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import traceback
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import os
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from datetime import datetime, timedelta, timezone
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from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
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import numpy as np
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import requests
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import copy
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from spwc.amda import AMDA
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amda = AMDA()
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def amda_make_scalar(var=None):
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if var is None:
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return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SCALAR)
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else:
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return (((var.time, np.array([])), var.data), DataSeriesType.SCALAR)
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def amda_make_vector(var=None):
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if var is None:
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return (((np.array([]), np.array([])), np.array([])), DataSeriesType.VECTOR)
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else:
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return (((var.time, np.array([])), var.data), DataSeriesType.VECTOR)
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def amda_make_multi_comp(var=None):
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if var is None:
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return (((np.array([]), np.array([])), np.array([])), DataSeriesType.MULTICOMPONENT)
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else:
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return (((var.time, np.array([])), var.data), DataSeriesType.MULTICOMPONENT)
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def amda_make_spectro(var=None):
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if var is None:
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return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SPECTROGRAM)
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else:
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min_sampling = float(var.meta.get("DATASET_MIN_SAMPLING", "nan"))
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max_sampling = float(var.meta.get("DATASET_MAX_SAMPLING", "nan"))
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if var.y is None and len(var.data):
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var.y = np.logspace(1, 3, var.data.shape[1])[::-1]
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return (((var.time, var.y), var.data), DataSeriesType.SPECTROGRAM)
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#return pysciqlopcore.SpectrogramTimeSerie(var.time,y,var.data,min_sampling,max_sampling,True)
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def amda_get_sample(metadata, start, stop):
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ts_type = amda_make_scalar
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try:
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param_id = None
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for key, value in metadata:
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if key == 'xml:id':
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param_id = value
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elif key == 'type':
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if value == 'vector':
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ts_type = amda_make_vector
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elif value == 'multicomponent':
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ts_type = amda_make_multi_comp
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elif value == 'spectrogram':
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ts_type = amda_make_spectro
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tstart = datetime.fromtimestamp(start, tz=timezone.utc)
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tend = datetime.fromtimestamp(stop, tz=timezone.utc)
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var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST")
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return ts_type(var)
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except Exception as e:
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print(traceback.format_exc())
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print("Error in amda.py ", str(e))
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return ts_type()
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class AmdaProvider(PyDataProvider):
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def __init__(self):
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super(AmdaProvider, self).__init__()
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if len(amda.component) is 0:
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amda.update_inventory()
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parameters = copy.deepcopy(amda.parameter)
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for name, component in amda.component.items():
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if 'components' in parameters[component['parameter']]:
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parameters[component['parameter']]['components'].append(component)
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else:
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parameters[component['parameter']]['components']=[component]
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products = []
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for key, parameter in parameters.items():
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path = f"/AMDA/{parameter['mission']}/{parameter.get('observatory','')}/{parameter['instrument']}/{parameter['dataset']}/{parameter['name']}"
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components = [component['name'] for component in parameter.get('components',[])]
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metadata = {key: item for key, item in parameter.items() if key is not 'components'}
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n_components = parameter.get('size', 0)
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if n_components == '3':
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metadata["type"] = "vector"
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elif parameter.get('display_type', '')=="spectrogram":
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metadata["type"] = "spectrogram"
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elif n_components != 0:
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metadata["type"] = "multicomponent"
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else:
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metadata["type"] = "scalar"
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products.append(Product(path, components, metadata))
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self.register_products(products)
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for mission in amda.mission:
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self.set_icon(f'/AMDA/{mission}','satellite')
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def get_data(self, metadata, start, stop):
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ts_type = amda_make_scalar
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try:
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param_id = metadata['xml:id']
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ts_type_str = metadata['type']
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if ts_type_str == 'vector':
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ts_type = amda_make_vector
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elif ts_type_str == 'multicomponent':
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ts_type = amda_make_multi_comp
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elif ts_type_str == 'spectrogram':
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ts_type = amda_make_spectro
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tstart = datetime.fromtimestamp(start, tz=timezone.utc)
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tend = datetime.fromtimestamp(stop, tz=timezone.utc)
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var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST")
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return ts_type(var)
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except Exception as e:
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print(traceback.format_exc())
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print("Error in amda.py ", str(e))
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return ts_type()
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_amda = AmdaProvider()
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