コード例 #1
0
 def test_dewpoint(self):
     """ test out computation of dew point """
     for t0, r0, a0 in [[80, 80, 73.42], [80, 20, 35.87]]:
         t = datatypes.temperature(t0, 'F')
         rh = datatypes.humidity(r0, '%')
         dwpk = meteorology.dewpoint(t, rh)
         self.assertAlmostEqual(dwpk.value("F"), a0, 2)
コード例 #2
0
ファイル: test_meteorology.py プロジェクト: akrherz/pyIEM
def test_dewpoint():
    """ test out computation of dew point """
    for t0, r0, a0 in [[80, 80, 73.42], [80, 20, 35.87]]:
        t = datatypes.temperature(t0, 'F')
        rh = datatypes.humidity(r0, '%')
        dwpk = meteorology.dewpoint(t, rh)
        assert abs(dwpk.value("F") - a0) < 0.01
コード例 #3
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def test_dewpoint():
    """ test out computation of dew point """
    for t0, r0, a0 in [[80, 80, 73.42], [80, 20, 35.87]]:
        t = datatypes.temperature(t0, "F")
        rh = datatypes.humidity(r0, "%")
        dwpk = meteorology.dewpoint(t, rh)
        assert abs(dwpk.value("F") - a0) < 0.01
コード例 #4
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 def test_dewpoint(self):
     """ test out computation of dew point """
     for t0,r0,a0 in [[80,80,73.42], [80,20,35.87]]:
         t = datatypes.temperature(t0, 'F')
         rh = datatypes.humidity(r0, '%')
         dwpk = meteorology.dewpoint(t, rh)
         self.assertAlmostEqual( dwpk.value("F"), a0, 2)
コード例 #5
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def hourly_process(nwsli, maxts):
    """ Process the hourly file """
    fn = "%s/%s_HrlySI.dat" % (BASE, STATIONS[nwsli])
    df = common_df_logic(fn, maxts, nwsli, "sm_hourly")
    if df is None:
        return 0
    processed = 0
    LOG.debug("processing %s rows from %s", len(df.index), fn)
    acursor = ACCESS.cursor()
    for _i, row in df.iterrows():
        # Update IEMAccess
        ob = Observation(nwsli, "ISUSM", row["valid"])
        tmpc = temperature(row["tair_c_avg_qc"], "C")
        if tmpc.value("F") > -50 and tmpc.value("F") < 140:
            ob.data["tmpf"] = tmpc.value("F")
            relh = humidity(row["rh_qc"], "%")
            ob.data["relh"] = relh.value("%")
            ob.data["dwpf"] = met.dewpoint(tmpc, relh).value("F")
        ob.data["srad"] = row["slrkw_avg_qc"]
        ob.data["phour"] = round(
            distance(row["rain_mm_tot_qc"], "MM").value("IN"), 2
        )
        ob.data["sknt"] = speed(row["ws_mps_s_wvt_qc"], "MPS").value("KT")
        if "ws_mph_max" in df.columns:
            ob.data["gust"] = speed(row["ws_mph_max_qc"], "MPH").value("KT")
            ob.data["max_gust_ts"] = row["ws_mph_tmx"]
        ob.data["drct"] = row["winddir_d1_wvt_qc"]
        if "tsoil_c_avg" in df.columns:
            ob.data["c1tmpf"] = temperature(row["tsoil_c_avg_qc"], "C").value(
                "F"
            )
        if "t12_c_avg_qc" in df.columns:
            ob.data["c2tmpf"] = temperature(row["t12_c_avg_qc"], "C").value(
                "F"
            )
        if "t24_c_avg_qc" in df.columns:
            ob.data["c3tmpf"] = temperature(row["t24_c_avg_qc"], "C").value(
                "F"
            )
        if "t50_c_avg" in df.columns:
            ob.data["c4tmpf"] = temperature(row["t50_c_avg_qc"], "C").value(
                "F"
            )
        if "calc_vwc_12_avg" in df.columns:
            ob.data["c2smv"] = row["calc_vwc_12_avg_qc"] * 100.0
        if "calc_vwc_24_avg" in df.columns:
            ob.data["c3smv"] = row["calc_vwc_24_avg_qc"] * 100.0
        if "calc_vwc_50_avg" in df.columns:
            ob.data["c4smv"] = row["calc_vwc_50_avg_qc"] * 100.0
        ob.save(acursor)
        processed += 1
    acursor.close()
    ACCESS.commit()
    return processed
コード例 #6
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ファイル: meteorology.py プロジェクト: xoxo143/pyIEM
def relh(temperature, _dewpoint):
    """
    Compute Relative Humidity based on a temperature and dew point
    """
    # Get temperature in Celsius
    tmpc = temperature.value("C")
    dwpc = _dewpoint.value("C")

    e = 6.112 * np.exp((17.67 * dwpc) / (dwpc + 243.5))
    es = 6.112 * np.exp((17.67 * tmpc) / (tmpc + 243.5))
    _relh = (e / es) * 100.00
    return dt.humidity(_relh, "%")
コード例 #7
0
ファイル: meteorology.py プロジェクト: akrherz/pyIEM
def relh(temperature, dewpoint):
    """
    Compute Relative Humidity based on a temperature and dew point
    """
    # Get temperature in Celsius
    tmpc = temperature.value("C")
    dwpc = dewpoint.value("C")

