diff --git a/MANIFEST.in b/MANIFEST.in index 890b8fb22..bc2fc4e88 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -7,6 +7,7 @@ recursive-include orangecontrib/spectroscopy/datasets emsc/* recursive-include orangecontrib/spectroscopy/datasets NeaReaderGSF_test/* recursive-include orangecontrib/spectroscopy/datasets renishaw_test_files/* recursive-include orangecontrib/spectroscopy/datasets photothermal/* +recursive-include orangecontrib/spectroscopy/datasets polar/* global-exclude __pycache__ diff --git a/doc/index.rst b/doc/index.rst index 0fd62172d..4a2c0c0b3 100644 --- a/doc/index.rst +++ b/doc/index.rst @@ -36,6 +36,7 @@ Widgets widgets/pls widgets/peakfit widgets/snr + widgets/polar Indices and tables ------------------ diff --git a/doc/widgets.json b/doc/widgets.json index f41ac3697..2321b8233 100644 --- a/doc/widgets.json +++ b/doc/widgets.json @@ -128,7 +128,14 @@ "icon": "../orangecontrib/spectroscopy/widgets/icons/stackalign.svg", "background": "light-blue", "keywords": [] + }, + { + "text": "4+ Angle Polarisation", + "doc": "widgets/polar.md", + "icon": "../orangecontrib/spectroscopy/widgets/icons/unknown.svg", + "background": "light-blue", + "keywords": [] } ] ] -] \ No newline at end of file +] diff --git a/doc/widgets/images/Polar-Example1.PNG b/doc/widgets/images/Polar-Example1.PNG new file mode 100644 index 000000000..73b8a205c Binary files /dev/null and b/doc/widgets/images/Polar-Example1.PNG differ diff --git a/doc/widgets/images/Polar-Example2.PNG b/doc/widgets/images/Polar-Example2.PNG new file mode 100644 index 000000000..7bbd5bf9b Binary files /dev/null and b/doc/widgets/images/Polar-Example2.PNG differ diff --git a/doc/widgets/images/Polar-stamped.png b/doc/widgets/images/Polar-stamped.png new file mode 100644 index 000000000..4941d5d13 Binary files /dev/null and b/doc/widgets/images/Polar-stamped.png differ diff --git a/doc/widgets/polar.md b/doc/widgets/polar.md new file mode 100644 index 000000000..8ab07b1e6 --- /dev/null +++ b/doc/widgets/polar.md @@ -0,0 +1,38 @@ +4+ Angle Polarisation +============ + +Calculates vibrational mode orientation from polarised datasets + +**Inputs** + +- Data: input dataset(s) + +**Outputs** + +- Polar Data: dataset with selected feature(s) orientation information +- Curve Fit Model Data: dataset with the optimal parameters of the curve fit model + +The **4+ Angle Polarisation** widget allows you to calculate orientation information of selected features using polarised spectroscopy data collected at 4 or more polarisation angles. The implemented algorithm is the same as that outlined by Hikima et. al. (2013)1 + +![](images/Polar-stamped.png) + +1. Inputs: Define the polarisation angles of the input dataset. Data can be passed to widget with two methods: + - *Multifile Input*: A single input with data from all polarisation angles in a single dataset. (Each polarisation angle must be separated with a categorical variable). + - *Multiple Inputs*: 1 input per polarisation angle. +2. Features: Select the features to calculate the orientation of. +3. Data XY Selection: Define the attributes for the x and y axes for 2D datasets. +4. Alpha value: The value (α) to use when calculating Herman's orientation function . +5. Invert Angles: Invert the calculated Azimuth Angles about the 0 degree axis (i.e. so that 90 degrees is output as -90 degrees). + +Input Examples +------- +MultiFile Input + +![](images/Polar-Example1.PNG) + +Multiple Inputs + +![](images/Polar-Example2.PNG) + + +1. Hikima, Y.; Morikawa, J.; Hashimoto, T., Wavenumber Dependence of FT-IR Image of Molecular Orientation in Banded Spherulites of Poly(3-hydroxybutyrate) and Poly(L-lactic acid). Macromolecules 2013, 46, 1582-1590. diff --git a/orangecontrib/spectroscopy/datasets/polar/4-angle-ftir_multifile.tab b/orangecontrib/spectroscopy/datasets/polar/4-angle-ftir_multifile.tab new file mode 100644 index 000000000..d3c091abd --- /dev/null +++ b/orangecontrib/spectroscopy/datasets/polar/4-angle-ftir_multifile.tab @@ -0,0 +1,19 @@ +1697.131066748047 1693.2739506872558 1689.416834626465 1685.5597185656738 1681.702602504883 1677.8454864440919 1673.9883703833011 1670.13125432251 1666.2741382617191 1662.417022200928 1658.5599061401367 1654.702790079346 1650.8456740185547 1646.988557957764 1643.1314418969728 1639.274325836182 1635.4172097753908 1631.5600937145996 1627.7029776538088 1623.8458615930176 1619.9887455322269 1616.1316294714356 1612.2745134106449 1608.4173973498537 1604.5602812890625 1600.7031652282717 1596.8460491674805 1592.9889331066897 1589.1318170458985 1585.2747009851078 1581.4175849243165 1577.5604688635258 1573.7033528027346 1569.8462367419434 1565.9891206811526 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a/orangecontrib/spectroscopy/datasets/polar/4-angle-ftir_multiin_polar-results.tab b/orangecontrib/spectroscopy/datasets/polar/4-angle-ftir_multiin_polar-results.tab new file mode 100644 index 000000000..3c29d7aca --- /dev/null +++ b/orangecontrib/spectroscopy/datasets/polar/4-angle-ftir_multiin_polar-results.tab @@ -0,0 +1,19 @@ +1697.131066748047 1693.2739506872558 1689.416834626465 1685.5597185656738 1681.702602504883 1677.8454864440919 1673.9883703833011 1670.13125432251 1666.2741382617191 1662.417022200928 1658.5599061401367 1654.702790079346 1650.8456740185547 1646.988557957764 1643.1314418969728 1639.274325836182 1635.4172097753908 1631.5600937145996 1627.7029776538088 1623.8458615930176 1619.9887455322269 1616.1316294714356 1612.2745134106449 1608.4173973498537 1604.5602812890625 1600.7031652282717 1596.8460491674805 1592.9889331066897 1589.1318170458985 1585.2747009851078 1581.4175849243165 1577.5604688635258 1573.7033528027346 1569.8462367419434 1565.9891206811526 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Azimuth Angle (1500.0 - 1580.0) Hermans Orientation Function (1500.0 - 1580.0) Intensity (1500.0 - 1580.0) Amplitude (1500.0 - 1580.0) R-squared (1500.0 - 1580.0) +continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous continuous 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0.3314375877380371 0.33745360374450684 0.3465556502342224 0.355802059173584 0.358920693397522 0.35263997316360474 0.33765292167663574 0.3183898329734802 0.30118611454963684 0.2887457013130188 0.28239473700523376 0.2824958264827728 0.2819530665874481 30442.5687 41541.616519999996 14.148486745442884 40.914534151939826 135.0 Degrees -58.74617564278722 0.012249198283408431 28.641297420407064 0.5230459500184083 0.9052486894719146 -31.249461838574835 0.010471285030812348 83.8267974762999 1.3098037700862717 0.5510780301748821 +0.3650876581668854 0.44027072191238403 0.49740421772003174 0.5676716566085815 0.6565104126930237 0.7217820286750793 0.776906430721283 0.8554854989051819 0.9431904554367065 0.99639892578125 0.9918259382247925 0.9632425308227539 0.9571559429168701 0.9453587532043457 0.9196834564208984 0.9045694470405579 0.8967841863632202 0.8714707493782043 0.8187240958213806 0.7500607967376709 0.6737703084945679 0.5944964289665222 0.5322104096412659 0.48620209097862244 0.4495582580566406 0.4267524480819702 0.4147963225841522 0.4065539836883545 0.40079763531684875 0.40120112895965576 0.4117395281791687 0.4343542158603668 0.4588378369808197 0.4770737290382385 