diff --git a/hapi_parser.py b/hapi_parser.py index 93df951..2dd0f49 100644 --- a/hapi_parser.py +++ b/hapi_parser.py @@ -12,6 +12,7 @@ import time from time import gmtime, strftime +from io import StringIO # Python2 uses urlparse, Python3 uses urllib.parse #import urlparse import urllib.parse as urlparse @@ -48,9 +49,55 @@ class defaultvars(): tags_allowed = [''] # no subparams allowed stream_flag = True -def fetchdata(hapi_handler, id, timemin, timemax, parameters, mydata, +def tolist(csvline): + return csvline.split(',') + +def test_server(): + from hapiclient import hapi + from hapiplot import hapiplot + server = 'http://localhost:8000/hapi' + start = '2023-12-01T00:00:00Z' + stop = '2023-12-07T00:00:00Z' + dataset = "indices_all" + parameters="SME,SML" + data, meta = hapi(server, dataset, parameters, start, stop) + hapiplot(data,meta) + +def test_serverless(USE_CASE='supermag',plot=False): + + start = '2023-12-01T00:00:00Z' + stop = '2023-12-07T00:00:00Z' + id = "indices_all" + parameters="SME,SML" + + CFG = parse_config(USE_CASE) + #xopts=[] + CFG.floc['customOptions'] = [] # handle_customRequestOptions(query, xopts) + tags = [] # (tags, path) = get_hapi_tags(path,CFG.tags_allowed) + + (start, stop, errorcode) = clean_query_time(None,timemin=start,timemax=stop) + # info call: id = query['id'][0], parameters = handle_key_parameters(query) + # catalog call: for l in open(CFG.HAPI_HOME+'catalog.json'): print(l) + # capabilities call: for l in ...capabilities + + # data call: + parameters = parameters.split(',') + (status, jsondata) = fetch_info_params(id,CFG.HAPI_HOME,False) + (status, data) = CFG.hapi_handler(id, start, stop, parameters, jsondata, CFG.floc, False, None) + + #adata = data.split('\n') + fdata = StringIO(data) + meta, hapidata = csv_to_hapi_conv(id,parameters,CFG.HAPI_HOME,fdata) + + if plot: + from hapiplot import hapiplot + hapiplot(data,meta) + + return meta, hapidata + +def fetchdata(hapi_handler, id, timemin, timemax, parameters, jsondata, floc, stream_flag, s): - (status, data) = hapi_hander(id, timemin, timemax, parameters, mydata, floc, stream_flag, s) + (status, data) = hapi_hander(id, timemin, timemax, parameters, jsondata, floc, stream_flag, s) return (status, data) def parse_config(myname): @@ -75,6 +122,8 @@ def parse_config(myname): hapi_handler = CFG.hapi_handler tags_allowed = CFG.tags_allowed stream_flag = CFG.stream_flag + CFG.floc['customOptions'] = [] + CFG.tags = [] if CFG.loaded_config: print("Successfully loaded ",cfile) except: @@ -120,7 +169,7 @@ def fetch_info_params(id, hapihome, isFile): # TESTED # open the info/[id].json file and return the parameter array # set isFile=True if 'id' is a filename, False if 'id' is actually an id - # e.g. mydata['startDate'], mydata['stopDate'], etc + # e.g. jsondata['startDate'], jsondata['stopDate'], etc status=False try: if isFile: @@ -129,24 +178,24 @@ def fetch_info_params(id, hapihome, isFile): else: #print("Debug: id file is ", HAPI_HOME + 'info/' + id + '.json' ) jo = open( hapihome + 'info/' + id + '.json' ) - mydata=json.loads(jo.read()) + jsondata=json.loads(jo.read()) jo.close() status=True except: #print("debug: could not access file for ",id) - mydata={'startDate':'30010101T00:00', + jsondata={'startDate':'30010101T00:00', 'stopDate':'00010101T00:00', 'parameters':{}} # handle HAPI's in-house 'lasthour' as a proper date - if 'stopDate' in mydata.keys(): - mydata['stopDate'] = lasthour_mod(mydata['stopDate']) + if 'stopDate' in jsondata.keys(): + jsondata['stopDate'] = lasthour_mod(jsondata['stopDate']) # added 'limitduration' as a new HAPI keyword that might exist # in info/[id].json, units=sec - if 'limitduration' not in mydata.keys(): - mydata['limitduration']=0 # 0 = no limit enforced + if 'limitduration' not in jsondata.keys(): + jsondata['limitduration']=0 # 0 = no limit enforced #print("Debug: status on checking limits is: ",status) - return(status,mydata) + return(status,jsondata) ### Sample generic HAPI formatting utilities for user-made parsers @@ -188,18 +237,18 @@ def generic_check_error(id, timemin, timemax, parameters, hapihome): timemax = lasthour_mod(timemax) errorcode = 0 # assume all is well - (stat,mydata)=fetch_info_params(id,hapihome,False) + (stat,jsondata)=fetch_info_params(id,hapihome,False) if stat == False: errorcode = 1406 # no valid json exists so 'Bad request - unknown dataset id' qtimemin= timemin # no change qtimemax= timemax # no change else: - #print("debug: for id ",id," got ",mydata) - limit_duration=mydata['limitduration'] - archive_startdate=parse(mydata['startDate'],ignoretz=True) + #print("debug: for id ",id," got ",jsondata) + limit_duration=jsondata['limitduration'] + archive_startdate=parse(jsondata['startDate'],ignoretz=True) # yet more datehandling, for now/lastday/lasthour/etc - stopdate=mydata['stopDate'] + stopdate=jsondata['stopDate'] if 'now' in stopdate or 'last' in stopdate: archive_stopdate=datetime.datetime.now() else: @@ -474,11 +523,13 @@ def check_v2_v3(query): query['time.max']=query['stop'] return(query) -def clean_query_time(query): +def clean_query_time(query,timemin=None,timemax=None): # TESTED errorcode = 0 # assume all is well - timemin= query['time.min'][0] - timemax= lasthour_mod(query['time.max'][0]) + if timemin == None: + timemin= query['time.min'][0] + if timemax == None: + timemax= lasthour_mod(query['time.max'][0]) # right now our parser can only handle format %Y-%m-%dT%H:%MZ # so truncatee entries with seconds.milliseconds timemin=timemin[0:16]+'Z' @@ -518,8 +569,8 @@ def prep_data(query, hapihome, tags): (check_error,timemin,timemax) = generic_check_error( id,timemin,timemax,parameters,hapihome) # Two passes here-- first, that no non-HAPI params exist - (stat,mydata)=fetch_info_params(id,hapihome,False) - allparams = [ item['name'] for item in mydata['parameters'] ] + (stat,jsondata)=fetch_info_params(id,hapihome,False) + allparams = [ item['name'] for item in jsondata['parameters'] ] if parameters != None: if 'Time' not in allparams: allparams.append('Time') # always make sure this is there @@ -549,13 +600,13 @@ def prep_data(query, hapihome, tags): parameters.extend(tags) # returns an array of validated additional query strings # (or empty array) - if 'x_customRequestOptions' in mydata.keys(): - xopts = mydata['x_customRequestOptions'] + if 'x_customRequestOptions' in jsondata.keys(): + xopts = jsondata['x_customRequestOptions'] else: xopts=[] #print("Debug, xopts = ",xopts) ## xopts = jset['x_customRequestOptions'] - return(parameters, xopts, mydata, check_error) + return(parameters, xopts, jsondata, check_error) def print_hapi_intropage(myname, hapihome): # TESTED @@ -580,17 +631,17 @@ def print_hapi_intropage(myname, hapihome): ff= glob.glob( hapihome + 'info/*.json' ) n= len( hapihome + 'info/' ) for f in sorted(ff): - (stat,mydata)=fetch_info_params(f,hapihome,True) + (stat,jsondata)=fetch_info_params(f,hapihome,True) u= "/hapi/info?%s=%s" % ( datasetkey, f[n:-5] ) mystr += "%s
\n" % ( u,u ) # also extract dates etc from file #print("debug: checking info file ",f) - #print("debug:",mydata) - timemin=mydata['startDate'] - timemax=mydata['stopDate'] + #print("debug:",jsondata) + timemin=jsondata['startDate'] + timemax=jsondata['stopDate'] try: - timemin=mydata['sampleStartDate'] - timemax=mydata['sampleStopDate'] + timemin=jsondata['sampleStartDate'] + timemax=jsondata['sampleStopDate'] except: pass u= "/hapi/data?%s=%s&%s=%s&%s=%s" % ( @@ -599,7 +650,7 @@ def print_hapi_intropage(myname, hapihome): mystr += "%s
\n" % ( u,u ) mystr += "Parameters:\n" mystr += "" - for para in mydata['parameters']: + for para in jsondata['parameters']: #mystr += "
  • " mystr += "
    • " mystr += "" % (para['name']) @@ -651,12 +702,20 @@ def fetch_modifiedsince(lms): -def sampleconv(): +def csv_to_hapi_conv(id='cputemp', + parameters=None, + floc='home_csv/', + finput='home_csv/data/cputemp/2018/cputemp.20180119.csv'): + """ + Given a CSV filename or file-like object, returns HAPI-style meta, data + includes a test mode using 'cputemp' + """ from hapiclient.hapi import compute_dt from hapiclient.util import jsonparse import json - fname = 'home_csv/info/cputemp.json' - with open(fname) as fin: + + jname = floc+'/info/'+id+'.json' + with open(jname) as fin: meta = json.load(fin) meta.update({"x_server": 'whatever'}) meta.update({"x_dataset": 'whatever'}) @@ -664,17 +723,26 @@ def sampleconv(): opts['format'] = 'csv' opts['method'] = 'numpynolength' dt, cols, psizes, pnames, pytpes, missing_length = compute_dt(meta, opts) - fname = 'home_csv/data/cputemp/2018/cputemp.20180119.csv' - import numpy as np - data = hapi_conv_np(fname,dt) - from hapiplot import hapiplot - hapiplot(data,meta) + + if parameters != None: + dt = [d for d in dt if d[0] in parameters or d[0] == 'Time'] + meta['parameters'] = [p for p in meta['parameters'] if p['name'] in parameters or p['name'] == 'Time'] + try: + data = hapi_conv_np_fromtxt(finput,dt) + except: + print("Error converting data to numpy format, returning raw data instead") + return dt, finput + return meta, data -def hapi_conv_np(fnamecsv,dt): +def hapi_conv_np_fromtxt(fname_or_data_csv,dt): + # takes files or list of strings only + import numpy as np data = np.array([], dtype=dt) - data = np.genfromtxt(fnamecsv, + if not exists(fname_or_data_csv): + fname_or_data_csv = StringIO(fname_or_data_csv) + data = np.genfromtxt(fname_or_data_csv, dtype=dt, delimiter=',', replace_space=' ', @@ -682,7 +750,18 @@ def hapi_conv_np(fnamecsv,dt): encoding='utf-8') return data +def hapi_conv_np_alttxt(sdata,dt): + # takes file or list of strings + import numpy as np + data = np.array([], dtype=dt) + data = np.loadtxt(sdata, + dtype=dt, + delimiter=',', + encoding='utf-8') + return