0], sets[1]
|
|
if real_set != '':
|
|
data = self.data[real_set]
|
|
new_data = new_type(data.x, data.y.real)
|
|
if imag_set != '':
|
|
imag_data = self.data[imag_set]
|
|
if len(imag_data) == len(data):
|
|
new_data.y.imag = imag_data.y.real
|
|
else:
|
|
error_list.append(f'Lengths mismatch of {data.name} ({len(data)}) and {imag_data.name} ({len(imag_data)})')
|
|
continue
|
|
|
|
else:
|
|
data = self.data[imag_set]
|
|
new_data = new_type(data.x, np.zeros(data.x.size))
|
|
new_data.y.imag = data.y.real
|
|
|
|
else:
|
|
data = self.data[sets[0]]
|
|
if isinstance(data.data, new_type):
|
|
error_list.append(f'{data.name} is alreade of type {new_type.__name__}')
|
|
continue
|
|
|
|
new_data = new_type(data.x, np.zeros(data.x.size))
|
|
new_data.y.real = data.y.real
|
|
|
|
new_data.update(data.opts)
|
|
new_id = self.add(data.change_type(new_data))
|
|
if graph_id not in new_graph:
|
|
new_graph[graph_id] = []
|
|
|
|
new_graph[graph_id].append(new_id)
|
|
|
|
for g, s in new_graph.items():
|
|
self.newData.emit(s, g)
|
|
|
|
if error_list:
|
|
err_string = "\n- ".join(error_list)
|
|
_ = QtWidgets.QMessageBox.information(QtWidgets.QWidget(), 'Something was skipped',
|
|
f'Some conversions were skipped:\n{err_string}')
|
|
|
|
def get_namespace(self):
|
|
from ..lib.namespace import Namespace
|
|
self.namespace = Namespace(basic=True, const=True, fitfuncs=True)
|
|
|
|
for i, g in enumerate(self.graphs.values()):
|
|
for j, sid in enumerate(g.sets):
|
|
sets = self.data[sid]
|
|
self.namespace.add_namespace(sets.get_namespace(i, j), parents=('Data', f'{sets.name} ({g.title})'))
|
|
|
|
return self.namespace
|
|
|
|
@QtCore.pyqtSlot(list, list, bool)
|
|
def eval_expression(self, cmds: list, set_ids: list, overwrite: bool):
|
|
ns = self.namespace.flatten()
|
|
|
|
if overwrite:
|
|
self.undostack.beginMacro('Evaluate expression')
|
|
|
|
failures = []
|
|
for i, g in enumerate(self.graphs.values()):
|
|
for j, sid in enumerate(g.sets):
|
|
|
|
if sid not in set_ids:
|
|
continue
|
|
|
|
data_i = self.data[sid]
|
|
try:
|
|
# use a copy of original namespace
|
|
new_data = data_i.eval_expression(cmds, dict(ns), i=i, j=j)
|
|
if overwrite:
|
|
cmd = EvalCommand(self.data, sid, new_data, 'Evaluate expression')
|
|
self.undostack.push(cmd)
|
|
else:
|
|
new_id = self.copy_sets(sets=[sid])
|
|
self.data[new_id[0]].data = new_data
|
|
except Exception as e:
|
|
failures.append((data_i, e))
|
|
logger.warning(str(data_i) + ' failed with Exception: ' + ''.join(e.args))
|
|
continue
|
|
|
|
if overwrite:
|
|
self.undostack.endMacro()
|
|
|
|
if failures:
|
|
err_msg = QtWidgets.QMessageBox(parent=self.sender())
|
|
err_msg.setText('One or more errors occured during evaluation.')
