@@ -1,15 +1,16 | |||||
1 | build/ |
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1 | build/ | |
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2 | _build/ | |||
2 | CMakeLists.txt.user |
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3 | CMakeLists.txt.user | |
3 | /.project |
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4 | /.project | |
4 | core/src/Version.cpp |
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5 | core/src/Version.cpp | |
5 | core/include/Version.h |
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6 | core/include/Version.h | |
6 | 3rdparty/ |
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7 | 3rdparty/ | |
7 | subprojects/* |
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8 | subprojects/* | |
8 | documentation/* |
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9 | documentation/* | |
9 | **/.idea/* |
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10 | **/.idea/* | |
10 | **/__pycache__/* |
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11 | **/__pycache__/* | |
11 | *.srctrl* |
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12 | *.srctrl* | |
12 | *.kdev4 |
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13 | *.kdev4 | |
13 | .vscode |
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14 | .vscode | |
14 | *.pyc |
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15 | *.pyc | |
15 | *.swp |
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16 | *.swp |
@@ -1,121 +1,128 | |||||
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 |
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9 | |||
10 | amda = AMDA() |
|
10 | amda = AMDA() | |
11 |
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11 | |||
12 |
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12 | |||
13 | def amda_make_scalar(var=None): |
|
13 | def amda_make_scalar(var=None): | |
14 | if var is None: |
|
14 | if var is None: | |
15 | return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SCALAR) |
|
15 | return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SCALAR) | |
16 | else: |
|
16 | else: | |
17 | return (((var.time, np.array([])), var.data), DataSeriesType.SCALAR) |
|
17 | return (((var.time, np.array([])), var.data), DataSeriesType.SCALAR) | |
18 |
|
18 | |||
19 |
|
19 | |||
20 | def amda_make_vector(var=None): |
|
20 | def amda_make_vector(var=None): | |
21 | if var is None: |
|
21 | if var is None: | |
22 | return (((np.array([]), np.array([])), np.array([])), DataSeriesType.VECTOR) |
|
22 | return (((np.array([]), np.array([])), np.array([])), DataSeriesType.VECTOR) | |
23 | else: |
|
23 | else: | |
24 | return (((var.time, np.array([])), var.data), DataSeriesType.VECTOR) |
|
24 | return (((var.time, np.array([])), var.data), DataSeriesType.VECTOR) | |
25 |
|
25 | |||
26 |
|
26 | |||
27 | def amda_make_multi_comp(var=None): |
|
27 | def amda_make_multi_comp(var=None): | |
28 | if var is None: |
|
28 | if var is None: | |
29 | return (((np.array([]), np.array([])), np.array([])), DataSeriesType.MULTICOMPONENT) |
|
29 | return (((np.array([]), np.array([])), np.array([])), DataSeriesType.MULTICOMPONENT) | |
30 | else: |
|
30 | else: | |
31 | return (((var.time, np.array([])), var.data), DataSeriesType.MULTICOMPONENT) |
|
31 | return (((var.time, np.array([])), var.data), DataSeriesType.MULTICOMPONENT) | |
32 |
|
32 | |||
33 |
|
33 | |||
34 | def amda_make_spectro(var=None): |
|
34 | def amda_make_spectro(var=None): | |
35 | if var is None: |
|
35 | if var is None: | |
36 | return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SPECTROGRAM) |
|
36 | return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SPECTROGRAM) | |
37 | else: |
|
37 | else: | |
38 | min_sampling = float(var.meta.get("DATASET_MIN_SAMPLING", "nan")) |
