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1 | Subproject commit 5f1aaa704ac36252027b9da0064bdf1de063df0d | |
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1 | Subproject commit 7c86e13f8a6242eb5fe07f0da91a96a4cf68b5bf | |
| @@ -30,10 +30,9 def get_sample(metadata,start,stop): | |||
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30 | 30 | tstart=datetime.datetime.fromtimestamp(start, tz=timezone.utc) |
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31 | 31 | tend=datetime.datetime.fromtimestamp(stop, tz=timezone.utc) |
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32 | 32 | df = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST") |
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33 | #t = np.array([d.timestamp()-7200 for d in df.index]) | |
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34 | 33 | t = np.array([d.timestamp() for d in df.index]) |
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35 | 34 | values = df.values |
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36 |
return ts_type(t,values |
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35 | return ts_type(t,values) | |
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37 | 36 | except Exception as e: |
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38 | 37 | print(traceback.format_exc()) |
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39 | 38 | print("Error in amda.py ",str(e)) |
| @@ -11,19 +11,42 from spwc.cdaweb import cdaweb | |||
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11 | 11 | |
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12 | 12 | cd = cdaweb() |
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13 | 13 | |
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14 |
def get_sample( |
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14 | def cda_get_sample(metadata, start,stop): | |
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15 | ts_type = pysciqlopcore.ScalarTimeSerie | |
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16 | default_ctor_args = 1 | |
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15 | 17 | try: |
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16 | tstart=datetime.datetime.fromtimestamp(start) | |
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17 | tend=datetime.datetime.fromtimestamp(stop) | |
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18 | df = cd.get_variable(dataset="MMS2_SCM_SRVY_L2_SCSRVY",variable="mms2_scm_acb_gse_scsrvy_srvy_l2",tstart=tstart,tend=tend) | |
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19 | t = np.array([d.timestamp()-7200 for d in df.index]) | |
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18 | variable_id = None | |
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19 | dataset_id = None | |
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20 | for key,value in metadata: | |
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21 | if key == 'VAR_ID': | |
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22 | variable_id = value | |
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23 | elif key == 'DATASET_ID': | |
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24 | dataset_id = value | |
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25 | elif key == 'type': | |
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26 | if value == 'vector': | |
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27 | ts_type = pysciqlopcore.VectorTimeSerie | |
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28 | elif value == 'multicomponent': | |
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29 | ts_type = pysciqlopcore.MultiComponentTimeSerie | |
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30 | default_ctor_args = (0,2) | |
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31 | tstart=datetime.datetime.fromtimestamp(start, tz=timezone.utc) | |
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32 | tend=datetime.datetime.fromtimestamp(stop, tz=timezone.utc) | |
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33 | df = cd.get_variable(dataset=dataset_id,variable=variable_id,tstart=tstart,tend=tend) | |
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34 | t = np.array([d.timestamp() for d in df.index]) | |
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20 | 35 | values = df.values |
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21 | return pysciqlopcore.VectorTimeSerie(t,values) | |
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36 | print(values.shape) | |
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37 | return ts_type(t,values) | |
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22 | 38 | except Exception as e: |
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23 |
print( |
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24 | return pysciqlopcore.VectorTimeSerie(1) | |
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39 | print(traceback.format_exc()) | |
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40 | print("Error in amda.py ",str(e)) | |
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41 | return ts_type(default_ctor_args) | |
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25 | 42 | |
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26 | 43 | |
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27 | PythonProviders.register_product([("/CDA/mms4_scm_acb_gse_scsrvy_srvy_l2",[],[("type","vector")])],get_sample) | |
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44 | products = [ | |
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45 | ("/CDA/Themis/ThA/tha_fgl_gsm", [], [("type","multicomponent"), ('size','4'), ("DATASET_ID","THA_L2_FGM"), ("VAR_ID","tha_fgl_gsm")]), | |
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46 | ("/CDA/Themis/ThB/thb_fgl_gsm", [], [("type","multicomponent"), ('size','4'), ("DATASET_ID","THB_L2_FGM"), ("VAR_ID","thb_fgl_gsm")]), | |
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47 | ||
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48 | ] | |
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49 | ||
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50 | PythonProviders.register_product(products, cda_get_sample) | |
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28 | 51 | |
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29 | 52 | |
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