|
|
err_msg.setDetailedText('\n'.join(f'{d.name} failed with error: {err.args}' for d, err in failures))
|
|
err_msg.exec()
|
|
|
|
self.sender().success = not failures
|
|
self.sender().add_data(self.active_sets)
|
|
|
|
@QtCore.pyqtSlot(list, dict)
|
|
def create_from_function(self, cmds: list, opts: dict):
|
|
ns = dict(self.namespace.flatten())
|
|
|
|
dtype = [Points, FID, Spectrum, BDS][opts.pop('dtype')]
|
|
|
|
try:
|
|
for c in cmds:
|
|
exec(c, globals(), ns)
|
|
|
|
name = opts.pop('name')
|
|
value = opts.pop('val')
|
|
graph = opts.pop('graph')
|
|
|
|
data = dtype(x=ns['x'], y=ns['y'], y_err=ns['y_err'], name=name, value=value)
|
|
s_id = self.add(data, **opts)
|
|
self.sender().success = True
|
|
self.newData.emit([s_id], graph)
|
|
|
|
except Exception as err:
|
|
logger.exception('Creation failed with error: ' + ', '.join(err.args))
|
|
err_msg = QtWidgets.QMessageBox(parent=self.sender())
|
|
err_msg.setText('One or more errors occurred during evaluation.')
|
|
err_msg.setDetailedText('Creation failed with error: ' + ', '.join(err.args))
|
|
err_msg.exec()
|
|
|
|
self.sender().success = False
|
|
|
|
def show_statistics(self, mode):
|
|
x, y, = [], []
|
|
|
|
for i in self.active_id:
|
|
_temp = self.data[i]
|
|
try:
|
|
x.append(float(_temp.name))
|
|
except ValueError:
|
|
x.append(i)
|
|
y.append(_temp.statistic(mode))
|
|
|
|
@QtCore.pyqtSlot()
|
|
def calc_magn(self):
|
|
new_id = []
|
|
for k in self.active_id:
|
|
dataset = self.data[k]
|
|
if isinstance(dataset, SignalContainer):
|
|
new_value = dataset.copy(full=True)
|
|
new_value.data = dataset.data.magnitude()
|
|
new_id.append(self.add(new_value))
|
|
|
|
self.newData.emit(new_id, '')
|
|
|
|
@QtCore.pyqtSlot()
|
|
def center(self):
|
|
new_id = []
|
|
for k in self.active_id:
|
|
new_value = self.data[k].copy(full=True)
|
|
new_value.x -= new_value.x[np.argmax(new_value.y.real)]
|
|
new_id.append(self.add(new_value))
|
|
|
|
self.newData.emit(new_id, '')
|
|
|
|
def integrate(self, **kwargs):
|
|
new_sets = []
|
|
log = kwargs['log']
|
|
limits = kwargs.get('limits')
|
|
mode = kwargs['mode']
|
|
|
|
for set_id in kwargs['sets']:
|
|
data_i = self.data[set_id]
|
|
if mode == 'i':
|
|
new_data = data_i.data.integrate(log=log, limits=limits)
|
|
elif mode == 'd':
|
|
new_data = data_i.data.diff(log=log)
|
|
else:
|
|
raise ValueError(f'Unknown mode {mode}.')