|
38 | min_sampling = float(var.meta.get("DATASET_MIN_SAMPLING", "nan")) | |
39 | max_sampling = float(var.meta.get("DATASET_MAX_SAMPLING", "nan")) |
|
39 | max_sampling = float(var.meta.get("DATASET_MAX_SAMPLING", "nan")) | |
40 | if var.y is None and len(var.data): |
|
40 | if var.y is None and len(var.data): | |
41 | var.y = np.logspace(1, 3, var.data.shape[1])[::-1] |
|
41 | var.y = np.logspace(1, 3, var.data.shape[1])[::-1] | |
42 | return (((var.time, var.y), var.data), DataSeriesType.SPECTROGRAM) |
|
42 | return (((var.time, var.y), var.data), DataSeriesType.SPECTROGRAM) | |
43 | #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) | |
44 |
|
44 | |||
45 |
|
45 | |||
46 | def amda_get_sample(metadata, start, stop): |
|
46 | def amda_get_sample(metadata, start, stop): | |
47 | ts_type = amda_make_scalar |
|
47 | ts_type = amda_make_scalar | |
48 | try: |
|
48 | try: | |
49 | param_id = None |
|
49 | param_id = None | |
50 | for key, value in metadata: |
|
50 | for key, value in metadata: | |
51 | if key == 'xml:id': |
|
51 | if key == 'xml:id': | |
52 | param_id = value |
|
52 | param_id = value | |
53 | elif key == 'type': |
|
53 | elif key == 'type': | |
54 | if value == 'vector': |
|
54 | if value == 'vector': | |
55 | ts_type = amda_make_vector |
|
55 | ts_type = amda_make_vector | |
56 | elif value == 'multicomponent': |
|
56 | elif value == 'multicomponent': | |
57 | ts_type = amda_make_multi_comp |
|
57 | ts_type = amda_make_multi_comp | |
58 | elif value == 'spectrogram': |
|
58 | elif value == 'spectrogram': | |
59 | ts_type = amda_make_spectro |
|
59 | ts_type = amda_make_spectro | |
60 | tstart = datetime.fromtimestamp(start, tz=timezone.utc) |
|
60 | tstart = datetime.fromtimestamp(start, tz=timezone.utc) | |
61 | tend = datetime.fromtimestamp(stop, tz=timezone.utc) |
|
61 | tend = datetime.fromtimestamp(stop, tz=timezone.utc) | |
62 | 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") | |
63 | return ts_type(var) |
|
63 | return ts_type(var) | |
64 | except Exception as e: |
|
64 | except Exception as e: | |
65 | print(traceback.format_exc()) |
|
65 | print(traceback.format_exc()) | |
66 | print("Error in amda.py ", str(e)) |
|
66 | print("Error in amda.py ", str(e)) | |
67 | return ts_type() |
|
67 | return ts_type() | |
68 |
|
68 | |||
69 |
|
69 | |||
70 | class AmdaProvider(PyDataProvider): |
|
70 | class AmdaProvider(PyDataProvider): | |
71 | def __init__(self): |
|
71 | def __init__(self): | |
72 | super(AmdaProvider, self).__init__() |
|
72 | super(AmdaProvider, self).__init__() | |
73 | if len(amda.component) is 0: |
|
73 | if len(amda.component) is 0: | |
74 | amda.update_inventory() |
|
74 | amda.update_inventory() | |
75 | parameters = copy.deepcopy(amda.parameter) |
|
75 | parameters = copy.deepcopy(amda.parameter) | |
76 | for name, component in amda.component.items(): |
|
76 | for name, component in amda.component.items(): | |
77 | if 'components' in parameters[component['parameter']]: |
|
77 | if 'components' in parameters[component['parameter']]: | |
78 | parameters[component['parameter']]['components'].append(component) |
|
78 | parameters[component['parameter']]['components'].append(component) | |
79 | else: |
|
79 | else: | |
80 | parameters[component['parameter']]['components']=[component] |
|
80 | parameters[component['parameter']]['components']=[component] | |
81 |
|
81 | |||
82 | products = [] |
|
82 | products = [] | |
83 | for key, parameter in parameters.items(): |
|
83 | for key, parameter in parameters.items(): | |
84 | path = f"/AMDA/{parameter['mission']}/{parameter.get('observatory','')}/{parameter['instrument']}/{parameter['dataset']}/{parameter['name']}" |
|
84 | mission_name = amda.mission[parameter['mission']]['name'] | |
|
85 | observatory_name = parameter.get('observatory','') | |||
