| @@ -269,14 +269,11 struct PlottablesUpdater<T, | |||
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269 | 269 | double minValue = 0., maxValue = 0.; |
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270 | 270 | if (auto serie = dynamic_cast<MultiComponentTimeSerie*>(&dataSeries)) |
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271 | 271 | { |
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272 | // TODO | |
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273 | // std::for_each( | |
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274 | // std::begin(*serie), std::end(*serie), [&minValue, &maxValue](const | |
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275 | // auto& v) { | |
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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()) }); | |
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279 | // }); | |
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272 | std::for_each( | |
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273 | std::begin(*serie), std::end(*serie), [&minValue, &maxValue](const auto& v) { | |
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274 | minValue = std::min( minValue, std::min_element(v.begin(), v.end())->v() ); | |
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275 | maxValue = std::max( maxValue, std::max_element(v.begin(), v.end())->v() ); | |
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276 | }); | |
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280 | 277 | } |
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281 | 278 | |
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282 | 279 | plot.yAxis->setRange(QCPRange { minValue, maxValue }); |
| @@ -12,16 +12,16 def make_scalar(x): | |||
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12 | 12 | return pysciqlopcore.ScalarTimeSerie(x,y) |
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13 | 13 | |
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14 | 14 | def make_vector(x): |
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15 |
v=np.ones(( |
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15 | v=np.ones((len(x),3)) | |
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16 | 16 | for i in range(3): |
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17 | v[:][i] = np.cos(x/10. + float(i)) | |
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17 | v.transpose()[:][i] = np.cos(x/10. + float(i)) | |
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18 | 18 | return pysciqlopcore.VectorTimeSerie(x,v) |
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19 | 19 | |
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20 | 20 | |
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21 | 21 | def make_multicomponent(x): |
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22 |
v=np.ones(( |
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22 | v=np.ones((len(x),4)) | |
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23 | 23 | for i in range(4): |
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24 | v[:][i] = float(i+1) * np.cos(x/10. + float(i)) | |
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24 | v.transpose()[:][i] = float(i+1) * np.cos(x/10. + float(i)) | |
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25 | 25 | return pysciqlopcore.MultiComponentTimeSerie(x,v) |
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26 | 26 | |
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27 | 27 | |
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