@@ -1,1 +1,1 | |||||
1 | Subproject commit 41273d8529cddde1c8b6bcea03d71d9cd1a18c06 |
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1 | Subproject commit 9a080a34054c21a67236f761e8843005c07ff0ba |
@@ -95,7 +95,8 struct AxisSetter | |||||
95 | template <typename T> |
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95 | template <typename T> | |
96 | struct AxisSetter<T, |
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96 | struct AxisSetter<T, | |
97 | typename std::enable_if_t<std::is_base_of<ScalarTimeSerie, T>::value |
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97 | typename std::enable_if_t<std::is_base_of<ScalarTimeSerie, T>::value | |
98 |
or std::is_base_of<VectorTimeSerie, T>::value |
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98 | or std::is_base_of<VectorTimeSerie, T>::value | |
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99 | or std::is_base_of<MultiComponentTimeSerie, T>::value>> | |||
99 | { |
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100 | { | |
100 | static void setProperties(QCustomPlot&, SqpColorScale&) |
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101 | static void setProperties(QCustomPlot&, SqpColorScale&) | |
101 | { |
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102 | { | |
@@ -204,6 +205,9 std::unique_ptr<IAxisHelper> IAxisHelperFactory::create(Variable2& variable) noe | |||||
204 | case DataSeriesType::VECTOR: |
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205 | case DataSeriesType::VECTOR: | |
205 | return std::make_unique<AxisHelper<VectorTimeSerie>>( |
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206 | return std::make_unique<AxisHelper<VectorTimeSerie>>( | |
206 | std::dynamic_pointer_cast<VectorTimeSerie>(variable.data())); |
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207 | std::dynamic_pointer_cast<VectorTimeSerie>(variable.data())); | |
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208 | case DataSeriesType::MULTICOMPONENT: | |||
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209 | return std::make_unique<AxisHelper<MultiComponentTimeSerie>>( | |||
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210 | std::dynamic_pointer_cast<MultiComponentTimeSerie>(variable.data())); | |||
207 | default: |
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211 | default: | |
208 | // Creates default helper |
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212 | // Creates default helper | |
209 | break; |
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213 | break; |
@@ -33,7 +33,8 struct PlottablesSetter | |||||
33 | template <typename T> |
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33 | template <typename T> | |
34 | struct PlottablesSetter<T, |
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34 | struct PlottablesSetter<T, | |
35 | typename std::enable_if_t<std::is_base_of<ScalarTimeSerie, T>::value |
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35 | typename std::enable_if_t<std::is_base_of<ScalarTimeSerie, T>::value | |
36 |
or std::is_base_of<VectorTimeSerie, T>::value |
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36 | or std::is_base_of<VectorTimeSerie, T>::value | |
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37 | or std::is_base_of<MultiComponentTimeSerie, T>::value>> | |||
37 | { |
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38 | { | |
38 | static void setProperties(PlottablesMap& plottables) |
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39 | static void setProperties(PlottablesMap& plottables) | |
39 | { |
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40 | { | |
@@ -124,6 +125,8 std::unique_ptr<IPlottablesHelper> IPlottablesHelperFactory::create(Variable2& v | |||||
124 | return std::make_unique<PlottablesHelper<SpectrogramTimeSerie>>(); |
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125 | return std::make_unique<PlottablesHelper<SpectrogramTimeSerie>>(); | |
125 | case DataSeriesType::VECTOR: |
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126 | case DataSeriesType::VECTOR: | |
126 | return std::make_unique<PlottablesHelper<VectorTimeSerie>>(); |
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127 | return std::make_unique<PlottablesHelper<VectorTimeSerie>>(); | |
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128 | case DataSeriesType::MULTICOMPONENT: | |||
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129 | return std::make_unique<PlottablesHelper<MultiComponentTimeSerie>>(); | |||
127 | default: |
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130 | default: | |
128 | // Returns default helper |
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131 | // Returns default helper | |
129 | break; |
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132 | break; |
@@ -261,7 +261,8 struct PlottablesUpdater<T, typename std::enable_if_t<std::is_base_of<VectorTime | |||||
261 |
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261 | |||
262 |
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262 | |||
263 | template <typename T> |
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263 | template <typename T> | |
264 | struct PlottablesUpdater<T, typename std::enable_if_t<std::is_base_of<MultiComponentTimeSerie, T>::value>> |
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264 | struct PlottablesUpdater<T, | |
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265 | typename std::enable_if_t<std::is_base_of<MultiComponentTimeSerie, T>::value>> | |||
265 | { |
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266 | { | |
266 | static void setPlotYAxisRange(T& dataSeries, const DateTimeRange& xAxisRange, QCustomPlot& plot) |
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267 | static void setPlotYAxisRange(T& dataSeries, const DateTimeRange& xAxisRange, QCustomPlot& plot) | |
267 | { |
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268 | { | |
@@ -270,9 +271,11 struct PlottablesUpdater<T, typename std::enable_if_t<std::is_base_of<MultiCompo | |||||