    e = 6.112 * np.exp((17.67 * dwpc) / (dwpc + 243.5))
    es = 6.112 * np.exp((17.67 * tmpc) / (tmpc + 243.5))
    relh = (e / es) * 100.00
    return dt.humidity(relh, '%')
コード例 #8
0
def hourly_process(nwsli, maxts):
    """ Process the hourly file """
    fn = "%s/%s_HrlySI.dat" % (BASE, STATIONS[nwsli])
    df = common_df_logic(fn, maxts, nwsli, "sm_hourly")
    if df is None:
        return 0
    processed = 0
    LOG.debug("processing %s rows from %s", len(df.index), fn)
    acursor = ACCESS.cursor()
    for _i, row in df.iterrows():
        # Update IEMAccess
        # print nwsli, valid
        ob = Observation(nwsli, 'ISUSM', row['valid'])
        tmpc = temperature(row['tair_c_avg_qc'], 'C')
        if tmpc.value('F') > -50 and tmpc.value('F') < 140:
            ob.data['tmpf'] = tmpc.value('F')
            relh = humidity(row['rh_qc'], '%')
            ob.data['relh'] = relh.value('%')
            ob.data['dwpf'] = met.dewpoint(tmpc, relh).value('F')
        ob.data['srad'] = row['slrkw_avg_qc']
        ob.data['phour'] = round(distance(row['rain_mm_tot_qc'],
                                          'MM').value('IN'), 2)
        ob.data['sknt'] = speed(row['ws_mps_s_wvt_qc'], 'MPS').value("KT")
        if 'ws_mph_max' in df.columns:
            ob.data['gust'] = speed(row['ws_mph_max_qc'], 'MPH').value('KT')
            ob.data['max_gust_ts'] = row['ws_mph_tmx']
        ob.data['drct'] = row['winddir_d1_wvt_qc']
        if 'tsoil_c_avg' in df.columns:
            ob.data['c1tmpf'] = temperature(row['tsoil_c_avg_qc'],
                                            'C').value('F')
        if 't12_c_avg_qc' in df.columns:
            ob.data['c2tmpf'] = temperature(
                row['t12_c_avg_qc'], 'C').value('F')
        if 't24_c_avg_qc' in df.columns:
            ob.data['c3tmpf'] = temperature(
                row['t24_c_avg_qc'], 'C').value('F')
        if 't50_c_avg' in df.columns:
            ob.data['c4tmpf'] = temperature(row['t50_c_avg_qc'],
                                            'C').value('F')
        if 'calc_vwc_12_avg' in df.columns:
            ob.data['c2smv'] = row['calc_vwc_12_avg_qc'] * 100.0
        if 'calc_vwc_24_avg' in df.columns:
            ob.data['c3smv'] = row['calc_vwc_24_avg_qc'] * 100.0
        if 'calc_vwc_50_avg' in df.columns:
            ob.data['c4smv'] = row['calc_vwc_50_avg_qc'] * 100.0
        ob.save(acursor)
        # print 'soilm_ingest.py station: %s ts: %s hrly updated no data?' % (
        #                                        nwsli, valid)
        processed += 1
    acursor.close()
    ACCESS.commit()
    return processed
コード例 #9
0
def processfile(icursor, filename):
    """Process this file"""
    lines = open("/mesonet/data/incoming/rwis/%s" % (filename, ),
                 "r").readlines()
    if len(lines) < 2:
        return
    heading = lines[0].split(",")
    cols = lines[1].split(",")
    data = {}
    if len(cols) < len(heading):
        return
    for i, h in enumerate(heading):
        if cols[i].strip() != "/":
            data[h.strip()] = cols[i].strip()

    nwsli = LOOKUP[filename]
    if filename in ["portableExportP1.csv", "miniExportIFB.csv"]:
        ts = datetime.datetime.strptime(data["date_time"][:16],
                                        "%Y-%m-%d %H:%M")
    else:
        ts = datetime.datetime.strptime(data["date_time"][:-6],
                                        "%Y-%m-%d %H:%M")
    ts = ts.replace(tzinfo=pytz.UTC)
    iem = Observation(nwsli, "IA_RWIS", ts)
    if ts.year < 2010:
        print(("rwis/mini_portable.py file: %s bad timestamp: %s"
               "") % (filename, data["date_time"]))
        return
    iem.load(icursor)

    # IEM Tracker stuff is missing

    if data.get("wind_speed", "") != "":
        iem.data["sknt"] = float(data["wind_speed"]) * 1.17
    if data.get("sub", "") != "":
        iem.data["rwis_subf"] = float(data["sub"])
    if data.get("air_temp", "") != "":
        iem.data["tmpf"] = float(data["air_temp"])
    if data.get("pave_temp", "") != "":
        iem.data["tsf0"] = float(data["pave_temp"])
    if data.get("pave_temp2", "") != "":
        iem.data["tsf1"] = float(data["pave_temp2"])
    if data.get("press", "") != "":
        iem.data["alti"] = float(data["press"])
    if data.get("RH", "") != "":
        if float(data["RH"]) > 1:
            t = temperature(iem.data["tmpf"], "F")
            rh = humidity(float(data["RH"]), "%")
            iem.data["dwpf"] = meteorology.dewpoint(t, rh).value("F")
    if data.get("wind_dir", "") != "":
        iem.data["drct"] = float(data["wind_dir"])
    iem.save(icursor)
コード例 #10
0
ファイル: mini_portable.py プロジェクト: nemochina2008/iem
def processfile(icursor, filename):
    """Process this file"""
    lines = open("/mesonet/data/incoming/rwis/%s" % (filename, ),
                 'r').readlines()
    if len(lines) < 2:
        return
    heading = lines[0].split(",")
    cols = lines[1].split(",")
    data = {}
    if len(cols) < len(heading):
        return
    for i in range(len(heading)):
        if cols[i].strip() != "/":
            data[heading[i].strip()] = cols[i].strip()

    nwsli = LOOKUP[filename]
    if filename in ['portableExportP1.csv', 'miniExportIFB.csv']:
        ts = datetime.datetime.strptime(data['date_time'][:16],
                                        '%Y-%m-%d %H:%M')
    else:
        ts = datetime.datetime.strptime(data['date_time'][:-6],
                                        '%Y-%m-%d %H:%M')
    ts = ts.replace(tzinfo=pytz.timezone("UTC"))
    iem = Observation(nwsli, 'IA_RWIS', ts)
    if ts.year < 2010:
        print(("rwis/mini_portable.py file: %s bad timestamp: %s"
               "") % (filename, data['date_time']))
        return
    iem.load(icursor)

    # IEM Tracker stuff is missing

    if data.get('wind_speed', '') != '':
        iem.data['sknt'] = float(data['wind_speed']) * 1.17
    if data.get('sub', '') != '':
        iem.data['rwis_subf'] = float(data['sub'])
    if data.get('air_temp', '') != '':
        iem.data['tmpf'] = float(data['air_temp'])
    if data.get('pave_temp', '') != '':
        iem.data['tsf0'] = float(data['pave_temp'])
    if data.get('pave_temp2', '') != '':
        iem.data['tsf1'] = float(data['pave_temp2'])
    if data.get('press', '') != '':
        iem.data['alti'] = float(data['press'])
    if data.get('RH', '') != '':
        if float(data['RH']) > 1:
            t = temperature(iem.data['tmpf'], 'F')
            rh = humidity(float(data['RH']), '%')
            iem.data['dwpf'] = meteorology.dewpoint(t, rh).value('F')
    if data.get('wind_dir', '') != '':
        iem.data['drct'] = float(data['wind_dir'])
    iem.save(icursor)
コード例 #11
0
ファイル: mini_portable.py プロジェクト: KayneWest/iem
def processfile( fp ):
    o = open("/mesonet/data/incoming/rwis/%s" % (fp,), 'r').readlines()
    if len(o) < 2:
        return
    heading = o[0].split(",")
    cols = o[1].split(",")
    data = {}
    if len(cols) < len(heading):
        return
    for i in range(len(heading)):
        if cols[i].strip() != "/":
            data[heading[i].strip()] = cols[i].strip()

    nwsli = lkp[fp]
    if fp in ['portableExportP1.csv', 'miniExportIFB.csv']:
        ts = datetime.datetime.strptime(data['date_time'][:16],
                                        '%Y-%m-%d %H:%M')
    else:
        ts = datetime.datetime.strptime(data['date_time'][:-6],
                                        '%Y-%m-%d %H:%M')
    ts = ts.replace(tzinfo=pytz.timezone("UTC"))
    iem = Observation(nwsli, 'IA_RWIS', ts)
    if ts.year < 2010:
        print(("rwis/mini_portable.py file: %s bad timestamp: %s"
               "") % (fp, data['date_time']))
        return
    iem.load(icursor)

