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Spectrograms works again, needs more polish......
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r1498:d1a5badbcf0e
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1 #pragma once
1 #pragma once
2 #include <Data/DataProviderParameters.h>
2 #include <Data/DataProviderParameters.h>
3 #include <Data/DataSeriesType.h>
3 #include <Data/DataSeriesType.h>
4 #include <Data/IDataProvider.h>
4 #include <Data/IDataProvider.h>
5 #include <DataSource/DataSourceItem.h>
5 #include <DataSource/DataSourceItem.h>
6 #include <DataSource/DataSourceItemAction.h>
6 #include <DataSource/DataSourceItemAction.h>
7 #include <DataSource/datasources.h>
7 #include <DataSource/datasources.h>
8
8
9 #include <QPair>
9 #include <QPair>
10 #include <QList>
10 #include <SqpApplication.h>
11 #include <SqpApplication.h>
11 // must be included last because of Python/Qt definition of slots
12 // must be included last because of Python/Qt definition of slots
12 #include "numpy_wrappers.h"
13 #include "numpy_wrappers.h"
13
14
14 struct Product
15 struct Product
15 {
16 {
16 QString path;
17 QString path;
17 std::vector<std::string> components;
18 std::vector<std::string> components;
18 QMap<QString, QString> metadata;
19 QMap<QString, QString> metadata;
19 Product() = default;
20 Product() = default;
20 explicit Product(const QString& path, const std::vector<std::string>& components,
21 explicit Product(const QString& path, const std::vector<std::string>& components,
21 const QMap<QString, QString>& metadata)
22 const QMap<QString, QString>& metadata)
22 : path { path }, components { components }, metadata { metadata }
23 : path { path }, components { components }, metadata { metadata }
23 {
24 {
24 }
25 }
25 ~Product() = default;
26 ~Product() = default;
26 };
27 };
27
28
28 template <typename T>
29 template <typename T>
29 ScalarTimeSerie* make_scalar(T& t, T& y)
30 ScalarTimeSerie* make_scalar(T& t, T& y)
30 {
31 {
31 return new ScalarTimeSerie { std::move(t.data), std::move(y.data) };
32 return new ScalarTimeSerie { std::move(t.data), std::move(y.data) };
32 }
33 }
33
34
34 template <typename T>
35 template <typename T>
35 VectorTimeSerie* make_vector(T& t, T& y)
36 VectorTimeSerie* make_vector(T& t, T& y)
36 {
37 {
37 return new VectorTimeSerie { std::move(t.data), y.to_std_vect_vect() };
38 return new VectorTimeSerie { std::move(t.data), y.to_std_vect_vect() };
38 }
39 }
39
40
40 template <typename T>
41 template <typename T>
41 MultiComponentTimeSerie* make_multi_comp(T& t, T& y)
42 MultiComponentTimeSerie* make_multi_comp(T& t, T& y)
42 {
43 {
43 auto y_size = y.flat_size();
44 auto y_size = y.flat_size();
44 auto t_size = t.flat_size();
45 auto t_size = t.flat_size();
45 if (t_size && (y_size % t_size) == 0)
46 if (t_size && (y_size % t_size) == 0)
46 {
47 {
47 return new MultiComponentTimeSerie { std::move(t.data), std::move(y.data),
48 return new MultiComponentTimeSerie { std::move(t.data), std::move(y.data),
48 { t_size, y_size / t_size } };
49 { t_size, y_size / t_size } };
49 }
50 }
50 return nullptr;
51 return nullptr;
51 }
52 }
52
53
53 template <typename T>
54 template <typename T>
54 SpectrogramTimeSerie* make_spectro(T& t, T& y)
55 SpectrogramTimeSerie* make_spectro(T& t, T& y, T& z)
55 {
56 {
56 auto y_size = y.flat_size();
57 auto z_size = z.flat_size();
57 auto t_size = t.flat_size();
58 auto t_size = t.flat_size();
58 if (t_size && (y_size % t_size) == 0)
59 if (t_size && (z_size % t_size) == 0)
59 {
60 {
60 return new SpectrogramTimeSerie { std::move(t.data), std::move(y.data),