data + def hapi_conv_pandas(fnamecsv,dt,df,pnames,psizes,cols): + import pandas df = pandas.read_csv(fnamecsv, sep=',', header=None, diff --git a/home_supermag/capabilities.json b/home_supermag/capabilities.json new file mode 100755 index 0000000..476b88d --- /dev/null +++ b/home_supermag/capabilities.json @@ -0,0 +1,10 @@ +{ + "HAPI": "3.1", + "outputFormats": [ + "csv" + ], + "status": { + "code": 1200, + "message": "OK request successful" + } +} diff --git a/home_supermag/catalog.json b/home_supermag/catalog.json new file mode 100755 index 0000000..844d817 --- /dev/null +++ b/home_supermag/catalog.json @@ -0,0 +1,845 @@ +{ + "HAPI": "3.1", + "catalog": [ + { + "id": "indices_all", + "title": "Data indices for time span, indices_all" + }, + { + "id": "indices_base", + "title": "Data indices for time span, indices_base" + }, + { + "id": "indices_dark", + "title": "Data indices for time span, indices_dark" + }, + { + "id": "indices_imf", + "title": "Data indices for time span, indices_imf" + }, + { + "id": "indices_reg", + "title": "Data indices for time span, indices_reg" + }, + { + "id": "indices_sun", + "title": "Data indices for time span, indices_sun" + }, + { + "id": "indices_swi", + "title": "Data indices for time span, indices_swi" + }, + { + "id": "data_AAA", + "title": "Data for station AAA" + }, + { + "id": "data_AIA", + "title": "Data for station AIA" + }, + { + "id": "data_AMS", + "title": "Data for station AMS" + }, + { + "id": "data_AND", + "title": "Data for station AND" + }, + { + "id": "data_API", + "title": "Data for station API" + }, + { + "id": "data_ARS", + "title": "Data for station ARS" + }, + { + "id": "data_ASC", + "title": "Data for station ASC" + }, + { + "id": "data_ASP", + "title": "Data for station ASP" + }, + { + "id": "data_BFE", + "title": "Data for station BFE" + }, + { + "id": "data_BFO", + "title": "Data for station BFO" + }, + { + "id": "data_BJN", + "title": "Data for station BJN" + }, + { + "id": "data_BLC", + "title": "Data for station BLC" + }, + { + "id": "data_BMT", + "title": "Data for station BMT" + }, + { + "id": "data_BOU", + "title": "Data for station BOU" + }, + { + "id": "data_BOX", + "title": "Data for station BOX" + }, + { + "id": "data_BRD", + "title": "Data for station BRD" + }, + { + "id": "data_BRN", + "title": "Data for station BRN" + }, + { + "id": "data_BRW", + "title": "Data for station BRW" + }, + { + "id": "data_BSL", + "title": "Data for station BSL" + }, + { + "id": "data_C04", + "title": "Data for station C04" + }, + { + "id": "data_C06", + "title": "Data for station C06" + }, + { + "id": "data_C08", + "title": "Data for station C08" + }, + { + "id": "data_C10", + "title": "Data for station C10" + }, + { + "id": "data_CBB", + "title": "Data for station CBB" + }, + { + "id": "data_CDC", + "title": "Data for station CDC" + }, + { + "id": "data_CHC", + "title": "Data for station CHC" + }, + { + "id": "data_CKI", + "title": "Data for station CKI" + }, + { + "id": "data_CLF", + "title": "Data for station CLF" + }, + { + "id": "data_CMO", + "title": "Data for station CMO" + }, + { + "id": "data_CNB", + "title": "Data for station CNB" + }, + { + "id": "data_CPS", + "title": "Data for station CPS" + }, + { + "id": "data_CSY", + "title": "Data for station CSY" + }, + { + "id": "data_CTA", + "title": "Data for station CTA" + }, + { + "id": "data_CYG", + "title": "Data for station CYG" + }, + { + "id": "data_CZT", + "title": "Data for station CZT" + }, + { + "id": "data_DAW", + "title": "Data for station DAW" + }, + { + "id": "data_DED", + "title": "Data for station DED" + }, + { + "id": "data_DIK", + "title": "Data for station DIK" + }, + { + "id": "data_DLT", + "title": "Data for station DLT" + }, + { + "id": "data_DMC", + "title": "Data for station DMC" + }, + { + "id": "data_DMH", + "title": "Data for station DMH" + }, + { + "id": "data_DOB", + "title": "Data for station DOB" + }, + { + "id": "data_DON", + "title": "Data for station DON" + }, + { + "id": "data_DRV", + "title": "Data for station DRV" + }, + { + "id": "data_DUR", + "title": "Data for station DUR" + }, + { + "id": "data_EAG", + "title": "Data for station EAG" + }, + { + "id": "data_EBR", + "title": "Data for station EBR" + }, + { + "id": "data_ESK", + "title": "Data for station ESK" + }, + { + "id": "data_EYR", + "title": "Data for station EYR" + }, + { + "id": "data_FCC", + "title": "Data for station FCC" + }, + { + "id": "data_FHB", + "title": "Data for station FHB" + }, + { + "id": "data_FMC", + "title": "Data for station FMC" + }, + { + "id": "data_FRD", + "title": "Data for station FRD" + }, + { + "id": "data_FRN", + "title": "Data for station FRN" + }, + { + "id": "data_FSP", + "title": "Data for station FSP" + }, + { + "id": "data_GAN", + "title": "Data for station GAN" + }, + { + "id": "data_GCK", + "title": "Data for station GCK" + }, + { + "id": "data_GDH", + "title": "Data for station GDH" + }, + { + "id": "data_GHB", + "title": "Data for station GHB" + }, + { + "id": "data_GHC", + "title": "Data for station GHC" + }, + { + "id": "data_GIM", + "title": "Data for station GIM" + }, + { + "id": "data_GNG", + "title": "Data for station GNG" + }, + { + "id": "data_GUA", + "title": "Data for station GUA" + }, + { + "id": "data_GUI", + "title": "Data for station GUI" + }, + { + "id": "data_HAN", + "title": "Data for station HAN" + }, + { + "id": "data_HBK", + "title": "Data for station HBK" + }, + { + "id": "data_HER", + "title": "Data for station HER" + }, + { + "id": "data_HON", + "title": "Data for station HON" + }, + { + "id": "data_HRB", + "title": "Data for station HRB" + }, + { + "id": "data_HUA", + "title": "Data for station HUA" + }, + { + "id": "data_HYB", + "title": "Data for station HYB" + }, + { + "id": "data_IGC", + "title": "Data for station IGC" + }, + { + "id": "data_IQA", + "title": "Data for station IQA" + }, + { + "id": "data_IRT", + "title": "Data for station IRT" + }, + { + "id": "data_ISL", + "title": "Data for station ISL" + }, + { + "id": "data_IVA", + "title": "Data for station IVA" + }, + { + "id": "data_IZN", + "title": "Data for station IZN" + }, + { + "id": "data_JAI", + "title": "Data for station JAI" + }, + { + "id": "data_JAN", + "title": "Data for station JAN" + }, + { + "id": "data_JCK", + "title": "Data for station JCK" + }, + { + "id": "data_JCO", + "title": "Data for station JCO" + }, + { + "id": "data_KAG", + "title": "Data for station KAG" + }, + { + "id": "data_KAK", + "title": "Data for station KAK" + }, + { + "id": "data_KAR", + "title": "Data for station KAR" + }, + { + "id": "data_KDU", + "title": "Data for station KDU" + }, + { + "id": "data_KEP", + "title": "Data for station KEP" + }, + { + "id": "data_KEV", + "title": "Data for station KEV" + }, + { + "id": "data_KHB", + "title": "Data for station KHB" + }, + { + "id": "data_KIL", + "title": "Data for station KIL" + }, + { + "id": "data_KIR", + "title": "Data for station KIR" + }, + { + "id": "data_KLI", + "title": "Data for station KLI" + }, + { + "id": "data_KNY", + "title": "Data for station KNY" + }, + { + "id": "data_KOU", + "title": "Data for station KOU" + }, + { + "id": "data_KUV", + "title": "Data for station KUV" + }, + { + "id": "data_KZN", + "title": "Data for station KZN" + }, + { + "id": "data_LER", + "title": "Data for station LER" + }, + { + "id": "data_LON", + "title": "Data for station LON" + }, + { + "id": "data_LOZ", + "title": "Data for station LOZ" + }, + { + "id": "data_LRM", + "title": "Data for station LRM" + }, + { + "id": "data_LRV", + "title": "Data for station LRV" + }, + { + "id": "data_LVV", + "title": "Data for station LVV" + }, + { + "id": "data_LYR", + "title": "Data for station LYR" + }, + { + "id": "data_MAS", + "title": "Data for station MAS" + }, + { + "id": "data_MAW", + "title": "Data for station MAW" + }, + { + "id": "data_MBO", + "title": "Data for station MBO" + }, + { + "id": "data_MCQ", + "title": "Data for station MCQ" + }, + { + "id": "data_MEA", + "title": "Data for station MEA" + }, + { + "id": "data_MEK", + "title": "Data for station MEK" + }, + { + "id": "data_MGD", + "title": "Data for station MGD" + }, + { + "id": "data_MHV", + "title": "Data for station MHV" + }, + { + "id": "data_MMB", + "title": "Data for station MMB" + }, + { + "id": "data_MNK", + "title": "Data for station MNK" + }, + { + "id": "data_MSR", + "title": "Data for station MSR" + }, + { + "id": "data_MUO", + "title": "Data for station MUO" + }, + { + "id": "data_NAL", + "title": "Data for station NAL" + }, + { + "id": "data_NAQ", + "title": "Data for station NAQ" + }, + { + "id": "data_NCK", + "title": "Data for station NCK" + }, + { + "id": "data_NEW", + "title": "Data for station NEW" + }, + { + "id": "data_NGK", + "title": "Data for station NGK" + }, + { + "id": "data_NR2", + "title": "Data for station NR2" + }, + { + "id": "data_NUR", + "title": "Data for station NUR" + }, + { + "id": "data_NVS", + "title": "Data for station NVS" + }, + { + "id": "data_ODE", + "title": "Data for station ODE" + }, + { + "id": "data_ORC", + "title": "Data for station ORC" + }, + { + "id": "data_OTT", + "title": "Data for station OTT" + }, + { + "id": "data_OUJ", + "title": "Data for station OUJ" + }, + { + "id": "data_PAG", + "title": "Data for station PAG" + }, + { + "id": "data_PBK", + "title": "Data for station PBK" + }, + { + "id": "data_PEG", + "title": "Data for station PEG" + }, + { + "id": "data_PEL", + "title": "Data for station PEL" + }, + { + "id": "data_PET", + "title": "Data for station PET" + }, + { + "id": "data_PG1", + "title": "Data for station PG1" + }, + { + "id": "data_PG5", + "title": "Data for station PG5" + }, + { + "id": "data_PGC", + "title": "Data for station