    # IEM Tracker stuff is missing

    if data.get('wind_speed', '') != '':
        iem.data['sknt'] = float(data['wind_speed']) * 1.17
    if data.get('sub', '') != '':
        iem.data['rwis_subf'] = float(data['sub'])
    if data.get('air_temp', '') != '':
        iem.data['tmpf'] = float(data['air_temp'])
    if data.get('pave_temp', '') != '':
        iem.data['tsf0'] = float(data['pave_temp'])
    if data.get('pave_temp2', '') != '':
        iem.data['tsf1'] = float(data['pave_temp2'])
    if data.get('press', '') != '':
        iem.data['alti'] = float(data['press'])
    if data.get('RH', '') != '':
        if float(data['RH']) > 1:
            t = temperature(iem.data['tmpf'], 'F')
            rh = humidity(float(data['RH']), '%')
            iem.data['dwpf'] = meteorology.dewpoint(t, rh).value('F')
    if data.get('wind_dir', '') != '':
        iem.data['drct'] = float(data['wind_dir'])
    iem.save(icursor)
コード例 #12
0
ファイル: parse0006.py プロジェクト: skmichaeldavis/iem
def main():
    """Go Main Go"""
    pgconn = get_dbconn("iem")
    icursor = pgconn.cursor()

    now = datetime.datetime.now().replace(
        tzinfo=pytz.timezone("America/Chicago"))

    fn = ("/mesonet/ARCHIVE/data/%s/text/ot/ot0006.dat"
          "") % (now.strftime("%Y/%m/%d"), )

    if not os.path.isfile(fn):
        return
    lines = open(fn, 'r').readlines()
    line = lines[-1]

    # January 17, 2017 02:57 PM
    # 35.1 35.8 33.4 92 3 351 14 2:13PM 30.03 0.00 1.12 1.12 68.6 36
    tokens = line.split(" ")
    if len(tokens) != 19:
        sys.exit(0)

    ts = datetime.datetime.strptime(" ".join(tokens[:5]), "%B %d, %Y %I:%M %p")

    ts = now.replace(year=ts.year,
                     month=ts.month,
                     day=ts.day,
                     hour=ts.hour,
                     minute=ts.minute)

    iemob = Observation("OT0006", "OT", ts)

    iemob.data['tmpf'] = float(tokens[5])
    iemob.data['relh'] = float(tokens[8])
    tmpf = temperature(iemob.data['tmpf'], 'F')
    relh = humidity(iemob.data['relh'], '%')
    iemob.data['dwpf'] = meteorology.dewpoint(tmpf, relh).value('F')
    iemob.data['sknt'] = speed(float(tokens[9]), 'MPH').value('KT')
    iemob.data['drct'] = tokens[10]
    iemob.data['alti'] = float(tokens[13])
    iemob.data['pday'] = float(tokens[14])
    iemob.save(icursor)

    icursor.close()
    pgconn.commit()
    pgconn.close()
コード例 #13
0
ファイル: parse0007.py プロジェクト: stormchas4/iem
def main():
    """Go Main Go"""
    pgconn = get_dbconn("iem")
    icursor = pgconn.cursor()

    now = datetime.datetime.now()

    fn = ("/mesonet/ARCHIVE/data/%s/text/ot/ot0007.dat"
          "") % (now.strftime("%Y/%m/%d"), )

    if not os.path.isfile(fn):
        sys.exit(0)

    lines = open(fn, "r").readlines()
    line = lines[-1]

    # 114,2006,240,1530,18.17,64.70, 88.9,2.675,21.91,1014.3,0.000
    tokens = line.split(",")
    if len(tokens) != 11:
        sys.exit(0)
    hhmm = "%04i" % (int(tokens[3]), )
    ts = now.replace(
        hour=int(hhmm[:2]),
        minute=int(hhmm[2:]),
        second=0,
        microsecond=0,
        tzinfo=pytz.timezone("America/Chicago"),
    )

    iemob = Observation("OT0007", "OT", ts)

    iemob.data["tmpf"] = float(tokens[5])
    iemob.data["relh"] = float(tokens[6])
    tmpf = temperature(iemob.data["tmpf"], "F")
    relh = humidity(iemob.data["relh"], "%")
    iemob.data["dwpf"] = meteorology.dewpoint(tmpf, relh).value("F")
    iemob.data["sknt"] = float(tokens[7]) * 1.94
    iemob.data["drct"] = tokens[8]
    iemob.data["pres"] = float(tokens[9]) / 960 * 28.36
    iemob.save(icursor)

    icursor.close()
    pgconn.commit()
    pgconn.close()
コード例 #14
0
ファイル: parse0010.py プロジェクト: ELjungdahl/iem
def main():
    """Go Main Go"""
    iemaccess = get_dbconn('iem')
    cursor = iemaccess.cursor()

    valid = datetime.datetime.utcnow()
    valid = valid.replace(tzinfo=pytz.utc)
    valid = valid.astimezone(pytz.timezone("America/Chicago"))
    fn = valid.strftime("/mesonet/ARCHIVE/data/%Y/%m/%d/text/ot/ot0010.dat")

    if not os.path.isfile(fn):
        sys.exit(0)

    lines = open(fn, "r").readlines()
    lastline = lines[-1].strip()
    tokens = re.split(r"[\s+]+", lastline)
    if len(tokens) != 20:
        return

    tparts = re.split(":", tokens[3])
    valid = valid.replace(hour=int(tparts[0]),
                          minute=int(tparts[1]),
                          second=0,
                          microsecond=0)

    iem = Observation("OT0010", "OT", valid)

    iem.data['tmpf'] = float(tokens[4])
    iem.data['max_tmpf'] = float(tokens[5])
    iem.data['min_tmpf'] = float(tokens[6])
    iem.data['relh'] = int(tokens[7])
    iem.data['dwpf'] = dewpoint(temperature(iem.data['tmpf'], 'F'),
                                humidity(iem.data['relh'], '%')).value("F")
    iem.data['sknt'] = speed(float(tokens[8]), 'mph').value('KT')
    iem.data['drct'] = int(tokens[9])
    iem.data['max_sknt'] = speed(float(tokens[10]), 'mph').value('KT')
    iem.data['alti'] = float(tokens[12])
    iem.data['pday'] = float(tokens[13])
    iem.data['srad'] = float(tokens[18])

    iem.save(cursor)

