@@ -12,6 +12,7 class SCIQLOP_CORE_EXPORT SpectrogramTimeSerie | |||||
12 | public: |
|
12 | public: | |
13 | double min_sampling = std::nan(""); |
|
13 | double min_sampling = std::nan(""); | |
14 | double max_sampling = std::nan(""); |
|
14 | double max_sampling = std::nan(""); | |
|
15 | bool y_is_log = true; | |||
15 | using item_t = |
|
16 | using item_t = | |
16 | decltype(std::declval< |
|
17 | decltype(std::declval< | |
17 | TimeSeries::TimeSerie<double, SpectrogramTimeSerie, 2>>()[0]); |
|
18 | TimeSeries::TimeSerie<double, SpectrogramTimeSerie, 2>>()[0]); | |
@@ -26,10 +27,11 public: | |||||
26 | SpectrogramTimeSerie::container_type< |
|
27 | SpectrogramTimeSerie::container_type< | |
27 | SpectrogramTimeSerie::raw_value_type>&& values, |
|
28 | SpectrogramTimeSerie::raw_value_type>&& values, | |
28 | std::vector<std::size_t>& shape, double min_sampling, |
|
29 | std::vector<std::size_t>& shape, double min_sampling, | |
29 | double max_sampling) |
|
30 | double max_sampling, bool y_is_log = true) | |
30 | : TimeSeries::TimeSerie<double, SpectrogramTimeSerie, 2>(t, values, |
|
31 | : TimeSeries::TimeSerie<double, SpectrogramTimeSerie, 2>(t, values, | |
31 | shape), |
|
32 | shape), | |
32 | min_sampling{min_sampling}, max_sampling{max_sampling} |
|
33 | min_sampling{min_sampling}, max_sampling{max_sampling}, y_is_log{ | |
|
34 | y_is_log} | |||
33 | { |
|
35 | { | |
34 | _axes[1] = y; |
|
36 | _axes[1] = y; | |
35 | } |
|
37 | } |
@@ -233,7 +233,7 PYBIND11_MODULE(pysciqlopcore, m) | |||||
233 | .def(py::init<const std::vector<std::size_t>>()) |
|
233 | .def(py::init<const std::vector<std::size_t>>()) | |
234 | .def(py::init([](py::array_t<double> t, py::array_t<double> y, |
|
234 | .def(py::init([](py::array_t<double> t, py::array_t<double> y, | |
235 | py::array_t<double> values, double min_sampling, |
|
235 | py::array_t<double> values, double min_sampling, | |
236 | double max_sampling) { |
|
236 | double max_sampling, bool y_is_log) { | |
237 | if(t.size() >= values.size() and t.size() != 0) |
|
237 | if(t.size() >= values.size() and t.size() != 0) | |
238 | SCIQLOP_ERROR(decltype(py::self), "Doesn't look like a Spectrogram"); |
|
238 | SCIQLOP_ERROR(decltype(py::self), "Doesn't look like a Spectrogram"); | |
239 | if(y.size() != values.shape(1)) |
|
239 | if(y.size() != values.shape(1)) | |
@@ -250,7 +250,7 PYBIND11_MODULE(pysciqlopcore, m) | |||||
250 | shape.push_back(values.shape(1)); |
|
250 | shape.push_back(values.shape(1)); | |
251 | return SpectrogramTimeSerie(std::move(_t), std::move(_y), |
|
251 | return SpectrogramTimeSerie(std::move(_t), std::move(_y), | |
252 | std::move(_values), shape, min_sampling, |
|
252 | std::move(_values), shape, min_sampling, | |
253 | max_sampling); |
|
253 | max_sampling, y_is_log); | |
254 | })) |
|
254 | })) | |
255 | .def("__getitem__", |
|
255 | .def("__getitem__", | |
256 | [](SpectrogramTimeSerie& ts, |
|
256 | [](SpectrogramTimeSerie& ts, |
General Comments 0
You need to be logged in to leave comments.
Login now