HG_REPOSITORIES/LPP/SciQLOP_Repos/SciQLop Commit - r1432:db5304cf6c8c

MultiComponent TS almost complete...

jeandet -

r1432:db5304cf6c8c

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r1432:db5304cf6c8c

core +1 -1

	@@ -1,1 +1,1
	1	Subproject commit 41273d8529cddde1c8b6bcea03d71d9cd1a18c06		1	Subproject commit 9a080a34054c21a67236f761e8843005c07ff0ba

gui/src/Visualization/AxisRenderingUtils.cpp +5 -1

             template <typename T>
             struct AxisSetter<T,
                 typename std::enable_if_t<std::is_base_of<ScalarTimeSerie, T>::value
-                    or std::is_base_of<VectorTimeSerie, T>::value>>
+                    or std::is_base_of<VectorTimeSerie, T>::value
+                    or std::is_base_of<MultiComponentTimeSerie, T>::value>>
             {
                 static void setProperties(QCustomPlot&, SqpColorScale&)
                 {
                     case DataSeriesType::VECTOR:
                         return std::make_unique<AxisHelper<VectorTimeSerie>>(
                             std::dynamic_pointer_cast<VectorTimeSerie>(variable.data()));
+                    case DataSeriesType::MULTICOMPONENT:
+                        return std::make_unique<AxisHelper<MultiComponentTimeSerie>>(
+                            std::dynamic_pointer_cast<MultiComponentTimeSerie>(variable.data()));
                     default:
                         // Creates default helper
                         break;

gui/src/Visualization/PlottablesRenderingUtils.cpp +4 -1

             template <typename T>
             struct PlottablesSetter<T,
                 typename std::enable_if_t<std::is_base_of<ScalarTimeSerie, T>::value
-                    or std::is_base_of<VectorTimeSerie, T>::value>>
+                    or std::is_base_of<VectorTimeSerie, T>::value
+                    or std::is_base_of<MultiComponentTimeSerie, T>::value>>
             {
                 static void setProperties(PlottablesMap& plottables)
                 {
                         return std::make_unique<PlottablesHelper<SpectrogramTimeSerie>>();
                     case DataSeriesType::VECTOR:
                         return std::make_unique<PlottablesHelper<VectorTimeSerie>>();
+                    case DataSeriesType::MULTICOMPONENT:
+                        return std::make_unique<PlottablesHelper<MultiComponentTimeSerie>>();
                     default:
                         // Returns default helper
                         break;

gui/src/Visualization/VisualizationGraphHelper.cpp +15 -7

             template <typename T>
-            struct PlottablesUpdater<T, typename std::enable_if_t<std::is_base_of<MultiComponentTimeSerie, T>::value>>
+            struct PlottablesUpdater<T,
+                typename std::enable_if_t<std::is_base_of<MultiComponentTimeSerie, T>::value>>
             {
                 static void setPlotYAxisRange(T& dataSeries, const DateTimeRange& xAxisRange, QCustomPlot& plot)
                 {
                     if (auto serie = dynamic_cast<MultiComponentTimeSerie*>(&dataSeries))
                     {
                         // TODO
-            //            std::for_each(
+                        //            std::for_each(
-            //                std::begin(*serie), std::end(*serie), [&minValue, &maxValue](const auto& v) {
+                        //                std::begin(*serie), std::end(*serie), [&minValue, &maxValue](const
-            //                    minValue = std::min({ minValue, std::min_element(v.begin(),v.end()) });
+                        //                auto& v) {
-            //                    maxValue = std::max({ maxValue, std::max_element(v.begin(),v.end()) });
+                        //                    minValue = std::min({ minValue,
-            //                });
+                        //                    std::min_element(v.begin(),v.end()) }); maxValue = std::max({
+                        //                    maxValue, std::max_element(v.begin(),v.end()) });
+                        //                });
                     }
                     plot.yAxis->setRange(QCPRange { minValue, maxValue });
                             auto dataContainer = QSharedPointer<SqpDataContainer>::create();
                             if (auto serie = dynamic_cast<MultiComponentTimeSerie*>(&dataSeries))
                             {
-            // TODO
+                                // TODO
+                                std::for_each(std::begin(*serie), std::end(*serie),
+                                    [&dataContainer, component = plottable.first](const auto& value) {
+                                        dataContainer->appendGraphData(
+                                            QCPGraphData(value.t(), value[component]));
+                                    });
                             }
                             graph->setData(dataContainer);
                         }