PGC" + }, + { + "id": "data_PHU", + "title": "Data for station PHU" + }, + { + "id": "data_PIL", + "title": "Data for station PIL" + }, + { + "id": "data_PST", + "title": "Data for station PST" + }, + { + "id": "data_R04", + "title": "Data for station R04" + }, + { + "id": "data_RAL", + "title": "Data for station RAL" + }, + { + "id": "data_RAN", + "title": "Data for station RAN" + }, + { + "id": "data_RES", + "title": "Data for station RES" + }, + { + "id": "data_RIK", + "title": "Data for station RIK" + }, + { + "id": "data_ROE", + "title": "Data for station ROE" + }, + { + "id": "data_RPB", + "title": "Data for station RPB" + }, + { + "id": "data_RVK", + "title": "Data for station RVK" + }, + { + "id": "data_SBA", + "title": "Data for station SBA" + }, + { + "id": "data_SBL", + "title": "Data for station SBL" + }, + { + "id": "data_SFS", + "title": "Data for station SFS" + }, + { + "id": "data_SHU", + "title": "Data for station SHU" + }, + { + "id": "data_SIT", + "title": "Data for station SIT" + }, + { + "id": "data_SJG", + "title": "Data for station SJG" + }, + { + "id": "data_SKT", + "title": "Data for station SKT" + }, + { + "id": "data_SMI", + "title": "Data for station SMI" + }, + { + "id": "data_SOD", + "title": "Data for station SOD" + }, + { + "id": "data_SOL", + "title": "Data for station SOL" + }, + { + "id": "data_SON", + "title": "Data for station SON" + }, + { + "id": "data_SOR", + "title": "Data for station SOR" + }, + { + "id": "data_SPG", + "title": "Data for station SPG" + }, + { + "id": "data_SPT", + "title": "Data for station SPT" + }, + { + "id": "data_STF", + "title": "Data for station STF" + }, + { + "id": "data_STJ", + "title": "Data for station STJ" + }, + { + "id": "data_SUA", + "title": "Data for station SUA" + }, + { + "id": "data_SUM", + "title": "Data for station SUM" + }, + { + "id": "data_SVS", + "title": "Data for station SVS" + }, + { + "id": "data_T03", + "title": "Data for station T03" + }, + { + "id": "data_T29", + "title": "Data for station T29" + }, + { + "id": "data_T31", + "title": "Data for station T31" + }, + { + "id": "data_T32", + "title": "Data for station T32" + }, + { + "id": "data_T33", + "title": "Data for station T33" + 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b/home_supermag/info/indices_swi.json new file mode 100755 index 0000000..b2340dd --- /dev/null +++ b/home_supermag/info/indices_swi.json @@ -0,0 +1,35 @@ +{ + "HAPI": "2.0", + "status": { + "code": 1200, + "message": "OK request successful" + }, + "modificationDate": "lastday", + "parameters": [ + { + "length": 24, + "name": "Time", + "type": "isotime", + "units": "UTC", + "fill": null + }, + {"name": "smr", "type": "double", "units": "nT", "fill": "999999.0"}, + {"name": "smrnum", "type": "double", "units": "nT", "fill": "999999.0"}, + {"name": "ltnum", "type": "double", "units": "nT", "size": [4], "fill": "999999.0"}, + {"name": "bgse", "type": "double", "units": "nT", "size": [3], "fill": "999999.0"}, + {"name": "bgsm", "type": "double", "units": "nT", "size": [3], "fill": "999999.0"}, + {"name": "vgse", "type": "double", "units": "nT", "size": [3], "fill": "999999.0"}, + {"name": "vgsm", "type": "double", "units": "nT", "size": [3], "fill": "999999.0"}, + {"name": "clockgse", "type": "double", "units": "degrees", "fill": "999999.0"}, + {"name": "clockgsm", "type": "double", "units": "degrees", "fill": "999999.0"}, + {"name": "density", "type": "double", "units": "mA/cm^2", "fill": "999999.0"}, + {"name": "pdyn", "type": "double", "units": "mA/cm^2", "fill": "999999.0"}, + {"name": "epsilon", "type": "double", "units": "GW", "fill": "999999.0"}, + {"name": "newell", "type": "double", "units": "Wb/s", "fill": "999999.0"} + ], + "startDate": "2018-01-01T00:00Z", + "stopDate": "lastday-P1D", + "sampleStartDate": "2018-01-18T00:00Z", + "sampleStopDate": "2018-01-19T00:00Z", + "cadence": "PT1M" +} diff --git a/home_supermag/info/stations.json b/home_supermag/info/stations.json new file mode 100755 index 0000000..d3231af --- /dev/null +++ b/home_supermag/info/stations.json @@ -0,0 +1,23 @@ +{ + "HAPI": "2.0", + "status": { + "code": 1200, + "message": "OK request successful" + }, + "parameters": [ + { + "length": 24, + "name": "Time", + "type": "isotime", + "fill": null, + "units": "UTC" + }, + {"name": "IAGA", "type": "string", "units": "TLA", "fill": null, "length": 3}, + {"name": "window_end", "type": "isotime", "units": "UTC", "fill": null} + ], + "startDate": "2018-01-01T00:00Z", + "stopDate": "lastday-P1D", + "sampleStartDate": "2018-01-18T00:00Z", + "sampleStopDate": "2018-01-19T00:00Z", + "cadence": "PT1M" +} diff --git a/supermag_api.py b/supermag_api.py new file mode 100644 index 0000000..174df74 --- /dev/null +++ b/supermag_api.py @@ -0,0 +1,575 @@ +import urllib.request + +# the 'certifi' library is required at APL and other sites that +# require SSL certs for web fetches. If you need this, install certifi +# (pip install certifi) +import importlib +certspec = importlib.util.find_spec("certifi") +found = certspec is not None +if found: import certifi + +import pandas as pd # dataframes and also to_datetime +import json +import re +import datetime + +globaldebug = True # False + +""" +;supermag-api.py +; ================ +; Author S. Antunes, based on supermag-api.pro by R.J.Barnes + + +; (c) 2021 The Johns Hopkins University Applied Physics Laboratory +;LLC. All Rights Reserved. + +;This material may be only be used, modified, or reproduced by or for +;the U.S. Government pursuant to the license rights granted under the +;clauses at DFARS 252.227-7013/7014 or FAR 52.227-14. For any other +;permission, +;please contact the Office of Technology Transfer at JHU/APL. + +; NO WARRANTY, NO LIABILITY. THIS MATERIAL IS PROVIDED "AS IS." +; JHU/APL MAKES NO REPRESENTATION OR WARRANTY WITH RESPECT TO THE +; PERFORMANCE OF THE MATERIALS, INCLUDING THEIR SAFETY, EFFECTIVENESS, +; OR COMMERCIAL VIABILITY, AND DISCLAIMS ALL WARRANTIES IN THE +; MATERIAL, WHETHER EXPRESS OR IMPLIED, INCLUDING (BUT NOT LIMITED TO) +; ANY AND ALL IMPLIED WARRANTIES OF PERFORMANCE, MERCHANTABILITY, +; FITNESS FOR A PARTICULAR PURPOSE, AND NON-INFRINGEMENT OF +; INTELLECTUAL PROPERTY OR OTHER THIRD PARTY RIGHTS. ANY USER OF THE +; MATERIAL ASSUMES THE ENTIRERISK AND LIABILITY FOR USING THE +; MATERIAL. IN NO EVENT SHALL JHU/APL BE LIABLE TO ANY USER OF THE +; MATERIAL FOR ANY ACTUAL, INDIRECT, CONSEQUENTIAL, SPECIAL OR OTHER +; DAMAGES ARISING FROM THE USE OF, OR INABILITY TO USE, THE MATERIAL, +; INCLUDING, BUT NOT LIMITED TO, ANY DAMAGES FOR LOST PROFITS. +""" +# Sample URLs, type into browser if you want to compare the data vs python +#https://supermag.jhuapl.edu/services/data-api.php?fmt=json&logon=YOURNAME&start=2019-10-15T10:40&extent=3600&all&station=NCK +#https://supermag.jhuapl.edu/services/indices.php?fmt=json&logon=YOURNAME&start=2019-10-15T10:40&extent=3600&all +#https://supermag.jhuapl.edu/services/inventory.php?fmt=json&logon=YOURNAME&start=2019-10-15T10:40&extent=3600 + + +def sm_coreurl(page,logon,start,extent): + # internal helper function + baseurl = "https://supermag.jhuapl.edu/" + + mytime = sm_parsestart(start) + urlstr = baseurl + 'services/'+page+'?python&nohead' + urlstr+='&start='+mytime + urlstr += '&logon='+logon + urlstr+='&extent='+ ("%12.12d" % extent) + + #print("debug:",urlstr) + + return(urlstr) + +# handy helper function when using complicated CVS encoding of lists +def sm_csvitem_to_list(myarr): + # converts entity of form ['HOP', 'NVS', 'IRT'] to an actual list of HOP, NVS, IRT + mylist=[] + for myline in myarr: + myline=re.sub("'","",myline[1:-1]) + mylist.append(myline.split(", ")) + return(mylist) + + +# handy helper function when using complicated CVS encoding of dicts +def sm_csvitem_to_dict(myarr,**kwargs): + # converts entity of form {'X': -12.213, 'Y': -5.5, 'Z': 1.2} to an actual dict of var.X, var.Y, etc + # items are presumed strings by default + # optional argument "convert=num" will convert them to doubles + mylist=[] + for myline in myarr: + myline2=re.sub(" ","",myline[1:-1]) # scrub out extra spaces + myline2=re.sub("'","",myline2) + elements = dict(x.split(":") for x in myline2.split(",")) + # little sanity check to make sure float subitems remain floats + try: elements = {item: float(value) for (item, value) in elements.items()} + except: pass + + #type(elements) + mylist.append(elements) + return(mylist) + +def sm_parsestart(start): + # internal helper function + # takes either list of [yyyy, mo, dd, hh, mm, opt_ss] + # or string of a normal datetime 'YYYY-MM-DD hh-mm' (optional ss) + # or the SuperMAG-ready 'YYYY-MM-DDThh-mm-ss' + + if isinstance(start,list): + timestring = "%4.4d-%2.2d-%2.2dT%2.2d:%2.2d" % tuple(start[0:5]) + elif isinstance(start,datetime.date): + # good to go, TBD + timestring=start.strftime("%Y-%m-%dT%H:%M") + else: + # is a string, reparse, TBD + timestring=start + + return(timestring) + + +def sm_DateToYMDHMS(tval,yr,mo,dy,hr,mt,sc): + # not used but here as an example of date conversion + julday=(tval/86400.0)+2440587.5 + datestr=pd.to_datetime(julday,unit='D',origin='julian') # format YYYY-MM-DD HH:MM:SS.ssssss + return(datestr) + +def sm_keycheck_data(flagstring): + # internal helper function + toggles=['mlt','mag','geo','decl','sza','delta=start','baseline=yearly','baseline=none'] + + myflags='' + if type(flagstring) is list: + flags=flagstring + else: + flags=[x.strip() for x in flagstring.split(',')] + + for i in range(0,len(flags)): + chk=flags[i] + chk=chk.lower() + # check for the '*all', also individual keys, and assemble url flags + if chk == 'all': myflags += '&mlt&mag&geo&decl&sza' + for ikey in range(0,len(toggles)): + if chk == toggles[ikey]: myflags += '&'+toggles[ikey] + + return(myflags) + + + +def sm_parcel_keys(flagstring): + # for allowed keys, places them as indices=, imf=, swi= + + imfkeys=["bgse","bgsm","vgse","vgsm"] + swikeys=["pdyn","epsilon","newell","clockgse","clockgsm","density"] + + myflags='' + indices='&indices=' + swi='&swi=' + imf='&imf=' + + if type(flagstring) is list: + flags=flagstring + else: + flags=[x.strip() for x in flagstring.split(',')] + + for ff in flags: + if ff in swikeys: + swi += ff+',' + elif ff in imfkeys: + imf += ff+',' + else: + # default is indices= + indices += ff+',' + + # clean it up a bit by removing extraneous tags/characters + if indices == "&indices=": indices="" + if swi == "&swi=": swi="" + if imf == "&imf=": imf="" + # add them together + myflags = indices + swi + imf + # a little more cleaning for tidiness, removes extraneous commas + myflags = re.sub(',&','&',myflags) + myflags = re.sub(',$','',myflags) + if globaldebug: print("debug: flags are ",myflags) + + return(myflags) + +## NEXT UP--- FIX THIS CHECK VIS A VIS THE ACTUAL PARAMETER FLAGS NEEDED +## VIA JSON AND MATRIX, OY +def sm_keycheck_indices(flagstring): + # internal helper function + # For category='indices', always returns: + # tval + # additional flags to return data include: + # indicesall (or its alias: all) + # (or any of) + # baseall, sunall, darkall, regionalall, plusall + # (or specify individual items to include, from the sets below) + # + print("Debug, flagstring is: ",flagstring) + basekeys=["sme","sml","smu","mlat","mlt","glat","glon","stid","num"] + # sunkeys: alias allowed of SUN___ -> ___s + sunkeys=["smes","smls","smus","mlats","mlts","glats","glons","stids","nums"] + # darkkeys: alias allowed of DARK___ -> ___d + darkkeys=["smed","smld","smud","mlatd","mltd","glatd","glond","stidd","num"] + # regkeys: alias allowed of REGIONAL___ -> ___r + regkeys=["smer","smlr","smur","mlatr","mltr","glatr","glonr","stidr","numr"] + pluskeys=["smr","ltsmr","ltnum","nsmr","smr00","smr06","smr12","smr18","smrnum","smrnum00","smrnum06","smrnum12","smrnum18"] + indiceskeys = basekeys + sunkeys + darkkeys + regkeys + pluskeys + # 'all' means all the above + + imfkeys=["bgse","bgsm","vgse","vgsm"] # or imfall for all these + swikeys=["pdyn","epsilon","newell","clockgse","clockgsm","density"] # % or swiall for all these + myflags='' + indices='&indices=' + swi='&swi=' + imf='&imf=' + + if type(flagstring) is list: + flags=flagstring + else: + flags=[x.strip() for x in flagstring.split(',')] + + for i in range(0,len(flags)): + chk=flags[i] + chk=chk.lower() + + # check for the '*all', also individual keys, and assemble url flags + if chk == 'all': indices += 'all,' + if chk == 'indicesall': indices += 'all,' + if chk == 'imfall': imf += 'all,' + if chk == 'swiall': swi += 'all,' + # available keywords, we allow both the url version and the + # aliases of "SUN___ -> ___s", "DARK___ -> ___d", "REGIONAL___ -> ___r" + + for ikey in range(0,len(indiceskeys)): + mykey=indiceskeys[ikey] + sunkey="sun"+mykey # allow alias + darkkey="dark"+mykey # allow alias + regkey1="regional"+mykey # allow alias + regkey2="reg"+mykey # allow alias + + if chk == mykey: + indices += mykey+',' # base key is correct + elif sunkey == mykey: + indices += mykey+'s,' # alias, so base key + 's' + elif darkkey == mykey: + indices += mykey+'d,' # alias, so base key + 'd' + elif regkey1 == mykey or regkey2 == mykey: + indices += mykey+'r,' # alias, so base key + 'r' + + for ikey in range(0,len(swikeys)): + if chk == swikeys[ikey]: swi += swikeys[ikey] + ',' + + for ikey in range(0,len(imfkeys)): + if chk == imfkeys[ikey]: imf += imfkeys[ikey] + ',' + + # more aliases to the user + if chk == 'baseall': indices += ','.join(basekeys) + if chk == 'sunall': indices += ','.join(sunkeys) + if chk == 'darkall': indices += ','.join(darkkeys) + if chk == 'regionalall' or chk == 'regall': indices += ','.join(regkeys) + if chk == 'plusall': indices += ','.join(pluskeys) + # clean it up a bit by removing extraneous tags/characters + if indices == "&indices=": indices="" + if swi == "&swi=": swi="" + if imf == "&imf=": imf="" + # add them together + myflags = indices + swi + imf + # a little more cleaning for tidiness, removes extraneous commas + myflags = re.sub(',&','&',myflags) + myflags = re.sub(',$','',myflags) + if globaldebug: print("debug: flags are ",myflags) + return(myflags) + +def sm_GetUrl(fetchurl,fetch='list'): + # internal helper function + # returned data choices are 'raw', 'list' or 'json', default is 'list' + # converts an http bytestream into a python list (list) + # or list of dict (json) or just return the raw webfetch (raw) + # 'stations' should be 'list' and returns a list + # 'data' should be 'json', returns a list (which converts to a dataframe) + # 'indices' should be 'json', returns a list (which converts to a dataframe) + + success = 0 # gets changed to 1 good data is fetched + longstring=b"ERROR: Unknown error" # prepare for the worst + + if globaldebug: print("debug: url trying ",fetch,"is",fetchurl) + # If the url object throws an error it will be caught here + try: + #with urllib.request.urlopen(fetchurl,cafile=certifi.where()) as response: + # note that 'cafile' is deprecated past python 3.5 but we keep it here + # to have stronger backward compatability with earlier versions + try: + cafile=certifi.where() + except: + cafile='' + with urllib.request.urlopen(fetchurl,cafile=cafile) as response: + longstring = response.read() + + if fetch == 'json': + if len(longstring) > 3: + #mydata = json.loads(longstring[3:]) # skipping initial OK + mydata = json.loads(longstring) + else: + mydata=[] # just the word 'OK', no data, so return no data + success=1 + elif fetch == 'raw': + # case of just returning the json object itself + mydata=longstring + else: + # default is list-- take byte string which we split into a list + mydata = (longstring.decode('UTF-8')).split('\n') + success = 1 # it worked + if re.search(r'ERROR',mydata[0]): success=0 # legit return, but of an err + + except urllib.error.URLError as e: + #print, !ERROR_STATE.msg + mydata=['ERROR:HTTP error',e.reason] + except: + longstring = longstring.decode('UTF-8') + mydata=[longstring] # catch-all if nothing below works + + #print("debug: function return type is:",type(mydata),".") + # returns a list for 'list' or a list of dictionaries for 'json' + return(success,mydata) + + +# Gets a list of stations. +# Return value is either '1' plus list of stations, or +# '0' plus a string with the error message +# Sample usage: +# 'extent' is how long a window, in seconds, to grab. (86400 sec = 1 day) +# (status, stations) =supermaggetinventory('myname',2019,11,2,20,24,00,86400) +# In this case, 'status'=1 and 'stations' is a list of 184 stations + +def supermag_getinventory(logon,start,extent): + # One of the core 3 functions + + iarr="" + errstr="" + + # construct URL + urlstr = sm_coreurl('inventory.php',logon,start,extent) + + # get the string array of stations + (success,stations)=sm_GetUrl(urlstr,'list') + + # if the inventory is valid extract the stations to an array + # if an error occurs set the the ERROR keyword to be the error string + + if success: + # first data item is how many stations were found + numstations = int(stations[0]) + #print("debug: found",numstations,"stations") + if numstations > 0: stations=stations[1:-1] # remove OK,#stations,'' + else: stations=[] # empty list because no stations found + #print('debug, got back:',stations) + # success: return true (1) if the call was successful otherwise false (0) + # stations: return list with true/1 plus data, or false/0 plus errstr + return(success,stations) + + +def supermag_getindices(logon,start,extent,flagstring='',**kwargs): + # One of the core 3 functions + # usual return is 'json' aka pandas frame, but also can just return raw fetch + typecode = kwargs.get('FORMAT','json').lower() + + urlstr = sm_coreurl('indices.php',logon,start,extent) + #indices = sm_keycheck_indices(flagstring) + indices = sm_parcel_keys(flagstring) + urlstr += indices + + # get the string array of JSON data + (status,data_list)=sm_GetUrl(urlstr,typecode) + + # default is to return a dataframe, but can also return an array + # or even the raw server data + if typecode == 'list' or typecode == 'raw': + return(status,data_list) + else: + # default, converts the json 'list of dictionaries' into a dataframe + data_df = pd.DataFrame(data_list) + return(status,data_df) + +def supermag_getdata(logon,start,extent,flagstring,stationlist,**kwargs): + # One of the core 3 functions + + # optional options for 'data': + # ALL=&mlt&mag&geo&decl&sza + # MLT=&mlt,MAG=&mag,GEO=&geo,DECL=&decl,SZA=&sza, + # DELTA='start',BASELINE='none/yearly' + # e.g. can pass MLT=1,MAG=1 and they will be evaluated. Full set checked: ALL, MLT, MAG, GEO, DECL, SZA, also values for DELTA, BASELINE + # also arg FORMAT='list', otherwise defaults to FORMAT='json' + + # default FORMAT='json' aka dataframe, alt is FORMAT='list' or 'raw' + # can accept either a single station or multiples + + if type(stationlist) is not list: + # single item + (status,data)=sm_supermag_getdata_single(logon,start,extent,flagstring,stationlist,**kwargs) + else: + # multiple stations, append into larger dataframe + frames=[] + status=0 + for station in stationlist: + (tstatus,tdata)=sm_supermag_getdata_single(logon,start,extent,flagstring,station,**kwargs) + frames.append(tdata) + status += tstatus + # done them all so aggregate + data = pd.concat(frames) + + return(status,data) + +def sm_supermag_getdata_single(logon,start,extent,flagstring,station,**kwargs): + + typecode = kwargs.get('FORMAT','json').lower() + urlstr = sm_coreurl('data-api.php',logon,start,extent) + #print("debug: flagstring pre-check is ",flagstring) + indices = sm_keycheck_data(flagstring) + #print("debug: flagstring post-check is ",flagstring) + urlstr += indices + urlstr += '&' + flagstring + urlstr += '&station='+station.upper() + + (status,data_list)=sm_GetUrl(urlstr,typecode) + + # default is to return a dataframe, but can also return an array + if typecode == 'list' or typecode == 'raw': + return(status,data_list) + else: + # default, converts the json 'list of dictionaries' into a dataframe + data_df = pd.DataFrame(data_list) + return(status,data_df) + +def sm_grabme(dataf,key,subkey): + # syntactical sugar to grab nested subitems from a dataframe + data = dataf[key] + subdata = [temp[subkey] for temp in data] + return(subdata) + +# Unlike IDL, which returns as Array or Struct, +# we return as List (of dictionaries) or DataFrame + +def sm_microtest(choice,userid): + # 3 simple unit tests to verify the core fetches work + import matplotlib.pyplot as plt + + start=[2019,11,15,10,40,00] # alt: start='2019-11-15T10:40' + + if choice == 1 or choice == 4: + (status,stations) = supermag_getinventory(userid,start,3600) + print(status) + print(stations) + + if choice == 2 or choice == 4: + (status,data) = supermag_getdata(userid,start,3600,'all,delta=start,baseline=yearly','HBK') + print(status) + print(data) + print(data.keys()) + + tval=data.tval + mlt=data.mlt + ### Python way + N_nez = [temp['nez'] for temp in data.N] + N_geo = [temp['geo'] for temp in data.N] + ### or, supermag helper shorthand way + N_nez = sm_grabme(data,'N','nez') + N_geo = sm_grabme(data,'N','geo') + # + plt.plot(tval,N_nez) + plt.plot(tval,N_geo) + plt.ylabel('N_geo vs N_nez') + plt.xlabel('date') + plt.show() + + if choice == 3 or choice == 4: + (status,idxdata) = supermag_getindices(userid,start,3600,'swiall,density,darkall,regall,smes') + #print(status) + #print(idxdata) + idxdata.keys() + tval=idxdata.tval + hours=list(range(24)) + y=idxdata.SMLr + for i in range(len(tval)-1): + plt.plot( hours, y[i] ) + plt.ylabel('SMLr') + plt.xlabel('hour') + plt.title('SMLr variation by hour, for successive days') + plt.show() + +def supermag_testing(userid): + + start=[2019,11,15,10,40,00] # alt: start='2019-11-15T10:40' + + (status,stations) = supermag_getinventory(userid,start,3600) + + + # DATA fetches + # BARE CALL, dataframe returned + (status,mydata1a) = supermag_getdata(userid,start,3600,'','HBK') + mydata1a # is 1440 rows x 6 columns dataframe + mydata1a.keys() # Index(['tval', 'ext', 'iaga', 'N', 'E', 'Z'], dtype='object') + + # CALL with ALLINDICES, dataframe returned + (status,mydata1a) = supermag_getdata(userid,start,3600,'all','HBK') + mydata1a # is 1440 rows x 12 columns dataframe + mydata1a.keys() # Index(['tval', 'ext', 'iaga', 'glon', 'glat', 'mlt', 'mcolat', 'decl', 'sza', 'N', 'E', 'Z'], dtype='object') + + # BARE CALL, list returned + (status,mydata1b) = supermag_getdata(userid,start,3600,'','HBK',FORMAT='list') + len(mydata1b) # is 1440 rows of dicts (key-value pairs) + mydata1b[0:1] # {'tval': 1572726240.0, 'ext': 60.0, 'iaga': 'DOB', 'N': {'nez': -3.942651, 'geo': -5.964826}, 'E': {'nez': 4.492887, 'geo': 0.389075}, 'Z': {'nez': 7.608168, 'geo': 7.608168}} + + # CALL with ALLINDICES, list returned + (status,mydata1b) = supermag_getdata(userid,start,3600,'all','HBK',FORMAT='list') + mydata1b # is 1440 rows of dicts (key-value pairs) + mydata1b[0:1] # {'tval': 1572726240.0, 'ext': 60.0, 'iaga': 'DOB', 'glon': 9.11, 'glat': 62.07, 'mlt': 21.694675, 'mcolat': 30.361519, 'decl': 3.067929, 'sza': 124.698227, 'N': {'nez': -3.942651, 'geo': -5.964826}, 'E': {'nez': 4.492887, 'geo': 0.389075}, 'Z': {'nez': 7.608168, 'geo': 7.608168}} + + #################### + # INDICES fetches + (status,idxdata) = supermag_getindices(userid,start,3600) + idxdata # empty! + + (status,idxdata) = supermag_getindices(userid,start,3600,'all,swiall,imfall') + idxdata # 1440 rows x 77 columns dataframe + idxdata.keys() # Index(['tval', 'SME', 'SML', 'SMLmlat', 'SMLmlt', 'SMLglat', 'SMLglon', 'SMLstid', 'SMU', 'SMUmlat', 'SMUmlt', 'SMUglat', 'SMUglon', 'SMUstid', 'SMEnum', 'SMEs', 'SMLs', 'SMLsmlat', 'SMLsmlt', 'SMLsglat', 'SMLsglon', 'SMLsstid', 'SMUs', 'SMUsmlat', 'SMUsmlt', 'SMUsglat', 'SMUsglon', 'SMUsstid', 'SMEsnum', 'SMEd', 'SMLd', 'SMLdmlat', 'SMLdmlt', 'SMLdglat', 'SMLdglon', 'SMLdstid', 'SMUd', 'SMUdmlat', 'SMUdmlt', 'SMUdglat', 'SMUdglon', 'SMUdstid', 'SMEdnum', 'SMEr', 'SMLr', 'SMLrmlat', 'SMLrmlt', 'SMLrglat', 'SMLrglon', 'SMLrstid', 'SMUr', 'SMUrmlat', 'SMUrmlt', 'SMUrglat', 'SMUrglon', 'SMUrstid', 'SMErnum', 'smr', 'smr00', 'smr06', 'smr12', 'smr18', 'smrnum', 'smrnum00', 'smrnum06', 'smrnum12', 'smrnum18', 'bgse', 'bgsm', 'vgse', 'vgsm', 'clockgse', 'clockgsm', 'density', 'dynpres', 'epsilon', 'newell'], dtype='object') + # + # just INDICESALL = 67 columns, above 'tval' through 'smrnum18' + # just IMFALL = 5 columns, Index(['tval', 'bgse', 'bgsm', 'vgse', 'vgsm'], dtype='object') + # just SWIALL = 7 columns, Index(['tval', 'clockgse', 'clockgsm', 'density', 'dynpres', 'epsilon', 'newell'], dtype='object') + # + # Dataframes are awesome! To manipulate, just pull out what you need + import pandas as pd # call once at the top of your code if you are using dataframes + tval = idxdata.tval + density = idxdata.density + vgse = idxdata.vgse + # or all as 1 line of code + tval, density, vgse = idxdata.tval, idxdata.density, idxdata.vgse + # note that vgse is itself a dictionary of values for X/Y/Z, so you can get subitems from it like this + vgse_x = [d.get('X') for d in idxdata.vgse] + + # to save the data, there are many formats. Here is how to save as csv + idxdata.to_csv('mydata.csv') + + # to read it back in later + import pandas as pd + import re + mydata2b=pd.read_csv('mydata.csv',index_col=0) # you can read it into any variable name, we just used 'mydata2b' as an example + # now you can do all the above items again, with one exception: each line of the CVS file got split into a dict (key-value pairs) but items like 'vsge' are part of the pandas structure + # the 'd.get()' approach will _not_ work once read from csv + stationlist = mydata2b.SMLrstid # item is a pandas series (not python list) + print(stationlist[0]) # prints a list of stations as a string, but cannot easily access a single item because it is a pandas series + # so you can convert a pandas series to a list + stationlist2=sm_csvitem_to_list(mydata2b.SMLrstid) # goal is a list of stations + slist = stationlist2[0] # grabs a list of stations for row 0 + s1 = stationlist2[0][0] # grabs the first station for row 0 + + vgse=sm_csvitem_to_dict(mydata2b.vgse) # goal is a dict of coords or other values + x = vgse[0]['X'] # grab just the 'X' value for the 1st row of data + vgse_x = [mydat['X'] for mydat in vgse] # grab all the 'X' values as a new list + vgse_xyz = [(mydat['X'],mydat['Y'],mydat['Z']) for mydat in vgse] # grab all 3 + + # We also offer a list format, for users who prefer to work in python lists + (status,mydata2c) = supermag_getindices(userid,start,3600,'all,swiall,imfall',FORMAT='list') + len(mydata2c) # is 1440 rows of dicts (key-value pairs) + mydata2c[0:1] # {'tval': 1572726240.0, 'SME': 58.887299, 'SML': -27.709055, 'SMLmlat': 73.529922, 'SMLmlt': 23.321493, 'SMLglat': 76.510002, 'SMLglon': 25.01, 'SMLstid': 'HOP', 'SMU': 31.178246, 'SMUmlat': 74.702339, 'SMUmlt': 2.090216, 'SMUglat': 79.480003, 'SMUglon': 76.980003, 'SMUstid': 'VIZ', 'SMEnum': 118, 'SMEs': 34.451469, 'SMLs': -16.599854, 'SMLsmlat': 62.368008, 'SMLsmlt': 9.399416, 'SMLsglat': 62.299999, 'SMLsglon': 209.800003, 'SMLsstid': 'T39', 'SMUs': 17.851616, 'SMUsmlat': 73.989975, 'SMUsmlt': 18.228394, 'SMUsglat': 67.93, 'SMUsglon': 306.429993, 'SMUsstid': 'ATU', 'SMEsnum': 54, 'SMEd': 58.887299, 'SMLd': -27.709055, 'SMLdmlat': 73.529922, 'SMLdmlt': 23.321493, 'SMLdglat': 76.510002, 'SMLdglon': 25.01, 'SMLdstid': 'HOP', 'SMUd': 31.178246, 'SMUdmlat': 74.702339, 'SMUdmlt': 2.090216, 'SMUdglat': 79.480003, 'SMUdglon': 76.980003, 'SMUdstid': 'VIZ', 'SMEdnum': 64, 'SMEr': [29.685059, 29.857538, 31.387127, 41.707573, 10.320444, 10.885443, 9.604616, 13.479583, 15.471248, 15.471248, 15.714731, 5.434914, 12.13654, 11.156847, 9.62884, 14.752592, 14.752592, 24.204388, 21.41181, 21.41181, 27.121195, 46.345322, 51.403328, 51.403328], 'SMLr': [-27.709055, 1.320708, -0.208882, -10.529325, -10.529325, -10.529325, -9.248499, -13.123466, -16.599854, -16.599854, -16.599854, -5.449972, -5.449972, -4.470279, -2.942272, -6.352773, -6.352773, -6.352773, -3.560194, -3.560194, -7.514064, -22.651047, -27.709055, -27.709055], 'SMLrmlat': [73.529922, 51.264774, 47.791527, 66.696564, 66.696564, 66.696564, 41.771515, 70.602707, 62.368008, 62.368008, 62.368008, 67.471809, 67.471809, 60.639145, 68.500282, 72.20977, 72.20977, 72.20977, 75.762718, 75.762718, 77.33667, 71.889503, 73.529922, 73.529922], 'SMLrmlt': [23.321493, 2.119074, 3.578985, 4.929673, 4.929673, 4.929673, 5.414416, 8.57761, 9.399416, 9.399416, 9.399416, 11.35623, 11.35623, 12.266475, 13.977451, 16.720993, 16.720993, 16.720993, 19.65963, 19.65963, 21.307804, 22.863134, 23.321493, 23.321493], 'SMLrglat': [76.510002, 55.029999, 52.169998, 71.580002, 71.580002, 71.580002, 47.799999, 71.300003, 62.299999, 62.299999, 62.299999, 61.756001, 61.756001, 53.351002, 58.763, 63.75, 63.75, 63.75, 72.300003, 72.300003, 76.769997, 74.5, 76.510002, 76.510002], 'SMLrglon': [25.01, 82.900002, 104.449997, 129.0, 129.0, 129.0, 132.414001, 203.25, 209.800003, 209.800003, 209.800003, 238.770004, 238.770004, 247.026001, 265.920013, 291.480011, 291.480011, 291.480011, 321.700012, 321.700012, 341.369995, 19.200001, 25.01, 25.01], 'SMLrstid': ['HOP', 'NVS', 'IRT', 'TIK', 'TIK', 'TIK', 'BRN', 'BRW', 'T39', 