| 1 | """ |
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| 2 | Adapters for fitting module |
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| 3 | """ |
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| 4 | import copy |
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| 5 | import numpy as np |
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| 6 | import math |
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| 7 | from sas.sascalc.data_util.uncertainty import Uncertainty |
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| 8 | from sas.sasgui.plottools.plottables import Data1D as PlotData1D |
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| 9 | from sas.sasgui.plottools.plottables import Data2D as PlotData2D |
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| 10 | from sas.sasgui.plottools.plottables import Theory1D as PlotTheory1D |
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| 11 | |
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| 12 | from sas.sascalc.dataloader.data_info import Data1D as LoadData1D |
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| 13 | from sas.sascalc.dataloader.data_info import Data2D as LoadData2D |
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| 14 | |
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| 15 | |
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| 16 | class Data1D(PlotData1D, LoadData1D): |
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| 17 | """ |
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| 18 | """ |
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| 19 | |
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| 20 | def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None, isSesans=False): |
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| 21 | """ |
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| 22 | """ |
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| 23 | if x is None: |
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| 24 | x = [] |
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| 25 | if y is None: |
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| 26 | y = [] |
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| 27 | self.isSesans = isSesans |
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| 28 | PlotData1D.__init__(self, x, y, dx, dy, lam, dlam) |
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| 29 | LoadData1D.__init__(self, x, y, dx, dy, lam, dlam, isSesans) |
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| 30 | |
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| 31 | self.id = None |
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| 32 | self.list_group_id = [] |
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| 33 | self.group_id = None |
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| 34 | self.is_data = True |
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| 35 | self.path = None |
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| 36 | self.xtransform = None |
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| 37 | if self.isSesans: |
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| 38 | self.xtransform = "x" |
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| 39 | self.ytransform = None |
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| 40 | if self.isSesans: |
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| 41 | self.ytransform = "y" |
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| 42 | self.title = "" |
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| 43 | self.scale = None |
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| 44 | |
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| 45 | def copy_from_datainfo(self, data1d): |
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| 46 | """ |
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| 47 | copy values of Data1D of type DataLaoder.Data_info |
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| 48 | """ |
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| 49 | self.x = copy.deepcopy(data1d.x) |
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| 50 | self.y = copy.deepcopy(data1d.y) |
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| 51 | self.dy = copy.deepcopy(data1d.dy) |
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| 52 | |
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| 53 | if hasattr(data1d, "dx"): |
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| 54 | self.dx = copy.deepcopy(data1d.dx) |
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| 55 | if hasattr(data1d, "dxl"): |
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| 56 | self.dxl = copy.deepcopy(data1d.dxl) |
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| 57 | if hasattr(data1d, "dxw"): |
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| 58 | self.dxw = copy.deepcopy(data1d.dxw) |
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| 59 | |
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| 60 | self.xaxis(data1d._xaxis, data1d._xunit) |
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| 61 | self.yaxis(data1d._yaxis, data1d._yunit) |
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| 62 | self.title = data1d.title |
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| 63 | |
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| 64 | def __str__(self): |
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| 65 | """ |
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| 66 | print data |
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| 67 | """ |
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| 68 | _str = "%s\n" % LoadData1D.__str__(self) |
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| 69 | |
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| 70 | return _str |
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| 71 | |
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| 72 | def _perform_operation(self, other, operation): |
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| 73 | """ |
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| 74 | """ |
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| 75 | # First, check the data compatibility |
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| 76 | dy, dy_other = self._validity_check(other) |
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| 77 | result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=None) |
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| 78 | result.clone_without_data(length=len(self.x), clone=self) |
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| 79 | result.copy_from_datainfo(data1d=self) |
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| 80 | if self.dxw is None: |
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| 81 | result.dxw = None |
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| 82 | else: |
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| 83 | result.dxw = np.zeros(len(self.x)) |
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| 84 | if self.dxl is None: |
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| 85 | result.dxl = None |
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| 86 | else: |