0.49635985493659973 0.5230758190155029 0.5750504732131958 0.6321943402290344 0.6574925780296326 0.6613973379135132 0.6457144618034363 0.6232727766036987 0.6174584627151489 0.6194400787353516 0.6105873584747314 0.5773681402206421 0.5304786562919617 0.4934249520301819 0.45931971073150635 0.41730549931526184 0.38470304012298584 0.3595018684864044 0.3293219804763794 0.30435964465141296 0.2891426980495453 0.2798253893852234 0.2746725082397461 0.2748556435108185 0.2886051833629608 0.3117738366127014 0.32717078924179077 0.33106401562690735 0.3289177715778351 0.33031389117240906 0.33271220326423645 0.3304341435432434 0.32225725054740906 0.30900219082832336 0.2952777147293091 0.2869744896888733 0.28450044989585876 0.2863030433654785 0.29052266478538513 0.29561755061149597 0.3012177348136902 0.3077249825000763 0.3149780333042145 0.3194979727268219 0.31837978959083557 0.3156931400299072 0.31331557035446167 0.3074597716331482 0.29792141914367676 0.28665927052497864 0.2769920229911804 0.2717728316783905 0.2680080831050873 0.26393961906433105 0.2608543634414673 0.25888293981552124 0.25867512822151184 0.2605808675289154 0.263666570186615 0.26618891954421997 0.2665948271751404 0.2663698196411133 0.2670312225818634 0.26882821321487427 0.27096620202064514 0.2717668414115906 0.2718110680580139 0.2726369798183441 0.27475622296333313 0.2783312201499939 0.2822757363319397 0.285504013299942 0.2890436351299286 0.29262956976890564 0.292468398809433 0.2886587381362915 0.28673070669174194 0.2884071469306946 0.29260167479515076 0.30139777064323425 0.31254521012306213 0.32084983587265015 0.329580694437027 0.34177514910697937 0.35234349966049194 0.3568665683269501 0.3554323613643646 0.3491654396057129 0.3388620913028717 0.32499754428863525 0.3104616105556488 0.29853302240371704 0.28830283880233765 0.27974289655685425 0.27512240409851074 30445.38885 41541.616519999996 14.216843459338445 41.87857263213592 135.0 Degrees -75.66121752117968 0.024705796952298773 28.883928755026126 1.0573395108768266 0.9941901147353087 -87.96943280855872 0.008170118041294187 85.4864922350208 1.0433897898712823 0.1657092533769018 diff --git a/orangecontrib/spectroscopy/tests/test_owhyper.py b/orangecontrib/spectroscopy/tests/test_owhyper.py index e21516de8..33f7b706c 100644 --- a/orangecontrib/spectroscopy/tests/test_owhyper.py +++ b/orangecontrib/spectroscopy/tests/test_owhyper.py @@ -632,3 +632,40 @@ def test_compat_no_group(self): self.assertEqual(settings, {"compat_no_group": True}) self.widget = self.create_widget(OWHyper, stored_settings=settings) self.assertTrue(self.widget.compat_no_group) + + +class TestVectorPlot(WidgetTest): + + @classmethod + def setUpClass(cls): + super().setUpClass() + cls.whitelight = Orange.data.Table("whitelight.gsf") + cls.iris = Orange.data.Table("iris") + + def setUp(self): + super().setUp() + self.widget = self.create_widget(OWHyper) # type: OWHyper + + def test_enable_disable(self): + w = self.widget + for data in [None, self.whitelight, self.iris]: + self.send_signal(w.Inputs.data, data) + self.assertFalse(w.show_vector_plot) + self.assertFalse(w.controls.vector_magnitude.isEnabled()) + self.assertFalse(w.controls.vector_angle.isEnabled()) + self.assertFalse(w.controls.vector_colour_index.isEnabled()) + self.assertFalse(w.controls.vector_scale.isEnabled()) + self.assertFalse(w.controls.vector_opacity.isEnabled()) + w.controls.show_vector_plot.click() + self.assertTrue(w.show_vector_plot) + self.assertTrue(w.controls.vector_magnitude.isEnabled()) + self.assertTrue(w.controls.vector_angle.isEnabled()) + self.assertTrue(w.controls.vector_colour_index.isEnabled()) + self.assertTrue(w.controls.vector_scale.isEnabled()) + self.assertTrue(w.controls.vector_opacity.isEnabled()) + w.controls.show_vector_plot.click() + self.assertFalse(w.controls.vector_magnitude.isEnabled()) + self.assertFalse(w.controls.vector_angle.isEnabled()) + self.assertFalse(w.controls.vector_colour_index.isEnabled()) + self.assertFalse(w.controls.vector_scale.isEnabled()) + self.assertFalse(w.controls.vector_opacity.isEnabled()) diff --git a/orangecontrib/spectroscopy/tests/test_owpolar.py b/orangecontrib/spectroscopy/tests/test_owpolar.py new file mode 100644 index 000000000..8352145fd --- /dev/null +++ b/orangecontrib/spectroscopy/tests/test_owpolar.py @@ -0,0 +1,274 @@ +import unittest +import numpy as np +import Orange +from Orange.data import ContinuousVariable, DiscreteVariable, Domain +from Orange.widgets.tests.base import WidgetTest +from orangecontrib.spectroscopy.widgets.owpolar import OWPolar + +class TestOWPolar(WidgetTest): + + @classmethod + def setUpClass(cls): + super().setUpClass() + cls.multifile = Orange.data.Table("polar/4-angle-ftir_multifile.tab") + cls.in1 = Orange.data.Table("polar/4-angle-ftir_multiin1.tab") + cls.in2 = Orange.data.Table("polar/4-angle-ftir_multiin2.tab") + cls.in3 = Orange.data.Table("polar/4-angle-ftir_multiin3.tab") + cls.in4 = Orange.data.Table("polar/4-angle-ftir_multiin4.tab") + cls.multifile_polar = Orange.data.Table("polar/4-angle-ftir_multifile_polar-results.tab") + cls.multifile_model = Orange.data.Table("polar/4-angle-ftir_multifile_model-results.tab") + cls.multiin_polar = Orange.data.Table("polar/4-angle-ftir_multiin_polar-results.tab") + cls.multiin_model = Orange.data.Table("polar/4-angle-ftir_multiin_model-results.tab") + + def setUp(self): + self.widget = self.create_widget(OWPolar) + + def test_multifile_init(self): + self.send_signal("Data", self.multifile, 0) + + testfeats = [ft for ft in self.multifile.domain.metas + if isinstance(ft, ContinuousVariable)] + testfeats = testfeats + [ft for ft in self.multifile.domain.attributes + if isinstance(ft, ContinuousVariable)] + polfeats = [ft for ft in self.widget.featureselect[:] + if isinstance(ft, ContinuousVariable)] + self.assertEqual(polfeats, testfeats) + testinputs = [inp for inp in self.multifile.domain + if isinstance(inp, DiscreteVariable)] + self.assertEqual(self.widget.anglemetas[:], testinputs) + testxy = [xy for xy in self.multifile.domain.metas + if isinstance(xy, ContinuousVariable)] + self.assertEqual(self.widget.x_axis[:], testxy) + self.assertEqual(self.widget.y_axis[:], testxy) + + def test_multifile_in(self): + self.send_signal("Data", self.multifile, 0) + + self.assertTrue(self.widget.isEnabled()) + for i in self.widget.multiin_labels: + self.assertFalse(i.isEnabled()) + for i in self.widget.multiin_lines: + self.assertFalse(i.isEnabled()) + self.widget.angles = self.widget.anglemetas[0] + self.assertEqual(self.widget.angles, self.multifile.domain.metas[2]) + self.widget._change_angles() + self.assertEqual(len(self.widget.labels), 4) + self.assertEqual(len(self.widget.lines), 4) + self.assertEqual(self.widget.polangles, list(np.linspace(0, 180, 5)[:4])) + for i in self.widget.labels: + self.assertTrue(i.isEnabled()) + for i in self.widget.lines: + self.assertTrue(i.isEnabled()) + self.widget.map_x = self.widget.x_axis[0] + self.assertEqual(self.widget.map_x, self.multifile.domain.metas[0]) + self.widget.map_y = self.widget.y_axis[1] + self.assertEqual(self.widget.map_y, self.multifile.domain.metas[1]) + self.widget.feats = [self.widget.feat_view.model()[:][2], + self.widget.feat_view.model()[:][3]] + self.assertEqual(self.widget.feats[0], self.multifile.domain.metas[3]) + self.assertEqual(self.widget.feats[1], self.multifile.domain.metas[4]) + self.widget.alpha = 0 + self.widget.invert_angles = True + self.widget.autocommit = True + self.commit_and_wait(self.widget, 20000) + + polar = self.get_output("Polar Data") + model = self.get_output("Curve Fit model data") + + np.testing.assert_allclose(np.asarray(self.multifile_polar.metas, dtype=float), + np.asarray(polar.metas, dtype=float)) + np.testing.assert_allclose(np.asarray(self.multifile_polar.X, dtype=float), + np.asarray(polar.X, dtype=float)) + np.testing.assert_allclose(np.asarray(self.multifile_model.metas, dtype=float), + np.asarray(model.metas, dtype=float)) + np.testing.assert_allclose(np.asarray(self.multifile_model.X, dtype=float), + np.asarray(model.X, dtype=float)) + + def test_multi_inputs(self): + self.send_signal("Data", self.in1, 0, widget=self.widget) + self.send_signal("Data", self.in2, 1, widget=self.widget) + + self.assertFalse(self.widget.anglesel.isEnabled()) + for i in self.widget.multiin_labels: + self.assertFalse(i.isEnabled()) + for i in self.widget.multiin_lines: + self.assertFalse(i.isEnabled()) + self.send_signal("Data", self.in3, 2, widget=self.widget) + self.send_signal("Data", self.in4, 3, widget=self.widget) + self.assertFalse(self.widget.anglesel.isEnabled()) + for i in self.widget.multiin_labels: + self.assertTrue(i.isEnabled()) + for i in self.widget.multiin_lines: + self.assertTrue(i.isEnabled()) + + self.widget.map_x = self.widget.x_axis[0] + self.assertEqual(self.widget.map_x, self.in1.domain.metas[0]) + self.widget.map_y = self.widget.y_axis[1] + self.assertEqual(self.widget.map_y, self.in1.domain.metas[1]) + + self.widget.feats = [self.widget.feat_view.model()[:][2], + self.widget.feat_view.model()[:][3]] + self.assertEqual(self.widget.feats[0], + self.in1.domain.metas[2].copy(compute_value=None)) + self.assertEqual(self.widget.feats[1], + self.in1.domain.metas[3].copy(compute_value=None)) + self.widget.alpha = 0 + self.widget.invert_angles = True + self.widget.autocommit = True + self.commit_and_wait(self.widget, 20000) + + polar = self.get_output("Polar Data") + model = self.get_output("Curve Fit model data") + + np.testing.assert_allclose( + np.asarray(self.multiin_polar.metas[:,np.r_[0:2,3:7]], dtype=float), + np.asarray(polar.metas[:,np.r_[0:2,3:7]], dtype=float)) + np.testing.assert_allclose( + np.asarray(self.multiin_polar.metas[:,7:], dtype=float), + np.asarray(polar.metas[:,7:], dtype=float)) + np.testing.assert_equal(self.multiin_polar.X, np.flip(polar.X, axis=1)) + np.testing.assert_allclose( + np.asarray(self.multiin_model.metas[:,np.r_[0:2,3:7]], dtype=float), + np.asarray(model.metas[:,np.r_[0:2,3:7]], dtype=float)) + np.testing.assert_allclose( + np.asarray(self.multiin_model.metas[:,7:], dtype=float), + np.asarray(model.metas[:,7:], dtype=float)) + np.testing.assert_equal(self.multiin_model.X, np.flip(model.X, axis=1)) + + def test_pixelsubset(self): + #Test multi in with subset of pixels selected + rng = np.random.default_rng() + sub_idx = rng.choice(4, size=(2), replace=False) + subset = self.in1[sub_idx] + + self.send_signal("Data", subset, 0, widget=self.widget) + self.send_signal("Data", self.in2, 1, widget=self.widget) + self.send_signal("Data", self.in3, 2, widget=self.widget) + self.send_signal("Data", self.in4, 3, widget=self.widget) + + self.widget.map_x = self.widget.x_axis[0] + self.widget.map_y = self.widget.y_axis[1] + self.widget.feats = [self.widget.feat_view.model()[:][2], + self.widget.feat_view.model()[:][3]] + self.widget.alpha = 0 + self.widget.invert_angles = True + self.widget.autocommit = True + self.commit_and_wait(self.widget, 20000) + + polar = self.get_output("Polar Data") + model = self.get_output("Curve Fit model data") + + self.assertEqual(len(polar), len(sub_idx)*4) + self.assertEqual(len(model), len(sub_idx)*4) + + def test_multiin_mismatched_domain(self): + + metadom = self.in1.domain.metas + metadom = [i for i in metadom if isinstance(i, ContinuousVariable)] + attdom = self.in1.domain.attributes + attdom = attdom[0::2] + mismatched_domain = Domain(attdom, metas = metadom) + mismatched_table = self.in1.transform(mismatched_domain) + + self.send_signal("Data", mismatched_table, 0, widget=self.widget) + self.send_signal("Data", self.in2, 1, widget=self.widget) + self.send_signal("Data", self.in3, 2, widget=self.widget) + self.send_signal("Data", self.in4, 3, widget=self.widget) + + feat_len = len(metadom) + len(attdom) + 1 + XY_len = len(metadom) + self.assertEqual(feat_len, len(self.widget.feat_view.model()[:])) + self.assertEqual(XY_len, len(self.widget.x_axis[:])) + self.assertEqual(XY_len, len(self.widget.y_axis[:])) + + self.send_signal("Data", self.in2, 0, widget=self.widget) + self.send_signal("Data", self.in3, 1, widget=self.widget) + self.send_signal("Data", mismatched_table, 2, widget=self.widget) + self.send_signal("Data", self.in4, 3, widget=self.widget) + + feat_len = len(metadom) + len(attdom) + 1 + XY_len = len(metadom) + self.assertEqual(feat_len, len(self.widget.feat_view.model()[:])) + self.assertEqual(XY_len, len(self.widget.x_axis[:])) + self.assertEqual(XY_len, len(self.widget.y_axis[:])) + + def test_custom_angles(self): + # test inputting custom angles (multin and multifile) + self.send_signal("Data", self.multifile, 0, widget=self.widget) + angles = np.array([0, 22.5, 45.0, 90]) + + for i, j in enumerate(self.widget.lines): + j.setText(str(angles[i])) + self.widget._send_angles() + for i, j in enumerate(self.widget.polangles): + self.assertEqual(j, angles[i]) + + self.send_signal("Data", self.in1, 0, widget=self.widget) + self.send_signal("Data", self.in2, 1, widget=self.widget) + self.send_signal("Data", self.in3, 2, widget=self.widget) + self.send_signal("Data", self.in4, 3, widget=self.widget) + + for i, j in enumerate(self.widget.multiin_lines): + j.setText(str(angles[i])) + self.widget._send_ind_angles() + for i, j in enumerate(self.widget.polangles): + self.assertEqual(j, angles[i]) + + def test_warnings(self): + #test all warnings + self.send_signal("Data", self.multifile, 0, widget=self.widget) + self.widget.autocommit = True + + self.commit_and_wait(self.widget) + self.assertTrue(self.widget.Warning.nofeat.is_shown()) + + self.widget.feats = [self.widget.feat_view.model()[:][4]] + self.widget.map_x = None + self.widget.map_y = None + self.commit_and_wait(self.widget) + self.assertTrue(self.widget.Warning.noxy.is_shown()) + + self.widget.map_x = self.widget.x_axis[0] + self.widget.map_y = self.widget.y_axis[1] + self.widget.polangles = [] + self.commit_and_wait(self.widget) + self.assertTrue(self.widget.Warning.pol.is_shown()) + self.widget.polangles = [0.0,45.0,'hi',135.0] + self.commit_and_wait(self.widget) + self.assertTrue(self.widget.Warning.pol.is_shown()) + + self.widget.polangles = [0.0,45.0,90.0,135.0] + self.widget.feats = [self.widget.feat_view.model()[:][0]] + self.commit_and_wait(self.widget) + self.assertTrue(self.widget.Warning.XYfeat.is_shown()) + + self.send_signal("Data", self.in1, 0, widget=self.widget) + self.send_signal("Data", self.in2, 1, widget=self.widget) + self.assertTrue(self.widget.Warning.notenough.is_shown()) + + self.send_signal("Data", self.in3, 