[570a58f9] | 1 | """ |
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| 2 | Adds a linear fit plot to the chart |
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| 3 | """ |
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[fed94a2] | 4 | import re |
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[570a58f9] | 5 | import numpy |
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[4992ff2] | 6 | from PyQt5 import QtCore |
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| 7 | from PyQt5 import QtGui |
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| 8 | from PyQt5 import QtWidgets |
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[570a58f9] | 9 | |
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[d6b8a1d] | 10 | from sas.qtgui.Utilities.GuiUtils import formatNumber, DoubleValidator |
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[570a58f9] | 11 | |
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[dc5ef15] | 12 | from sas.qtgui.Plotting import Fittings |
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| 13 | from sas.qtgui.Plotting import DataTransform |
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| 14 | from sas.qtgui.Plotting.LineModel import LineModel |
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[e4c475b7] | 15 | import sas.qtgui.Utilities.GuiUtils as GuiUtils |
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[570a58f9] | 16 | |
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| 17 | # Local UI |
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[cd2cc745] | 18 | from sas.qtgui.UI import main_resources_rc |
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[83eb5208] | 19 | from sas.qtgui.Plotting.UI.LinearFitUI import Ui_LinearFitUI |
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[570a58f9] | 20 | |
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[4992ff2] | 21 | class LinearFit(QtWidgets.QDialog, Ui_LinearFitUI): |
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[7969b9c] | 22 | updatePlot = QtCore.pyqtSignal(tuple) |
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[570a58f9] | 23 | def __init__(self, parent=None, |
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| 24 | data=None, |
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| 25 | max_range=(0.0, 0.0), |
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| 26 | fit_range=(0.0, 0.0), |
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| 27 | xlabel="", |
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| 28 | ylabel=""): |
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| 29 | super(LinearFit, self).__init__() |
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| 30 | |
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| 31 | self.setupUi(self) |
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[33c0561] | 32 | # disable the context help icon |
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| 33 | self.setWindowFlags(self.windowFlags() & ~QtCore.Qt.WindowContextHelpButtonHint) |
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| 34 | |
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[570a58f9] | 35 | assert(isinstance(max_range, tuple)) |
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| 36 | assert(isinstance(fit_range, tuple)) |
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| 37 | |
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| 38 | self.data = data |
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| 39 | self.parent = parent |
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| 40 | |
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| 41 | self.max_range = max_range |
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| 42 | self.fit_range = fit_range |
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| 43 | self.xLabel = xlabel |
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| 44 | self.yLabel = ylabel |
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| 45 | |
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[b46f285] | 46 | self.x_is_log = self.xLabel == "log10(x)" |
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| 47 | self.y_is_log = self.yLabel == "log10(y)" |
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| 48 | |
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[d6b8a1d] | 49 | self.txtFitRangeMin.setValidator(DoubleValidator()) |
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| 50 | self.txtFitRangeMax.setValidator(DoubleValidator()) |
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[570a58f9] | 51 | |
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| 52 | # Default values in the line edits |
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| 53 | self.txtA.setText("1") |
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| 54 | self.txtB.setText("1") |
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| 55 | self.txtAerr.setText("0") |
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| 56 | self.txtBerr.setText("0") |
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| 57 | self.txtChi2.setText("0") |
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[fed94a2] | 58 | |
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[570a58f9] | 59 | # Initial ranges |
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| 60 | self.txtRangeMin.setText(str(max_range[0])) |
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| 61 | self.txtRangeMax.setText(str(max_range[1])) |
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[e4c475b7] | 62 | # Assure nice display of ranges |
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| 63 | fr_min = GuiUtils.formatNumber(fit_range[0]) |
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| 64 | fr_max = GuiUtils.formatNumber(fit_range[1]) |
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| 65 | self.txtFitRangeMin.setText(str(fr_min)) |
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| 66 | self.txtFitRangeMax.setText(str(fr_max)) |
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[570a58f9] | 67 | |
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[fed94a2] | 68 | # cast xLabel into html |
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| 69 | label = re.sub(r'\^\((.)\)(.*)', r'<span style=" vertical-align:super;">\1</span>\2', |
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| 70 | str(self.xLabel).rstrip()) |
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| 71 | self.lblRange.setText('Fit range of ' + label) |
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[570a58f9] | 72 | |
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| 73 | self.model = LineModel() |
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| 74 | # Display the fittings values |
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| 75 | self.default_A = self.model.getParam('A') |
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| 76 | self.default_B = self.model.getParam('B') |
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[dc5ef15] | 77 | self.cstA = Fittings.Parameter(self.model, 'A', self.default_A) |
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| 78 | self.cstB = Fittings.Parameter(self.model, 'B', self.default_B) |
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| 79 | self.transform = DataTransform |
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[570a58f9] | 80 | |
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[2e3e959] | 81 | self.setFixedSize(self.minimumSizeHint()) |
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| 82 | |
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[fed94a2] | 83 | # connect Fit button |
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[570a58f9] | 84 | self.cmdFit.clicked.connect(self.fit) |
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| 85 | |
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| 86 | def setRangeLabel(self, label=""): |