'T39', 'T39', 'FSP', 'FSP', 'C06', 'FCC', 'IQA', 'IQA', 'IQA', 'SUM', 'SUM', 'DMH', 'BJN', 'HOP', 'HOP'], 'SMUr': [1.976003, 31.178246, 31.178246, 31.178246, -0.208882, 0.356117, 0.356117, 0.356117, -1.128606, -1.128606, -0.885122, -0.015059, 6.686568, 6.686568, 6.686568, 8.399819, 8.399819, 17.851616, 17.851616, 17.851616, 19.60713, 23.694275, 23.694275, 23.694275], 'SMUrmlat': [52.904049, 74.702339, 74.702339, 74.702339, 47.791527, 54.29908, 54.29908, 54.29908, 66.244217, 66.244217, 57.76614, 54.597057, 55.715378, 55.715378, 55.715378, 57.829525, 57.829525, 73.989975, 73.989975, 73.989975, 70.473801, 68.194489, 68.194489, 68.194489], 'SMUrmlt': [0.510692, 2.090216, 2.090216, 2.090216, 3.578985, 6.394085, 6.394085, 6.394085, 9.99274, 9.99274, 11.729218, 12.269058, 13.969843, 13.969843, 13.969843, 16.160952, 16.160952, 18.228394, 18.228394, 18.228394, 21.200783, 22.967857, 22.967857, 22.967857], 'SMUrglat': [56.432999, 79.480003, 79.480003, 79.480003, 52.169998, 59.970001, 59.970001, 59.970001, 64.047997, 64.047997, 51.882999, 47.664001, 45.870998, 45.870998, 45.870998, 48.650002, 48.650002, 67.93, 67.93, 67.93, 70.900002, 71.089996, 71.089996, 71.089996], 'SMUrglon': [58.567001, 76.980003, 76.980003, 76.980003, 104.449997, 150.860001, 150.860001, 150.860001, 220.889999, 220.889999, 239.973999, 245.791, 264.916992, 264.916992, 264.916992, 287.549988, 287.549988, 306.429993, 306.429993, 306.429993, 351.299988, 25.790001, 25.790001, 25.790001], 'SMUrstid': ['ARS', 'VIZ', 'VIZ', 'VIZ', 'IRT', 'MGD', 'MGD', 'MGD', 'DAW', 'DAW', 'C13', 'C10', 'C08', 'C08', 'C08', 'T50', 'T50', 'ATU', 'ATU', 'ATU', 'JAN', 'NOR', 'NOR', 'NOR'], 'SMErnum': [5, 3, 3, 4, 5, 6, 6, 4, 8, 9, 12, 13, 20, 17, 17, 11, 12, 14, 12, 14, 22, 51, 51, 35], 'smr': 0.252399, 'smr00': -0.531382, 'smr06': 0.885406, 'smr12': 1.051192, 'smr18': -0.395618, 'smrnum': 72, 'smrnum00': 26, 'smrnum06': 23, 'smrnum12': 6, 'smrnum18': 17, 'bgse': {'X': 1.07, 'Y': -3.75, 'Z': -0.74}, 'bgsm': {'X': 1.07, 'Y': -3.82, 'Z': -0.06}, 'vgse': {'X': -351.100006, 'Y': -5.5, 'Z': -4.0}, 'vgsm': {'X': 351.100006, 'Y': 6.128625, 'Z': -2.947879}, 'clockgse': 258.340698, 'clockgsm': 268.664337, 'density': 5.03, 'dynpres': 1.25, 'epsilon': 29.468521, 'newell': 2504.155029} + # sample accessing + print(mydata2c[0]['tval'],mydata2c[0]['density']) # single element + result=[ (myeach['tval'],myeach['density']) for myeach in mydata2c] # pull out pairs e.g. 'tval, density') + # two-line method for extracting any variable set from this + pairsets= [ (myeach['tval'],myeach['density'],myeach['vgse']) for myeach in mydata2c] # same, pull out pairs, only assign e.g. x=tval, y=density + tval, density, vgse = [ [z[i] for z in pairsets] for i in (0,1,2)] + # since 'vgse' is itself an dict of 3 values X/Y/Z, you can pull out nested items like this + pairsets= [ (myeach['tval'],myeach['density'],myeach['vgse']['X']) for myeach in mydata2c] # same, pull out pairs, only assign e.g. x=tval, y=density + tval, density, vgse_x = [ [z[i] for z in pairsets] for i in (0,1,2)] + # the above methods are extensible to any number of variables, just update the (0,1,2) to reflect now many you have + + +# Uncomment to run quick sample tests +# userid=YOUR_SUPERMAG_USER_ID +#sm_microtest(1,userid) # sample stations fetch +#sm_microtest(2,userid) # sample data fetch, with plotting +#sm_microtest(3,userid) # sample indices fetch, with plotting diff --git a/supermag_config.py b/supermag_config.py new file mode 100644 index 0000000..faa5fb8 --- /dev/null +++ b/supermag_config.py @@ -0,0 +1,23 @@ +""" supermag_config.py, specific config file for SuperMAG web pass-thru + + Part of the HAPI Python Server. The code and documentation resides at: + + https://github.com/hapi-server/server-python + + See accompanying 'superhapi.py' file for the pass-thru reader. + +""" + +from supermag_api import * # APL library as distributed by SuperMAG +from supermag_hapireader import * # APL includes 'do_data_supermag' +api_datatype = 'web' # added here in case I later add files too +floc={} +HAPI_HOME= 'home_supermag/' +hapi_handler = do_data_supermag +tags_allowed = ['delta=default','delta=start','baseline=yearly','baseline=none','baseline=default'] # allowed subparams +loaded_config = True # required, used to verify config variables exists on load +# Currently SuperMAG can't stream because it is a web pass-thru +stream_flag=False +# In theory, could stream by figuring out maximum interval SuperMAG website +# allows, then loop over that and stream each chunk. But this would require +# discussion/permission from SuperMAG since their limits are for a reason. diff --git a/supermag_hapireader.py b/supermag_hapireader.py new file mode 100644 index 0000000..512dbc4 --- /dev/null +++ b/supermag_hapireader.py @@ -0,0 +1,632 @@ +""" superhapi.py, web pass-thru reader for SuperMAG + + Part of the HAPI Python Server. The code and documentation resides at: + + https://github.com/hapi-server/server-python + + See accompanying 'supermag_config.py' file for the site-specific details. + + +""" + +# hapi supermag test routines (and general python testing) + +#import netCDF4 as nc +#import numpy as np +#import pandas as pd +import xarray as xr +import pandas as pd +import time +import os +# +import urllib.request +import certifi # needed at APL for SSL +from pandas import to_datetime # used for julian date, actually +import json +import re +#from datetime import datetime, timedelta +import datetime + +from supermag_api import * + +#https://supermag.jhuapl.edu/services/data-api.php?fmt=json&logon=antunes&start=2019-10-15T10:40&extent=000000003600&station=HRN&mlt&aacgm&geo&decl&sza #https://supermag.jhuapl.edu/services/data-api.php?fmt=json&logon=antunes&start=2019-10-15T10:40&extent=000000003600&station=NCK&mlt&aacgm&geo&decl&sza + +def sm_filter_data(magdata, parameters): + # Handles wonky SuperMAG data_NNN API keys + # because all queries return ext, iaga, and the NEZ set + allparams = ['ext','iaga','N','E','Z'] + dropme = [] + for para in allparams: + if para not in parameters: + dropme.append(para) + #print("Debug, magdata pre-delete is ",magdata) + #print("Debug, desired parameters are ",parameters) + #print("Debug, deleting: ",dropme) + if dropme != None: + magdata=magdata.drop(columns=dropme,errors='ignore') + #print("Debug, magdata after delete is ",magdata) + + return(magdata) + + +def sm_lookup(parameters): + # converts HAPI 'parameters' into keywords expected by API call + # for data that requires 2 API keywords, gives them here + clean_out_later=[] # for storing 'excess' data items temp needed + #parameters = [x.lower() for x in parameters] + x_apikeys = {'SMLmlat':['sml','mlat'], + 'SMLmlt':['sml','mlt'], + 'SMLglon':['sml','glon'], + 'SMLstid':['sml','stid'], + 'SMLglat':['sml','glat'], + 'SMLstid':['sml','stid'], + 'SMUmlat':['smu','mlat'], + 'SMUmlt':['smu','mlt'], + 'SMUglon':['smu','glon'], + 'SMUstid':['smu','stid'], + 'SMUglat':['smu','glat'], + 'SMUstid':['smu','stid'], + + 'SMLsmlat':['smls','mlats'], + 'SMLsmlt':['smls','mlts'], + 'SMLsglon':['smls','glons'], + 'SMLsstid':['smls','stids'], + 'SMLsglat':['smls','glats'], + 'SMLsstid':['smls','stids'], + 'SMUsmlat':['smus','mlats'], + 'SMUsmlt':['smus','mlts'], + 'SMUsglon':['smus','glons'], + 'SMUsstid':['smus','stids'], + 'SMUsglat':['smus','glats'], + 'SMUsstid':['smus','stids'], + + 'SMLdmlat':['smld','mlatd'], + 'SMLdmlt':['smld','mltd'], + 'SMLdglon':['smld','glond'], + 'SMLdstid':['smld','stidd'], + 'SMLdglat':['smld','glatd'], + 'SMLdstid':['smld','stidd'], + 'SMUdmlat':['smud','mlatd'], + 'SMUdmlt':['smud','mltd'], + 'SMUdglon':['smud','glond'], + 'SMUdstid':['smud','stidd'], + 'SMUdglat':['smud','glatd'], + 'SMUdstid':['smud','stidd'], + + 'SMLrmlat':['smlr','mlatd'], + 'SMLrmlt':['smlr','mltd'], + 'SMLrglon':['smlr','glonr'], + 'SMLrstid':['smlr','stidr'], + 'SMLrglat':['smlr','glatr'], + 'SMLrstid':['smlr','stidr'], + 'SMUrmlat':['smur','mlatr'], + 'SMUrmlt':['smur','mltr'], + 'SMUrglon':['smur','glonr'], + 'SMUrstid':['smur','stidr'], + 'SMUrglat':['smur','glatr'], + 'SMUrstid':['smur','stidr'] + } + + # note that we need to send msl, smu, sme in lowercase to supermag, + # but the data they return is uppercase, so when we later filter + # them out, we need the awkward .upper() casting below + + # Edge case, asking just for 'Time' or 'Time'+ other stuff, when + # time is _always_ returned anyway + if len(parameters) == 1 and parameters[0] == 'Time': + parameters[0]='sme' # replace Time with a junk data so data is fetched + clean_out_later.append('SME') # and mark that junk data later + + # general clean-up + try: + parameters.remove('Time') + except: + pass + + for para in parameters: + if para in x_apikeys.keys(): + # replace it + #print("debug, replacing: ",para) + parameters.remove(para) + for element in x_apikeys[para]: + # remember to check if spurious exists, before adding in + #print("debug, checking on ",element) + # See above note on why .upper() is here + if element.upper() not in parameters: + clean_out_later.append(element.upper()) + parameters.append(element) + + #print("debug: para: ",parameters) + + # and again, have to cast to lower because api expects that + parameters = [x.lower() for x in parameters] + + return(parameters, clean_out_later) + + +def sm_fill_empty(magdata,parameters,paramspec): + # validate, fill if necessary + # Although designed for SuperMAG, works well for any DataFrame data + # + # Note only can fill up to 1D lists (not built for 2D+ empty elements yet) + # 'parameters' is the subset of data items we are using + # 'paramspec' is the array potentially containing size and fill info + # goes through each parameter, calls up paramspec['size'], + # if data does not