增加对大数据云平台的探空数据的读取.
This commit is contained in:
NMC-DAVE
parent
96af87195a
commit
deff6c5c56
@ -4,4 +4,4 @@ from various data sources.
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"""
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__author__ = "The R & D Center for Weather Forecasting Technology in NMC, CMA"
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__version__ = '0.1.9.3'
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__version__ = '0.1.10.0'
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@ -249,7 +249,7 @@ def cmadaas_get_obs_files(times, data_code="SURF_CMPA_RT_NC", out_dir=None, pbar
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def cmadaas_obs_by_time(times, data_code="SURF_CHN_MUL_HOR_N",
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sta_levels=None, ranges=None, order=None,
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count=None, distinct=False, trans_type=True,
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count=None, distinct=False, trans_type=True,
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elements="Station_Id_C,Station_Id_d,lat,lon,Datetime,TEM"):
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"""
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Retrieve station records from CMADaaS by times.
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@ -1498,6 +1498,381 @@ def cmadaas_obs_by_years(data_code="SURF_CHN_YER_MMUT_19812010",
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return data
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def cmadaas_get_sounding_latest_time(data_code="UPAR_CHN_MUL_FTM", latestTime=24):
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"""
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Get the latest time of the soundings.
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Args:
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data_code (str, optional): dataset code. Defaults to "UPAR_CHN_MUL_FTM".
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latestTime (int, optional): latestTime > 0, like 2 is return
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the latest time in 2 hours. Defaults to 12.
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Returns:
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datetime object, the latest time
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Examples:
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>>> print(cmadaas_get_sounding_latest_time())
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2020-03-12 03:00:00
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"""
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# set retrieve parameters
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params = {'dataCode': data_code,
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'latestTime': str(latestTime+8)} # 由于服务器是世界时, 因此需要+8才能与当前时间比较.
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# interface id
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interface_id = "getUparLatestTime"
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# retrieve data contents
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contents = get_rest_result(interface_id, params)
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contents = _load_contents(contents)
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# construct pandas DataFrame
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data = pd.DataFrame(contents['DS'])
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time = pd.to_datetime(data['Datetime'], format="%Y%m%d%H%M%S")
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return time[0]
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def cmadaas_sounding_by_time(times, data_code="UPAR_CHN_MUL_FTM", ranges=None,
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order=None, count=None, distinct=False, trans_type=True,
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elements="Station_Name,Station_Id_C,Lat,Lon,Alti,Year,Mon,Day,Hour,Min,Second,PRS_HWC,GPH,TEM,DPT,DTD,WIN_D"):
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"""
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Retrieve sounding records from CMADaaS by times.
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Args:
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times (str): times for retrieve, 'YYYYMMDDHHMISS,YYYYMMDDHHMISS,...'
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data_code (str, optional): dataset code. Defaults to "UPAR_CHN_MUL_FTM".
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ranges (str, optional): elements value ranges, seperated by ';'
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range: (a,) is >a, [a,) is >=a, (,a) is <a, (,a] is <=a, (a,b) is >a & <b,
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[a,b) is >=a & <b, (a,b] is >a & <=b, [a,b] is >=a & <=b
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list: a,b,c;
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e.g., "VIS:(,1000);RHU:(70,)", "Q_PRE_1h:0,3,4" is PRE quantity is credible.. Defaults to None.
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order (str, optional): elements order, seperated by ',', like
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"TEM:asc,SUM_PRE_1h:desc" is ascending order temperature first and descending PRE_1h. Defaults to None.
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count (int, optional): the number of maximum returned records. Defaults to None.
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distinct (bool, optional): return unique records. Defaults to False.
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trans_type (bool, optional): transform the return data frame's column type to datetime, numeric. Defaults to True.
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elements (str, optional): elements for retrieve, 'ele1,ele2,...'.
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Returns:
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pandas data frame: sounding records.
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Examples:
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uparData = cmadaas_sounding_by_time('20220531000000')
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"""
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# set retrieve parameters
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params = {'dataCode': data_code,
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'times': times,
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'orderby': order if order is not None else "Datetime:ASC",
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'elements': elements}
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if ranges is not None: params['eleValueRanges'] = ranges
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if count is not None: params['limitCnt'] = str(count)
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if distinct: params['distinct'] = "true"
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# Interface, refer to
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interface_id = "getUparEleByTime"
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# retrieve data contents
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contents = get_rest_result(interface_id, params)
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contents = _load_contents(contents)
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if contents is None:
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return None
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# construct pandas DataFrame
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data = pd.DataFrame(contents['DS'])
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if trans_type: data = cmadaas_obs_convert_type(data)
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# return
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return data
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def cmadaas_sounding_by_time_and_press(
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times, data_code="UPAR_CHN_MUL_FTM", press=500, ranges=None,
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order=None, count=None, distinct=False, trans_type=True,
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elements="Station_Name,Station_Id_C,Lat,Lon,Alti,Year,Mon,Day,Hour,Min,Second,PRS_HWC,GPH,TEM,DPT,DTD,WIN_D"):
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"""
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Retrieve sounding records from CMADaaS by times.