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| 87 | """ |
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| 88 | Overwrite default fit range label to correspond to actual unit |
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| 89 | """ |
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[b3e8629] | 90 | assert(isinstance(label, str)) |
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[570a58f9] | 91 | self.lblRange.setText(label) |
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| 92 | |
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| 93 | def range(self): |
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| 94 | return (float(self.txtFitRangeMin.text()), float(self.txtFitRangeMax.text())) |
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| 95 | |
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| 96 | def fit(self, event): |
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| 97 | """ |
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| 98 | Performs the fit. Receive an event when clicking on |
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| 99 | the button Fit.Computes chisqr , |
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| 100 | A and B parameters of the best linear fit y=Ax +B |
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| 101 | Push a plottable to the caller |
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| 102 | """ |
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| 103 | tempx = [] |
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| 104 | tempy = [] |
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| 105 | tempdy = [] |
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| 106 | |
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| 107 | # Checks to assure data correctness |
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| 108 | if len(self.data.view.x) < 2: |
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| 109 | return |
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| 110 | if not self.checkFitValues(self.txtFitRangeMin): |
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| 111 | return |
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| 112 | |
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| 113 | self.xminFit, self.xmaxFit = self.range() |
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| 114 | |
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[b46f285] | 115 | xmin = self.xminFit |
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| 116 | xmax = self.xmaxFit |
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| 117 | xminView = xmin |
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| 118 | xmaxView = xmax |
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| 119 | |
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[570a58f9] | 120 | # Set the qmin and qmax in the panel that matches the |
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| 121 | # transformed min and max |
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[fed94a2] | 122 | value_xmin = self.floatInvTransform(xmin) |
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| 123 | value_xmax = self.floatInvTransform(xmax) |
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| 124 | self.txtRangeMin.setText(formatNumber(value_xmin)) |
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| 125 | self.txtRangeMax.setText(formatNumber(value_xmax)) |
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[570a58f9] | 126 | |
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[b46f285] | 127 | tempx, tempy, tempdy = self.origData() |
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[570a58f9] | 128 | |
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| 129 | # Find the fitting parameters |
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[dc5ef15] | 130 | self.cstA = Fittings.Parameter(self.model, 'A', self.default_A) |
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| 131 | self.cstB = Fittings.Parameter(self.model, 'B', self.default_B) |
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[570a58f9] | 132 | tempdy = numpy.asarray(tempdy) |
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| 133 | tempdy[tempdy == 0] = 1 |
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| 134 | |
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[b46f285] | 135 | if self.x_is_log: |
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| 136 | xmin = numpy.log10(xmin) |
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| 137 | xmax = numpy.log10(xmax) |
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| 138 | |
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[dc5ef15] | 139 | chisqr, out, cov = Fittings.sasfit(self.model, |
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[b46f285] | 140 | [self.cstA, self.cstB], |
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| 141 | tempx, tempy, tempdy, |
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| 142 | xmin, xmax) |
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[570a58f9] | 143 | # Use chi2/dof |
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| 144 | if len(tempx) > 0: |
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| 145 | chisqr = chisqr / len(tempx) |
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| 146 | |
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| 147 | # Check that cov and out are iterable before displaying them |
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| 148 | errA = numpy.sqrt(cov[0][0]) if cov is not None else 0 |
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| 149 | errB = numpy.sqrt(cov[1][1]) if cov is not None else 0 |
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| 150 | cstA = out[0] if out is not None else 0.0 |
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| 151 | cstB = out[1] if out is not None else 0.0 |
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| 152 | |
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| 153 | # Reset model with the right values of A and B |
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| 154 | self.model.setParam('A', float(cstA)) |
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| 155 | self.model.setParam('B', float(cstB)) |
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| 156 | |
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| 157 | tempx = [] |
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| 158 | tempy = [] |
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| 159 | y_model = 0.0 |
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| 160 | |
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[b46f285] | 161 | # load tempy with the minimum transformation |
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| 162 | y_model = self.model.run(xmin) |
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| 163 | tempx.append(xminView) |
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[d6b8a1d] | 164 | tempy.append(numpy.power(10.0, y_model) if self.y_is_log else y_model) |
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[570a58f9] | 165 | |
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| 166 | # load tempy with the maximum transformation |
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[b46f285] | 167 | y_model = self.model.run(xmax) |
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| 168 | tempx.append(xmaxView) |
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[d6b8a1d] | 169 | tempy.append(numpy.power(10.0, y_model) if self.y_is_log else y_model) |
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[570a58f9] | 170 | |
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| 171 | # Set the fit parameter display when FitDialog is opened again |
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| 172 | self.Avalue = cstA |
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| 173 | self.Bvalue = cstB |