270 | { |
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271 | { | |
271 | // TODO |
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272 | // TODO | |
272 | // std::for_each( |
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273 | // std::for_each( | |
273 |
// std::begin(*serie), std::end(*serie), [&minValue, &maxValue](const |
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274 | // std::begin(*serie), std::end(*serie), [&minValue, &maxValue](const | |
274 | // minValue = std::min({ minValue, std::min_element(v.begin(),v.end()) }); |
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275 | // auto& v) { | |
275 | // maxValue = std::max({ maxValue, std::max_element(v.begin(),v.end()) }); |
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276 | // minValue = std::min({ minValue, | |
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277 | // std::min_element(v.begin(),v.end()) }); maxValue = std::max({ | |||
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278 | // maxValue, std::max_element(v.begin(),v.end()) }); | |||
276 | // }); |
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279 | // }); | |
277 | } |
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280 | } | |
278 |
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281 | |||
@@ -290,6 +293,11 struct PlottablesUpdater<T, typename std::enable_if_t<std::is_base_of<MultiCompo | |||||
290 | if (auto serie = dynamic_cast<MultiComponentTimeSerie*>(&dataSeries)) |
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293 | if (auto serie = dynamic_cast<MultiComponentTimeSerie*>(&dataSeries)) | |
291 | { |
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294 | { | |
292 | // TODO |
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295 | // TODO | |
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296 | std::for_each(std::begin(*serie), std::end(*serie), | |||
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297 | [&dataContainer, component = plottable.first](const auto& value) { | |||
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298 | dataContainer->appendGraphData( | |||
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299 | QCPGraphData(value.t(), value[component])); | |||
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300 | }); | |||
293 | } |
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301 | } | |
294 | graph->setData(dataContainer); |
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302 | graph->setData(dataContainer); | |
295 | } |
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303 | } |
@@ -8,6 +8,7 import pysciqlopcore | |||||
8 | import numpy as np |
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8 | import numpy as np | |
9 | import pandas as pds |
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9 | import pandas as pds | |
10 | import requests |
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10 | import requests | |
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11 | import copy | |||
11 | from spwc.amda import AMDA |
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12 | from spwc.amda import AMDA | |
12 |
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13 | |||
13 | amda = AMDA() |
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14 | amda = AMDA() | |
@@ -22,13 +23,15 def get_sample(metadata,start,stop): | |||||
22 | elif key == 'type': |
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23 | elif key == 'type': | |
23 | if value == 'vector': |
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24 | if value == 'vector': | |
24 | ts_type = pysciqlopcore.VectorTimeSerie |
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25 | ts_type = pysciqlopcore.VectorTimeSerie | |
25 | tstart=datetime.datetime.utcfromtimestamp(start) |
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26 | elif value == 'multicomponent': | |
26 | tend=datetime.datetime.utcfromtimestamp(stop) |
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27 | ts_type = pysciqlopcore.MultiComponentTimeSerie | |
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28 | tstart=datetime.datetime.fromtimestamp(start, tz=timezone.utc) | |||
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29 | tend=datetime.datetime.fromtimestamp(stop, tz=timezone.utc) | |||
27 | df = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id) |
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30 | df = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id) | |
28 | #t = np.array([d.timestamp()-7200 for d in df.index]) |
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31 | #t = np.array([d.timestamp()-7200 for d in df.index]) | |
29 | t = np.array([d.timestamp() for d in df.index]) |
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32 | t = np.array([d.timestamp() for d in df.index]) | |
30 | values = df.values |
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33 | values = df.values | |
31 | return ts_type(t,values) |
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34 | return ts_type(t,values.transpose()) | |
32 | return ts_type(1) |
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35 | return ts_type(1) | |
33 | except Exception as e: |
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36 | except Exception as e: | |
34 | print(traceback.format_exc()) |
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37 | print(traceback.format_exc()) | |
@@ -38,7 +41,7 def get_sample(metadata,start,stop): | |||||
38 |
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41 | |||
39 | if len(amda.component) is 0: |
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42 | if len(amda.component) is 0: | |
40 | amda.update_inventory() |
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43 | amda.update_inventory() | |
41 |
parameters = amda.parameter |
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44 | parameters = copy.deepcopy(amda.parameter) | |
42 | for name,component in amda.component.items(): |