plugins/python_providers/resources/amda.py +11 -5

             import numpy as np
             import pandas as pds
             import requests
+            import copy
             from spwc.amda import AMDA
             amda = AMDA()
                         elif key == 'type':
                             if value == 'vector':
                                 ts_type = pysciqlopcore.VectorTimeSerie
-                    tstart=datetime.datetime.utcfromtimestamp(start)
+                            elif value == 'multicomponent':
-                    tend=datetime.datetime.utcfromtimestamp(stop)
+                                ts_type = pysciqlopcore.MultiComponentTimeSerie
+                    tstart=datetime.datetime.fromtimestamp(start, tz=timezone.utc)
+                    tend=datetime.datetime.fromtimestamp(stop, tz=timezone.utc)
                     df = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id)
                     #t = np.array([d.timestamp()-7200 for d in df.index])
                     t = np.array([d.timestamp() for d in df.index])
                     values = df.values
-                    return ts_type(t,values)
+                    return ts_type(t,values.transpose())
                     return ts_type(1)
                 except Exception as e:
                     print(traceback.format_exc())
             if len(amda.component) is 0:
                 amda.update_inventory()
-            parameters = amda.parameter.copy()
+            parameters = copy.deepcopy(amda.parameter)
             for name,component in amda.component.items():
                 if 'components' in parameters[component['parameter']]:
                     parameters[component['parameter']]['components'].append(component)
                 path = f"/AMDA/{parameter['mission']}/{parameter['instrument']}/{parameter['dataset']}/{parameter['name']}"
                 components = [component['name'] for component in parameter.get('components',[])]
                 metadata = [ (key,item) for key,item in parameter.items() if key is not 'components' ]
-                if parameter.get('size',0) is '3':
+                n_components = parameter.get('size',0)
+                if n_components is '3':
                     metadata.append(("type","vector"))
+                elif n_components !=0:
+                    metadata.append(("type","multicomponent"))
                 else:
                     metadata.append(("type","scalar"))
                 products.append( (path, components, metadata))

plugins/python_providers/resources/test.py +30 -3

@@ -6,12 +6,39 import numpy as np
6		6
7	someglobal = 1	7	someglobal = 1
8		8
9	def test(name,start,stop):	9	def make_scalar(x):
10	x = np.arange(start, stop)
11	y = np.cos(x/10.)	10	y = np.cos(x/10.)
12	return pysciqlopcore.ScalarTimeSerie(x,y)	11	return pysciqlopcore.ScalarTimeSerie(x,y)
13		12
		13	def make_vector(x):
		14	v=np.ones((3,len(x)))
		15	for i in range(3):
		16	v[:][i] = np.cos(x/10. + float(i))
		17	return pysciqlopcore.VectorTimeSerie(x,v)
		18
		19
		20	def make_multicomponent(x):
		21	v=np.ones((4,len(x)))
		22	for i in range(4):
		23	v[:][i] = float(i+1) * np.cos(x/10. + float(i))
		24	return pysciqlopcore.MultiComponentTimeSerie(x,v)
		25
		26
		27	def get_data(metadata,start,stop):
		28	x = np.arange(start, stop)
		29	for key,value in metadata:
		30	if key == 'xml:id':
		31	param_id = value
		32	elif key == 'type':
		33	if value == 'vector':
		34	return make_vector(x)
		35	elif value == 'multicomponent':
		36	return make_multicomponent(x)
		37	return make_scalar(x)
		38
		39
		40
14		41
15	#PythonProviders.register_product(["/folder1/folder2/product1", "/folder1/folder3/product2", "/folder4/folder5/product3"],test)	42	PythonProviders.register_product([("/tests/scalar",[],[("type","scalar")]), ("/tests/vector",[],[("type","vector")]), ("/tests/multicomponent",[],[("type","multicomponent"),('size','4')])],get_data)
16		43
17		44

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