61 return new SpectrogramTimeSerie { std::move(t.data), std::move(y.data), std::move(z.data),
61 { t_size, y_size / t_size } };
62 { t_size, z_size / t_size }, std::nan("1"), std::nan("1") };
62 }
63 }
63 return nullptr;
64 return nullptr;
64 }
65 }
65
66
66
67
67 class PyDataProvider : public IDataProvider
68 class PyDataProvider : public IDataProvider
68 {
69 {
69 public:
70 public:
70 PyDataProvider()
71 PyDataProvider()
71 {
72 {
72 auto& dataSources = sqpApp->dataSources();
73 auto& dataSources = sqpApp->dataSources();
73 dataSources.addProvider(this);
74 dataSources.addProvider(this);
74 }
75 }
75
76
76 virtual ~PyDataProvider() {}
77 virtual ~PyDataProvider() {}
77
78
78 virtual QPair<QPair<NpArray, NpArray>, DataSeriesType> get_data(
79 virtual QPair<QPair<QPair<NpArray,NpArray>,NpArray>, DataSeriesType> get_data(
79 const QMap<QString, QString>& key, double start_time, double stop_time)
80 const QMap<QString, QString>& key, double start_time, double stop_time)
80 {
81 {
81 (void)key, (void)start_time, (void)stop_time;
82 (void)key, (void)start_time, (void)stop_time;
82 return {};
83 return {};
83 }
84 }
84
85
85 virtual TimeSeries::ITimeSerie* getData(const DataProviderParameters& parameters) override
86 virtual TimeSeries::ITimeSerie* getData(const DataProviderParameters& parameters) override
86 {
87 {
87 TimeSeries::ITimeSerie* ts = nullptr;
88 TimeSeries::ITimeSerie* ts = nullptr;
88 if (parameters.m_Data.contains("name"))
89 if (parameters.m_Data.contains("name"))
89 {
90 {
90 QMap<QString, QString> metadata;
91 QMap<QString, QString> metadata;
91 std::for_each(parameters.m_Data.constKeyValueBegin(),
92 std::for_each(parameters.m_Data.constKeyValueBegin(),
92 parameters.m_Data.constKeyValueEnd(),
93 parameters.m_Data.constKeyValueEnd(),
93 [&metadata](const auto& item) { metadata[item.first] = item.second.toString(); });
94 [&metadata](const auto& item) { metadata[item.first] = item.second.toString(); });
94 auto [data, type]
95 auto [data, type]
95 = get_data(metadata, parameters.m_Range.m_TStart, parameters.m_Range.m_TEnd);
96 = get_data(metadata, parameters.m_Range.m_TStart, parameters.m_Range.m_TEnd);
96
97
97 auto& [t, y] = data;
98 auto& [axes, values] = data;
99 auto& [x, y] = axes;
98 switch (type)
100 switch (type)
99 {
101 {
100 case DataSeriesType::SCALAR:
102 case DataSeriesType::SCALAR:
101 ts = make_scalar(t, y);
103 ts = make_scalar(x, values);
102 break;
104 break;
103 case DataSeriesType::VECTOR:
105 case DataSeriesType::VECTOR:
104 ts = make_vector(t, y);
106 ts = make_vector(x, values);
105 break;
107 break;
106 case DataSeriesType::MULTICOMPONENT:
108 case DataSeriesType::MULTICOMPONENT:
107 ts = make_multi_comp(t, y);
109 ts = make_multi_comp(x, values);
108 break;
110 break;
109 case DataSeriesType::SPECTROGRAM:
111 case DataSeriesType::SPECTROGRAM:
110 ts = make_spectro(t, y);
112 ts = make_spectro(x, y, values);
111 break;
113 break;
112 default:
114 default:
113 break;
115 break;
114 }
116 }
115 }
117 }
116 return ts;
118 return ts;
117 }
119 }
118
120
119 inline void set_icon(const QString& path, const QString& name)
121 inline void set_icon(const QString& path, const QString& name)
120 {
122 {
121 sqpApp->dataSources().setIcon(path, name);
123 sqpApp->dataSources().setIcon(path, name);
122 }
124 }
123
125
124 inline void register_products(const QVector<Product*>& products)
126 inline void register_products(const QVector<Product*>& products)
125 {
127 {
126 auto& dataSources = sqpApp->dataSources();
128 auto& dataSources = sqpApp->dataSources();