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| 174 | self.ErrAvalue = errA |
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| 175 | self.ErrBvalue = errB |
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| 176 | self.Chivalue = chisqr |
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| 177 | |
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| 178 | # Update the widget |
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| 179 | self.txtA.setText(formatNumber(self.Avalue)) |
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| 180 | self.txtAerr.setText(formatNumber(self.ErrAvalue)) |
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| 181 | self.txtB.setText(formatNumber(self.Bvalue)) |
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| 182 | self.txtBerr.setText(formatNumber(self.ErrBvalue)) |
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| 183 | self.txtChi2.setText(formatNumber(self.Chivalue)) |
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| 184 | |
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[7969b9c] | 185 | self.updatePlot.emit((tempx, tempy)) |
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[570a58f9] | 186 | |
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[b46f285] | 187 | def origData(self): |
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| 188 | # Store the transformed values of view x, y and dy before the fit |
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| 189 | xmin_check = numpy.log10(self.xminFit) |
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| 190 | # Local shortcuts |
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| 191 | x = self.data.view.x |
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| 192 | y = self.data.view.y |
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| 193 | dy = self.data.view.dy |
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| 194 | |
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| 195 | if self.y_is_log: |
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| 196 | if self.x_is_log: |
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| 197 | tempy = [numpy.log10(y[i]) |
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| 198 | for i in range(len(x)) if x[i] >= xmin_check] |
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[dc5ef15] | 199 | tempdy = [DataTransform.errToLogX(y[i], 0, dy[i], 0) |
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[b46f285] | 200 | for i in range(len(x)) if x[i] >= xmin_check] |
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| 201 | else: |
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[b3e8629] | 202 | tempy = list(map(numpy.log10, y)) |
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| 203 | tempdy = list(map(lambda t1,t2:DataTransform.errToLogX(t1,0,t2,0),y,dy)) |
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[b46f285] | 204 | else: |
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| 205 | tempy = y |
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| 206 | tempdy = dy |
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| 207 | |
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| 208 | if self.x_is_log: |
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| 209 | tempx = [numpy.log10(x) for x in self.data.view.x if x > xmin_check] |
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| 210 | else: |
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| 211 | tempx = x |
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| 212 | |
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| 213 | return tempx, tempy, tempdy |
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| 214 | |
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[570a58f9] | 215 | def checkFitValues(self, item): |
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| 216 | """ |
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| 217 | Check the validity of input values |
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| 218 | """ |
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| 219 | flag = True |
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| 220 | value = item.text() |
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| 221 | p_white = item.palette() |
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| 222 | p_white.setColor(item.backgroundRole(), QtCore.Qt.white) |
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| 223 | p_pink = item.palette() |
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| 224 | p_pink.setColor(item.backgroundRole(), QtGui.QColor(255, 128, 128)) |
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[b46f285] | 225 | item.setAutoFillBackground(True) |
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[570a58f9] | 226 | # Check for possible values entered |
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[b46f285] | 227 | if self.x_is_log: |
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[570a58f9] | 228 | if float(value) > 0: |
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| 229 | item.setPalette(p_white) |
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| 230 | else: |
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| 231 | flag = False |
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| 232 | item.setPalette(p_pink) |
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| 233 | return flag |
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| 234 | |
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| 235 | def floatInvTransform(self, x): |
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| 236 | """ |
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| 237 | transform a float.It is used to determine the x.View min and x.View |
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| 238 | max for values not in x. Also used to properly calculate RgQmin, |
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| 239 | RgQmax and to update qmin and qmax in the linear range boxes on the |
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| 240 | panel. |
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| 241 | |
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| 242 | """ |
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| 243 | # TODO: refactor this. This is just a hack to make the |
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| 244 | # functionality work without rewritting the whole code |
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| 245 | # with good design (which really should be done...). |
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| 246 | if self.xLabel == "x": |
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| 247 | return x |
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| 248 | elif self.xLabel == "x^(2)": |
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| 249 | return numpy.sqrt(x) |
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| 250 | elif self.xLabel == "x^(4)": |
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[b46f285] | 251 | return numpy.sqrt(numpy.sqrt(x)) |
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[570a58f9] | 252 | elif self.xLabel == "log10(x)": |
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[d6b8a1d] | 253 | return numpy.power(10.0, x) |
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[570a58f9] | 254 | elif self.xLabel == "ln(x)": |
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| 255 | return numpy.exp(x) |
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| 256 | elif self.xLabel == "log10(x^(4))": |
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[d6b8a1d] | 257 | return numpy.sqrt(numpy.sqrt(numpy.power(10.0, x))) |
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[570a58f9] | 258 | return x |
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[2e3e959] | 259 | |
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| 260 | |
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