2, widget=self.widget) + self.assertTrue(self.widget.Warning.notenough.is_shown()) + + self.send_signal("Data", self.in4, 3, widget=self.widget) + self.assertFalse(self.widget.Warning.notenough.is_shown()) + + def test_disconnect(self): + self.send_signal("Data", self.multifile, 0, widget=self.widget) + self.widget.angles = self.widget.anglemetas[0] + self.widget.map_x = self.widget.x_axis[0] + self.widget.map_y = self.widget.y_axis[1] + self.widget.alpha = 0 + self.widget.invert_angles = True + self.widget.autocommit = True + self.widget.feats = [self.widget.feat_view.model()[:][2], + self.widget.feat_view.model()[:][3]] + self.widget.handleNewSignals() + self.wait_until_stop_blocking() + self.send_signal("Data", None, 0, widget=self.widget) + + # def test_clearangles(self): + # #test clearing angles + # pass + +if __name__ == "__main__": + unittest.main() diff --git a/orangecontrib/spectroscopy/widgets/owhyper.py b/orangecontrib/spectroscopy/widgets/owhyper.py index f008aa3d5..c2a8bd88a 100644 --- a/orangecontrib/spectroscopy/widgets/owhyper.py +++ b/orangecontrib/spectroscopy/widgets/owhyper.py @@ -22,7 +22,7 @@ import Orange.data from Orange.preprocess.transformation import Identity -from Orange.data import Domain, DiscreteVariable, ContinuousVariable +from Orange.data import Domain, DiscreteVariable, ContinuousVariable, Variable from Orange.widgets.widget import OWWidget, Msg, OWComponent, Input from Orange.widgets import gui from Orange.widgets.settings import \ @@ -163,6 +163,7 @@ def render(self): else: lut = self.lut + image = self.image levels = self.levels if self.axisOrder == 'col-major': @@ -229,8 +230,23 @@ def color_palette_table(colors, underflow=None, overflow=None): # misc ("rainbow", {0: np.array(colorcet.rainbow_bgyr_35_85_c73) * 255}), ("isolum", {0: np.array(colorcet.isoluminant_cgo_80_c38) * 255}), -] + ("Jet", {0: pg.colormap.get("jet", source='matplotlib').getLookupTable(nPts=256)}), + ("Viridis", {0: pg.colormap.get("viridis", source='matplotlib').getLookupTable(nPts=256)}), + # cyclic + ("HSV", {0: pg.colormap.get("hsv", source='matplotlib').getLookupTable(nPts=256)}), +] +#r, g, b, c, m, y, k, w +vector_colour = [ + ("Black", {0: (0,0,0)}), + ("White", {0: (255,255,255)}), + ("Red", {0: (255,0,0)}), + ("Green", {0: (0,255,0)}), + ("Blue", {0: (0,0,255)}), + ("Cyan", {0: (0,255,255)}), + ("Magenta", {0: (255,0,255)}), + ("Yellow", {0: (255,255,0)}), +] def palette_gradient(colors): n = len(colors) @@ -268,6 +284,13 @@ def color_palette_model(palettes, iconsize=QSize(64, 16)): model.appendRow([item]) return model +def vector_colour_model(colours): + model = QStandardItemModel() + for name, palette in colours: + item = QStandardItem(name) + item.setData(palette, Qt.UserRole) + model.appendRow([item]) + return model class ImageColorSettingMixin: threshold_low = Setting(0.0, schema_only=True) @@ -600,6 +623,8 @@ def __init__(self, parent): self.data_values = None self.data_imagepixels = None self.data_valid_positions = None + self.xindex = None + self.yindex = None self.plotview = pg.GraphicsLayoutWidget() self.plot = pg.PlotItem(background="w", viewBox=InteractiveViewBox(self)) @@ -624,6 +649,10 @@ def __init__(self, parent): self.plot.vb.setAspectLocked() self.plot.scene().sigMouseMoved.connect(self.plot.vb.mouseMovedEvent) + self.vector_plot = pg.PlotCurveItem() + self.vector_plot.hide() + self.plot.addItem(self.vector_plot) + layout = QGridLayout() self.plotview.setLayout(layout) self.button = QPushButton("Menu", self.plotview) @@ -817,6 +846,9 @@ def update_view(self): self.data_values = None self.data_imagepixels = None self.data_valid_positions = None + self.xindex = None + self.yindex = None + self.update_vectors() # clears the vector plot if self.data and self.attr_x and self.attr_y: self.start(self.compute_image, self.data, self.attr_x, self.attr_y, @@ -843,9 +875,43 @@ def set_visible_image_opacity(self, opacity: int): def set_visible_image_comp_mode(self, comp_mode: QPainter.CompositionMode): self.vis_img.setCompositionMode(comp_mode) + def update_vector_colour(self): + pen = self.parent.get_vector_colour() + self.vector_plot.setPen(pen) + + def update_vectors(self): + v = self.parent.get_vector_data() + if self.lsx is None: # image is not shown or is being computed + v = None + if v is None: + self.vector_plot.hide() + else: + valid = self.data_valid_positions + lsx, lsy = self.lsx, self.lsy + xindex, yindex = self.xindex, self.yindex + scale = self.parent.vector_scale + th = v[:,0] + v_mag = v[:,1] + amp = v_mag / max(v_mag) * (scale/100) + wy = _shift(lsx)*2 + wx = _shift(lsx)*2 + y = np.linspace(*lsy)[yindex[valid]] + x = np.linspace(*lsx)[xindex[valid]] + dispx = amp*wx/2*np.cos(np.radians(th)) + dispy = amp*wy/2*np.sin(np.radians(th)) + xcurve = np.empty((dispx.shape[0]*2)) + ycurve = np.empty((dispy.shape[0]*2)) + xcurve[0::2], xcurve[1::2] = x - dispx, x + dispx + ycurve[0::2], ycurve[1::2] = y - dispy, y + dispy + connect = np.ones((dispx.shape[0]*2)) + connect[1::2] = 0 + self.vector_plot.setData(x=xcurve, y=ycurve, connect=connect) + self.vector_plot.show() + @staticmethod def compute_image(data: Orange.data.Table, attr_x, attr_y, - image_values, image_values_fixed_levels, state: TaskState): + image_values, image_values_fixed_levels, + state: TaskState): def progress_interrupt(i: float): if state.is_interruption_requested(): @@ -928,6 +994,13 @@ def on_done(self, res): height = (lsy[1]-lsy[0]) + 2*shifty self.img.setRect(QRectF(left, bottom, width, height)) + # indices need to be saved to quickly draw vectors + self.yindex = yindex + self.xindex = xindex + + self.update_vectors() + self.update_vector_colour() + self.refresh_img_selection() self.image_updated.emit() @@ -977,6 +1050,13 @@ class Outputs(SelectionOutputsMixin.Outputs): rgb_green_value = ContextSetting(None) rgb_blue_value = ContextSetting(None) + show_vector_plot = Setting(False) + vector_angle = ContextSetting(None) + vector_magnitude = ContextSetting(None) + vector_colour_index = ContextSetting(0) + vector_scale = Setting(1) + vector_opacity = Setting(255) + show_visible_image = Setting(False) visible_image_name = Setting(None) visible_image_composition = Setting('Normal') @@ -1081,6 +1161,8 @@ def __init__(self): self.imageplot = ImagePlot(self) self.imageplot.selection_changed.connect(self.output_image_selection) + self.setup_vector_plot_controls() + # do not save visible image (a complex structure as a setting; # only save its name) self.visible_image = None @@ -1115,6 +1197,85 @@ def __init__(self): # prepare interface according to the new context self.contextAboutToBeOpened.connect(lambda x: self.init_interface_data(x[0])) + def setup_vector_plot_controls(self): + self.vectorbox = gui.widgetBox(self.controlArea, box=True) + + gui.checkBox(self.vectorbox, self, 'show_vector_plot', + label='Plot vector overlay', callback=self._update_vector) + + self.vector_opts = DomainModel(DomainModel.SEPARATED, + valid_types=DomainModel.PRIMITIVE, placeholder='None') + self.vector_angle = None + self.vector_magnitude = None + self.colour_opts = vector_colour + + self.v_angle_select = gui.comboBox(self.vectorbox, self, 'vector_angle', searchable=True, + label="Vector