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Args:
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times (str): times for retrieve, 'YYYYMMDDHHMISS,YYYYMMDDHHMISS,...'
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data_code (str, optional): dataset code. Defaults to "UPAR_CHN_MUL_FTM".
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press (str, optional): pressure level. Defaults to 500.
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ranges (str, optional): elements value ranges, seperated by ';'
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range: (a,) is >a, [a,) is >=a, (,a) is <a, (,a] is <=a, (a,b) is >a & <b,
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[a,b) is >=a & <b, (a,b] is >a & <=b, [a,b] is >=a & <=b
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list: a,b,c;
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e.g., "VIS:(,1000);RHU:(70,)", "Q_PRE_1h:0,3,4" is PRE quantity is credible.. Defaults to None.
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order (str, optional): elements order, seperated by ',', like
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"TEM:asc,SUM_PRE_1h:desc" is ascending order temperature first and descending PRE_1h. Defaults to None.
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count (int, optional): the number of maximum returned records. Defaults to None.
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distinct (bool, optional): return unique records. Defaults to False.
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trans_type (bool, optional): transform the return data frame's column type to datetime, numeric. Defaults to True.
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elements (str, optional): elements for retrieve, 'ele1,ele2,...'.
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Returns:
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pandas data frame: sounding records.
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Examples:
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uparData = cmadaas_sounding_by_time_and_press('20220531000000', press=500)
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"""
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# set retrieve parameters
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params = {'dataCode': data_code,
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'times': times,
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'pLayers': str(press).strip(),
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'orderby': order if order is not None else "Datetime:ASC",
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'elements': elements}
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if ranges is not None: params['eleValueRanges'] = ranges
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if count is not None: params['limitCnt'] = str(count)
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if distinct: params['distinct'] = "true"
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# Interface, refer to
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interface_id = "getUparEleByTimeAndPress"
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# retrieve data contents
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contents = get_rest_result(interface_id, params)
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contents = _load_contents(contents)
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if contents is None:
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return None
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# construct pandas DataFrame
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data = pd.DataFrame(contents['DS'])
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if trans_type: data = cmadaas_obs_convert_type(data)
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# return
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return data
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def cmadaas_sounding_by_time_and_height(
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times, data_code="UPAR_CHN_MUL_FTM", height=5000, ranges=None,
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order=None, count=None, distinct=False, trans_type=True,
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elements="Station_Name,Station_Id_C,Lat,Lon,Alti,Year,Mon,Day,Hour,Min,Second,PRS_HWC,GPH,TEM,DPT,DTD,WIN_D"):
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"""
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Retrieve sounding records from CMADaaS by times.
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Args:
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times (str): times for retrieve, 'YYYYMMDDHHMISS,YYYYMMDDHHMISS,...'
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data_code (str, optional): dataset code. Defaults to "UPAR_CHN_MUL_FTM".
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height (str, optional): height level. Defaults to 5000.
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ranges (str, optional): elements value ranges, seperated by ';'
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range: (a,) is >a, [a,) is >=a, (,a) is <a, (,a] is <=a, (a,b) is >a & <b,
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[a,b) is >=a & <b, (a,b] is >a & <=b, [a,b] is >=a & <=b
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list: a,b,c;
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e.g., "VIS:(,1000);RHU:(70,)", "Q_PRE_1h:0,3,4" is PRE quantity is credible.. Defaults to None.
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order (str, optional): elements order, seperated by ',', like
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"TEM:asc,SUM_PRE_1h:desc" is ascending order temperature first and descending PRE_1h. Defaults to None.
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count (int, optional): the number of maximum returned records. Defaults to None.
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distinct (bool, optional): return unique records. Defaults to False.
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trans_type (bool, optional): transform the return data frame's column type to datetime, numeric. Defaults to True.
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elements (str, optional): elements for retrieve, 'ele1,ele2,...'.
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Returns:
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pandas data frame: sounding records.