    cursor.close()
    iemaccess.commit()
コード例 #15
0
ファイル: ingest_isusm.py プロジェクト: stormchas4/iem
def minute_iemaccess(df):
    """Process dataframe into iemaccess."""
    pgconn = get_dbconn("iem")
    cursor = pgconn.cursor()
    for _i, row in df.iterrows():
        # Update IEMAccess
        # print nwsli, valid
        ob = Observation(row["station"], "ISUSM", row["valid"])
        tmpc = temperature(row["tair_c_avg_qc"], "C")
        if tmpc.value("F") > -50 and tmpc.value("F") < 140:
            ob.data["tmpf"] = tmpc.value("F")
            relh = humidity(row["rh_avg_qc"], "%")
            ob.data["relh"] = relh.value("%")
            ob.data["dwpf"] = met.dewpoint(tmpc, relh).value("F")
        # database srad is W/ms2
        ob.data["srad"] = row["slrkj_tot_qc"] / 60.0 * 1000.0
        ob.data["pcounter"] = row["rain_in_tot_qc"]
        ob.data["sknt"] = speed(row["ws_mph_s_wvt_qc"], "MPH").value("KT")
        if "ws_mph_max" in df.columns:
            ob.data["gust"] = speed(row["ws_mph_max_qc"], "MPH").value("KT")
        ob.data["drct"] = row["winddir_d1_wvt_qc"]
        if "tsoil_c_avg" in df.columns:
            ob.data["c1tmpf"] = temperature(row["tsoil_c_avg_qc"], "C").value(
                "F"
            )
        ob.data["c2tmpf"] = temperature(row["t12_c_avg_qc"], "C").value("F")
        ob.data["c3tmpf"] = temperature(row["t24_c_avg_qc"], "C").value("F")
        if "t50_c_avg" in df.columns:
            ob.data["c4tmpf"] = temperature(row["t50_c_avg_qc"], "C").value(
                "F"
            )
        if "calcvwc12_avg" in df.columns:
            ob.data["c2smv"] = row["calcvwc12_avg_qc"] * 100.0
        if "calcvwc24_avg" in df.columns:
            ob.data["c3smv"] = row["calcvwc24_avg_qc"] * 100.0
        if "calcvwc50_avg" in df.columns:
            ob.data["c4smv"] = row["calcvwc50_avg_qc"] * 100.0
        ob.save(cursor)
    cursor.close()
    pgconn.commit()
コード例 #16
0
ファイル: ingest_hicks.py プロジェクト: akrherz/datateam
def process(sheets):

    resdf = pd.DataFrame({
        'precip': sheets['RainOut']['Rain_mm_Tot'],
        'tmpf': sheets['TempRHVPOut']['AirT_C_Avg'],
        'rh': sheets['TempRHVPOut']['RH'],
        'drct': sheets['WindOut']['WindDir_D1_WVT'],
        'sknt': sheets['WindOut']['WS_ms_S_WVT'],
        'srad': sheets['SolarRad1Out']['Slr_kW_Avg']
    })
    # Do unit conversion
    resdf['srad'] = resdf['srad'] * 1000.
    resdf['precip'] = distance(resdf['precip'], 'MM').value('IN')
    resdf['tmpf'] = temperature(resdf['tmpf'], 'C').value('F')
    resdf['dwpf'] = dewpoint(temperature(resdf['tmpf'], 'F'),
                             humidity(resdf['rh'], '%')).value('F')
    resdf['sknt'] = speed(resdf['sknt'], 'MPS').value('KT')
    print(resdf.describe())
    minval = resdf.index.min()
    maxval = resdf.index.max()
    cursor = pgconn.cursor()
    cursor.execute(
        """DELETE from weather_data_obs WHERE
    valid between '%s-06' and '%s-06' and station = 'HICKS.P'
    """ %
        (minval.strftime("%Y-%m-%d %H:%M"), maxval.strftime("%Y-%m-%d %H:%M")))
    print("DELETED %s rows between %s and %s" %
          (cursor.rowcount, minval, maxval))
    for valid, row in resdf.iterrows():
        if pd.isnull(valid):
            continue
        cursor.execute(
            """INSERT into weather_data_obs
        (station, valid, tmpf, dwpf, drct, precip, srad, sknt) VALUES
        ('HICKS.P', %s, %s, %s, %s, %s, %s, %s)
        """, (valid.strftime("%Y-%m-%d %H:%M-06"), row['tmpf'], row['dwpf'],
              row['drct'], row['precip'], row['srad'], row['sknt']))
    cursor.close()
    pgconn.commit()
コード例 #17
0
ファイル: ingest_isusm.py プロジェクト: jamayfieldjr/iem
def minute_iemaccess(df):
    """Process dataframe into iemaccess."""
    pgconn = get_dbconn('iem')
    cursor = pgconn.cursor()
    for _i, row in df.iterrows():
        # Update IEMAccess
        # print nwsli, valid
        ob = Observation(row['station'], 'ISUSM', row['valid'])
        tmpc = temperature(row['tair_c_avg_qc'], 'C')
        if tmpc.value('F') > -50 and tmpc.value('F') < 140:
            ob.data['tmpf'] = tmpc.value('F')
            relh = humidity(row['rh_avg_qc'], '%')
            ob.data['relh'] = relh.value('%')
            ob.data['dwpf'] = met.dewpoint(tmpc, relh).value('F')
        # database srad is W/ms2
        ob.data['srad'] = row['slrkj_tot_qc'] / 60. * 1000.
        ob.data['pcounter'] = row['rain_in_tot_qc']
        ob.data['sknt'] = speed(row['ws_mph_s_wvt_qc'], 'MPH').value("KT")
        if 'ws_mph_max' in df.columns:
            ob.data['gust'] = speed(row['ws_mph_max_qc'], 'MPH').value('KT')
        ob.data['drct'] = row['winddir_d1_wvt_qc']
        if 'tsoil_c_avg' in df.columns:
            ob.data['c1tmpf'] = temperature(row['tsoil_c_avg_qc'],
                                            'C').value('F')
        ob.data['c2tmpf'] = temperature(row['t12_c_avg_qc'], 'C').value('F')
        ob.data['c3tmpf'] = temperature(row['t24_c_avg_qc'], 'C').value('F')
        if 't50_c_avg' in df.columns:
            ob.data['c4tmpf'] = temperature(row['t50_c_avg_qc'],
                                            'C').value('F')
        if 'calcvwc12_avg' in df.columns:
            ob.data['c2smv'] = row['calcvwc12_avg_qc'] * 100.0
        if 'calcvwc24_avg' in df.columns:
            ob.data['c3smv'] = row['calcvwc24_avg_qc'] * 100.0
        if 'calcvwc50_avg' in df.columns:
            ob.data['c4smv'] = row['calcvwc50_avg_qc'] * 100.0
        ob.save(cursor)
    cursor.close()
    pgconn.commit()
コード例 #18
0
ファイル: ingest_hicks.py プロジェクト: akrherz/datateam
def process(sheets):