Angle", model=self.vector_opts, + callback=self._update_vector) + + self.v_mag_select = gui.comboBox(self.vectorbox, self, 'vector_magnitude', searchable=True, + label="Vector Magnitude", model=self.vector_opts, + callback=self._update_vector) + + self.v_colour_select = gui.comboBox(self.vectorbox, self, 'vector_colour_index', + label="Vector Colour", callback=self.update_vector_colour) + model = vector_colour_model(vector_colour) + model.setParent(self) + self.v_colour_select.setModel(model) + + self.v_scale_slider = gui.hSlider(self.vectorbox, self, 'vector_scale', label="Scale", + minValue=0, maxValue=1000, step=10, createLabel=False, + callback=self.update_vector_scale) + + self.v_opacity_slider = gui.hSlider(self.vectorbox, self, 'vector_opacity', label="Opacity", + minValue=0, maxValue=255, step=5, createLabel=False, + callback=self.update_vector_colour) + + self._update_vector() + + + def update_vector_plot_interface(self): + vector_params = ['vector_angle', 'vector_magnitude', 'vector_colour_index', + 'vector_scale', 'vector_opacity'] + for i in vector_params: + getattr(self.controls, i).setEnabled(self.show_vector_plot) + + def _update_vector(self): + self.update_vector_plot_interface() + self.imageplot.update_vectors() + self.imageplot.update_vector_colour() + + def get_vector_data(self): + if self.show_vector_plot is False or self.data is None: + return None + + ang = self.vector_angle + mag = self.vector_magnitude + angs = self.data.get_column_view(ang)[0] if ang else np.full(len(self.data), 0) + mags = self.data.get_column_view(mag)[0] if mag else np.full(len(self.data), 1) + + return np.vstack([angs, mags]).T + + def get_vector_colour(self): + return vector_colour[self.vector_colour_index][1][0] + (self.vector_opacity,) + + def update_vector_colour(self): + self.imageplot.update_vector_colour() + + def update_vector_scale(self): + self.imageplot.update_vectors() + + def init_vector_plot(self, data): + domain = data.domain if data is not None else None + self.vector_opts.set_domain(domain) + + # initialize values so that the combo boxes are not in invalid states + if self.vector_opts: + # TODO here we could instead set good default values if available + self.vector_magnitude = self.vector_angle = None + else: + self.vector_magnitude = self.vector_angle = None + def setup_visible_image_controls(self): self.visbox = gui.widgetBox(self.controlArea, True) @@ -1166,6 +1327,7 @@ def update_visible_image_opacity(self): def init_interface_data(self, data): self.init_attr_values(data) self.init_visible_images(data) + self.init_vector_plot(data) def output_image_selection(self): _, selected = self.send_selection(self.data, self.imageplot.selection_group) diff --git a/orangecontrib/spectroscopy/widgets/owpolar.py b/orangecontrib/spectroscopy/widgets/owpolar.py new file mode 100644 index 000000000..9f0768712 --- /dev/null +++ b/orangecontrib/spectroscopy/widgets/owpolar.py @@ -0,0 +1,822 @@ +import os +import multiprocessing +from multiprocessing.managers import SharedMemoryManager +from typing import List, Optional, Sequence + +import math +from types import SimpleNamespace +import numpy as np +import pandas as pd +from AnyQt.QtCore import QItemSelectionModel, QItemSelection, QItemSelectionRange +from AnyQt.QtWidgets import QFormLayout, QWidget, QListView, QLabel, QSizePolicy +from scipy.optimize import curve_fit + + +import Orange.data +from Orange.data import DiscreteVariable, ContinuousVariable, Domain, Variable +from Orange.data.table import Table +from Orange.widgets.widget import OWWidget, Msg, Output, MultiInput +from Orange.widgets import gui, settings + +from Orange.widgets.settings import \ + Setting, ContextSetting, DomainContextHandler +from Orange.widgets.utils.itemmodels import DomainModel +from Orange.widgets.utils.concurrent import TaskState, ConcurrentWidgetMixin +from Orange.widgets.data import owconcatenate +from Orange.widgets.data.oweditdomain import disconnected +from orangewidget.utils.listview import ListViewSearch + + +def _restore_selected_items(model, view, setting, connector): + selection = QItemSelection() + sel_model: QItemSelectionModel = view.selectionModel() + with disconnected(sel_model.selectionChanged, + connector): + valid = [] + model_values = model[:] + for var in setting: + index = model_values.index(var) + model_index = view.model().index(index, 0) + selection.append(QItemSelectionRange(model_index)) + valid.append(var) + sel_model.select(selection, QItemSelectionModel.ClearAndSelect) + + +class Results(SimpleNamespace): + out = None + model = None + errorstate = 0 + +def sort_domain(domain): + dom = [domain.metas, domain.attributes, domain.class_vars] + sorted_dom_lst = [] + for i in dom: + cvs = [[i, j, j.name] for i, j in enumerate(i)] + rcvs_idx = [] + rcvs = [] + for j, k in enumerate(cvs): + try: + cvs[j][-1] = float(k[-1]) + except ValueError: + rcvs.append(k[1]) + rcvs_idx.append(j) + for j in reversed(rcvs_idx): + cvs.pop(j) + cvs_arr = np.array(cvs) + if cvs_arr.shape[0] > 0: + cvs_arr_sorted = cvs_arr[cvs_arr[:,2].argsort()] + odom_cv = [i[1] for i in cvs_arr_sorted] + odom = rcvs + odom_cv + else: + odom = rcvs + sorted_dom_lst.append(tuple(odom)) + out = Domain(sorted_dom_lst[1], class_vars=sorted_dom_lst[2], metas=sorted_dom_lst[0]) + return out + +def combine_visimg(data, polangles): + atts = [] + for k, i in enumerate(data): + try: + temp = i.attributes['visible_images'] + for j in temp: + tempname = str(j['name'] + f'({polangles[k]} Degrees)') + dictcopy = j.copy() + dictcopy.update({'name': tempname}) + atts = atts + [dictcopy] + except KeyError: + pass + except AttributeError: + pass + attsdict = {'visible_images': atts} + return attsdict + +def run(data, feature, alpha, map_x, map_y, invert_angles, polangles, average, + sep, state: TaskState): + + results = Results() + + output, model, spectra, origmetas, errorstate = process_polar_abs(data, alpha, feature, map_x, + map_y, invert_angles, polangles, average, state) + + tempoutaddmetas = [[ContinuousVariable.make('Azimuth Angle (' + i.name + ')'), + ContinuousVariable.make('Hermans Orientation Function (' + i.name + ')'), + ContinuousVariable.make('Intensity (' + i.name + ')'), + ContinuousVariable.make('Amplitude (' + i.name + ')'), + ContinuousVariable.make('R-squared (' + i.name + ')')] for i in feature] + outaddmetas = [] + for i in tempoutaddmetas: + outaddmetas = outaddmetas + i + + tempmodaddmetas = [[ContinuousVariable.make('R-squared (' + i.name + ')'), + ContinuousVariable.make('a0 (' + i.name + ')'), + ContinuousVariable.make('a1 (' + i.name + ')'), + ContinuousVariable.make('a2 (' + i.name + ')')] for i in feature] + modaddmetas = [] + for i in tempmodaddmetas: + modaddmetas = modaddmetas + i + ometadom = data[0].domain.metas + if average is False: + values = tuple(f'{i} Degrees' for i in polangles) + PolAng = DiscreteVariable.make('Polarisation Angle', values=values) + outmetadom = (ometadom + tuple([PolAng]) + tuple(outaddmetas)) + modmetadom = (ometadom + tuple([PolAng]) + tuple(modaddmetas)) + output_stack = tuple(output for i in polangles) + model_stack = tuple(model for i in polangles) + output = np.vstack(output_stack) + model = np.vstack(model_stack) + elif