amda.py
60 lines
| 2.0 KiB
| text/x-python
|
PythonLexer
| r1429 | import sys | |||
| sys.path.append("/home/jeandet/Documents/prog/build-SciQLop-Desktop-Debug/core") | ||||
| import os | ||||
| import datetime | ||||
| import PythonProviders | ||||
| import pysciqlopcore | ||||
| import numpy as np | ||||
| import pandas as pds | ||||
| import requests | ||||
| r1430 | from spwc.amda import AMDA | |||
| r1429 | ||||
| r1430 | amda = AMDA() | |||
| def get_sample(metadata,start,stop): | ||||
| ts_type = pysciqlopcore.ScalarTimeSerie | ||||
| r1429 | try: | |||
| r1430 | param_id = None | |||
| for key,value in metadata: | ||||
| if key == 'xml:id': | ||||
| param_id = value | ||||
| elif key == 'type': | ||||
| if value == 'vector': | ||||
| ts_type = pysciqlopcore.VectorTimeSerie | ||||
| tstart=datetime.datetime.fromtimestamp(start) | ||||
| tend=datetime.datetime.fromtimestamp(stop) | ||||
| df = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id) | ||||
| r1429 | t = np.array([d.timestamp()-7200 for d in df.index]) | |||
| values = df.values | ||||
| r1430 | print(len(t)) | |||
| print(len(values)) | ||||
| return ts_type(t,values) | ||||
| return ts_type(1) | ||||
| r1429 | except Exception as e: | |||
| r1430 | print("Error in amda.py ",str(e)) | |||
| return ts_type(1) | ||||
| if len(amda.component) is 0: | ||||
| amda.update_inventory() | ||||
| parameters = amda.parameter.copy() | ||||
| for name,component in amda.component.items(): | ||||
| if 'components' in parameters[component['parameter']]: | ||||
| parameters[component['parameter']]['components'].append(component) | ||||
| else: | ||||
| parameters[component['parameter']]['components']=[component] | ||||
| products = [] | ||||
| for key,parameter in parameters.items(): | ||||
| path = f"/AMDA/{parameter['mission']}/{parameter['instrument']}/{parameter['dataset']}/{parameter['name']}" | ||||
| components = [component['name'] for component in parameter.get('components',[])] | ||||
| metadata = [ (key,item) for key,item in parameter.items() if key is not 'components' ] | ||||
| if parameter.get('size',0) is '3': | ||||
| metadata.append(("type","vector")) | ||||
| else: | ||||
| metadata.append(("type","scalar")) | ||||
| products.append( (path, components, metadata)) | ||||
| r1429 | ||||
| r1430 | PythonProviders.register_product(products, get_sample) | |||
| r1429 | ||||