    resdf = pd.DataFrame({
            'precip': sheets['RainOut']['Rain_mm_Tot'],
            'tmpf': sheets['TempRHVPOut']['AirT_C_Avg'],
            'rh': sheets['TempRHVPOut']['RH'],
            'drct': sheets['WindOut']['WindDir_D1_WVT'],
            'sknt': sheets['WindOut']['WS_ms_S_WVT'],
            'srad': sheets['SolarRad1Out']['Slr_kW_Avg']})
    # Do unit conversion
    resdf['srad'] = resdf['srad'] * 1000.
    resdf['precip'] = distance(resdf['precip'], 'MM').value('IN')
    resdf['tmpf'] = temperature(resdf['tmpf'], 'C').value('F')
    resdf['dwpf'] = dewpoint(temperature(resdf['tmpf'], 'F'),
                             humidity(resdf['rh'], '%')).value('F')
    resdf['sknt'] = speed(resdf['sknt'], 'MPS').value('KT')
    print(resdf.describe())
    minval = resdf.index.min()
    maxval = resdf.index.max()
    cursor = pgconn.cursor()
    cursor.execute("""DELETE from weather_data_obs WHERE
    valid between '%s-06' and '%s-06' and station = 'HICKS.P'
    """ % (minval.strftime("%Y-%m-%d %H:%M"),
           maxval.strftime("%Y-%m-%d %H:%M")))
    print("DELETED %s rows between %s and %s" % (cursor.rowcount, minval,
                                                 maxval))
    for valid, row in resdf.iterrows():
        if pd.isnull(valid):
            continue
        cursor.execute("""INSERT into weather_data_obs
        (station, valid, tmpf, dwpf, drct, precip, srad, sknt) VALUES
        ('HICKS.P', %s, %s, %s, %s, %s, %s, %s)
        """, (valid.strftime("%Y-%m-%d %H:%M-06"), row['tmpf'], row['dwpf'],
              row['drct'], row['precip'], row['srad'], row['sknt']))
    cursor.close()
    pgconn.commit()
コード例 #19
0
ファイル: fxgridder.py プロジェクト: akrherz/iemgrid
def write_grids(fp, valid, fhour):
    """Do the write to disk"""
    gribfn = "%s/%sF%03i.grib2" % (TMP, valid.strftime("%Y%m%d%H%M"),
                                   fhour)
    if not os.path.isfile(gribfn):
        print("Skipping write_grids because of missing fn: %s" % (gribfn,))
        return
    gribs = pygrib.open(gribfn)
    grids = dict()
    for grib in gribs:
        grids[grib.name] = grib
    d = dict()
    if '2 metre temperature' in grids:
        g = grids['2 metre temperature']
        if G['LATS'] is None:
            G['LATS'], G['LONS'] = g.latlons()
        vals = temperature(g.values, 'K').value('C')
        nn = NearestNDInterpolator((G['LONS'].flatten(), G['LATS'].flatten()),
                                   vals.flatten())
        d['tmpc'] = nn(XI, YI)
        if 'Relative humidity' in grids:
            g = grids['Relative humidity']
            vals = g.values
            nn = NearestNDInterpolator((G['LONS'].flatten(),
                                        G['LATS'].flatten()),
                                       vals.flatten())
            rh = nn(XI, YI)
            d['dwpc'] = dewpoint(temperature(d['tmpc'], 'C'),
                                 humidity(rh, '%')).value('C')
    if ('10 metre U wind component' in grids and
            '10 metre V wind component' in grids):
        u = grids['10 metre U wind component'].values
        v = grids['10 metre V wind component'].values
        vals = ((u ** 2) + (v ** 2)) ** 0.5
        nn = NearestNDInterpolator((G['LONS'].flatten(), G['LATS'].flatten()),
                                   vals.flatten())
        d['smps'] = nn(XI, YI)
        vals = drct(speed(u, 'MPS'), speed(v, 'MPS')).value('deg')
        nn = NearestNDInterpolator((G['LONS'].flatten(), G['LATS'].flatten()),
                                   vals.flatten())
        d['drct'] = nn(XI, YI)
    if 'Total Precipitation' in grids:
        vals = grids['Total Precipitation'].values
        nn = NearestNDInterpolator((G['LONS'].flatten(), G['LATS'].flatten()),
                                   vals.flatten())
        d['pcpn'] = nn(XI, YI)
    if 'Visibility' in grids:
        vals = grids['Visibility'].values / 1000.  # km
        nn = NearestNDInterpolator((G['LONS'].flatten(), G['LATS'].flatten()),
                                   vals.flatten())
        d['vsby'] = nn(XI, YI)

    fp.write("""{"forecast_hour": "%03i",
    "gids": [
""" % (fhour,))
    fmt = ('{"gid": %s, "tmpc": %s, "dwpc": %s, '
           '"smps": %s, "drct": %s, "vsby": %s, "pcpn": %s}')
    i = 1
    ar = []

    def f(label, row, col, fmt):
        if label not in d:
            return 'null'
        return fmt % d[label][row, col]

    for row in range(len(YAXIS)):
        for col in range(len(XAXIS)):
            ar.append(fmt % (i, f('tmpc', row, col, '%.2f'),
                             f('dwpc', row, col, '%.2f'),
                             f('smps', row, col, '%.1f'),
                             f('drct', row, col, '%i'),
                             f('vsby', row, col, '%.3f'),
                             f('pcpn', row, col, '%.2f')))
            i += 1
    fp.write(",\n".join(ar))
    fp.write("]}%s\n" % ("," if fhour != 84 else '',))
コード例 #20
0
def m15_process(nwsli, maxts):
    """ Process the 15minute file """
    fn = "%s/%s_Min15SI.dat" % (BASE, STATIONS[nwsli])
    if not os.path.isfile(fn):
        return
    lines = open(fn).readlines()
    if len(lines) < 5:
        return
    # Read header....
    headers = []
    for col in lines[1].strip().replace('"', '').split(","):
        headers.append(VARCONV.get(col.lower(), col.lower()))
    # Read data
    processed = 0
    for i in range(len(lines) - 1, 3, -1):
        tokens = lines[i].strip().replace('"', '').split(",")
        if len(tokens) != len(headers):
            continue
        valid = make_time(tokens[headers.index('timestamp')])
        if valid <= maxts:
            break
        gust_valid = make_time(tokens[headers.index('ws_mph_tmx')])
        # print valid, tokens[ headers.index('timestamp')]
        # We are ready for dbinserting, we duplicate the data for the _qc
        # column
        dbcols = ("station,valid,%s,%s") % (",".join(headers[2:]), ",".join(
            ["%s_qc" % (h, ) for h in headers[2:]]))
        dbvals = "'%s','%s-06'," % (nwsli, valid.strftime("%Y-%m-%d %H:%M:%S"))
        for v in tokens[2:]:
            dbvals += "%s," % (formatter(v), )
        for v in tokens[2:]:
            dbvals += "%s," % (formatter(v), )
        sql = "INSERT into sm_15minute (%s) values (%s)" % (dbcols,
                                                            dbvals[:-1])
        icursor.execute(sql)