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| 87 | result.dxl = np.zeros(len(self.x)) |
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| 88 | |
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| 89 | for i in range(len(self.x)): |
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| 90 | result.x[i] = self.x[i] |
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| 91 | if self.dx is not None and len(self.x) == len(self.dx): |
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| 92 | result.dx[i] = self.dx[i] |
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| 93 | if self.dxw is not None and len(self.x) == len(self.dxw): |
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| 94 | result.dxw[i] = self.dxw[i] |
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| 95 | if self.dxl is not None and len(self.x) == len(self.dxl): |
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| 96 | result.dxl[i] = self.dxl[i] |
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| 97 | |
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| 98 | a = Uncertainty(self.y[i], dy[i]**2) |
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| 99 | if isinstance(other, Data1D): |
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| 100 | b = Uncertainty(other.y[i], dy_other[i]**2) |
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| 101 | if other.dx is not None: |
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| 102 | result.dx[i] *= self.dx[i] |
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| 103 | result.dx[i] += (other.dx[i]**2) |
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| 104 | result.dx[i] /= 2 |
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| 105 | result.dx[i] = math.sqrt(result.dx[i]) |
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| 106 | if result.dxl is not None and other.dxl is not None: |
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| 107 | result.dxl[i] *= self.dxl[i] |
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| 108 | result.dxl[i] += (other.dxl[i]**2) |
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| 109 | result.dxl[i] /= 2 |
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| 110 | result.dxl[i] = math.sqrt(result.dxl[i]) |
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| 111 | else: |
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| 112 | b = other |
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| 113 | |
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| 114 | output = operation(a, b) |
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| 115 | result.y[i] = output.x |
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| 116 | result.dy[i] = math.sqrt(math.fabs(output.variance)) |
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| 117 | return result |
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| 118 | |
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| 119 | def _perform_union(self, other): |
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| 120 | """ |
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| 121 | """ |
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| 122 | # First, check the data compatibility |
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| 123 | self._validity_check_union(other) |
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| 124 | result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=None) |
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| 125 | tot_length = len(self.x) + len(other.x) |
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| 126 | result = self.clone_without_data(length=tot_length, clone=result) |
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| 127 | if self.dlam is None or other.dlam is None: |
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| 128 | result.dlam = None |
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| 129 | else: |
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| 130 | result.dlam = np.zeros(tot_length) |
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| 131 | if self.dy is None or other.dy is None: |
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| 132 | result.dy = None |
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| 133 | else: |
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| 134 | result.dy = np.zeros(tot_length) |
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| 135 | if self.dx is None or other.dx is None: |
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| 136 | result.dx = None |
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| 137 | else: |
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| 138 | result.dx = np.zeros(tot_length) |
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| 139 | if self.dxw is None or other.dxw is None: |
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| 140 | result.dxw = None |
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| 141 | else: |
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| 142 | result.dxw = np.zeros(tot_length) |
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| 143 | if self.dxl is None or other.dxl is None: |
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| 144 | result.dxl = None |
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| 145 | else: |
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| 146 | result.dxl = np.zeros(tot_length) |
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| 147 | |
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| 148 | result.x = np.append(self.x, other.x) |
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| 149 | #argsorting |
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| 150 | ind = np.argsort(result.x) |
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| 151 | result.x = result.x[ind] |
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| 152 | result.y = np.append(self.y, other.y) |
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| 153 | result.y = result.y[ind] |
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| 154 | result.lam = np.append(self.lam, other.lam) |
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| 155 | result.lam = result.lam[ind] |
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| 156 | if result.dlam is not None: |
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| 157 | result.dlam = np.append(self.dlam, other.dlam) |
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| 158 | result.dlam = result.dlam[ind] |
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| 159 | if result.dy is not None: |
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| 160 | result.dy = np.append(self.dy, other.dy) |
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| 161 | result.dy = result.dy[ind] |
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| 162 | if result.dx is not None: |
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| 163 | result.dx = np.append(self.dx, other.dx) |
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| 164 | result.dx = result.dx[ind] |
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| 165 | if result.dxw is not None: |
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| 166 | result.dxw = np.append(self.dxw, other.dxw) |
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| 167 | result.dxw = result.dxw[ind] |