127 auto id = this->id();
129 auto id = this->id();
128 auto data_source_name = this->name();
130 auto data_source_name = this->name();
129 std::for_each(std::cbegin(products), std::cend(products),
131 std::for_each(std::cbegin(products), std::cend(products),
130 [&id, &dataSources](const Product* product) {
132 [&id, &dataSources](const Product* product) {
131 dataSources.addDataSourceItem(id, product->path, product->metadata);
133 dataSources.addDataSourceItem(id, product->path, product->metadata);
132 });
134 });
133 }
135 }
134 };
136 };
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@@ -1,124 +1,121
1 import traceback
1 import traceback
2 import os
2 import os
3 from datetime import datetime, timedelta, timezone
3 from datetime import datetime, timedelta, timezone
4 from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
4 from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
5 import numpy as np
5 import numpy as np
6 import requests
6 import requests
7 import copy
7 import copy
8 from spwc.amda import AMDA
8 from spwc.amda import AMDA
9
9
10 amda = AMDA()
10 amda = AMDA()
11
11
12
12 def amda_make_scalar(var=None):
13 def amda_make_scalar(var=None):
13 if var is None:
14 if var is None:
14 return ((np.array(), np.array()), DataSeriesType.SCALAR)
15 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SCALAR)
15 else:
16 else:
16 return ((var.time,var.data), DataSeriesType.SCALAR)
17 return (((var.time, np.array([])), var.data), DataSeriesType.SCALAR)
18
17
19
18 def amda_make_vector(var=None):
20 def amda_make_vector(var=None):
19 if var is None:
21 if var is None:
20 return ((np.array(), np.array()), DataSeriesType.VECTOR)
22 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.VECTOR)
21 else:
23 else:
22 return ((var.time,var.data), DataSeriesType.VECTOR)
24 return (((var.time, np.array([])), var.data), DataSeriesType.VECTOR)
25
23
26
24 def amda_make_multi_comp(var=None):
27 def amda_make_multi_comp(var=None):
25 if var is None:
28 if var is None:
26 return ((np.array(), np.array()), DataSeriesType.MULTICOMPONENT)
29 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.MULTICOMPONENT)
27 else:
30 else:
28 return ((var.time,var.data), DataSeriesType.MULTICOMPONENT)
31 return (((var.time, np.array([])), var.data), DataSeriesType.MULTICOMPONENT)
32
29
33
30 def amda_make_spectro(var=None):
34 def amda_make_spectro(var=None):
31 if var is None:
35 if var is None:
32 return ((np.array(), np.array()), DataSeriesType.SPECTROGRAM)
36 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SPECTROGRAM)
33 else:
37 else:
34 min_sampling = float(var.meta.get("DATASET_MIN_SAMPLING","nan"))
38 min_sampling = float(var.meta.get("DATASET_MIN_SAMPLING", "nan"))
35 max_sampling = float(var.meta.get("DATASET_MAX_SAMPLING","nan"))
39 max_sampling = float(var.meta.get("DATASET_MAX_SAMPLING", "nan"))
36 if "PARAMETER_TABLE_MIN_VALUES[1]" in var.meta:
40 if var.y is None and len(var.data):
37 min_v = np.array([ float(v) for v in var.meta["PARAMETER_TABLE_MIN_VALUES[1]"].split(',') ])
41 var.y = np.logspace(1, 3, var.data.shape[1])[::-1]
38 max_v = np.array([ float(v) for v in var.meta["PARAMETER_TABLE_MAX_VALUES[1]"].split(',') ])
42 return (((var.time, var.y), var.data), DataSeriesType.SPECTROGRAM)
39 y = (max_v + min_v)/2.
40 elif "PARAMETER_TABLE_MIN_VALUES[0]" in var.meta:
41 min_v = np.array([ float(v) for v in var.meta["PARAMETER_TABLE_MIN_VALUES[0]"].split(',') ])
42 max_v = np.array([ float(v) for v in var.meta["PARAMETER_TABLE_MAX_VALUES[0]"].split(',') ])
43 y = (max_v + min_v)/2.