|
|
|
|
new_container = data_i.copy(full=True)
|
|
new_container.data = new_data
|
|
|
|
new_sets.append(self.add(new_container))
|
|
|
|
self.newData.emit(new_sets, kwargs['graph'])
|
|
|
|
def integral_datasets(self, ranges: list, x_vals: list, y_vals: np.ndarry):
|
|
new_sets = []
|
|
for range_i, y_val_i in zip(ranges, y_vals):
|
|
new_sets.append(self.add(Points(x=x_vals, y=y_val_i, name=f'{range_i[0]:.4g}-{range_i[1]:.4g}')))
|
|
|
|
self.newData.emit(new_sets, '')
|
|
|
|
def bds_deriv(self):
|
|
new_sets = []
|
|
|
|
for set_id in self.active_id:
|
|
data_i = self.data[set_id]
|
|
diff = data_i.data.diff(log=True)
|
|
new_data = Points(x=diff.x, y=-np.pi/2*diff.y.real)
|
|
new_data.update(data_i.data.meta)
|
|
|
|
new_sets.append(self.add(new_data, color=data_i.plot_imag.linecolor))
|
|
|
|
self.newData.emit(new_sets, '')
|
|
|
|
def logft(self, **kwargs):
|
|
new_sets = []
|
|
ft_mode = kwargs['ft_mode']
|
|
|
|
for set_id in kwargs['sets']:
|
|
data_i = self.data[set_id]
|
|
if ft_mode in ['cos', 'sin']:
|
|
new_data = Points(*logft(data_i.x, data_i.y, mode=ft_mode))
|
|
else:
|
|
new_data = Signal(*logft(data_i.x, data_i.y, mode=ft_mode))
|
|
|
|
new_sets.append(self.add(new_data, color=data_i['color'], symbol=data_i['symbol'], line=data_i['line']))
|
|
self.data[new_sets[-1]].update(data_i.data.meta)
|
|
|
|
self.newData.emit(new_sets, kwargs['graph'])
|
|
|
|
def skip_points(self, offset: int, step: int, invert: bool = False, copy: bool = False):
|
|
for k in self.active_id:
|
|
src = self.data[k]
|
|
if invert:
|
|
mask = np.mod(np.arange(offset, src.x.size+offset), step) != 0
|
|
else:
|
|
mask = np.mod(np.arange(offset, src.x.size+offset), step) == 0
|
|
|
|
if copy:
|
|
data = src.copy()
|
|
temp = data.mask.copy()
|
|
temp[temp] = mask
|
|
|
|
data.remove(np.where(~temp))
|
|
data.mask = np.ones(data.x.shape)
|
|
|
|
idd = self.add(data)
|
|
self.newData.emit([idd], self.current_graph)
|
|
else:
|
|
src.mask[src.mask] = mask
|
|
src.mask = src.mask
|
|
|
|
@QtCore.pyqtSlot(dict)
|
|
def calc_relaxation(self, opts: dict):
|
|
params = opts['pts']
|
|
if len(params) == 4:
|
|
if params[3]:
|
|
_x = x1 = np.geomspace(params[0], params[1], num=params[2])
|
|
else:
|
|
_x = x1 = np.linspace(params[0], params[1], num=params[2])
|
|
|
|
if opts['axis1'] in ['t', 'invt1000']:
|
|
t_p = opts['t_param']
|
|
if len(t_p) == 2:
|
|
from nmreval.models import Arrhenius as Func
|
|
else:
|
|
from nmreval.models import VFT as Func
|
|
|
|
_x = Func.func(x1, *t_p, invt=opts['axis1'])
|
|
|
|
else:
|
|
if params[1]:
|
|
x1 = self.data[params[0]].x
|
|
_x = self.data[params[0]].y.real
|
|
else:
|
|
_x = x1 = self.data[params[0]].x
|
|
|
|
x2 = opts['val2']
|
|
|
|
sd = opts['spec_dens']
|
|
sd_param = [self.data[p].y.real if isinstance(p, str) else p for p in opts['sd_param'][0]]
|
|
sd.convert(_x, *sd_param, from_=opts['tau_type'], to_='raw')
|
|
|
|
relax = Relaxation()
|
|
relax.set_distribution(sd, parameter=sd_param, keywords=opts['sd_param'][1])
|
|
|
|
cp_param = [self.data[p].y.real if isinstance(p, str) else p for p in opts['cp_param'][0]]
|
|