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45 | for name,component in amda.component.items(): | |
43 | if 'components' in parameters[component['parameter']]: |
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46 | if 'components' in parameters[component['parameter']]: | |
44 | parameters[component['parameter']]['components'].append(component) |
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47 | parameters[component['parameter']]['components'].append(component) | |
@@ -50,8 +53,11 for key,parameter in parameters.items(): | |||||
50 | path = f"/AMDA/{parameter['mission']}/{parameter['instrument']}/{parameter['dataset']}/{parameter['name']}" |
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53 | path = f"/AMDA/{parameter['mission']}/{parameter['instrument']}/{parameter['dataset']}/{parameter['name']}" | |
51 | components = [component['name'] for component in parameter.get('components',[])] |
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54 | components = [component['name'] for component in parameter.get('components',[])] | |
52 | metadata = [ (key,item) for key,item in parameter.items() if key is not 'components' ] |
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55 | metadata = [ (key,item) for key,item in parameter.items() if key is not 'components' ] | |
53 |
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56 | n_components = parameter.get('size',0) | |
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57 | if n_components is '3': | |||
54 | metadata.append(("type","vector")) |
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58 | metadata.append(("type","vector")) | |
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59 | elif n_components !=0: | |||
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60 | metadata.append(("type","multicomponent")) | |||
55 | else: |
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61 | else: | |
56 | metadata.append(("type","scalar")) |
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62 | metadata.append(("type","scalar")) | |
57 | products.append( (path, components, metadata)) |
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63 | products.append( (path, components, metadata)) |
@@ -6,12 +6,39 import numpy as np | |||||
6 |
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6 | |||
7 | someglobal = 1 |
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7 | someglobal = 1 | |
8 |
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8 | |||
9 | def test(name,start,stop): |
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9 | def make_scalar(x): | |
10 | x = np.arange(start, stop) |
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|||
11 | y = np.cos(x/10.) |
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10 | y = np.cos(x/10.) | |
12 | return pysciqlopcore.ScalarTimeSerie(x,y) |
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11 | return pysciqlopcore.ScalarTimeSerie(x,y) | |
13 |
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12 | |||
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13 | def make_vector(x): | |||
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14 | v=np.ones((3,len(x))) | |||
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15 | for i in range(3): | |||
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16 | v[:][i] = np.cos(x/10. + float(i)) | |||
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17 | return pysciqlopcore.VectorTimeSerie(x,v) | |||
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18 | ||||
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19 | ||||
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20 | def make_multicomponent(x): | |||
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21 | v=np.ones((4,len(x))) | |||
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22 | for i in range(4): | |||
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23 | v[:][i] = float(i+1) * np.cos(x/10. + float(i)) | |||
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24 | return pysciqlopcore.MultiComponentTimeSerie(x,v) | |||
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25 | ||||
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26 | ||||
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27 | def get_data(metadata,start,stop): | |||
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28 | x = np.arange(start, stop) | |||
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29 | for key,value in metadata: | |||
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30 | if key == 'xml:id': | |||
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31 | param_id = value | |||
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32 | elif key == 'type': | |||
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33 | if value == 'vector': | |||
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34 | return make_vector(x) | |||
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35 | elif value == 'multicomponent': | |||
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36 | return make_multicomponent(x) | |||
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37 | return make_scalar(x) | |||
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38 | ||||
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39 | ||||
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40 | ||||
14 |
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41 | |||
15 | #PythonProviders.register_product(["/folder1/folder2/product1", "/folder1/folder3/product2", "/folder4/folder5/product3"],test) |
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42 | PythonProviders.register_product([("/tests/scalar",[],[("type","scalar")]), ("/tests/vector",[],[("type","vector")]), ("/tests/multicomponent",[],[("type","multicomponent"),('size','4')])],get_data) | |
16 |
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43 | |||
17 |
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44 |
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