44 else:
45 y = np.logspace(1,3,var.data.shape[1])[::-1]
46 return ((var.time,var.data), DataSeriesType.SPECTROGRAM)
47 #return pysciqlopcore.SpectrogramTimeSerie(var.time,y,var.data,min_sampling,max_sampling,True)
43 #return pysciqlopcore.SpectrogramTimeSerie(var.time,y,var.data,min_sampling,max_sampling,True)
48
44
49 def amda_get_sample(metadata,start,stop):
45
46 def amda_get_sample(metadata, start, stop):
50 ts_type = amda_make_scalar
47 ts_type = amda_make_scalar
51 try:
48 try:
52 param_id = None
49 param_id = None
53 for key,value in metadata:
50 for key, value in metadata:
54 if key == 'xml:id':
51 if key == 'xml:id':
55 param_id = value
52 param_id = value
56 elif key == 'type':
53 elif key == 'type':
57 if value == 'vector':
54 if value == 'vector':
58 ts_type = amda_make_vector
55 ts_type = amda_make_vector
59 elif value == 'multicomponent':
56 elif value == 'multicomponent':
60 ts_type = amda_make_multi_comp
57 ts_type = amda_make_multi_comp
61 elif value == 'spectrogram':
58 elif value == 'spectrogram':
62 ts_type = amda_make_spectro
59 ts_type = amda_make_spectro
63 tstart=datetime.fromtimestamp(start, tz=timezone.utc)
60 tstart = datetime.fromtimestamp(start, tz=timezone.utc)
64 tend=datetime.fromtimestamp(stop, tz=timezone.utc)
61 tend = datetime.fromtimestamp(stop, tz=timezone.utc)
65 var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST")
62 var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST")
66 return ts_type(var)
63 return ts_type(var)
67 except Exception as e:
64 except Exception as e:
68 print(traceback.format_exc())
65 print(traceback.format_exc())
69 print("Error in amda.py ",str(e))
66 print("Error in amda.py ", str(e))
70 return ts_type()
67 return ts_type()
71
68
72
69
73 class AmdaProvider(PyDataProvider):
70 class AmdaProvider(PyDataProvider):
74 def __init__(self):
71 def __init__(self):
75 super(AmdaProvider,self).__init__()
72 super(AmdaProvider, self).__init__()
76 if len(amda.component) is 0:
73 if len(amda.component) is 0:
77 amda.update_inventory()
74 amda.update_inventory()
78 parameters = copy.deepcopy(amda.parameter)
75 parameters = copy.deepcopy(amda.parameter)
79 for name,component in amda.component.items():
76 for name, component in amda.component.items():
80 if 'components' in parameters[component['parameter']]:
77 if 'components' in parameters[component['parameter']]:
81 parameters[component['parameter']]['components'].append(component)
78 parameters[component['parameter']]['components'].append(component)
82 else:
79 else:
83 parameters[component['parameter']]['components']=[component]
80 parameters[component['parameter']]['components']=[component]
84
81
85 products = []
82 products = []
86 for key,parameter in parameters.items():
83 for key, parameter in parameters.items():
87 path = f"/AMDA/{parameter['mission']}/{parameter.get('observatory','')}/{parameter['instrument']}/{parameter['dataset']}/{parameter['name']}"
84 path = f"/AMDA/{parameter['mission']}/{parameter.get('observatory','')}/{parameter['instrument']}/{parameter['dataset']}/{parameter['name']}"
88 components = [component['name'] for component in parameter.get('components',[])]
85 components = [component['name'] for component in parameter.get('components',[])]
89 metadata = { key:item for key,item in parameter.items() if key is not 'components' }
86 metadata = {key: item for key, item in parameter.items() if key is not 'components'}
90 n_components = parameter.get('size',0)
87 n_components = parameter.get('size', 0)
91 if n_components == '3':
88 if n_components == '3':
92 metadata["type"]="vector"
89 metadata["type"] = "vector"
93 elif parameter.get('display_type','')=="spectrogram":
90 elif parameter.get('display_type', '')=="spectrogram":
94 metadata["type"]="spectrogram"
91 metadata["type"] = "spectrogram"
95 elif n_components !=0:
92 elif n_components != 0:
96 metadata["type"]="multicomponent"
93 metadata["type"] = "multicomponent"
97 else:
94 else:
98 metadata["type"]="scalar"
95 metadata["type"] = "scalar"
99 products.append( Product(path, components, metadata))
96 products.append(Product(path, components, metadata))
100 self.register_products(products)
97 self.register_products(products)
101 for mission in amda.mission:
98 for mission in amda.mission:
102 self.set_icon(f'/AMDA/{mission}','satellite')
99 self.set_icon(f'/AMDA/{mission}','satellite')
103
100