relax.set_coupling(opts['coup'], parameter=cp_param, keywords=opts['cp_param'][1])
|
|
|
|
if opts['out'] == 't1':
|
|
y = relax.t1(x2, _x)
|
|
else:
|
|
y = relax.t2(x2, _x)
|
|
|
|
pts = Points(x1, y, name=sd.name)
|
|
pts.meta.update(opts)
|
|
|
|
# we do not want class instances
|
|
pts.meta['coup'] = opts['coup'].name
|
|
pts.meta['spec_dens'] = sd.name
|
|
|
|
self.newData.emit([self.add(pts)], opts['graph'])
|
|
self.sender().update_graphs(self.graphs.list())
|
|
|
|
@QtCore.pyqtSlot(str, list)
|
|
def mask_value(self, idx: str, m: list):
|
|
self.data[idx].mask = m
|
|
|
|
@QtCore.pyqtSlot(str, list)
|
|
def remove_values(self, idx: str, m: list):
|
|
self.data[idx].remove(m)
|
|
|
|
@QtCore.pyqtSlot(str, int)
|
|
def split_set(self, idx: str, row: int):
|
|
selected_data = self.data[idx]
|
|
popular_front_of_judea = selected_data.copy(full=True)
|
|
|
|
selected_data.remove(slice(row, None))
|
|
popular_front_of_judea.remove(slice(None, row))
|
|
|
|
new_id = self.add(popular_front_of_judea)
|
|
self.newData.emit([new_id], selected_data.graph)
|
|
|
|
def set_values(self, idx: str, pos: tuple, value):
|
|
self.data[idx].setvalues(pos, value)
|
|
|
|
def append(self, idx: str):
|
|
self.data[idx].add([0.0, 0.0, 0.0])
|
|
|
|
def save(self, outpath: str | pathlib.Path, extension: str, strip_spaces=False):
|
|
path = pathlib.Path(outpath)
|
|
suffix = path.suffix
|
|
|
|
if not suffix:
|
|
m = re.match(r'[\w\s]*\(\*(\.\w+)\)', extension)
|
|
if m:
|
|
suffix = m.group(1)
|
|
path = path.with_suffix(suffix)
|
|
else:
|
|
raise ValueError('No file extension detected')
|
|
|
|
if suffix == '.nmr':
|
|
from nmreval.io.sessionwriter import NMRWriter
|
|
NMRWriter(self.graphs, self.data).export(path)
|
|
|
|
return
|
|
|
|
real_outnames = []
|
|
for set_id, set_name in self.active_sets:
|
|
full_name = path.stem
|
|
if '<label>' in full_name:
|
|
full_name = full_name.replace('<label>', convert(set_name, old='tex', new='str'))
|
|
|
|
data_i = self.data[set_id]
|
|
|
|
if isinstance(data_i, FitContainer):
|
|
try:
|
|
full_name += ' fit(' + self.data[data_i.parent_set].name + ')'
|
|
except KeyError:
|
|
# TODO fits should have a parent set
|
|
logger.warning(f'Fit {data_i} without valid parent : key is [{data_i.parent_set}')
|
|
full_name += ' fit'
|
|
|
|
if strip_spaces:
|
|
full_name = full_name.replace(' ', '_')
|
|
|
|
if full_name in real_outnames:
|
|
cnt = 1
|
|
while (full_name + '_' + str(cnt)) in real_outnames:
|
|
cnt += 1
|
|
real_outnames.append(full_name + '_' + str(cnt))
|
|
else:
|
|
real_outnames.append(full_name)
|
|
|
|
out_name = real_outnames[-1]
|
|
bad_character = r'/*<>\|:"'
|
|
for c in bad_character:
|
|
out_name = out_name.replace(c, '')
|
|
|
|
outpath_set = path.with_name(out_name+path.suffix)
|
|
data_i.save(outpath_set)
|
|
|
|
|
|
class FitWorker(QtCore.QObject):
|
|
finished = QtCore.pyqtSignal(list, bool)
|
|
|
|
def __init__(self, fitter):
|
|
super().__init__()
|
|
|
|
self.fitter = fitter
|
|
|
|
@QtCore.pyqtSlot()
|
|
def run(self):
|
|
try:
|
|
res = self.fitter.run()
|
|
success = True
|
|
except Exception as e:
|
|
res = [e]
|
|
success = False
|
|
self.finished.emit(res, success)
|