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Examples:
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uparData = cmadaas_sounding_by_time_and_height('20220531000000', height=5000)
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"""
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# set retrieve parameters
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params = {'dataCode': data_code,
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'times': times,
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'hLayers': str(height).strip(),
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'orderby': order if order is not None else "Datetime:ASC",
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'elements': elements}
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if ranges is not None: params['eleValueRanges'] = ranges
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if count is not None: params['limitCnt'] = str(count)
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if distinct: params['distinct'] = "true"
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# Interface, refer to
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interface_id = "getUparEleByTimeAndHeight"
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# retrieve data contents
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contents = get_rest_result(interface_id, params)
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contents = _load_contents(contents)
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if contents is None:
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return None
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# construct pandas DataFrame
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data = pd.DataFrame(contents['DS'])
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if trans_type: data = cmadaas_obs_convert_type(data)
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# return
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return data
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def cmadaas_sounding_in_rect_by_time(
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times, limit=[3.51, 73.33, 53.33, 135.05], data_code="UPAR_CHN_MUL_FTM",
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ranges=None, order=None, count=None, trans_type=True,
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elements="Station_Name,Station_Id_C,Lat,Lon,Alti,Year,Mon,Day,Hour,Min,Second,PRS_HWC,GPH,TEM,DPT,DTD,WIN_D,WIN_S"):
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"""
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Retrieve sounding records from CIMISS in region by times.
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Args:
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times (str): time for retrieve, 'YYYYMMDDHHMISS,YYYYMMDDHHMISS,...'
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limit (list, optional): map limits, [min_lat, min_lon, max_lat, max_lon]
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data_code (str, optional): dataset code. Defaults to "UPAR_CHN_MUL_FTM".
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ranges (str, optional): elements value ranges, seperated by ';'
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range: (a,) is >a, [a,) is >=a, (,a) is <a, (,a] is <=a, (a,b) is >a & <b,
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[a,b) is >=a & <b, (a,b] is >a & <=b, [a,b] is >=a & <=b
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list: a,b,c;
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e.g., "VIS:(,1000);RHU:(70,)", "Q_PRE_1h:0,3,4" is PRE quantity is credible.. Defaults to None.
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order (str, optional): elements order, seperated by ',', like
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"TEM:asc,SUM_PRE_1h:desc" is ascending order temperature first and descending PRE_1h. Defaults to None.
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count (int, optional): the number of maximum returned records. Defaults to None.
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trans_type (bool, optional): transform the return data frame's column type to datetime, numeric. Defaults to True.
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elements (str, optional): elements for retrieve, 'ele1,ele2,...'.
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Returns:
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pandas data frame: sounding records.
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Examples:
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>>> data = cmadaas_sounding_in_rect_by_time('20220531000000', limit=[3.51, 73.33, 53.33, 135.05])
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"""
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# set retrieve parameters
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params = {'dataCode': data_code,
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'elements': elements,
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'times': times,
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'minLat': '{:.10f}'.format(limit[0]),
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'minLon': '{:.10f}'.format(limit[1]),
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'maxLat': '{:.10f}'.format(limit[2]),
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'maxLon': '{:.10f}'.format(limit[3]),
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'orderby': order if order is not None else "Datetime:ASC"}
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if ranges is not None: params['eleValueRanges'] = ranges
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if count is not None: params['limitCnt'] = str(count)
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# interface id
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interface_id = "getUparEleInRectByTime"
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# retrieve data contents
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contents = get_rest_result(interface_id, params)
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contents = _load_contents(contents)
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if contents is None:
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return None
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# construct pandas DataFrame
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data = pd.DataFrame(contents['DS'])
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if trans_type: data = cmadaas_obs_convert_type(data)
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# return
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return data
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def cmadaas_sounding_by_time_and_id(
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times, data_code="UPAR_CHN_MUL_FTM", sta_ids='54511', ranges=None,
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order=None, count=None, distinct=False, trans_type=True,
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elements="Station_Name,Station_Id_C,Lat,Lon,Alti,Year,Mon,Day,Hour,Min,Second,PRS_HWC,GPH,TEM,DPT,DTD,WIN_D"):
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"""
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Retrieve sounding records from CMADaaS by times.
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Args:
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times (str): times for retrieve, 'YYYYMMDDHHMISS,YYYYMMDDHHMISS,...'
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data_code (str, optional): dataset code. Defaults to "UPAR_CHN_MUL_FTM".
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sta_ids (str, optional): station id, 多个以逗号(,)分隔，区域站以字母开头. Defaults to 54511.
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ranges (str, optional): elements value ranges, seperated by ';'
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range: (a,) is >a, [a,) is >=a, (,a) is <a, (,a] is <=a, (a,b) is >a & <b,
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[a,b) is >=a & <b, (a,b] is >a & <=b, [a,b] is >=a & <=b
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list: a,b,c;
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e.g., "VIS:(,1000);RHU:(70,)", "Q_PRE_1h:0,3,4" is PRE quantity is credible.. Defaults to None.
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order (str, optional): elements order, seperated by ',', like
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"TEM:asc,SUM_PRE_1h:desc" is ascending order temperature first and descending PRE_1h. Defaults to None.