104 def get_data(self,metadata,start,stop):
101 def get_data(self, metadata, start, stop):
105 ts_type = amda_make_scalar
102 ts_type = amda_make_scalar
106 try:
103 try:
107 param_id = metadata['xml:id']
104 param_id = metadata['xml:id']
108 ts_type_str = metadata['type']
105 ts_type_str = metadata['type']
109 if ts_type_str == 'vector':
106 if ts_type_str == 'vector':
110 ts_type = amda_make_vector
107 ts_type = amda_make_vector
111 elif ts_type_str == 'multicomponent':
108 elif ts_type_str == 'multicomponent':
112 ts_type = amda_make_multi_comp
109 ts_type = amda_make_multi_comp
113 elif ts_type_str == 'spectrogram':
110 elif ts_type_str == 'spectrogram':
114 ts_type = amda_make_spectro
111 ts_type = amda_make_spectro
115 tstart=datetime.fromtimestamp(start, tz=timezone.utc)
112 tstart = datetime.fromtimestamp(start, tz=timezone.utc)
116 tend=datetime.fromtimestamp(stop, tz=timezone.utc)
113 tend = datetime.fromtimestamp(stop, tz=timezone.utc)
117 var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST")
114 var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST")
118 return ts_type(var)
115 return ts_type(var)
119 except Exception as e:
116 except Exception as e:
120 print(traceback.format_exc())
117 print(traceback.format_exc())
121 print("Error in amda.py ",str(e))
118 print("Error in amda.py ", str(e))
122 return ts_type()
119 return ts_type()
123
120
124 _amda = AmdaProvider()
121 _amda = AmdaProvider()
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@@ -1,93 +1,93
1 import traceback
1 import traceback
2 from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
2 from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
3 import numpy as np
3 import numpy as np
4 import math
4 import math
5 from spwc.cache import _cache
5 from spwc.cache import _cache
6 from spwc.common.datetime_range import DateTimeRange
6 from spwc.common.datetime_range import DateTimeRange
7 from functools import partial
7 from functools import partial
8 from datetime import datetime, timedelta, timezone
8 from datetime import datetime, timedelta, timezone
9 from spwc.common.variable import SpwcVariable
9 from spwc.common.variable import SpwcVariable
10
10
11
11
12 def make_scalar(x):
12 def make_scalar(x):
13 y = np.cos(x/10.)
13 y = np.cos(x/10.)
14 return SpwcVariable(time=x, data=y)
14 return SpwcVariable(time=x, data=y)
15
15
16 def make_vector(x):
16 def make_vector(x):
17 v=np.ones((len(x),3))
17 v=np.ones((len(x),3))
18 for i in range(3):
18 for i in range(3):
19 v.transpose()[:][i] = np.cos(x/10. + float(i)) + (100. * np.cos(x/10000. + float(i)))
19 v.transpose()[:][i] = np.cos(x/10. + float(i)) + (100. * np.cos(x/10000. + float(i)))
20 return SpwcVariable(time=x, data=v)
20 return SpwcVariable(time=x, data=v)
21
21
22
22
23 def make_multicomponent(x):
23 def make_multicomponent(x):
24 v=np.ones((len(x),4))
24 v=np.ones((len(x),4))
25 for i in range(4):
25 for i in range(4):
26 v.transpose()[:][i] = float(i+1) * np.cos(x/10. + float(i))
26 v.transpose()[:][i] = float(i+1) * np.cos(x/10. + float(i))
27 return SpwcVariable(time=x, data=v)
27 return SpwcVariable(time=x, data=v)
28
28
29 def make_spectrogram(x):
29 def make_spectrogram(x):
30 v=np.ones((len(x),32))
30 v=np.ones((len(x),32))
31 for i in range(32):
31 for i in range(32):
32 v.transpose()[:][i] = 100.*(2.+ float(i+1) * np.cos(x/1024. + float(i)))
32 v.transpose()[:][i] = 100.*(2.+ float(i+1) * np.cos(x/1024. + float(i)))
33 return SpwcVariable(time=x, data=v)
33 return SpwcVariable(time=x, data=v)
34
34
35
35
36 def _get_data(p_type, start, stop):
36 def _get_data(p_type, start, stop):
37 if type(start) is datetime:
37 if type(start) is datetime:
38 start = start.timestamp()
38 start = start.timestamp()
39 stop = stop.timestamp()
39 stop = stop.timestamp()
40 x = np.arange(math.ceil(start), math.floor(stop))*1.
40 x = np.arange(math.ceil(start), math.floor(stop))*1.
41 if p_type == 'scalar':
41 if p_type == 'scalar':
42 return make_scalar(x)
42 return make_scalar(x)
43 if p_type == 'vector':
43 if p_type == 'vector':
44 return make_vector(x)
44 return make_vector(x)
45 if p_type == 'multicomponent':
45 if p_type == 'multicomponent':
46 return make_multicomponent(x)
46 return make_multicomponent(x)
47 if p_type == 'spectrogram':
47 if p_type == 'spectrogram':
48 return make_spectrogram(np.arange(math.ceil(start), math.floor(stop),15.))