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| 168 | if result.dxl is not None: |
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| 169 | result.dxl = np.append(self.dxl, other.dxl) |
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| 170 | result.dxl = result.dxl[ind] |
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| 171 | return result |
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| 172 | |
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| 173 | |
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| 174 | |
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| 175 | class Theory1D(PlotTheory1D, LoadData1D): |
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| 176 | """ |
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| 177 | """ |
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| 178 | def __init__(self, x=None, y=None, dy=None): |
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| 179 | """ |
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| 180 | """ |
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| 181 | if x is None: |
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| 182 | x = [] |
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| 183 | if y is None: |
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| 184 | y = [] |
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| 185 | PlotTheory1D.__init__(self, x, y, dy) |
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| 186 | LoadData1D.__init__(self, x, y, dy) |
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| 187 | self.id = None |
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| 188 | self.list_group_id = [] |
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| 189 | self.group_id = None |
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| 190 | self.is_data = True |
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| 191 | self.path = None |
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| 192 | self.xtransform = None |
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| 193 | self.ytransform = None |
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| 194 | self.title = "" |
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| 195 | self.scale = None |
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| 196 | |
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| 197 | def copy_from_datainfo(self, data1d): |
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| 198 | """ |
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| 199 | copy values of Data1D of type DataLaoder.Data_info |
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| 200 | """ |
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| 201 | self.x = copy.deepcopy(data1d.x) |
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| 202 | self.y = copy.deepcopy(data1d.y) |
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| 203 | self.dy = copy.deepcopy(data1d.dy) |
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| 204 | if hasattr(data1d, "dx"): |
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| 205 | self.dx = copy.deepcopy(data1d.dx) |
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| 206 | if hasattr(data1d, "dxl"): |
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| 207 | self.dxl = copy.deepcopy(data1d.dxl) |
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| 208 | if hasattr(data1d, "dxw"): |
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| 209 | self.dxw = copy.deepcopy(data1d.dxw) |
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| 210 | self.xaxis(data1d._xaxis, data1d._xunit) |
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| 211 | self.yaxis(data1d._yaxis, data1d._yunit) |
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| 212 | self.title = data1d.title |
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| 213 | |
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| 214 | def __str__(self): |
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| 215 | """ |
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| 216 | print data |
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| 217 | """ |
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| 218 | _str = "%s\n" % LoadData1D.__str__(self) |
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| 219 | |
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| 220 | return _str |
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| 221 | |
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| 222 | def _perform_operation(self, other, operation): |
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| 223 | """ |
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| 224 | """ |
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| 225 | # First, check the data compatibility |
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| 226 | dy, dy_other = self._validity_check(other) |
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| 227 | result = self.clone_without_data(len(self.x)) |
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| 228 | result.copy_from_datainfo(data1d=self) |
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| 229 | if self.dxw is None: |
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| 230 | result.dxw = None |
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| 231 | else: |
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| 232 | result.dxw = np.zeros(len(self.x)) |
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| 233 | if self.dxl is None: |
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| 234 | result.dxl = None |
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| 235 | else: |
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| 236 | result.dxl = np.zeros(len(self.x)) |
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| 237 | |
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| 238 | for i in range(np.size(self.x)): |
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| 239 | result.x[i] = self.x[i] |
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| 240 | if self.dx is not None and len(self.x) == len(self.dx): |
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| 241 | result.dx[i] = self.dx[i] |
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| 242 | if self.dxw is not None and len(self.x) == len(self.dxw): |
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| 243 | result.dxw[i] = self.dxw[i] |
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| 244 | if self.dxl is not None and len(self.x) == len(self.dxl): |
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| 245 | result.dxl[i] = self.dxl[i] |
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| 246 | |
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| 247 | a = Uncertainty(self.y[i], dy[i]**2) |
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| 248 | if isinstance(other, Data1D): |
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| 249 | b = Uncertainty(other.y[i], dy_other[i]**2) |
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| 250 | if other.dx is not None: |
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| 251 | result.dx[i] *= self.dx[i] |
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| 252 | result.dx[i] += (other.dx[i]**2) |