        # Update IEMAccess
        # print nwsli, valid
        ob = Observation(nwsli, 'ISUSM',
                         valid.astimezone(pytz.timezone("America/Chicago")))
        tmpc = temperature(float(tokens[headers.index('tair_c_avg')]), 'C')
        if tmpc.value('F') > -50 and tmpc.value('F') < 140:
            ob.data['tmpf'] = tmpc.value('F')
            relh = humidity(float(tokens[headers.index('rh')]), '%')
            ob.data['relh'] = relh.value('%')
            ob.data['dwpf'] = met.dewpoint(tmpc, relh).value('F')
        ob.data['srad'] = tokens[headers.index('slrkw_avg')]
        ob.data['phour'] = round(
            distance(float(tokens[headers.index('rain_mm_tot')]),
                     'MM').value('IN'), 2)
        ob.data['sknt'] = float(tokens[headers.index('ws_mps_s_wvt')]) * 1.94
        ob.data['gust'] = float(tokens[headers.index('ws_mph_max')]) / 1.15
        ob.data['max_gust_ts'] = "%s-06" % (
            gust_valid.strftime("%Y-%m-%d %H:%M:%S"), )
        ob.data['drct'] = float(tokens[headers.index('winddir_d1_wvt')])
        ob.data['c1tmpf'] = temperature(
            float(tokens[headers.index('tsoil_c_avg')]), 'C').value('F')
        ob.data['c2tmpf'] = temperature(
            float(tokens[headers.index('t12_c_avg')]), 'C').value('F')
        ob.data['c3tmpf'] = temperature(
            float(tokens[headers.index('t24_c_avg')]), 'C').value('F')
        ob.data['c4tmpf'] = temperature(
            float(tokens[headers.index('t50_c_avg')]), 'C').value('F')
        ob.data['c2smv'] = float(tokens[headers.index('vwc_12_avg')]) * 100.0
        ob.data['c3smv'] = float(tokens[headers.index('vwc_24_avg')]) * 100.0
        ob.data['c4smv'] = float(tokens[headers.index('vwc_50_avg')]) * 100.0
        ob.save(accesstxn, force_current_log=True)
        # print 'soilm_ingest.py station: %s ts: %s hrly updated no data?' % (
        #                                        nwsli, valid)
        processed += 1
    return processed
コード例 #21
0
ファイル: parse0007.py プロジェクト: KayneWest/iem
if not os.path.isfile(fn):
    sys.exit(0)

lines = open(fn, 'r').readlines()
line = lines[-1]

# 114,2006,240,1530,18.17,64.70, 88.9,2.675,21.91,1014.3,0.000
tokens = line.split(",")
if (len(tokens) != 11):
    sys.exit(0)
hhmm = "%04i" % (int(tokens[3]),)
ts = now.replace(hour=int(hhmm[:2]), minute=int(hhmm[2:]), second=0,
                 microsecond=0, tzinfo=pytz.timezone("America/Chicago"))

iemob = Observation("OT0007", "OT", ts)

iemob.data['tmpf'] = float(tokens[5])
iemob.data['relh'] = float(tokens[6])
tmpf = temperature(iemob.data['tmpf'], 'F')
relh = humidity(iemob.data['relh'], '%')
iemob.data['dwpf'] = meteorology.dewpoint(tmpf, relh).value('F')
iemob.data['sknt'] = float(tokens[7]) * 1.94
iemob.data['drct'] = tokens[8]
iemob.data['pres'] = float(tokens[9]) / 960 * 28.36
iemob.save(icursor)

icursor.close()
IEM.commit()
IEM.close()
コード例 #22
0
ファイル: soilm_ingest.py プロジェクト: akrherz/iem
def m15_process(nwsli, maxts):
    """ Process the 15minute file """
    fn = "%s/%s_Min15SI.dat" % (BASE, STATIONS[nwsli])
    if not os.path.isfile(fn):
        return
    lines = open(fn).readlines()
    if len(lines) < 5:
        return
    # Read header....
    headers = []
    for col in lines[1].strip().replace('"', '').split(","):
        headers.append(VARCONV.get(col.lower(), col.lower()))
    # Read data
    processed = 0
    for i in range(len(lines)-1, 3, -1):
        tokens = lines[i].strip().replace('"', '').split(",")
        if len(tokens) != len(headers):
            continue
        valid = make_time(tokens[headers.index('timestamp')])
        if valid <= maxts:
            break
        gust_valid = make_time(tokens[headers.index('ws_mph_tmx')])
        # print valid, tokens[ headers.index('timestamp')]
        # We are ready for dbinserting, we duplicate the data for the _qc
        # column
        dbcols = ("station,valid,%s,%s"
                  ) % (",".join(headers[2:]),
                       ",".join(["%s_qc" % (h,) for h in headers[2:]]))
        dbvals = "'%s','%s-06'," % (nwsli, valid.strftime("%Y-%m-%d %H:%M:%S"))
        for v in tokens[2:]:
            dbvals += "%s," % (formatter(v),)
        for v in tokens[2:]:
            dbvals += "%s," % (formatter(v),)
        sql = "INSERT into sm_15minute (%s) values (%s)" % (dbcols,
                                                            dbvals[:-1])
        icursor.execute(sql)

        # Update IEMAccess
        # print nwsli, valid
        ob = Observation(nwsli, 'ISUSM',
                         valid.astimezone(pytz.timezone("America/Chicago")))
        tmpc = temperature(float(tokens[headers.index('tair_c_avg')]), 'C')
        if tmpc.value('F') > -50 and tmpc.value('F') < 140:
            ob.data['tmpf'] = tmpc.value('F')
            relh = humidity(float(tokens[headers.index('rh')]), '%')
            ob.data['relh'] = relh.value('%')
            ob.data['dwpf'] = met.dewpoint(tmpc, relh).value('F')
        ob.data['srad'] = tokens[headers.index('slrkw_avg')]
        ob.data['phour'] = round(
            distance(
                     float(tokens[headers.index('rain_mm_tot')]),
                     'MM').value('IN'), 2)
        ob.data['sknt'] = float(tokens[headers.index('ws_mps_s_wvt')]) * 1.94
        ob.data['gust'] = float(tokens[headers.index('ws_mph_max')]) / 1.15
        ob.data['max_gust_ts'] = "%s-06" % (
            gust_valid.strftime("%Y-%m-%d %H:%M:%S"),)
        ob.data['drct'] = float(tokens[headers.index('winddir_d1_wvt')])
        ob.data['c1tmpf'] = temperature(
                float(tokens[headers.index('tsoil_c_avg')]), 'C').value('F')
        ob.data['c2tmpf'] = temperature(
                float(tokens[headers.index('t12_c_avg')]), 'C').value('F')
        ob.data['c3tmpf'] = temperature(
                float(tokens[headers.index('t24_c_avg')]), 'C').value('F')
        ob.data['c4tmpf'] = temperature(
                float(tokens[headers.index('t50_c_avg')]), 'C').value('F')
        ob.data['c2smv'] = float(tokens[headers.index('vwc_12_avg')]) * 100.0
        ob.data['c3smv'] = float(tokens[headers.index('vwc_24_avg')]) * 100.0
        ob.data['c4smv'] = float(tokens[headers.index('vwc_50_avg')]) * 100.0
        ob.save(accesstxn, force_current_log=True)
        # print 'soilm_ingest.py station: %s ts: %s hrly updated no data?' % (
        #                                        nwsli, valid)
        processed += 1
    return processed
コード例 #23
0
lines = open(fn, "r").readlines()
lastLine = lines[-1].strip()
tokens = re.split("[\s+]+", lastLine)
if len(tokens) != 20:
    sys.exit(0)

tparts = re.split(":", tokens[3])
valid = valid.replace(hour=int(tparts[0]),
                      minute=int(tparts[1]), second=0, microsecond=0)

iem = Observation("OT0010", "OT", valid)

iem.data['tmpf'] = float(tokens[4])
iem.data['max_tmpf'] = float(tokens[5])
iem.data['min_tmpf'] = float(tokens[6])
iem.data['relh'] = int(tokens[7])
iem.data['dwpf'] = dewpoint(temperature(iem.data['tmpf'], 'F'),
                            humidity(iem.data['relh'], '%')).value("F")
iem.data['sknt'] = speed(float(tokens[8]), 'mph').value('KT')
iem.data['drct'] = int(tokens[9])
iem.data['max_sknt'] = speed(float(tokens[10]), 'mph').value('KT')
iem.data['alti'] = float(tokens[12])
iem.data['pday'] = float(tokens[13])
iem.data['srad'] = float(tokens[18])


iem.save(cursor)

cursor.close()
iemaccess.commit()
コード例 #24
0
lines = open(fn, 'r').readlines()
line = lines[-1]