average is True: + if sep is not None: + sep_idx = ometadom.index(sep) + try: + origmetas = np.c_[origmetas[:,0:sep_idx], origmetas[:,sep_idx+1:]] + except ValueError: + origmetas = np.r_[origmetas[:,0:sep_idx]] + ometadom = tuple(i for i in ometadom if i is not sep) + outmetadom = (ometadom + tuple(outaddmetas)) + modmetadom = (ometadom + tuple(modaddmetas)) + + ofeatdom = data[0].domain.attributes + datadomain = Domain(ofeatdom, metas = outmetadom) + moddomain = Domain(ofeatdom, metas = modmetadom) + outmetas = np.hstack((origmetas, output)) + modmetas = np.hstack((origmetas, model)) + + out = Table.from_numpy(datadomain, X=spectra, Y=None, metas=outmetas) + mod = Table.from_numpy(moddomain, X=spectra, Y=None, metas=modmetas) + + results.out = out + results.model = mod + results.errorstate = errorstate + + attsdict = combine_visimg(data, polangles) + + results.out.attributes = attsdict + results.model.attributes = attsdict + return results + +#Calculate by fitting to function +def azimuth(x,a0,a1,a2): + t = 2*np.radians(x) + return a0*np.sin(t)+a1*np.cos(t)+a2 + +def azimuth_jac(x, a0, a1, a2): + t = 2*np.radians(x).reshape(-1, 1) + da0 = np.sin(t) + da1 = np.cos(t) + da2 = np.ones(t.shape) + return np.hstack((da0, da1, da2)) + +def calc_angles(a0,a1): + return np.degrees(0.5*np.arctan(a0/a1)) + +def ampl1(a0,a1,a2): + return (a2+(math.sqrt(a0**2+a1**2))+a2-(math.sqrt(a0**2+a1**2))) + +def ampl2(a0,a1): + return (2*(math.sqrt(a0**2+a1**2))) + +def orfunc(alpha,a0,a1,a2): + if alpha < 54.73: + Dmax = (2*a2+2*math.sqrt(a0**2+a1**2))/(2*a2-2*math.sqrt(a0**2+a1**2)) + return ((Dmax-1)/(Dmax+2)*(2/(3*np.cos(np.radians(alpha))**2-1))) + elif alpha >= 54.73: + Dmin = (2*a2-2*math.sqrt(a0**2+a1**2))/(2*a2+2*math.sqrt(a0**2+a1**2)) + return ((Dmin-1)/(Dmin+2)*(2/(3*np.cos(np.radians(alpha))**2-1))) + return None + +def find_az(alpha, params): + Az0 = calc_angles(params[0],params[1]) + Abs0 = azimuth(Az0, *params) + Az1 = calc_angles(params[0],params[1])+90 + Abs1 = azimuth(Az1, *params) + Az2 = calc_angles(params[0],params[1])-90 + + if alpha < 54.73: + if Abs0 > Abs1: + Az = Az0 + elif Abs1 > Abs0: + if Az1 < 90: + Az = Az1 + elif Az1 > 90: + Az = Az2 + elif alpha >= 54.73: + if Abs0 < Abs1: + Az = Az0 + elif Abs1 < Abs0: + if Az1 < 90: + Az = Az1 + elif Az1 > 90: + Az = Az2 + return Az + +def compute(xys, yidx, smms, shapes, dtypes, polangles): + tcvs = smms[0] + cvs = np.ndarray(shapes[0], dtype=dtypes[0], buffer=tcvs.buf) + tout = smms[3] + out = np.ndarray(shapes[3], dtype=dtypes[3], buffer=tout.buf) + tmod = smms[4] + mod = np.ndarray(shapes[4], dtype=dtypes[4], buffer=tmod.buf) + tcoords = smms[5] + coords = np.ndarray(shapes[5], dtype=dtypes[5], buffer=tcoords.buf) + tvars = smms[6] + vars = np.ndarray(shapes[6], dtype=dtypes[6], buffer=tvars.buf) + + x = np.asarray(polangles) + + for i in range(yidx[0], yidx[1]):#y-values(rows) + if vars[1] == 1: + break + for j in enumerate(xys[0]):#x-values(cols) + for l in range(cvs.shape[2]): + if np.any(np.isnan(cvs[i,j[0],l,:]), axis=0): + continue + out[i,j[0],l,0] = coords[i,j[0],1]#x-map + mod[i,j[0],l,0] = coords[i,j[0],1] + out[i,j[0],l,1] = coords[i,j[0],0]#y-map + mod[i,j[0],l,1] = coords[i,j[0],0] + + temp = list(cvs[i,j[0],l,:]) + + params = curve_fit(azimuth, x, temp, jac=azimuth_jac)[0] + + residuals = temp - azimuth(x, *params) + ss_res = np.sum(residuals**2) + ss_tot = np.sum((temp-np.mean(temp))**2) + if ss_tot == 0: + vars[1] = 1 + break + out[i,j[0],l,6] = 1-(ss_res/ss_tot) + mod[i,j[0],l,2] = 1-(ss_res/ss_tot) + out[i,j[0],l,2] = find_az(vars[0], params) + out[i,j[0],l,3] = orfunc(vars[0], *params) + out[i,j[0],l,4] = ampl1(*params) + out[i,j[0],l,5] = ampl2(params[0],params[1]) + mod[i,j[0],l,3] = params[0] + mod[i,j[0],l,4] = params[1] + mod[i,j[0],l,5] = params[2] + + +def unique_xys(images, map_x, map_y): + lsxs = np.empty(0) + lsys = np.empty(0) + for i in enumerate(images): + tempdata = i[1].transform(Domain([map_x, map_y])) + lsx = np.unique(tempdata.X[:,0]) + lsy = np.unique(tempdata.X[:,1]) + lsxs = np.append(lsxs, lsx) + lsys = np.append(lsys, lsy) + + ulsxs = np.unique(lsxs) + ulsys = np.unique(lsys) + return ulsxs, ulsys + +def start_compute(ulsxs, ulsys, names, shapes, dtypes, polangles, state): + # single core processing is faster for small data sets and small number of selected features + # if > x: + ncpu = os.cpu_count() + # ncpu = 6 + tulsys = np.array_split(ulsys, ncpu) + state.set_status("Calculating...") + threads=[] + cumu = 0 + for i in range(ncpu): + tlsxys = [ulsxs,tulsys[i]] + yidx = [cumu, cumu+len(tulsys[i])] + cumu += len(tulsys[i]) + # compute(tlsxys, yidx, shapes, dtypes, polangles, i) + t = multiprocessing.Process(target=compute, + args=(tlsxys, yidx, names, shapes, dtypes, polangles)) + threads.append(t) + t.start() + + # for t in threads: + # t.join() + + # else: + # ncpu = 1 + # tulsys = np.array_split(ulsys, ncpu) + # state.set_status("Calculating...") + # threads=[] + # cumu = 0 + # for i in range(ncpu): + # tlsxys = [ulsxs,tulsys[i]] + # yidx = [cumu, cumu+len(tulsys[i])] + # cumu += len(tulsys[i]) + # compute(tlsxys, yidx, shapes, dtypes, polangles, i) + return threads + +def process_polar_abs(images, alpha, feature, map_x, map_y, invert, polangles, average, state): + state.set_status("Preparing...") + + ulsxs, ulsys = unique_xys(images, map_x, map_y) + + if len(ulsxs) > 1: + dx = np.sum(np.diff(ulsxs))/(len(ulsxs)-1) + else: + dx = 1 + if len(ulsys) > 1: + dy = np.sum(np.diff(ulsys))/(len(ulsys)-1) + else: + dy = 1 + minx = np.min(ulsxs) + miny = np.min(ulsys) + + featnames = [i.name for i in feature] + cvs = np.full((np.shape(ulsys)[0], np.shape(ulsxs)[0], len(featnames), len(images)), np.nan) + spec = np.full((np.shape(ulsys)[0], np.shape(ulsxs)[0], + images[0].X.shape[1], len(images)), np.nan, dtype=object) + metas = np.full((np.shape(ulsys)[0], np.shape(ulsxs)[0], + images[0].metas.shape[1], len(images)), np.nan, dtype=object) + out = np.full((np.shape(ulsys)[0], np.shape(ulsxs)[0], len(featnames), 7), np.nan) + mod = np.full((np.shape(ulsys)[0], np.shape(ulsxs)[0], len(featnames), 6), np.nan) + coords = np.full((np.shape(ulsys)[0], np.shape(ulsxs)[0], 2), np.nan) + vars = np.asarray([alpha, 0]) + fill = np.full((np.shape(ulsys)[0], np.shape(ulsxs)[0]), np.nan) + for i, j in enumerate(images): + cv = [j.domain[k] for k in featnames] + doms = [map_x, map_y] + cv + tempdata: Table = j.transform(Domain(doms)) + temp_xy = tempdata.X[:,0:2].copy() + temp_xy[:,0] = np.rint(((temp_xy[:,0]-minx)/dx)) + temp_xy[:,1] = np.rint(((temp_xy[:,1]-miny)/dy)) + temp_xy = np.array(temp_xy, dtype=np.int_) + cvs[temp_xy[:,1],temp_xy[:,0],:,i] = tempdata[:,2:] + spec[temp_xy[:,1],temp_xy[:,0],:,i] = j.X + metas[temp_xy[:,1],temp_xy[:,0],:,i] = j.metas + xys = pd.DataFrame(fill, index=ulsys, columns=ulsxs, dtype=object) + for k, i in enumerate(xys.index): + for l, j in enumerate(xys.columns): + coords[k,l,0] = i + coords[k,l,1] = j + + with SharedMemoryManager() as smm: + tcvs = smm.SharedMemory(size=cvs.nbytes) + scvs = np.ndarray(cvs.shape, dtype=cvs.dtype, buffer=tcvs.buf) + scvs[:,:,:] = cvs[:,:,:] + tout = smm.SharedMemory(size=out.nbytes) + sout = np.ndarray(out.shape, dtype=out.dtype, buffer=tout.buf) + sout[:,:,:,:] = out[:,:,:,:] + tmod = smm.SharedMemory(size=mod.nbytes) + smod = np.ndarray(mod.shape, dtype=mod.dtype, buffer=tmod.buf) + smod[:,:,:,:] = mod[:,:,:,:] + tcoords = smm.SharedMemory(size=coords.nbytes) + scoords = np.ndarray(coords.shape, dtype=coords.dtype, buffer=tcoords.buf) + scoords[:,:,:] = coords[:,:,:] + tvars = smm.SharedMemory(size=vars.nbytes) + svars = np.ndarray(vars.shape, dtype=vars.dtype, buffer=tvars.buf) + svars[:] = vars[:] + + smms = [tcvs, None, None, tout, tmod, tcoords, tvars] + shapes = [cvs.shape, spec.shape, metas.shape, out.shape, mod.shape, coords.shape, vars.shape] + dtypes = [cvs.dtype, spec.dtype, metas.dtype, out.dtype, mod.dtype, coords.dtype, vars.dtype] + + threads = start_compute(ulsxs, ulsys, smms, shapes, dtypes, polangles, state) + + for t in threads: + t.join() + + state.set_status("Finishing...") + if invert is True: + sout[:,:,:,2] = sout[:,:,:,2]*-1 + outputs = np.reshape(sout[:,:,:,2:], (np.shape(ulsys)[0]*np.shape(ulsxs)[0], 5*len(featnames))) + model = np.reshape(smod[:,:,:,2:], (np.shape(ulsys)[0]*np.shape(ulsxs)[0], 4*len(featnames))) + + spectra = [] + met = [] + if average is False: + for i in range(len(polangles)): + spectratemp = np.reshape(spec[:,:,:,i], + (np.shape(ulsys)[0]*np.shape(ulsxs)[0], images[0].X.shape[1])) + spectratemp = spectratemp[~np.isnan(model).any(axis=1)] + spectra.append(spectratemp) + metatemp = np.reshape(metas[:,:,:,i], + (np.shape(ulsys)[0]*np.shape(ulsxs)[0], images[0].metas.shape[1])) + metatemp = metatemp[~np.isnan(model).any(axis=1)] + metatemp = np.append(metatemp, np.full((np.shape(metatemp)[0],1), i), axis=1) + met.append(metatemp) + elif average is True: + average_spec = np.average(spec, axis=3) + spectratemp = np.reshape(average_spec, + (np.shape(ulsys)[0]*np.shape(ulsxs)[0], images[0].X.shape[1])) + spectratemp = spectratemp[~np.isnan(model).any(axis=1)] + spectra.append(spectratemp) + metatemp = np.reshape(metas[:,:,:,0], + (np.shape(ulsys)[0]*np.shape(ulsxs)[0], images[0].metas.shape[1])) + metatemp = metatemp[~np.isnan(model).any(axis=1)] + met.append(metatemp) + + outputs = outputs[~np.isnan(model).any(axis=1)] + model = model[~np.isnan(model).any(axis=1)] + + spectra = np.concatenate((spectra), axis=0) + meta = np.concatenate((met), axis=0) + + return outputs, model, spectra, meta, vars[1] + + +class OWPolar(OWWidget, ConcurrentWidgetMixin): + + # Widget's name as displayed in the canvas + name = "4+ Angle Polarisation" + + # Short widget description + description = ( + "Calculate Azimuth Angle, Orientation function, Amplitude and Intensity of " + "vibrational mode(s) using polarised data measured at 4 or more polarisation angles.") + + icon = "icons/polar.svg" + + # Define inputs and outputs + class Inputs: + data = MultiInput("Data", Orange.data.Table, default=True) + + class Outputs: + polar = Output("Polar Data", Orange.data.Table, default=True) + model = Output("Curve Fit model data", Orange.data.Table) + + autocommit = settings.Setting(False) + + settingsHandler = DomainContextHandler() + + want_main_area = False + resizing_enabled = True + alpha = Setting(0, schema_only=True) + + map_x = ContextSetting(None) + map_y = ContextSetting(None) + invert_angles = Setting(False, schema_only=True) + average = Setting(False, schema_only=True) + angles = ContextSetting(None) + feats: List[Variable] = ContextSetting([]) + + class Warning(OWWidget.Warning): + nodata = Msg("No useful data on input!") + noang = Msg("Must receive 4 angles at specified polarisation") + nofeat = Msg("Select Feature") + noxy = Msg("Select X and Y variables") + pol = Msg("Invalid Polarisation angles") + notenough = Msg("Must have >= 4 angles") + wrongdata = Msg("Model returns inf. Inappropriate data") + tomany = Msg("Widget must receive data at data input or discrete angles only") + missingfeat = Msg("All inputs must have the selected feature") + renamed_variables = Msg("Variables with duplicated names have been renamed.") + XYfeat = Msg("Selected feature(s) cannot be the same as XY selection") + + def __init__(self): + super().__init__() + ConcurrentWidgetMixin.__init__(self) + gui.OWComponent.__init__(self) + + self.anglst = [] + self.lines = [] + self.labels = [] + self.multiin_anglst = [] + self.multiin_lines = [] + self.multiin_labels = [] + self.polangles = [] + self.n_inputs = 0 + + self._dumb_tables = owconcatenate.OWConcatenate._dumb_tables + self._get_part = owconcatenate.OWConcatenate._get_part + self.merge_domains = owconcatenate.OWConcatenate.merge_domains + + self._data_inputs: List[Optional[Table]] = [] + + hbox = gui.hBox(self.controlArea) + #col 1 + + vbox2 = gui.vBox(hbox, "Inputs") + + form2 = QWidget() + formlayout2 = QFormLayout() + form2.setLayout(formlayout2) + + self.multifile = gui.widgetBox(vbox2, "All angles in a single input", + sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Fixed)) + + self.anglemetas = DomainModel(DomainModel.METAS, valid_types=DiscreteVariable) + self.anglesel = gui.comboBox(self.multifile, self, 'angles', searchable=True, + label='Select Angles by:', callback=self._change_angles, + model=self.anglemetas) + self.anglesel.setDisabled(True) + + + self.multiin = gui.widgetBox(vbox2, "Single angle per input", + sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Fixed)) + + vbox2.layout().addWidget(form2) + + #col 2 + vbox1 = gui.vBox(hbox, "Features") + + self.featureselect = DomainModel(DomainModel.SEPARATED, + valid_types=ContinuousVariable) + self.feat_view = ListViewSearch(selectionMode=QListView.ExtendedSelection) + self.feat_view.setModel(self.featureselect) + self.feat_view.selectionModel().selectionChanged.connect(self._feat_changed) + vbox1.layout().addWidget(self.feat_view) + vbox1.setSizePolicy(QSizePolicy(QSizePolicy.Fixed, QSizePolicy.Minimum)) + self.contextOpened.connect( + lambda: _restore_selected_items(model=self.featureselect, + view=self.feat_view, + setting=self.feats, + connector=self._feat_changed)) + + #col 3 + vbox = gui.vBox(hbox, "Parameters") + + form = QWidget() + formlayout = QFormLayout() + form.setLayout(formlayout) + + xybox = gui.widgetBox(vbox, "Data XY Selection", + sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Fixed)) + + self.x_axis = DomainModel(DomainModel.METAS, valid_types=ContinuousVariable) + self.y_axis = DomainModel(DomainModel.METAS, valid_types=ContinuousVariable) + + gui.comboBox(xybox, self, 'map_x', searchable=True, label="X Axis", + callback=self._change_input, model=self.x_axis) + gui.comboBox(xybox, self, 'map_y', searchable=True, label="Y Axis", + callback=self._change_input, model=self.y_axis) + + vbox.layout().addWidget(form) + + pbox = gui.widgetBox(vbox, sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Fixed)) + gui.lineEdit(pbox, self, "alpha", "Alpha value", + callback=self._change_input, valueType=int) + + gui.checkBox(pbox, self, 'invert_angles', label="Invert Angles", + callback=self._change_input) + + gui.checkBox(pbox, self, 'average', label='Average Spectra', + callback=self._change_input) + + gui.auto_commit(self.controlArea, self, "autocommit", "Apply", commit=self.commit) + self._change_input() + self.contextAboutToBeOpened.connect(lambda x: self.init_attr_values(x[0])) + + + def _feat_changed(self): + rows = self.feat_view.selectionModel().selectedRows() + values = self.feat_view.model()[:] + self.feats = [values[row.row()] for row in sorted(rows)] + self.commit.deferred() + + def init_attr_values(self, data): + domain = data.domain if data is not None else None + self.featureselect.set_domain(domain) + self.x_axis.set_domain(domain) + self.y_axis.set_domain(domain) + self.anglemetas.set_domain(domain) + + def _change_input(self): + self.commit.deferred() + + def _change_angles(self): + self.Warning.nodata.clear() + if self.angles: + self.clear_angles(self.anglst, self.lines, self.labels, self.multifile) + self.anglst = [] + self.lines = [] + self.labels = [] + self.Warning.notenough.clear() + if len(self.angles.values) < 4: + self.Warning.notenough() + else: + tempangles = np.linspace(0, 180, len(self.angles.values)+1) + for i, j in enumerate(self.angles.values): + self.add_angles(self.anglst, j, self.labels, self.lines, self.multifile, + i, tempangles[i], self._send_angles) + self._send_angles() + for i in self.labels: + i.setDisabled(False) + for i in self.lines: + i.setDisabled(False) + self.commit.deferred() + + def add_angles(self, anglst, lab, labels, lines, widget, + i, place, callback): #to be used in a loop + file = os.path.basename(lab) + anglst.append(lab) + ledit = gui.lineEdit(widget, self, None, label = file, callback = callback) + ledit.setText(str(place)) + lines.append(ledit) + for j in ledit.parent().children(): + if isinstance(j, QLabel): + labels.append(j) + + def clear_angles(self, anglst, lines, labels, widget): + if widget is self.multiin: + for i in reversed(range(self.multiin.layout().count())): + self.multiin.layout().itemAt(i).widget().setParent(None) + if widget is self.multifile: + for i in reversed(range(self.multifile.layout().count())): + if i != 0: + self.multifile.layout().itemAt(i).widget().setParent(None) + anglst.clear() + lines.clear() + labels.clear() + self.polangles.clear() + + def _send_ind_angles(self): + self.polangles.clear() + for i in self.multiin_lines: + self.polangles.append(i.text()) + try: + pol = [] + for i in self.polangles: + pol.append(float(i)) + self.polangles = pol + self.commit.deferred() + except ValueError: + pass + + def _send_angles(self): + self.polangles.clear() + for i in self.lines: + self.polangles.append(i.text()) + try: + pol = [] + for i in self.polangles: + pol.append(float(i)) + self.polangles = pol + self.commit.deferred() + except ValueError: + pass + + def input_select(self): + self.angles = None + if len(self.data) == 0 or 1 < len(self.data) < 4: + self.anglesel.setDisabled(True) + for i in self.multiin_labels: + i.setDisabled(True) + for i in self.multiin_lines: + i.setDisabled(True) + elif len(self.data) == 1: + self.anglesel.setDisabled(False) + for i in self.multiin_labels: + i.setDisabled(True) + for i in self.multiin_lines: + i.setDisabled(True) + elif len(self.data) > 3: + self.anglesel.setDisabled(True) + for i in self.multiin_labels: + i.setDisabled(False) + for i in self.multiin_lines: + i.setDisabled(False) + self._send_ind_angles() + + def check_params(self): + self.Warning.nofeat.clear() + if self.feats is None or len(self.feats) == 0: + self.Warning.nofeat() + return + self.Warning.noxy.clear() + if self.map_x is None or self.map_y is None: + self.Warning.noxy() + return + self.Warning.pol.clear() + if len(self.polangles) == 0: + self.Warning.pol() + return + for i in self.polangles: + if isinstance(i, float) is False: + self.Warning.pol() + return + self.Warning.XYfeat.clear() + for i in self.feats: + if i in (self.map_x, self.map_y): + self.Warning.XYfeat() + return + self.Warning.wrongdata.clear() + + @Inputs.data + def set_data(self, index: int, dataset: Table): + self._data_inputs[index] = dataset + + @Inputs.data.insert + def insert_data(self, index, dataset): + self._data_inputs.insert(index, dataset) + self.n_inputs += 1 + self.idx = index + + @Inputs.data.remove + def remove_data(self, index): + self._data_inputs.pop(index) + self.n_inputs -= 1 + self.polangles.clear() + + @property + def more_data(self) -> Sequence[Table]: + return [t for t in self._data_inputs if t is not None] + + def handleNewSignals(self): + self.check_and_close_context() + self.data = None + self.Warning.clear() + self.Outputs.polar.send(None) + self.Outputs.model.send(None) + self.data = self.more_data + + self.clear_angles(self.anglst, self.lines, self.labels, self.multifile) + self.clear_angles(self.multiin_anglst, self.multiin_lines, + self.multiin_labels, self.multiin) + + names = [i.name for i in self.data] + + tempangles = np.linspace(0, 180, len(self.data)+1) + for i in range(len(self.data)): + self.add_angles(self.multiin_anglst, names[i], self.multiin_labels, + self.multiin_lines, self.multiin, i, tempangles[i], + self._send_ind_angles) + + self.input_select() + + if len(self.data) == 0: + self.Outputs.polar.send(None) + self.Outputs.model.send(None) + self.contextAboutToBeOpened.emit([Table.from_domain(Domain(()))]) + return + + if len(self.data) == 1: + self.openContext(self.data[0]) + self._change_angles() + elif 1 < len(self.data) < 4 or len(self.data) == 0: + self.Warning.notenough() + self.contextAboutToBeOpened.emit([Table.from_domain(Domain(()))]) + return + else: + tables = self._dumb_tables(self) + domains = [table.domain for table in tables] + self._get_part = self._get_part + self.merge_type = 0 + domain1 = self.merge_domains(self, domains) + domain1 = sort_domain(domain1) + self.merge_type = 1 + domain2 = self.merge_domains(self, domains) + + self.sorted_data = [table.transform(domain1) for table in tables] + self.openContext(Table.from_domain(domain2)) + + self.commit.now() + + @gui.deferred + def commit(self): + self.cancel() + self.check_params() + if len(self.Warning.active) > 0: + return + + if len(self.data) == 1: + if self.angles: + fncol = self.data[0][:, self.angles.name].metas.reshape(-1) + images = [] + for fn in self.anglst: + images.append(self.data[0][self.angles.to_val(fn) == fncol]) + sorted_data = images + else: + return + elif 1 < len(self.data) < 4: + self.Warning.notenough() + self.Outputs.polar.send(None) + self.Outputs.model.send(None) + return + else: + sorted_data = self.sorted_data + + self.start(run, sorted_data, list(self.feats), self.alpha, self.map_x, + self.map_y, self.invert_angles, list(self.polangles), + self.average, self.angles) + + def on_done(self, result: Results): + if result is None: + self.Outputs.polar.send(None) + self.Outputs.model.send(None) + return + if result.errorstate == 1: + self.Warning.wrongdata() + else: + self.Outputs.polar.send(result.out) + self.Outputs.model.send(result.model) + + def on_partial_result(self, result): + pass + + def onDeleteWidget(self): + self.shutdown() + super().onDeleteWidget() + + def check_and_close_context(self): + if hasattr(self, 'data'): + if len(self.data) == 1: + self.closeContext() + else: + self.angles = None + self.closeContext() + + +if __name__ == "__main__": # pragma: no cover + from Orange.widgets.utils.widgetpreview import WidgetPreview + import orangecontrib.spectroscopy # so that can be loaded + WidgetPreview(OWPolar).run(insert_data=[(0, Orange.data.Table("polar/4-angle-ftir_multifile.tab"))])