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| 253 | result.dx[i] /= 2 |
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| 254 | result.dx[i] = math.sqrt(result.dx[i]) |
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| 255 | if result.dxl is not None and other.dxl is not None: |
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| 256 | result.dxl[i] *= self.dxl[i] |
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| 257 | other.dxl[i] += (other.dxl[i]**2) |
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| 258 | result.dxl[i] /= 2 |
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| 259 | result.dxl[i] = math.sqrt(result.dxl[i]) |
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| 260 | if result.dxw is not None and self.dxw is not None: |
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| 261 | result.dxw[i] *= self.dxw[i] |
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| 262 | other.dxw[i] += (other.dxw[i]**2) |
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| 263 | result.dxw[i] /= 2 |
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| 264 | result.dxw[i] = math.sqrt(result.dxw[i]) |
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| 265 | else: |
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| 266 | b = other |
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| 267 | |
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| 268 | output = operation(a, b) |
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| 269 | result.y[i] = output.x |
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| 270 | result.dy[i] = math.sqrt(math.fabs(output.variance)) |
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| 271 | return result |
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| 272 | |
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| 273 | def _perform_union(self, other): |
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| 274 | """ |
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| 275 | """ |
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| 276 | # First, check the data compatibility |
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| 277 | self._validity_check_union(other) |
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| 278 | result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=[]) |
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| 279 | tot_length = len(self.x)+len(other.x) |
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| 280 | result.clone_without_data(length=tot_length, clone=self) |
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| 281 | if self.dlam is None or other.dlam is None: |
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| 282 | result.dlam = None |
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| 283 | else: |
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| 284 | result.dlam = np.zeros(tot_length) |
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| 285 | if self.dy is None or other.dy is None: |
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| 286 | result.dy = None |
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| 287 | else: |
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| 288 | result.dy = np.zeros(tot_length) |
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| 289 | if self.dx is None or other.dx is None: |
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| 290 | result.dx = None |
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| 291 | else: |
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| 292 | result.dx = np.zeros(tot_length) |
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| 293 | if self.dxw is None or other.dxw is None: |
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| 294 | result.dxw = None |
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| 295 | else: |
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| 296 | result.dxw = np.zeros(tot_length) |
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| 297 | if self.dxl is None or other.dxl is None: |
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| 298 | result.dxl = None |
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| 299 | else: |
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| 300 | result.dxl = np.zeros(tot_length) |
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| 301 | result.x = np.append(self.x, other.x) |
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| 302 | #argsorting |
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| 303 | ind = np.argsort(result.x) |
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| 304 | result.x = result.x[ind] |
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| 305 | result.y = np.append(self.y, other.y) |
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| 306 | result.y = result.y[ind] |
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| 307 | result.lam = np.append(self.lam, other.lam) |
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| 308 | result.lam = result.lam[ind] |
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| 309 | if result.dy is not None: |
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| 310 | result.dy = np.append(self.dy, other.dy) |
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| 311 | result.dy = result.dy[ind] |
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| 312 | if result.dx is not None: |
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| 313 | result.dx = np.append(self.dx, other.dx) |
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| 314 | result.dx = result.dx[ind] |
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| 315 | if result.dxw is not None: |
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| 316 | result.dxw = np.append(self.dxw, other.dxw) |
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| 317 | result.dxw = result.dxw[ind] |
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| 318 | if result.dxl is not None: |
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| 319 | result.dxl = np.append(self.dxl, other.dxl) |
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| 320 | result.dxl = result.dxl[ind] |
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| 321 | return result |
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| 322 | |
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| 323 | |
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| 324 | class Data2D(PlotData2D, LoadData2D): |
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| 325 | """ |
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| 326 | """ |
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| 327 | def __init__(self, image=None, err_image=None, |
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| 328 | qx_data=None, qy_data=None, q_data=None, |
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| 329 | mask=None, dqx_data=None, dqy_data=None, |
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| 330 | xmin=None, xmax=None, ymin=None, ymax=None, |
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| 331 | zmin=None, zmax=None): |
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| 332 | """ |
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| 333 | """ |
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| 334 | PlotData2D.__init__(self, image=image, err_image=err_image, |
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| 335 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
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| 336 | zmin=zmin, zmax=zmax, qx_data=qx_data, |
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| 337 | qy_data=qy_data) |
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| 338 | |
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| 339 | LoadData2D.__init__(self, data=image, err_data=err_image, |
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| 340 | qx_data=qx_data, qy_data=qy_data, |
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| 341 | dqx_data=dqx_data, dqy_data=dqy_data, |
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| 342 | q_data=q_data, mask=mask) |
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| 343 | self.id = None |
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| 344 | self.list_group_id = [] |
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| 345 | self.group_id = None |
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| 346 | self.is_data = True |
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| 347 | self.path = None |
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| 348 | self.xtransform = None |
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| 349 | self.ytransform = None |
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| 350 | self.title = "" |
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| 351 | self.scale = None |
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| 352 | |
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| 353 | def copy_from_datainfo(self, data2d): |
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| 354 | """ |
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| 355 | copy value of Data2D of type DataLoader.data_info |
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| 356 | """ |
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| 357 | self.data = copy.deepcopy(data2d.data) |
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| 358 | self.qx_data = copy.deepcopy(data2d.qx_data) |
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| 359 | self.qy_data = copy.deepcopy(data2d.qy_data) |
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| 360 | self.q_data = copy.deepcopy(data2d.q_data) |
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| 361 | self.mask = copy.deepcopy(data2d.mask) |
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| 362 | self.err_data = copy.deepcopy(data2d.err_data) |
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| 363 | self.x_bins = copy.deepcopy(data2d.x_bins) |
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| 364 | self.y_bins = copy.deepcopy(data2d.y_bins) |
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| 365 | if data2d.dqx_data is not None: |
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| 366 | self.dqx_data = copy.deepcopy(data2d.dqx_data) |
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| 367 | if data2d.dqy_data is not None: |
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| 368 | self.dqy_data = copy.deepcopy(data2d.dqy_data) |
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| 369 | self.xmin = data2d.xmin |
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| 370 | self.xmax = data2d.xmax |
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| 371 | self.ymin = data2d.ymin |
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| 372 | self.ymax = data2d.ymax |
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| 373 | if hasattr(data2d, "zmin"): |
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| 374 | self.zmin = data2d.zmin |
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| 375 | if hasattr(data2d, "zmax"): |
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| 376 | self.zmax = data2d.zmax |
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| 377 | self.xaxis(data2d._xaxis, data2d._xunit) |
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| 378 | self.yaxis(data2d._yaxis, data2d._yunit) |
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| 379 | self.title = data2d.title |
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| 380 | |
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| 381 | def __str__(self): |
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| 382 | """ |
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| 383 | print data |
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| 384 | """ |
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| 385 | _str = "%s\n" % LoadData2D.__str__(self) |
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| 386 | return _str |
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| 387 | |
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| 388 | def _perform_operation(self, other, operation): |
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| 389 | """ |
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| 390 | Perform 2D operations between data sets |
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| 391 | |
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| 392 | :param other: other data set |
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| 393 | :param operation: function defining the operation |
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| 394 | |
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| 395 | """ |
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| 396 | # First, check the data compatibility |
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| 397 | dy, dy_other = self._validity_check(other) |
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| 398 | result = Data2D(image=None, qx_data=None, qy_data=None, |
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| 399 | q_data=None, err_image=None, xmin=None, xmax=None, |
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| 400 | ymin=None, ymax=None, zmin=None, zmax=None) |
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| 401 | result.clone_without_data(len(self.data)) |
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| 402 | result.copy_from_datainfo(data2d=self) |
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| 403 | result.xmin = self.xmin |
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| 404 | result.xmax = self.xmax |
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| 405 | result.ymin = self.ymin |
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| 406 | result.ymax = self.ymax |
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| 407 | if self.dqx_data is None or self.dqy_data is None: |
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| 408 | result.dqx_data = None |
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| 409 | result.dqy_data = None |
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| 410 | else: |
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| 411 | result.dqx_data = np.zeros(len(self.data)) |
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| 412 | result.dqy_data = np.zeros(len(self.data)) |
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| 413 | for i in range(np.size(self.data)): |
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| 414 | result.data[i] = self.data[i] |