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count (int, optional): the number of maximum returned records. Defaults to None.
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distinct (bool, optional): return unique records. Defaults to False.
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trans_type (bool, optional): transform the return data frame's column type to datetime, numeric. Defaults to True.
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elements (str, optional): elements for retrieve, 'ele1,ele2,...'.
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Returns:
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pandas data frame: sounding records.
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Examples:
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uparData = cmadaas_sounding_by_time_and_id('20220531000000', sta_ids='54511')
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"""
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# set retrieve parameters
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params = {'dataCode': data_code,
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'times': times,
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'staIds': str(sta_ids).strip(),
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'orderby': order if order is not None else "Datetime:ASC",
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'elements': elements}
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if ranges is not None: params['eleValueRanges'] = ranges
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if count is not None: params['limitCnt'] = str(count)
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if distinct: params['distinct'] = "true"
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# Interface, refer to
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interface_id = "getUparEleByTimeAndStaID"
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# retrieve data contents
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contents = get_rest_result(interface_id, params)
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contents = _load_contents(contents)
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if contents is None:
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return None
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# construct pandas DataFrame
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data = pd.DataFrame(contents['DS'])
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if trans_type: data = cmadaas_obs_convert_type(data)
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# return
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return data
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def cmadaas_sounding_in_rect_by_time_range(
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time_range, limit=[3.51, 73.33, 53.33, 135.05], data_code="UPAR_CHN_MUL_FTM",
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ranges=None, order=None, count=None, trans_type=True,
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elements="Station_Name,Station_Id_C,Lat,Lon,Alti,Year,Mon,Day,Hour,Min,Second,PRS_HWC,GPH,TEM,DPT,DTD,WIN_D,WIN_S"):
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"""
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Retrieve sounding records from CIMISS in region by times.
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Args:
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time_range (str): time for retrieve, "[YYYYMMDDHHMISS,YYYYMMDDHHMISS]"
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limit (list, optional): map limits, [min_lat, min_lon, max_lat, max_lon]
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data_code (str, optional): dataset code. Defaults to "UPAR_CHN_MUL_FTM".
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ranges (str, optional): elements value ranges, seperated by ';'
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range: (a,) is >a, [a,) is >=a, (,a) is <a, (,a] is <=a, (a,b) is >a & <b,
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[a,b) is >=a & <b, (a,b] is >a & <=b, [a,b] is >=a & <=b
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list: a,b,c;
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e.g., "VIS:(,1000);RHU:(70,)", "Q_PRE_1h:0,3,4" is PRE quantity is credible.. Defaults to None.
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order (str, optional): elements order, seperated by ',', like
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"TEM:asc,SUM_PRE_1h:desc" is ascending order temperature first and descending PRE_1h. Defaults to None.
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count (int, optional): the number of maximum returned records. Defaults to None.
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trans_type (bool, optional): transform the return data frame's column type to datetime, numeric. Defaults to True.
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elements (str, optional): elements for retrieve, 'ele1,ele2,...'.
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Returns:
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pandas data frame: sounding records.
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Examples:
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>>> data = cmadaas_sounding_in_rect_by_time_range('[20220531000000,20220531010000]', limit=[3.51, 73.33, 53.33, 135.05])
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"""
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# set retrieve parameters
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params = {'dataCode': data_code,
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'elements': elements,
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'timeRange': time_range,
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'minLat': '{:.10f}'.format(limit[0]),
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'minLon': '{:.10f}'.format(limit[1]),
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'maxLat': '{:.10f}'.format(limit[2]),
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'maxLon': '{:.10f}'.format(limit[3]),
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'orderby': order if order is not None else "Datetime:ASC"}
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if ranges is not None: params['eleValueRanges'] = ranges
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if count is not None: params['limitCnt'] = str(count)
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# interface id
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interface_id = "getUparEleInRectByTimeRange"
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# retrieve data contents
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contents = get_rest_result(interface_id, params)
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contents = _load_contents(contents)
|
||||
if contents is None:
|
||||
return None
|
||||
|
||||
# construct pandas DataFrame
|
||||
data = pd.DataFrame(contents['DS'])
|
||||
if trans_type: data = cmadaas_obs_convert_type(data)
|
||||
|
||||
# return
|
||||
return data
|
||||
|
||||
|
||||
def cmadaas_analysis_by_time(time_str, limit=None, data_code='NAFP_CLDAS2.0_NRT_ASI_NC',
|
||||
levattrs={'long_name':'Height above Ground', 'units':'m'}, level_type='-',
|
||||
fcst_level=None, fcst_ele="TMP", zoom=None, units=None, scale_off=None,
|
||||
|
||||
Loading…
Reference in New Issue
Block a user