# 114,2006,240,1530,18.17,64.70, 88.9,2.675,21.91,1014.3,0.000
tokens = line.split(",")
if (len(tokens) != 11):
    sys.exit(0)
hhmm = "%04i" % (int(tokens[3]), )
ts = now.replace(hour=int(hhmm[:2]),
                 minute=int(hhmm[2:]),
                 second=0,
                 microsecond=0,
                 tzinfo=pytz.timezone("America/Chicago"))

iemob = Observation("OT0007", "OT", ts)

iemob.data['tmpf'] = float(tokens[5])
iemob.data['relh'] = float(tokens[6])
tmpf = temperature(iemob.data['tmpf'], 'F')
relh = humidity(iemob.data['relh'], '%')
iemob.data['dwpf'] = meteorology.dewpoint(tmpf, relh).value('F')
iemob.data['sknt'] = float(tokens[7]) * 1.94
iemob.data['drct'] = tokens[8]
iemob.data['pres'] = float(tokens[9]) / 960 * 28.36
iemob.save(icursor)

icursor.close()
IEM.commit()
IEM.close()
コード例 #25
0
ファイル: soilm_ingest.py プロジェクト: KayneWest/iem
def hourly_process(nwsli, maxts):
    """ Process the hourly file """
    #print '-------------- HOURLY PROCESS ---------------'
    fn = "%s%s" % (BASE, STATIONS[nwsli]['hourly'].split("/")[1])
    if not os.path.isfile(fn):
        return
    lines = open(fn).readlines()
    if len(lines) < 5:
        return
    # Read header....
    headers = []
    for col in lines[1].strip().replace('"', '').split(","):
        headers.append(VARCONV.get(col.lower(), col.lower()))
    # Read data
    processed = 0
    for i in range(len(lines)-1, 3, -1):
        tokens = lines[i].strip().replace('"','').split(",")
        if len(tokens) != len(headers):
            continue
        valid = datetime.datetime.strptime(tokens[ headers.index('timestamp')],
                                           '%Y-%m-%d %H:%M:%S')
        valid = valid.replace(tzinfo=pytz.FixedOffset(-360))
        if valid <= maxts:
            break
        #print valid, tokens[ headers.index('timestamp')]
        # We are ready for dbinserting!
        dbcols = "station,valid," + ",".join(headers[2:])
        dbvals = "'%s','%s-06'," % (nwsli, valid.strftime("%Y-%m-%d %H:%M:%S"))
        for v in tokens[2:]:
            dbvals += "%s," % (formatter(v),)
        sql = "INSERT into sm_hourly (%s) values (%s)" % (dbcols, dbvals[:-1])
        icursor.execute(sql)

        # Update IEMAccess
        #print nwsli, valid
        ob = Observation(nwsli, 'ISUSM', 
                         valid.astimezone(pytz.timezone("America/Chicago")))
        tmpc = temperature(float(tokens[headers.index('tair_c_avg')]), 'C')
        if tmpc.value('F') > -50 and tmpc.value('F') < 140:
            ob.data['tmpf'] = tmpc.value('F')
            relh = humidity(float(tokens[headers.index('rh')]), '%')
            ob.data['relh'] = relh.value('%')
            ob.data['dwpf'] = met.dewpoint(tmpc, relh).value('F')
        ob.data['srad'] = tokens[headers.index('slrkw_avg')]
        ob.data['phour'] = round(
            float(tokens[headers.index('rain_mm_tot')]) / 24.5, 2)
        ob.data['sknt'] = float(tokens[headers.index('ws_mps_s_wvt')]) * 1.94
        ob.data['gust'] = float(tokens[headers.index('ws_mph_max')]) / 1.15
        ob.data['drct'] = float(tokens[headers.index('winddir_d1_wvt')])
        ob.data['c1tmpf'] = temperature(
                float(tokens[headers.index('tsoil_c_avg')]), 'C').value('F')
        ob.data['c2tmpf'] = temperature(
                float(tokens[headers.index('t12_c_avg')]), 'C').value('F')
        ob.data['c3tmpf'] = temperature(
                float(tokens[headers.index('t24_c_avg')]), 'C').value('F')
        ob.data['c4tmpf'] = temperature(
                float(tokens[headers.index('t50_c_avg')]), 'C').value('F')
        ob.data['c2smv'] = float(tokens[headers.index('vwc_12_avg')]) * 100.0
        ob.data['c3smv'] = float(tokens[headers.index('vwc_24_avg')]) * 100.0
        ob.data['c4smv'] = float(tokens[headers.index('vwc_50_avg')]) * 100.0
        ob.save(accesstxn)
        #    print 'soilm_ingest.py station: %s ts: %s hrly updated no data?' % (
        #                                        nwsli, valid)
        processed += 1
    return processed
コード例 #26
0
ファイル: fxgridder.py プロジェクト: wkelongws/iemgrid
def write_grids(fp, valid, fhour):
    """Do the write to disk"""
    gribfn = "%s/%sF%03i.grib2" % (TMP, valid.strftime("%Y%m%d%H%M"), fhour)
    if not os.path.isfile(gribfn):
        print("Skipping write_grids because of missing fn: %s" % (gribfn, ))
        return
    gribs = pygrib.open(gribfn)
    grids = dict()
    for grib in gribs:
        grids[grib.name] = grib
    d = dict()
    if '2 metre temperature' in grids:
        g = grids['2 metre temperature']
        if G['LATS'] is None:
            G['LATS'], G['LONS'] = g.latlons()
        vals = temperature(g.values, 'K').value('C')
        nn = NearestNDInterpolator((G['LONS'].flatten(), G['LATS'].flatten()),
                                   vals.flatten())
        d['tmpc'] = nn(XI, YI)
        if 'Relative humidity' in grids:
            g = grids['Relative humidity']
            vals = g.values
            nn = NearestNDInterpolator(
                (G['LONS'].flatten(), G['LATS'].flatten()), vals.flatten())
            rh = nn(XI, YI)
            d['dwpc'] = dewpoint(temperature(d['tmpc'], 'C'),
                                 humidity(rh, '%')).value('C')
    if ('10 metre U wind component' in grids
            and '10 metre V wind component' in grids):
        u = grids['10 metre U wind component'].values
        v = grids['10 metre V wind component'].values
        vals = ((u**2) + (v**2))**0.5
        nn = NearestNDInterpolator((G['LONS'].flatten(), G['LATS'].flatten()),
                                   vals.flatten())
        d['smps'] = nn(XI, YI)
        vals = drct(speed(u, 'MPS'), speed(v, 'MPS')).value('deg')
        nn = NearestNDInterpolator((G['LONS'].flatten(), G['LATS'].flatten()),
                                   vals.flatten())
        d['drct'] = nn(XI, YI)
    if 'Total Precipitation' in grids:
        vals = grids['Total Precipitation'].values
        nn = NearestNDInterpolator((G['LONS'].flatten(), G['LATS'].flatten()),
                                   vals.flatten())
        d['pcpn'] = nn(XI, YI)
    if 'Visibility' in grids:
        vals = grids['Visibility'].values / 1000.  # km
        nn = NearestNDInterpolator((G['LONS'].flatten(), G['LATS'].flatten()),
                                   vals.flatten())
        d['vsby'] = nn(XI, YI)