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| 415 | if self.err_data is not None and \ |
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| 416 | np.size(self.data) == np.size(self.err_data): |
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| 417 | result.err_data[i] = self.err_data[i] |
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| 418 | if self.dqx_data is not None: |
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| 419 | result.dqx_data[i] = self.dqx_data[i] |
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| 420 | if self.dqy_data is not None: |
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| 421 | result.dqy_data[i] = self.dqy_data[i] |
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| 422 | result.qx_data[i] = self.qx_data[i] |
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| 423 | result.qy_data[i] = self.qy_data[i] |
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| 424 | result.q_data[i] = self.q_data[i] |
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| 425 | result.mask[i] = self.mask[i] |
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| 426 | |
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| 427 | a = Uncertainty(self.data[i], dy[i]**2) |
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| 428 | if isinstance(other, Data2D): |
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| 429 | b = Uncertainty(other.data[i], dy_other[i]**2) |
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| 430 | if other.dqx_data is not None and \ |
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| 431 | result.dqx_data is not None: |
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| 432 | result.dqx_data[i] *= self.dqx_data[i] |
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| 433 | result.dqx_data[i] += (other.dqx_data[i]**2) |
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| 434 | result.dqx_data[i] /= 2 |
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| 435 | result.dqx_data[i] = math.sqrt(result.dqx_data[i]) |
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| 436 | if other.dqy_data is not None and \ |
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| 437 | result.dqy_data is not None: |
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| 438 | result.dqy_data[i] *= self.dqy_data[i] |
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| 439 | result.dqy_data[i] += (other.dqy_data[i]**2) |
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| 440 | result.dqy_data[i] /= 2 |
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| 441 | result.dqy_data[i] = math.sqrt(result.dqy_data[i]) |
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| 442 | else: |
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| 443 | b = other |
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| 444 | |
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| 445 | output = operation(a, b) |
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| 446 | result.data[i] = output.x |
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| 447 | result.err_data[i] = math.sqrt(math.fabs(output.variance)) |
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| 448 | return result |
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| 449 | |
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| 450 | def _perform_union(self, other): |
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| 451 | """ |
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| 452 | Perform 2D operations between data sets |
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| 453 | |
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| 454 | :param other: other data set |
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| 455 | :param operation: function defining the operation |
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| 456 | |
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| 457 | """ |
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| 458 | # First, check the data compatibility |
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| 459 | self._validity_check_union(other) |
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| 460 | result = Data2D(image=None, qx_data=None, qy_data=None, |
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| 461 | q_data=None, err_image=None, xmin=None, xmax=None, |
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| 462 | ymin=None, ymax=None, zmin=None, zmax=None) |
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| 463 | length = len(self.data) |
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| 464 | tot_length = length + len(other.data) |
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| 465 | result.clone_without_data(tot_length) |
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| 466 | result.xmin = self.xmin |
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| 467 | result.xmax = self.xmax |
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| 468 | result.ymin = self.ymin |
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| 469 | result.ymax = self.ymax |
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| 470 | if self.dqx_data is None or self.dqy_data is None or \ |
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| 471 | other.dqx_data is None or other.dqy_data is None : |
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| 472 | result.dqx_data = None |
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| 473 | result.dqy_data = None |
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| 474 | else: |
|---|
| 475 | result.dqx_data = np.zeros(len(self.data) + \ |
|---|
| 476 | np.size(other.data)) |
|---|
| 477 | result.dqy_data = np.zeros(len(self.data) + \ |
|---|
| 478 | np.size(other.data)) |
|---|
| 479 | |
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| 480 | result.data = np.append(self.data, other.data) |
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| 481 | result.qx_data = np.append(self.qx_data, other.qx_data) |
|---|
| 482 | result.qy_data = np.append(self.qy_data, other.qy_data) |
|---|
| 483 | result.q_data = np.append(self.q_data, other.q_data) |
|---|
| 484 | result.mask = np.append(self.mask, other.mask) |
|---|
| 485 | if result.err_data is not None: |
|---|
| 486 | result.err_data = np.append(self.err_data, other.err_data) |
|---|
| 487 | if self.dqx_data is not None: |
|---|
| 488 | result.dqx_data = np.append(self.dqx_data, other.dqx_data) |
|---|
| 489 | if self.dqy_data is not None: |
|---|
| 490 | result.dqy_data = np.append(self.dqy_data, other.dqy_data) |
|---|
| 491 | |
|---|
| 492 | return result |
|---|
| 493 | |
|---|
| 494 | def check_data_validity(data): |
|---|
| 495 | """ |
|---|
| 496 | Return True is data is valid enough to compute chisqr, else False |
|---|
| 497 | """ |
|---|
| 498 | flag = True |
|---|
| 499 | if data is not None: |
|---|
| 500 | if issubclass(data.__class__, Data2D): |
|---|
| 501 | if (data.data is None) or (len(data.data) == 0)\ |
|---|
| 502 | or (len(data.err_data) == 0): |
|---|
| 503 | flag = False |
|---|
| 504 | else: |
|---|
| 505 | if (data.y is None) or (len(data.y) == 0): |
|---|
| 506 | flag = False |
|---|
| 507 | if not data.is_data: |
|---|
| 508 | flag = False |
|---|
| 509 | else: |
|---|
| 510 | flag = False |
|---|
| 511 | return flag |
|---|