match, then puts in paramspec['fill'] + # Also, we search case-insensitive for param matches, to be more robust. + + nele = magdata.shape[0] + for para in parameters: + #print("debug, para: ",para," and columns: ",magdata.columns, "and paramspec:",paramspec) + if para.lower() not in magdata.columns.str.lower(): + try: + details=[item for item in paramspec if item['name'].lower() == para.lower()][0] + #print("debug, param specs are: ",details) + except: + pass # no match, usually due to case-sensitivity + try: + mysize = details['size'][0] + except: + #print("debug, could not find size, using default") + mysize=1 + try: + myfill = details['fill'] + except: + #print("debug, could not find fill, using default") + myfill=0 + # cast to type since HAPI catalog uses strings for fills + try: + mytype = details['type'] + if mytype == 'double': myfill=float(myfill) + if mytype == 'integer': myfill=int(myfill) + except: + pass + #print("Debug-- missing data for ",para, "Got size ",mysize,", fill ",myfill) + if mysize > 1: + element = [myfill] * mysize + else: + element = myfill + dummy = [element] * nele + magdata[para] = dummy + #n1=len(parameters) + #n2 = magdata.shape[1] - 1 # remove Time and count + #for i in range(n2,n1): # only fills if n1>n2 + # print("debug: paramspec:",paramspec) + # dummy=[0] * nele + # magdata[parameters[i-n1]] = dummy + # print("Debug: adding col ",i,parameters[i-n1]) + # #print("Debug: sizes compare:",n1,' vs ',n2) + + +def test_polar(): + (yyyy,mo,dd,hh,mm,ss)=(2020,11,2,13,24,00) + (status,mydata)=serve_polar_df(yyyy,mo,dd,hh,mm) + if status > 0: print("Success",mydata) + else: print("Failed",mydata) + return(status,mydata) + +def samplerun_testtiming(): + + base=time.time() + + filename='hapi_sample.ncdf' + mydata = xr.open_dataset(filename) # get in as an xarray + print(time.time()-base,'sec to open') + base=time.time() + + minute, hour = 10, 20 + sub_d=mydata.sel(block=(hour*60)+minute) + #my_df = data.to_dataframe().reset_index() # if you need all the data + ##minute, hour = 1, 1 + # data files are for 1 day, so this lets you grab any given minute + ##sub_d=mydata.where( (mydata.time_mt == minute) & (mydata.time_hr == hour),drop=True) + print(time.time()-base,'sec to subselect 1st frame') + base=time.time() + + my_df=sub_d.to_dataframe().reset_index() + print(time.time()-base,'sec to convert to dataframe') + base=time.time() + + my_df.vector=maketimestamp_df(my_df) + my_df.drop(columns=['id']) # not needed, might confuse users + print(time.time()-base,'sec to make timestamps and drop 2 columns') + base=time.time() + + stringize_df(my_df) # prep it for csv-ing + print(time.time()-base,'sec to stringize for csv-ing') + base=time.time() + my_df.apply(csvme2screen,axis=1) # apply function to each row + print(time.time()-base,'sec to convert to csv') + base=time.time() + + #my_df = data.to_dataframe().reset_index() # if you need all the data + minute, hour = 2, 4 + sub_d2=mydata.where( (mydata.time_mt == minute) & (mydata.time_hr == hour),drop=True) + print(time.time()-base,'sec to subselect 2nd frame') + base=time.time() + my_df=sub_d2.to_dataframe().reset_index() + print(time.time()-base,'sec to convert to dataframe') + base=time.time() + + + +""" +from Robin 4/1 tagup: +SuperMAG polar plots aka level 3 derived data, take their netCDF files +and set up as a HAPI server, data is every 2 minutes and there are two +kinds of grids, the mlt map grid aka 1 hour of mlt is 5 degrees of +measured latitude so each point is a vector with north/vertical/mumble. +note level 1 data is gappy so not good to use, stations drop in and out +etc, so it requires finesse to see if data is available. use weatherwax +machine as it has the disks mounted on it, or go to SOF to get them to +mount. Port 9000 fine for local testing but we will have to work with +network once we go for real. current supermag is just curl request +using wget. they also have an idl client. +""" + +# Fast Access code: +#filename='hapi_sample.ncdf' +#mydata = xr.open_dataset(filename) +#subme=mydata.sel(block=100) +# next line 24 sec if 1st operation; <1 sec otherwise +#sub_d=mydata.where( (mydata.time_mt == 1) & (mydata.time_hr == 1),drop=True) +# next line 90 sec, if 1st operation; <1 sec otherwise +#full_df=mydata.to_dataframe() + +def sm_to_hapitimes(mytime): + mytime=time.strftime('%Y-%m-%dT%H:%MZ',time.gmtime(mytime)) + return(mytime) + +def unwind_csv_array(magdata): + """ Takes json-like arrays of e.g. + 60.0,DOB,"[ -19.104668,-20.155156]" + or + 60.0,DOB,[ -19.104668,-20.155156] + and converts to unwound HAPI version of e.g. + 60.0,DOB,-19.104668,-20.155156 + """ + + magdata = re.sub(r'\]\"','',magdata) + magdata = re.sub(r'\"\[','',magdata) + magdata = re.sub(r', ',',',magdata) # also remove extra spaces + return(magdata) + +def csv_removekeys(magdata): + # use: magdata = api_removekeys(magdata) + # changes {k:v,k:v} to just [v,v] + magdata = re.sub(r'\'\w+\':','',magdata) + magdata = re.sub(r'\{','[',magdata) + magdata = re.sub(r'\}',']',magdata) + magdata = re.sub(r' ',' ',magdata) + magdata = re.sub(r', ',',',magdata) + # also remove extraneous end commas from some parsings + magdata = re.sub(r',\n','\n',magdata) + + return(magdata) + +# TIMESTAMPING WORKS! +def maketimestamp_str(yr,mo,dy,hr,mt,sc): + mytime = "%4.4d%2.2d%2.2d%2.2d%2.2d%2d" % (yr, mo, dy, hr, mt, sc) + return(mytime) + +def maketimestamp_df(data_df): + timestamps = data_df.time_yr.apply(lambda x: "%4.4d" % x) + data_df.time_mo.apply(lambda x: "%2.2d" % x) + data_df.time_dy.apply(lambda x: "%2.2d" % x) + data_df.time_hr.apply(lambda x: "%2.2d" % x) + data_df.time_mt.apply(lambda x: "%2.2d" % x) + data_df.time_sc.apply(lambda x: "%2.2d" % x) + return(timestamps) + + +def csv_me_polar(row,printme=1): + me = '\"' + row['vector'] + '\",\"' + row['mlat'] + '\",\"' + row['mlon'] + '\",\"' + row['mcolat'] + '\",\"' + row['mlt'] + '\",\"' + row['dbn_nez'] + '\",\"' + row['dbe_nez'] + '\",\"' + row['dbz_nez'] + '\",\"' + row['dbn_geo'] + '\",\"' + row['dbe_geo'] + '\",\"' + row['dbz_geo'] + '\"' + if printme == 0: print(me) + return(me) + +def stringize_df(data_df): + # since data_df is a dataframe, this will permanently change it + data_df.mlat = data_df.mlat.apply(str) + data_df.mlon = data_df.mlon.apply(str) + data_df.mcolat = data_df.mcolat.apply(str) + data_df.mlt = data_df.mlt.apply(str) + data_df.dbn_nez = data_df.dbn_nez.apply(str) + data_df.dbe_nez = data_df.dbe_nez.apply(str) + data_df.dbz_nez = data_df.dbz_nez.apply(str) + data_df.dbn_geo = data_df.dbn_geo.apply(str) + data_df.dbe_geo = data_df.dbe_geo.apply(str) + data_df.dbz_geo = data_df.dbz_geo.apply(str) + + +def make_polarname(yyyy,mo,dd,orient='north'): + # currently all files of the form 20201231.north.schavec-mlt-supermag.60s.rev-0005.ncdf.gz + rev='rev-0005' + mytime = "%4.4d%2.2d%2.2d" % (yyyy, mo, dd) + fname = mytime + '.' + orient.lower() + '.schavec-mlt-supermag.60s.' + rev + '.ncdf' + '.gz' + return(fname) + + +def serve_polar_df(yyyy,mo,dd,hh,mm,orient='north'): + # for the given minute, returns the 600 vector field dataframe + status = 0 # track whether this works in the end or not + + filename=make_polarname(yyyy,mo,dd,orient) + + filename = '../data/'+ filename + if os.path.exists(filename): + try: + mydata = xr.open_dataset(filename) # get in as an xarray + sub_d=mydata.sel(block=(hh*60)+mm) + my_df=sub_d.to_dataframe().reset_index() + my_df.vector=maketimestamp_df(my_df) + my_df.drop(columns=['id']) # not needed, might confuse users + stringize_df(my_df) # prep it for csv-ing + mydata=my_df.apply(csv_me_polar,axis=1) # apply function to each row + status=1 # it worked + except: + mydata=pd.DataFrame({0:["error","unable to process data"]}) + else: + mydata=pd.DataFrame({0:["error",filename+" not found"]}) + + return(status,mydata) + +""" +# mini test + +from superhapi import * +timemin= '2020-01-19T00:00Z' +timemax= '2020-01-20T00:00Z' +parameters='tbd' +sout='filehandle to be defined later' +myjson=do_data_supermag('inventory',timemin,timemax,parameters,sout,null) + + +TBD: 1) return json, not bytes, also 2) verify mod to 'supermag_api.py' for adding **kwargs to supermag_getinventory did not break anything by re-rerunning test scripts. + +""" + +""" +#import pickle +#pickle.dump(dataframe,open("temp.sav","wb")) +#testing +import pickle +dataframe=pickle.load(open('temp.sav','rb')) +""" + +def tf_to_hapicode(status,datasize): + # converts 0=bad, 1=good to HAPI code + if status == 0: + status = 1500 # 1500 is HAPI "Internal server error" + elif datasize > 0: + status=1200 # 1200 is HAPI "OK" + else: + status=1201 # 1200 is HAPI "OK - no data for time range" + return(status) + + +# appends the given data to the file as csv +def sm_data_to_csv(filename,mydata): + comma="" + dsize=len(mydata) + for i, rec in enumerate(mydata): + if i == dsize-1: comma="" # turn off comma for last entry + s.wfile.write(bytes(comma+rec+"\n","utf-8")) + comma="," # ensures all entries past first get a comma +# e.g. key='N' + + +def do_data_supermag(id,timemin,timemax,parameters,catalog,floc, + stream_flag, stream): + #print("debug, got parameters: ",parameters) + # 'ignore' is because hapi-server uses that only for file-bsaed fetches + userid='antunes' # debug, temporarily for now + + #timenow = datetime.datetime.strptime(timemin,'%Y-%m-%dT%H:%M:%SZ') + #timeend = datetime.datetime.strptime(timemax,'%Y-%m-%dT%H:%M:%SZ') + start = datetime.datetime.strptime(timemin,'%Y-%m-%dT%H:%MZ') + timeend = datetime.datetime.strptime(timemax,'%Y-%m-%dT%H:%MZ') + + delta=timeend-start + extent = delta.total_seconds() + + if len(floc['customOptions']) > 0: + parameters += floc['customOptions'] + + #if ( parameters!