    fp.write("""{"forecast_hour": "%03i",
    "gids": [
""" % (fhour, ))
    fmt = ('{"gid": %s, "tmpc": %s, "dwpc": %s, '
           '"smps": %s, "drct": %s, "vsby": %s, "pcpn": %s}')
    i = 1
    ar = []

    def f(label, row, col, fmt):
        if label not in d:
            return 'null'
        return fmt % d[label][row, col]

    for row in range(len(YAXIS)):
        for col in range(len(XAXIS)):
            ar.append(
                fmt %
                (i, f('tmpc', row, col, '%.2f'), f('dwpc', row, col, '%.2f'),
                 f('smps', row, col, '%.1f'), f('drct', row, col, '%i'),
                 f('vsby', row, col, '%.3f'), f('pcpn', row, col, '%.2f')))
            i += 1
    fp.write(",\n".join(ar))
    fp.write("]}%s\n" % ("," if fhour != 84 else '', ))
コード例 #27
0
ファイル: snet_sub1min.py プロジェクト: akrherz/DEV
def main():
    """Go Main Go"""
    valid = []
    pres = []
    sped = []
    drct = []
    tmpf = []
    dwpf = []
    pday = []
    lines = []
    now = datetime.datetime(2018, 4, 13, 0, 0)

    for line in open('jefferson.txt'):
        if line.find("Min") > 0 or line.find("Max") > 0:
            continue
        ts = datetime.datetime.strptime(line[7:21], '%H:%M %m/%d/%y')
        if len(lines) == 0:
            now = ts
        if ts == now:
            lines.append(line)
            continue
        # Spread obs
        now = ts
        delta = 60.0 / len(lines)
        for line in lines:
            ts += datetime.timedelta(seconds=delta)
            t = float(line[42:45])
            rhval = float(line[47:50])
            tmpf.append(t)
            dwpf.append(dewpoint(temperature(t, 'F'),
                                 humidity(rhval, '%')).value("F"))
            pres.append(float(line[52:57]) * 33.86375)
            sped.append(float(line[26:28]))
            pday.append(float(line[59:64]))
            drct.append(float(txt2drct[line[22:25].strip()]) - 20.0)
            # Clock was not in CDT
            valid.append(ts + datetime.timedelta(minutes=60))
        lines = []

    sts = datetime.datetime(2018, 4, 13, 17, 0)
    ets = datetime.datetime(2018, 4, 13, 18, 0)
    interval = datetime.timedelta(minutes=15)
    xticks = []
    xticklabels = []
    now = sts
    while now < ets:
        fmt = ":%M"
        if now.minute == 0 or not xticks:
            fmt = "%-I:%M %p"
        xticks.append(now)
        xticklabels.append(now.strftime(fmt))

        now += interval

    fig, ax = plt.subplots(3, 1, sharex=True)

    """
    fancybox = mpatches.FancyBboxPatch(
            [mx.DateTime.DateTime(2012,5,3,8,6).ticks(),
            40], 60*18, 50,
            boxstyle='round', alpha=0.2, facecolor='#7EE5DE', edgecolor='#EEEEEE',
            zorder=1)
    ax[0].add_patch( fancybox)
    """
    ax[0].plot(valid, np.array(tmpf), label='Air')
    # print("%s %s" % (tmpf, max(tmpf)))
    ax[0].plot(valid, np.array(dwpf), color='g', label='Dew Point')
    # ax[0].set_ylim(40, 92)
    ax[1].scatter(valid, drct, zorder=2)
    ax2 = ax[1].twinx()
    ax2.plot(valid, sped, 'r')
    ax2.set_ylabel("Wind Speed [mph]")

    ax[2].plot(valid, pres, 'b', label="Pressure [mb]")
    ax[2].set_ylim(1006, 1014)
    #ax3 = ax[2].twinx()
    #ax3.plot(valid, pday, 'r')
    #ax3.set_ylabel("Daily Precip [inch]")

    ax[0].set_xticks(xticks)
    ax[0].set_xticklabels(xticklabels)
    ax[0].set_xlim(sts, ets)
    prop = matplotlib.font_manager.FontProperties(size=12)

    ax[0].legend(loc=2, prop=prop, ncol=2)
    ax[2].legend(loc=1, prop=prop)
    ax[0].grid(True)
    ax[1].grid(True)
    ax[2].grid(True)
    ax[0].set_title("Jefferson SchoolNet8 Site (~ $\Delta$6 second data)")
    ax[2].set_xlabel("Afternoon of 13 Apr 2018")
    #ax[2].set_ylabel("Pressure [mb]")
    #[t.set_color('red') for t in ax3.yaxis.get_ticklines()]
    #[t.set_color('red') for t in ax3.yaxis.get_ticklabels()]
    [t.set_color('red') for t in ax2.yaxis.get_ticklines()]
    [t.set_color('red') for t in ax2.yaxis.get_ticklabels()]
    [t.set_color('b') for t in ax[2].yaxis.get_ticklines()]
    [t.set_color('b') for t in ax[2].yaxis.get_ticklabels()]
    #[t.set_color('b') for t in ax[0].yaxis.get_ticklines()]
    #[t.set_color('b') for t in ax[0].yaxis.get_ticklabels()]
    [t.set_color('b') for t in ax[1].yaxis.get_ticklines()]
    [t.set_color('b') for t in ax[1].yaxis.get_ticklabels()]
    ax[1].set_ylabel("Wind Direction")
    ax[0].set_ylabel("Temperature $^{\circ}\mathrm{F}$")
    ax[1].set_yticks(np.arange(0, 361, 90))
    ax[1].set_ylim(0, 361)
    ax[1].set_yticklabels(['N', 'E', 'S', 'W', 'N'])
    ax[2].set_ylim(min(pres) - 2, max(pres) + 4)
    fig.savefig('test.png')