48 return make_spectrogram(np.arange(math.ceil(start), math.floor(stop),15.))
49 return None
49 return None
50
50
51 class MyProvider(PyDataProvider):
51 class MyProvider(PyDataProvider):
52 def __init__(self):
52 def __init__(self):
53 super(MyProvider,self).__init__()
53 super(MyProvider,self).__init__()
54 self.register_products([Product("/tests/without_cache/scalar",[],{"type":"scalar"}),
54 self.register_products([Product("/tests/without_cache/scalar",[],{"type":"scalar"}),
55 Product("/tests/without_cache/vector",[],{"type":"vector"}),
55 Product("/tests/without_cache/vector",[],{"type":"vector"}),
56 Product("/tests/without_cache/multicomponent",[],{"type":"multicomponent",'size':'4'}),
56 Product("/tests/without_cache/multicomponent",[],{"type":"multicomponent",'size':'4'}),
57 Product("/tests/without_cache/spectrogram",[],{"type":"spectrogram",'size':'32'}),
57 Product("/tests/without_cache/spectrogram",[],{"type":"spectrogram",'size':'32'}),
58 Product("/tests/with_cache/scalar",[],{"type":"scalar", "cache":"true"}),
58 Product("/tests/with_cache/scalar",[],{"type":"scalar", "cache":"true"}),
59 Product("/tests/with_cache/vector",[],{"type":"vector", "cache":"true"}),
59 Product("/tests/with_cache/vector",[],{"type":"vector", "cache":"true"}),
60 Product("/tests/with_cache/multicomponent",[],{"type":"multicomponent",'size':'4', "cache":"true"})
60 Product("/tests/with_cache/multicomponent",[],{"type":"multicomponent",'size':'4', "cache":"true"})
61 ])
61 ])
62
62
63 def get_data(self,metadata,start,stop):
63 def get_data(self,metadata,start,stop):
64 ts_type = DataSeriesType.SCALAR
64 ts_type = DataSeriesType.SCALAR
65 default_ctor_args = 1
65 default_ctor_args = 1
66 use_cache = False
66 use_cache = False
67 p_type = 'scalar'
67 p_type = 'scalar'
68 try:
68 try:
69 for key,value in metadata.items():
69 for key,value in metadata.items():
70 if key == 'type':
70 if key == 'type':
71 p_type = value
71 p_type = value
72 if value == 'vector':
72 if value == 'vector':
73 ts_type = DataSeriesType.VECTOR
73 ts_type = DataSeriesType.VECTOR
74 elif value == 'multicomponent':
74 elif value == 'multicomponent':
75 ts_type = DataSeriesType.MULTICOMPONENT
75 ts_type = DataSeriesType.MULTICOMPONENT
76 elif value == 'spectrogram':
76 elif value == 'spectrogram':
77 ts_type = DataSeriesType.SPECTROGRAM
77 ts_type = DataSeriesType.SPECTROGRAM
78 if key == 'cache' and value == 'true':
78 if key == 'cache' and value == 'true':
79 use_cache = True
79 use_cache = True
80 if use_cache:
80 if use_cache:
81 cache_product = f"tests/{p_type}"
81 cache_product = f"tests/{p_type}"
82 var = _cache.get_data(cache_product, DateTimeRange(datetime.fromtimestamp(start, tz=timezone.utc), datetime.fromtimestamp(stop, tz=timezone.utc)), partial(_get_data, p_type), fragment_hours=24)
82 var = _cache.get_data(cache_product, DateTimeRange(datetime.fromtimestamp(start, tz=timezone.utc), datetime.fromtimestamp(stop, tz=timezone.utc)), partial(_get_data, p_type), fragment_hours=24)
83 else:
83 else:
84 var = _get_data(p_type, start, stop)
84 var = _get_data(p_type, start, stop)
85 return ((var.time,var.data), ts_type)
85 return (((var.time, np.array([])),var.data), ts_type)
86 except Exception as e:
86 except Exception as e:
87 print(traceback.format_exc())
87 print(traceback.format_exc())
88 print("Error in test.py ",str(e))
88 print("Error in test.py ",str(e))
89 return ((np.array(), np.array()), ts_type)
89 return (((np.array([]), np.array([])), np.array([])), ts_type)
90
90
91
91
92 t=MyProvider()
92 t=MyProvider()
93
93
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