|
86 | if observatory_name != '': | |||
|
87 | observatory_name = amda.observatory[observatory_name]['name'] | |||
|
88 | instrument_name = amda.instrument[parameter['instrument']]['name'] | |||
|
89 | dataset_name = amda.dataset[parameter['dataset']]['name'] | |||
|
90 | path = f"/AMDA/{mission_name}/{observatory_name}/{instrument_name}/{dataset_name}/{parameter['name']}" | |||
85 | components = [component['name'] for component in parameter.get('components',[])] |
|
91 | components = [component['name'] for component in parameter.get('components',[])] | |
86 | metadata = {key: item for key, item in parameter.items() if key is not 'components'} |
|
92 | metadata = {key: item for key, item in parameter.items() if key is not 'components'} | |
87 | n_components = parameter.get('size', 0) |
|
93 | n_components = parameter.get('size', 0) | |
88 | if n_components == '3': |
|
94 | if n_components == '3': | |
89 | metadata["type"] = "vector" |
|
95 | metadata["type"] = "vector" | |
90 | elif parameter.get('display_type', '')=="spectrogram": |
|
96 | elif parameter.get('display_type', '')=="spectrogram": | |
91 | metadata["type"] = "spectrogram" |
|
97 | metadata["type"] = "spectrogram" | |
92 | elif n_components != 0: |
|
98 | elif n_components != 0: | |
93 | metadata["type"] = "multicomponent" |
|
99 | metadata["type"] = "multicomponent" | |
94 | else: |
|
100 | else: | |
95 | metadata["type"] = "scalar" |
|
101 | metadata["type"] = "scalar" | |
96 | products.append(Product(path, components, metadata)) |
|
102 | products.append(Product(path, components, metadata)) | |
97 | self.register_products(products) |
|
103 | self.register_products(products) | |
98 | for mission in amda.mission: |
|
104 | for _,mission in amda.mission.items(): | |
99 | self.set_icon(f'/AMDA/{mission}','satellite') |
|
105 | if ('target' in mission) and (mission['xml:id'] != 'Ephemerides') and (mission['target'] != 'Earth'): | |
|
106 | self.set_icon(f'/AMDA/{mission["name"]}','satellite') | |||
100 |
|
107 | |||
101 | def get_data(self, metadata, start, stop): |
|
108 | def get_data(self, metadata, start, stop): | |
102 | ts_type = amda_make_scalar |
|
109 | ts_type = amda_make_scalar | |
103 | try: |
|
110 | try: | |
104 | param_id = metadata['xml:id'] |
|
111 | param_id = metadata['xml:id'] | |
105 | ts_type_str = metadata['type'] |
|
112 | ts_type_str = metadata['type'] | |
106 | if ts_type_str == 'vector': |
|
113 | if ts_type_str == 'vector': | |
107 | ts_type = amda_make_vector |
|
114 | ts_type = amda_make_vector | |
108 | elif ts_type_str == 'multicomponent': |
|
115 | elif ts_type_str == 'multicomponent': | |
109 | ts_type = amda_make_multi_comp |
|
116 | ts_type = amda_make_multi_comp | |
110 | elif ts_type_str == 'spectrogram': |
|
117 | elif ts_type_str == 'spectrogram': | |
111 | ts_type = amda_make_spectro |
|
118 | ts_type = amda_make_spectro | |
112 | tstart = datetime.fromtimestamp(start, tz=timezone.utc) |
|
119 | tstart = datetime.fromtimestamp(start, tz=timezone.utc) | |
113 | tend = datetime.fromtimestamp(stop, tz=timezone.utc) |
|
120 | tend = datetime.fromtimestamp(stop, tz=timezone.utc) | |
114 | var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST") |
|
121 | var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST") | |
115 | return ts_type(var) |
|
122 | return ts_type(var) | |
116 | except Exception as e: |
|
123 | except Exception as e: | |
117 | print(traceback.format_exc()) |
|
124 | print(traceback.format_exc()) | |
118 | print("Error in amda.py ", str(e)) |
|
125 | print("Error in amda.py ", str(e)) | |
119 | return ts_type() |
|
126 | return ts_type() | |
120 |
|
127 | |||
121 | _amda = AmdaProvider() |
|
128 | _amda = AmdaProvider() |
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