=None ): + # mp= do_parameters_map( id, parameters ) + #else: + # mp= None + #print("debug: parameters found ",parameters) + final_parameters = parameters # save for later + + #print("debug: parameters updated ",parameters) + + #print("debug: id is ",id) + if id.startswith("stations"): + # no 'parameters' used by this + #print("Debug:",userid,start,extent) + (status,magdata) = supermag_getinventory(userid,start,extent) # FORMAT='list') + ## add column 'window_end' + for i, iaga in enumerate(magdata): + #print(timemin, iaga, timemax) + line = timemin + ',' + iaga + ',' + timemax + magdata[i] = line + magdata = '\n'.join(magdata) + #magdata = "#Time,IAGA,window_end\n" + magdata + #magdata = '\',\''.join(magdata) # cheap csv-ing + #magdata = '\'' + magdata + '\'' # add leading and following quote + status=tf_to_hapicode(status,len(magdata)) + elif id.startswith('indices'): + # 'parameters' is which data items to fetch, HAPI default = 'all' + (parameters, clean_out_later) = sm_lookup(parameters) + + (status,magdata)=supermag_getindices(userid,start,extent,parameters,FORMAT='json') + # (note we remove 'row' because HAPI requires start as 1st var) + + # converts to csv string with \n + #magdata = magdata.to_csv(header=1,index=False) + try: + magdata['tval'] = magdata['tval'].apply(sm_to_hapitimes) + except: + pass # pass when there is no valid data to parse + #print("Debug: all magdata = ",magdata) + + if parameters != None: + # verify and fill if no data exists + #print("debug: catalog is ",catalog) + #print("debug: catalog keys are ",catalog.keys()) + ### NOTE-- removed sm_fill_empty() BECAUSE SuperMAG data is weird + ###sm_fill_empty(magdata,parameters,catalog['parameters']) + #magdata.rename(indicesmap,inplace=True,errors='ignore') + #print("Debug: renamed magdata = ",magdata) + + if len(clean_out_later) > 0: + #print("Debug, removing ",clean_out_later,"\n from ",magdata.keys()) + magdata=magdata.drop(columns=clean_out_later,errors='ignore') + #print("Debug, removed ",clean_out_later,"\n from ",magdata.keys()) + #print("Debug: empty filled magdata = ",magdata) + + magdata = magdata.to_csv(header=0,index=False,sep=',') + magdata = csv_removekeys(magdata) # change {k:v,k:v} to just [v,v] + magdata = unwind_csv_array(magdata) # change [v,v] to just v,v + status=tf_to_hapicode(status,len(magdata)) + + elif id.startswith('data'): + # New 'data' code, replaces prior mess + (dataword,station)=id.split('_') + if parameters != None: + flagstring = '&'.join(parameters) # more than needed, will filter later + else: + flagstring = "&mlt&mag&geo&decl&sza" + + (status,magdata)=supermag_getdata(userid,start,extent,flagstring,station,FORMAT='json') + try: + magdata['tval'] = magdata['tval'].apply(sm_to_hapitimes) + except: + pass # pass when there is no valid data to parse + + # Massive filtering needed to match parameters requested + if parameters != None: + magdata=sm_filter_data(magdata,parameters) + + magdata = magdata.to_csv(header=0,index=False,sep=',') + magdata = csv_removekeys(magdata) # change {k:v,k:v} to just [v,v] + magdata = unwind_csv_array(magdata) # change [v,v] to just v,v + #magdata = magdata.split('\n')# optional, converts csv string to list + status=tf_to_hapicode(status,len(magdata)) + + elif id.startswith('data') and parameters != None: + # NOTE THIS NO LONGER GETS CALLED AT ALL, SUBPLANTED BY ABOVE + # 'parameters' is the usual HAPI variables to return + # station name is encoded in the data_XXX id + # (each station is its own endpoint) + #print("debug, parameters = ",parameters) + flagstring = '&'.join(parameters) + (dataword,station)=id.split('_') + #print("debug: looking for station ",station) + if len(station) != 3 and station != "allstations": + status=1400 # 1406 is HAPI "unknown dataset id" + magdata="Error, SuperMAG data calls require a station ID" + #print("debug, caught lack of station error") + # data calls must have a station, so throw error and exit + else: + # special case, 'data_allstations' + sortme = False + if station == "allstations": + (status,station) = supermag_getinventory(userid,start,extent) # FORMAT='list') + sortme = True + #print("debug: flags are ",flagstring) + (status,magdata)=supermag_getdata(userid,start,extent,flagstring,station,FORMAT='json') + # (note we add 'row' because that key is undefined in the dataframe) + #print("debug: data is ",magdata) + if sortme: + # sort dataframe in time order + #import pickle + #pickle.dump(magdata,open("temp.save","wb")) + #print("debug, saved temp.save") + magdata.sort_values('tval',inplace=True) + + #magdata = magdata.to_csv(header=1,index=False) + try: + magdata['tval'] = magdata['tval'].apply(sm_to_hapitimes) + except: + pass # pass when there is no valid data to parse + + #if parameters != None: + # # verify and fill if no data exists + # ### NOTE-- removed sm_fill_empty() BECAUSE SuperMAG data is weird + # ###sm_fill_empty(magdata,parameters,catalog['parameters']) + + magdata = magdata.to_csv(header=0,index=False,sep=',') + magdata = csv_removekeys(magdata) # change {k:v,k:v} to just [v,v] + magdata = unwind_csv_array(magdata) # change [v,v] to just v,v + #magdata = magdata.split('\n')# optional, converts csv string to list + status=tf_to_hapicode(status,len(magdata)) + else: + # did not match a SuperMAG-likely keyword, so produce error message + status=1406 # 1406 is HAPI "unknown dataset id" + magdata="Error, \"" + id + "\" is not a valid query" + + #print("Debug-- done for id,parameters: ",id,parameters) + return(status,magdata) + + +def do_file_supermag( id, timemin, timemax, parameters): + + # need to figure out time limits, and enforce them + #timemin= dateutil.parser.parse( timemin ).strftime('%Y-%m-%d-%H-%M-%S') + #(yyyy,mo,dd,hh,mm,ss)=(int(x) for x in timemin.split('-')) + #timenow=datetime.datetime(yyyy,mo,dd,hh,mm,ss).timestamp() + #timemax= dateutil.parser.parse( timemax ).strftime('%Y-%m-%d-%H-%M-%S') + #(yyyy,mo,dd,hh,mm,ss)=(int(x) for x in timemax.split('-')) + + timenow = datetime.datetime.strptime(timemin,'%Y-%m-%dT%H:%M:%SZ') + timeend = datetime.datetime.strptime(timemax,'%Y-%m-%dT%H:%M:%SZ') + + if ( parameters!=None ): + mp= do_parameters_map( id, parameters ) + else: + mp= None + + # go in X-minute increments????? + increment = 10*60 # 10 minute increments + + # TO DO: do we actually serve the data? + # TO DO: also pass parameters for subselecting data + + mydata = "" + + while timenow < timeend: + status=0 # gets set to 1 if this timestep works + if id == "polar": + # returns 600 vectors for that given minute as a dataframe + (status,mydata_df)= serve_polar_df(yyyy,dd,mo,hh,m) + mydata += mydata_df + status=tf_to_hapicode(status,len(mydata_list)) + + elif id == "inventory": + (status,mydata_list) = SuperMAGGetInventory(userid,timenow.year,timenow.month,timenow.day,timenow.hour,timenow.minute,0,increment) + mydata += mydata_list + status=tf_to_hapicode(status,len(mydata_list)) + + elif id == 'indices': + (status,magdata)=SuperMAGGetDataArray('indices',userid,timenow.year,timenow.month,timenow.day,timenow.hour,timenow.minute,0,increment,mystation) + mydata += magdata + status=tf_to_hapicode(status,len(magdata)) + + elif id == "all" or strlength(id) == 3: + # if a 3-digit string, is likely (?) a station request + if id == "all": + (status,stations_list) = SuperMAGGetInventory(userid,timenow.year,timenow.month,timenow.day,timenow.hour,timenow.minute,0,increment) + else: + stations_list=[id] # wants just 1 station + for mystation in stations_list: + (status,magdata)=SuperMAGGetDataStruct('data',userid,timenow.year,timenow.month,timenow.day,timenow.hour,timenow.minute,0,increment,mystation) + mydata += magdata + status=tf_to_hapicode(status,len(magdata)) + + else: + # did not match a HAPI-approved keyword, so produce error message + status=1406 # 1406 is HAPI "unknown dataset id" + mydata="Error, \"" + id + "\" is not a valid query" + + #s.wfile.write(bytes(',',"utf-8")) + #s.wfile.write(bytes(ss[i],"utf-8")) + timenow = timenow + datetime.timedelta(minutes=+increment) + sm_data_to_csv(filename,mydata) + diff --git a/tests/serverless_test.py b/tests/serverless_test.py new file mode 100644 index 0000000..2b2b7b6 --- /dev/null +++ b/tests/serverless_test.py @@ -0,0 +1,19 @@ +import hapi_parser as hp +from hapiplot import hapiplot +from io import StringIO + +USE_CASE = 'supermag' +start = '2023-12-01T00:00Z' +stop = '2023-12-07T00:00Z' +id = "indices_all" +parameters = "SME,SML" + +CFG = hp.parse_config(USE_CASE) +(status, jsondata) = hp.fetch_info_params(id,CFG.HAPI_HOME,False) +(start, stop, errorcode) = hp.clean_query_time(None,timemin=start,timemax=stop) +(status, data) = CFG.hapi_handler(id, start, stop, hp.tolist(parameters), jsondata, CFG.floc, False, None) +meta, hapidata = hp.csv_to_hapi_conv(id,parameters,CFG.HAPI_HOME,data) +print('meta=',meta) +hapiplot(hapidata,meta) + + diff --git a/tests/supermag_hapi_demo.py b/tests/supermag_hapi_demo.py new file mode 100644 index 0000000..3b487f1 --- /dev/null +++ b/tests/supermag_hapi_demo.py @@ -0,0 +1,26 @@ +from hapiclient import hapi +from hapiplot import hapiplot + +server = 'http://localhost:8000/hapi' +dataset = "stations" +# Start and stop times +start = '2023-12-01T00:00:00Z' +stop = '2023-12-07T00:00:00Z' +parameters = 'IAGA' +stations, meta = hapi(server, dataset, parameters, start, stop) +print(meta) +print("First 3 stations:") +for datapair in stations[:3]: + print(f"Station: {datapair[1]}") + dataset = f"data_{datapair[1]}" + parameters="geo,mag" + try: + data, meta = hapi(server, dataset, parameters, start, stop) + hapiplot(data,meta) + except Exception as e: + print(e) + +dataset = "indices_all" +parameters="SME,SML" +data, meta = hapi(server, dataset, parameters, start, stop) +hapiplot(data,meta)
    %s: