예제 #1
0
def plotter(fdict):
    """ Go """
    import seaborn as sns

    ctx = get_autoplot_context(fdict, get_description())
    phenomena = ctx["p"]
    date = ctx.get("date")
    wfo = ctx["wfo"]
    pgconn = get_dbconn("postgis")
    ps = [phenomena]
    if phenomena == "_A":
        ps = ["TO", "SV"]
    df = read_sql(
        """
        SELECT issue at time zone 'UTC' as issue,
        tml_direction, tml_sknt from sbw
        WHERE phenomena in %s and wfo = %s and status = 'NEW' and
        tml_direction is not null and tml_sknt is not null ORDER by issue
    """,
        pgconn,
        params=(tuple(ps), wfo),
    )
    if df.empty:
        raise NoDataFound("No Data Found.")

    g = sns.jointplot(
        df["tml_direction"],
        speed(df["tml_sknt"], "KT").value("MPH"),
        s=40,
        stat_func=None,
        zorder=1,
        color="tan",
    ).plot_joint(sns.kdeplot, n_levels=6)
    g.ax_joint.set_xlabel("Storm Motion From Direction")
    g.ax_joint.set_ylabel("Storm Speed [MPH]")
    g.ax_joint.set_xticks(range(0, 361, 45))
    g.ax_joint.set_xticklabels(
        ["N", "NE", "E", "SE", "S", "SW", "W", "NW", "N"])
    if date:
        df2 = df[df["issue"].dt.date == date]
        g.ax_joint.scatter(
            df2["tml_direction"],
            speed(df2["tml_sknt"], "KT").value("MPH"),
            color="r",
            s=50,
            label=date.strftime("%b %-d, %Y"),
            zorder=2,
        )
    g.ax_joint.legend()
    g.ax_joint.grid()
    g.ax_marg_x.set_title(("NWS %s\n%s Storm Motion\n"
                           "%s warnings ploted between %s and %s") % (
                               ctx["_nt"].sts[wfo]["name"],
                               PDICT[phenomena],
                               len(df.index),
                               df["issue"].min().date().strftime("%b %-d, %Y"),
                               df["issue"].max().date().strftime("%b %-d, %Y"),
                           ))
    g.fig.subplots_adjust(top=0.9)
    return g.fig, df
예제 #2
0
파일: p59.py 프로젝트: muthulatha/iem
def plotter(fdict):
    """ Go """
    import matplotlib
    matplotlib.use('agg')
    import matplotlib.pyplot as plt
    ASOS = psycopg2.connect(database='asos', host='iemdb', user='******')
    cursor = ASOS.cursor(cursor_factory=psycopg2.extras.DictCursor)

    station = fdict.get('station', 'AMW')
    units = fdict.get('units', 'mph')
    network = fdict.get('network', 'IA_ASOS')

    nt = NetworkTable(network)

    cursor.execute("""
    SELECT extract(doy from valid), sknt * 0.514, drct from alldata
    where station = %s and sknt >= 0 and drct >= 0
    """, (station, ))

    uwnd = np.zeros((366,), 'f')
    vwnd = np.zeros((366,), 'f')
    cnt = np.zeros((366,), 'f')
    for row in cursor:
        u, v = uv(row[1], row[2])
        uwnd[int(row[0]) - 1] += u
        vwnd[int(row[0]) - 1] += v
        cnt[int(row[0]) - 1] += 1

    u = speed(uwnd / cnt, 'MPS').value(units.upper())
    v = speed(vwnd / cnt, 'mps').value(units.upper())

    df = pd.DataFrame(dict(u=pd.Series(u),
                           v=pd.Series(v),
                           day_of_year=pd.Series(np.arange(1, 366))))

    (fig, ax) = plt.subplots(1, 1)

    ax.plot(np.arange(1, 366), smooth(u[:-1], 14, 'hamming'), color='r',
            label='u, West(+) : East(-) component')
    ax.plot(np.arange(1, 366), smooth(v[:-1], 14, 'hamming'), color='b',
            label='v, South(+) : North(-) component')
    ax.set_xticks([1, 32, 60, 91, 121, 152, 182, 213, 244, 274, 305, 335, 365])
    ax.set_xticklabels(calendar.month_abbr[1:])
    ax.legend(ncol=2, fontsize=11, loc=(0., -0.15))
    ax.grid(True)
    ax.set_xlim(0, 366)
    ax.set_title(("[%s] %s Daily Average Component Wind Speed\n"
                  "[%s-%s] 14 day smooth filter applied, %.0f obs found"
                  "") % (station, nt.sts[station]['name'],
                         nt.sts[station]['archive_begin'].year,
                         datetime.datetime.now().year, np.sum(cnt)))
    ax.set_ylabel("Average Wind Speed %s" % (PDICT.get(units), ))

    box = ax.get_position()
    ax.set_position([box.x0, box.y0 + box.height * 0.1, box.width,
                     box.height * 0.9])

    return fig, df
예제 #3
0
파일: 1minute.py 프로젝트: akrherz/DEV
def main():
    """Go Main"""
    pgconn = get_dbconn('asos')
    df = read_sql("""
    SELECT valid - '1 hour'::interval as valid,
    drct, sknt, gust_sknt, pres1, tmpf, dwpf
    from t2018_1minute
    where station = %s and valid >= '2018-06-14 08:30' and
    valid <= '2018-06-14 10:15' ORDER by valid ASC
    """, pgconn, params=('PHP', ), index_col='valid')
    xticks = []
    xticklabels = []
    for valid in df.index.values:
        if pd.to_datetime(valid).minute % 15 == 0:
            xticks.append(valid)
            ts = pd.to_datetime(valid) - datetime.timedelta(hours=5)
            xticklabels.append(ts.strftime("%-H:%M\n%p"))

    fig = plt.figure(figsize=(8, 9))
    ax = fig.add_axes([0.1, 0.55, 0.75, 0.35])
    ax.plot(df.index.values, df['tmpf'], label='Air Temp')
    ax.plot(df.index.values, df['dwpf'], label='Dew Point')
    ax.legend()
    ax.grid(True)
    ax.set_ylabel("Temperature $^\circ$F")
    ax.set_xticks(xticks)
    ax.set_xticklabels(xticklabels)
    ax.set_title(("Philip, SD (KPHP) ASOS 1 Minute Interval Data for 14 Jun 2018\n"
                  "Heat Burst Event, data missing in NCEI files 8:02 to 8:10 AM"))

    ax = fig.add_axes([0.1, 0.08, 0.75, 0.35])

    ax.bar(df.index.values, speed(df['gust_sknt'], 'KT').value('MPH'),
           width=1/1440., color='red')
    ax.bar(df.index.values, speed(df['sknt'], 'KT').value('MPH'),
           width=1/1440., color='tan')
    ax.set_ylabel("Wind Speed (tan) & Gust (red) [mph]")
    ax.grid(True, zorder=5)
    ax.set_ylim(0, 60)

    ax2 = ax.twinx()
    ax2.plot(df.index.values, pressure(df['pres1'], 'IN').value('MB'),
             color='g', lw=2)
    ax2.set_ylabel("Air Pressure [hPa]", color='green')
    ax2.set_xticks(xticks)
    ax2.set_xticklabels(xticklabels)
    ax.set_xlabel("14 June 2018 MDT")
    ax2.set_ylim(923, 926)
    ax2.set_yticks(np.arange(923, 926.1, 0.5))
    # ax2.set_zorder(ax.get_zorder()-1)
    # ax2.set_ylim(0, 360)
    # ax2.set_yticks(range(0, 361, 45))
    # ax2.set_yticklabels(['N', 'NE', 'E', 'SE', 'S', 'SW', 'W', 'NW', 'N'])

    fig.savefig('test.png')
예제 #4
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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
예제 #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
        # 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
예제 #6
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파일: ingest.py 프로젝트: akrherz/datateam
def read_excel(siteid, fn):
    df = pd.read_excel(fn, skiprows=[1, ])
    newcols = {}
    for k in df.columns:
        newcols[k] = XREF.get(k, k)
    df.rename(columns=newcols, inplace=True)
    df['valid'] = df['valid'] + datetime.timedelta(hours=TZREF[siteid])
    # do some conversions
    print("ALERT: doing windspeed unit conv")
    df['windspeed_mps'] = speed(df['windspeed_mps'].values, 'KMH').value('MPS')
    print("ALERT: doing windgustunit conv")
    df['windgust_mps'] = speed(df['windgust_mps'].values, 'KMH').value('MPS')
    return df
예제 #7
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def plotter(fdict):
    """ Go """
    import seaborn as sns
    ctx = get_autoplot_context(fdict, get_description())
    phenomena = ctx['p']
    date = ctx.get('date')
    wfo = ctx['wfo']
    pgconn = get_dbconn('postgis')
    ps = [phenomena]
    if phenomena == '_A':
        ps = ['TO', 'SV']
    df = read_sql("""
        SELECT issue at time zone 'UTC' as issue,
        tml_direction, tml_sknt from sbw
        WHERE phenomena in %s and wfo = %s and status = 'NEW' and
        tml_direction is not null and tml_sknt is not null ORDER by issue
    """,
                  pgconn,
                  params=(tuple(ps), wfo))
    if df.empty:
        raise NoDataFound("No Data Found.")

    g = sns.jointplot(df['tml_direction'],
                      speed(df['tml_sknt'], 'KT').value('MPH'),
                      s=40,
                      stat_func=None,
                      zorder=1,
                      color='tan').plot_joint(sns.kdeplot, n_levels=6)
    g.ax_joint.set_xlabel("Storm Motion From Direction")
    g.ax_joint.set_ylabel("Storm Speed [MPH]")
    g.ax_joint.set_xticks(range(0, 361, 45))
    g.ax_joint.set_xticklabels(
        ['N', 'NE', 'E', 'SE', 'S', 'SW', 'W', 'NW', 'N'])
    if date:
        df2 = df[df['issue'].dt.date == date]
        g.ax_joint.scatter(df2['tml_direction'],
                           speed(df2['tml_sknt'], 'KT').value('MPH'),
                           color='r',
                           s=50,
                           label=date.strftime("%b %-d, %Y"),
                           zorder=2)
    g.ax_joint.legend()
    g.ax_joint.grid()
    g.ax_marg_x.set_title(
        ("NWS %s\n%s Storm Motion\n"
         "%s warnings ploted between %s and %s") %
        (ctx['_nt'].sts[wfo]['name'], PDICT[phenomena], len(
            df.index), df['issue'].min().date().strftime("%b %-d, %Y"),
         df['issue'].max().date().strftime("%b %-d, %Y")))
    g.fig.subplots_adjust(top=.9)
    return g.fig, df
예제 #8
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def test_uv():
    """ Test calculation of uv wind components """
    speed = datatypes.speed([10, ], 'KT')
    mydir = datatypes.direction([0, ], 'DEG')
    u, v = meteorology.uv(speed, mydir)
    assert u.value("KT") == 0.
    assert v.value("KT") == -10.

    speed = datatypes.speed([10, 20, 15], 'KT')
    mydir = datatypes.direction([90, 180, 135], 'DEG')
    u, v = meteorology.uv(speed, mydir)
    assert u.value("KT")[0] == -10
    assert v.value("KT")[1] == 20.
    assert abs(v.value("KT")[2] - 10.6) < 0.1
예제 #9
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def test_uv():
    """ Test calculation of uv wind components """
    speed = datatypes.speed([10], "KT")
    mydir = datatypes.direction([0], "DEG")
    u, v = meteorology.uv(speed, mydir)
    assert u.value("KT") == 0.0
    assert v.value("KT") == -10.0

    speed = datatypes.speed([10, 20, 15], "KT")
    mydir = datatypes.direction([90, 180, 135], "DEG")
    u, v = meteorology.uv(speed, mydir)
    assert u.value("KT")[0] == -10
    assert v.value("KT")[1] == 20.0
    assert abs(v.value("KT")[2] - 10.6) < 0.1
예제 #10
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    def test_uv(self):
        """ Test calculation of uv wind components """
        speed = datatypes.speed([10,], 'KT')
        mydir = datatypes.direction([0,], 'DEG')
        u,v = meteorology.uv(speed, mydir)
        self.assertEqual(u.value("KT"), 0.)
        self.assertEqual(v.value("KT"), -10.)

        speed = datatypes.speed([10,20,15], 'KT')
        mydir = datatypes.direction([90,180,135], 'DEG')
        u,v = meteorology.uv(speed, mydir)
        self.assertEqual(u.value("KT")[0], -10)
        self.assertEqual(v.value("KT")[1], 20.)
        self.assertAlmostEquals(v.value("KT")[2], 10.6, 1)
예제 #11
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def rabbit_tracks(row):
    """Generate a rabbit track for this attr"""
    res = ""
    if row['sknt'] is None or row['sknt'] <= 5 or row['drct'] is None:
        return res
    # 5 carrots at six minutes to get 30 minutes?
    lat0 = row['lat']
    lon0 = row['lon']
    drct = row['drct']
    sknt = row['sknt']
    x0, y0 = P3857(lon0, lat0)
    smps = speed(sknt, 'KTS').value('MPS')
    angle = dir2ccwrot(drct)
    rotation = (drct + 180) % 360
    rad = math.radians(angle)
    x = x0 + math.cos(rad) * smps * SECONDS
    y = y0 + math.sin(rad) * smps * SECONDS
    # Draw white line out 30 minutes
    lons, lats = P3857(x, y, inverse=True)
    res += ("Line: 1, 0, \"Cell [%s]\"\n"
            "%.4f, %.4f\n"
            "%.4f, %.4f\n"
            "END:\n") % (row['storm_id'], lat0, lon0, lats[-1], lons[-1])
    for i in range(3):
        res += ("Icon: %.4f,%.4f,%.0f,1,10,\"+%.0f min\"\n") % (
            lats[i], lons[i], rotation, (i + 1) * 15)
    return res
예제 #12
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 def wind_message(self):
     """Convert this into a Jabber style message"""
     drct = 0
     sknt = 0
     time = self.time.replace(tzinfo=timezone.utc)
     if self.wind_gust:
         sknt = self.wind_gust.value("KT")
         if self.wind_dir:
             drct = self.wind_dir.value()
     if self.wind_speed_peak:
         v1 = self.wind_speed_peak.value("KT")
         d1 = self.wind_dir_peak.value()
         t1 = self.peak_wind_time.replace(tzinfo=timezone.utc)
         if v1 > sknt:
             sknt = v1
             drct = d1
             time = t1
     key = "%s;%s;%s" % (self.station_id, sknt, time)
     if key not in WIND_ALERTS:
         WIND_ALERTS[key] = 1
         speed = datatypes.speed(sknt, "KT")
         return ("gust of %.0f knots (%.1f mph) from %s @ %s") % (
             speed.value("KT"),
             speed.value("MPH"),
             drct2text(drct),
             time.strftime("%H%MZ"),
         )
예제 #13
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def one():
    """option 1"""
    icursor = ISUAG.cursor()
    iemcursor = IEM.cursor()
    icursor.execute(
        """
        SELECT station, valid, ws_mps_s_wvt, winddir_d1_wvt, rain_mm_tot,
        tair_c_max, tair_c_min
        from sm_daily
    """
    )

    for row in icursor:
        avg_sknt = speed(row[2], "MPS").value("KT")
        avg_drct = row[3]
        pday = distance(row[4], "MM").value("IN")
        high = temperature(row[5], "C").value("F")
        low = temperature(row[6], "C").value("F")
        iemcursor.execute(
            """
        UPDATE summary SET avg_sknt = %s, vector_avg_drct = %s, pday = %s,
        max_tmpf = %s, min_tmpf = %s
        WHERE
        iemid = (select iemid from stations WHERE network = 'ISUSM' and
        id = %s) and day = %s
        """,
            (avg_sknt, avg_drct, pday, high, low, row[0], row[1]),
        )
    iemcursor.close()
    IEM.commit()
    IEM.close()
예제 #14
0
파일: p82.py 프로젝트: jamayfieldjr/iem
def plotter(fdict):
    """ Go """
    pgconn = get_dbconn('iem')
    cursor = pgconn.cursor(cursor_factory=psycopg2.extras.DictCursor)

    ctx = get_autoplot_context(fdict, get_description())
    station = ctx['station']
    varname = ctx['var']
    sdate = ctx['sdate']
    edate = ctx['edate']

    # Get Climatology
    cdf = read_sql("""
        SELECT to_char(valid, 'mmdd') as sday, high, low,
        (high + low) / 2. as avg,
        precip from ncdc_climate81 WHERE station = %s
    """, get_dbconn('coop'),
                   params=(
                       ctx['_nt'].sts[station]['ncdc81'],), index_col='sday')
    if cdf.empty:
        raise NoDataFound("No Data Found.")

    cursor.execute("""
    SELECT day, max_tmpf, min_tmpf, max_dwpf, min_dwpf,
    (max_tmpf + min_tmpf) / 2. as avg_tmpf,
    pday, coalesce(avg_sknt, 0) as avg_sknt from summary s JOIN stations t
    on (t.iemid = s.iemid) WHERE s.day >= %s and s.day <= %s and
    t.id = %s and t.network = %s ORDER by day ASC
    """, (sdate, edate, station, ctx['network']))
    rows = []
    data = {}
    for row in cursor:
        hd = row['max_tmpf'] - cdf.at[row[0].strftime("%m%d"), 'high']
        ld = row['min_tmpf'] - cdf.at[row[0].strftime("%m%d"), 'low']
        ad = row['avg_tmpf'] - cdf.at[row[0].strftime("%m%d"), 'avg']
        rows.append(dict(day=row['day'], max_tmpf=row['max_tmpf'],
                         avg_smph=speed(row['avg_sknt'], 'KT').value('MPH'),
                         min_dwpf=row['min_dwpf'], max_dwpf=row['max_dwpf'],
                         high_departure=hd, low_departure=ld,
                         avg_departure=ad,
                         min_tmpf=row['min_tmpf'], pday=row['pday']))
        data[row[0]] = {'val': safe(rows[-1], varname)}
        if data[row[0]]['val'] == '0':
            data[row[0]]['color'] = 'k'
        elif varname == 'high_departure':
            data[row[0]]['color'] = 'b' if hd < 0 else 'r'
        elif varname == 'low_departure':
            data[row[0]]['color'] = 'b' if ld < 0 else 'r'
        elif varname == 'avg_departure':
            data[row[0]]['color'] = 'b' if ad < 0 else 'r'
    df = pd.DataFrame(rows)

    title = '[%s] %s Daily %s' % (
        station, ctx['_nt'].sts[station]['name'], PDICT.get(varname))
    subtitle = '%s thru %s' % (
        sdate.strftime("%-d %b %Y"), edate.strftime("%-d %b %Y"))

    fig = calendar_plot(
        sdate, edate, data, title=title, subtitle=subtitle)
    return fig, df
예제 #15
0
파일: l3attr.py 프로젝트: akrherz/iem
def rabbit_tracks(row):
    """Generate a rabbit track for this attr"""
    res = ""
    if row['sknt'] is None or row['sknt'] <= 5 or row['drct'] is None:
        return res
    # 5 carrots at six minutes to get 30 minutes?
    lat0 = row['lat']
    lon0 = row['lon']
    drct = row['drct']
    sknt = row['sknt']
    x0, y0 = P3857(lon0, lat0)
    smps = speed(sknt, 'KTS').value('MPS')
    angle = dir2ccwrot(drct)
    rotation = (drct + 180) % 360
    rad = math.radians(angle)
    x = x0 + math.cos(rad) * smps * SECONDS
    y = y0 + math.sin(rad) * smps * SECONDS
    # Draw white line out 30 minutes
    lons, lats = P3857(x, y, inverse=True)
    res += ("Line: 1, 0, \"Cell [%s]\"\n"
            "%.4f, %.4f\n"
            "%.4f, %.4f\n"
            "END:\n") % (row['storm_id'],
                         lat0, lon0, lats[-1], lons[-1])
    for i in range(3):
        res += ("Icon: %.4f,%.4f,%.0f,1,10,\"+%.0f min\"\n"
                ) % (lats[i], lons[i], rotation, (i+1)*15)
    return res
예제 #16
0
파일: l3attr.py 프로젝트: Xawwell/iem
def rabbit_tracks(row):
    """Generate a rabbit track for this attr"""
    res = ""
    if row["sknt"] is None or row["sknt"] <= 5 or row["drct"] is None:
        return res
    # 5 carrots at six minutes to get 30 minutes?
    lat0 = row["lat"]
    lon0 = row["lon"]
    drct = row["drct"]
    sknt = row["sknt"]
    x0, y0 = P3857(lon0, lat0)
    smps = speed(sknt, "KTS").value("MPS")
    angle = dir2ccwrot(drct)
    rotation = (drct + 180) % 360
    rad = math.radians(angle)
    x = x0 + math.cos(rad) * smps * SECONDS
    y = y0 + math.sin(rad) * smps * SECONDS
    # Draw white line out 30 minutes
    lons, lats = P3857(x, y, inverse=True)
    res += (
        'Line: 1, 0, "Cell [%s]"\n' "%.4f, %.4f\n" "%.4f, %.4f\n" "END:\n"
    ) % (row["storm_id"], lat0, lon0, lats[-1], lons[-1])
    for i in range(3):
        res += ('Icon: %.4f,%.4f,%.0f,1,10,"+%.0f min"\n') % (
            lats[i],
            lons[i],
            rotation,
            (i + 1) * 15,
        )
    return res
예제 #17
0
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/ot0002.dat")

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

    lines = open(fn, "r").readlines()
    lastline = lines[-1]
    tokens = re.split(r"[\s+]+", lastline)

    tparts = re.split(":", tokens[4])
    valid = valid.replace(hour=int(tparts[0]),
                          minute=int(tparts[1]),
                          second=int(tparts[2]))

    iem = Observation("OT0002", "OT", valid)

    sknt = speed(float(tokens[8]), 'MPH').value('KT')

    iem.data['sknt'] = sknt
    iem.data['drct'] = tokens[9]
    iem.data['tmpf'] = tokens[7]

    iem.save(cursor)

    cursor.close()
    iemaccess.commit()
예제 #18
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def daily_process(nwsli, maxts):
    """ Process the daily file """
    fn = "%s/%s_DailySI.dat" % (BASE, STATIONS[nwsli])
    df = common_df_logic(fn, maxts, nwsli, "sm_daily")
    if df is None:
        return 0
    LOG.debug("processing %s rows from %s", len(df.index), fn)
    processed = 0
    acursor = ACCESS.cursor()
    for _i, row in df.iterrows():
        # Need a timezone
        valid = datetime.datetime(
            row["valid"].year, row["valid"].month, row["valid"].day, 12, 0
        )
        valid = valid.replace(tzinfo=pytz.timezone("America/Chicago"))
        ob = Observation(nwsli, "ISUSM", valid)
        ob.data["max_tmpf"] = temperature(row["tair_c_max_qc"], "C").value("F")
        ob.data["min_tmpf"] = temperature(row["tair_c_min_qc"], "C").value("F")
        ob.data["pday"] = round(
            distance(row["rain_mm_tot_qc"], "MM").value("IN"), 2
        )
        if valid not in EVENTS["days"]:
            EVENTS["days"].append(valid)
        ob.data["et_inch"] = distance(row["dailyet_qc"], "MM").value("IN")
        ob.data["srad_mj"] = row["slrmj_tot_qc"]
        # Someday check if this is apples to apples here
        ob.data["vector_avg_drct"] = row["winddir_d1_wvt_qc"]
        if ob.data["max_tmpf"] is None:
            EVENTS["reprocess_temps"] = True
        if ob.data["srad_mj"] == 0 or np.isnan(ob.data["srad_mj"]):
            LOG.info(
                "soilm_ingest.py station: %s ts: %s has 0 solar",
                nwsli,
                valid.strftime("%Y-%m-%d"),
            )
            EVENTS["reprocess_solar"] = True
        if "ws_mps_max" in df.columns:
            ob.data["max_sknt"] = speed(row["ws_mps_max_qc"], "MPS").value(
                "KT"
            )
        ob.data["avg_sknt"] = speed(row["ws_mps_s_wvt_qc"], "MPS").value("KT")
        ob.save(acursor)

        processed += 1
    acursor.close()
    ACCESS.commit()
    return processed
예제 #19
0
def main():
    """Go Main Go"""
    pgconn = get_dbconn("coop")
    cursor = pgconn.cursor()

    # Need to have a merge of windspeed and average rh
    dsm = {}
    ipgconn = get_dbconn("iem")
    icursor = ipgconn.cursor()
    icursor.execute("""
        select day, avg_sknt, avg_rh from summary where iemid = 37004
        and day >= '1980-01-01' ORDER by day ASC""")
    for row in icursor:
        if row[1] is None or row[2] is None:
            dsm[row[0]] = dsm[row[0] - datetime.timedelta(days=1)]
        else:
            dsm[row[0]] = {
                "wind_speed": speed(row[1], "KTS").value("MPS"),
                "avg_rh": row[2],
            }

    os.chdir("baseline")
    for fn in glob.glob("*.met"):
        location = fn[:-4]
        cursor.execute(
            """
            DELETE from yieldfx_baseline where station = %s
        """,
            (location, ),
        )
        LOG.info("Removed %s rows for station: %s", cursor.rowcount, location)
        for line in open(fn):
            line = line.strip()
            if not line.startswith("19") and not line.startswith("20"):
                continue
            tokens = line.split()
            valid = datetime.date(int(
                tokens[0]), 1, 1) + datetime.timedelta(days=int(tokens[1]) - 1)
            cursor.execute(
                """
            INSERT into yieldfx_baseline (station, valid,
            radn, maxt, mint, rain, windspeed, rh)
            VALUES (%s, %s, %s, %s, %s, %s, %s, %s)
            """,
                (
                    location,
                    valid,
                    float(tokens[2]),
                    float(tokens[3]),
                    float(tokens[4]),
                    float(tokens[5]),
                    dsm[valid]["wind_speed"],
                    dsm[valid]["avg_rh"],
                ),
            )

    cursor.close()
    pgconn.commit()
    pgconn.close()
예제 #20
0
파일: p71.py 프로젝트: akrherz/iem
def plotter(fdict):
    """ Go """
    import matplotlib
    matplotlib.use('agg')
    import matplotlib.pyplot as plt
    import matplotlib.patheffects as PathEffects
    pgconn = psycopg2.connect(database='iem', host='iemdb', user='******')
    cursor = pgconn.cursor(cursor_factory=psycopg2.extras.DictCursor)

    station = fdict.get('zstation', 'AMW')
    network = fdict.get('network', 'IA_ASOS')
    units = fdict.get('units', 'MPH').upper()
    if units not in PDICT:
        units = 'MPH'
    year = int(fdict.get('year', datetime.datetime.now().year))
    month = int(fdict.get('month', datetime.datetime.now().month))
    sts = datetime.date(year, month, 1)
    ets = (sts + datetime.timedelta(days=35)).replace(day=1)
    nt = NetworkTable(network)

    cursor.execute("""
      SELECT day, avg_sknt, vector_avg_drct from summary s JOIN stations t
      ON (t.iemid = s.iemid) WHERE t.id = %s and t.network = %s and
      s.day >= %s and s.day < %s ORDER by day ASC
    """, (station, network, sts, ets))
    days = []
    drct = []
    sknt = []
    for row in cursor:
        if row[1] is None:
            continue
        days.append(row[0].day)
        drct.append(row[2])
        sknt.append(row[1])
    if len(sknt) == 0:
        return "ERROR: No Data Found"
    df = pd.DataFrame(dict(day=pd.Series(days),
                           drct=pd.Series(drct),
                           sknt=pd.Series(sknt)))
    sknt = speed(np.array(sknt), 'KT').value(units)
    (fig, ax) = plt.subplots(1, 1)
    ax.bar(np.array(days)-0.4, sknt, ec='green', fc='green')
    pos = max([min(sknt) / 2.0, 0.5])
    for d, _, r in zip(days, sknt, drct):
        draw_line(plt, d, max(sknt)+0.5, (270. - r) / 180. * np.pi)
        txt = ax.text(d, pos, drct2text(r), ha='center', rotation=90,
                      color='white', va='center')
        txt.set_path_effects([PathEffects.withStroke(linewidth=2,
                                                     foreground="k")])
    ax.grid(True, zorder=11)
    ax.set_title(("%s [%s]\n%s Daily Average Wind Speed and Direction"
                  ) % (nt.sts[station]['name'], station,
                       sts.strftime("%b %Y")))
    ax.set_xlim(0.5, max(days)+0.5)
    ax.set_ylim(top=max(sknt)+2)

    ax.set_ylabel("Average Wind Speed [%s]" % (PDICT.get(units),))

    return fig, df
예제 #21
0
def plotter(fdict):
    """ Go """
    pgconn = get_dbconn('iem')
    cursor = pgconn.cursor(cursor_factory=psycopg2.extras.DictCursor)
    ctx = get_autoplot_context(fdict, get_description())
    station = ctx['zstation']
    network = ctx['network']
    units = ctx['units']
    year = ctx['year']
    month = ctx['month']
    sts = datetime.date(year, month, 1)
    ets = (sts + datetime.timedelta(days=35)).replace(day=1)
    nt = NetworkTable(network)

    cursor.execute(
        """
      SELECT day, avg_sknt, vector_avg_drct from summary s JOIN stations t
      ON (t.iemid = s.iemid) WHERE t.id = %s and t.network = %s and
      s.day >= %s and s.day < %s ORDER by day ASC
    """, (station, network, sts, ets))
    days = []
    drct = []
    sknt = []
    for row in cursor:
        if row[1] is None:
            continue
        days.append(row[0].day)
        drct.append(row[2])
        sknt.append(row[1])
    if not sknt:
        raise ValueError("ERROR: No Data Found")
    df = pd.DataFrame(
        dict(day=pd.Series(days), drct=pd.Series(drct), sknt=pd.Series(sknt)))
    sknt = speed(np.array(sknt), 'KT').value(units)
    (fig, ax) = plt.subplots(1, 1)
    ax.bar(np.array(days), sknt, ec='green', fc='green', align='center')
    pos = max([min(sknt) / 2.0, 0.5])
    for d, _, r in zip(days, sknt, drct):
        draw_line(d, max(sknt) + 0.5, (270. - r) / 180. * np.pi)
        txt = ax.text(d,
                      pos,
                      drct2text(r),
                      ha='center',
                      rotation=90,
                      color='white',
                      va='center')
        txt.set_path_effects(
            [PathEffects.withStroke(linewidth=2, foreground="k")])
    ax.grid(True, zorder=11)
    ax.set_title(("%s [%s]\n%s Daily Average Wind Speed and Direction") %
                 (nt.sts[station]['name'], station, sts.strftime("%b %Y")))
    ax.set_xlim(0.5, 31.5)
    ax.set_xticks(range(1, 31, 5))
    ax.set_ylim(top=max(sknt) + 2)

    ax.set_ylabel("Average Wind Speed [%s]" % (PDICT.get(units), ))

    return fig, df
예제 #22
0
def uv(speed, direction):
    """
    Compute the u and v components of the wind
    @param wind speed in whatever units
    @param dir wind direction with zero as north
    @return u and v components
    """
    if (not isinstance(speed, dt.speed) or
            not isinstance(direction, dt.direction)):
        raise InvalidArguments(("uv() needs speed and direction "
                                "objects as args"))
    # Get radian units
    rad = direction.value("RAD")
    if rad is None or speed.value() is None:
        return None, None
    u = (0 - speed.value()) * np.sin(rad)
    v = (0 - speed.value()) * np.cos(rad)
    return (dt.speed(u, speed.get_units()), dt.speed(v, speed.get_units()))
예제 #23
0
    def test_uv(self):
        """ Test calculation of uv wind components """
        speed = datatypes.speed([
            10,
        ], 'KT')
        mydir = datatypes.direction([
            0,
        ], 'DEG')
        u, v = meteorology.uv(speed, mydir)
        self.assertEqual(u.value("KT"), 0.)
        self.assertEqual(v.value("KT"), -10.)

        speed = datatypes.speed([10, 20, 15], 'KT')
        mydir = datatypes.direction([90, 180, 135], 'DEG')
        u, v = meteorology.uv(speed, mydir)
        self.assertEqual(u.value("KT")[0], -10)
        self.assertEqual(v.value("KT")[1], 20.)
        self.assertAlmostEquals(v.value("KT")[2], 10.6, 1)
예제 #24
0
def uv(speed, direction):
    """
    Compute the u and v components of the wind
    @param wind speed in whatever units
    @param dir wind direction with zero as north
    @return u and v components
    """
    if not isinstance(speed, dt.speed) or not isinstance(
            direction, dt.direction):
        raise InvalidArguments(("uv() needs speed and direction "
                                "objects as args"))
    # Get radian units
    rad = direction.value("RAD")
    if rad is None or speed.value() is None:
        return None, None
    u = (0 - speed.value()) * np.sin(rad)
    v = (0 - speed.value()) * np.cos(rad)
    return (dt.speed(u, speed.get_units()), dt.speed(v, speed.get_units()))
예제 #25
0
파일: parse0010.py 프로젝트: 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()
예제 #26
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def daily_process(nwsli, maxts):
    """ Process the daily file """
    # print '-------------- DAILY PROCESS ----------------'
    fn = "%s/%s_DailySI.dat" % (BASE, STATIONS[nwsli])
    df = common_df_logic(fn, maxts, nwsli, "sm_daily")
    if df is None:
        return 0
    LOG.debug("processing %s rows from %s", len(df.index), fn)
    processed = 0
    acursor = ACCESS.cursor()
    for _i, row in df.iterrows():
        # Need a timezone
        valid = datetime.datetime(row['valid'].year, row['valid'].month,
                                  row['valid'].day, 12, 0)
        valid = valid.replace(tzinfo=pytz.timezone("America/Chicago"))
        ob = Observation(nwsli, 'ISUSM', valid)
        ob.data['max_tmpf'] = temperature(row['tair_c_max_qc'], 'C').value('F')
        ob.data['min_tmpf'] = temperature(row['tair_c_min_qc'], 'C').value('F')
        ob.data['pday'] = round(distance(row['rain_mm_tot_qc'],
                                         'MM').value('IN'), 2)
        if valid not in EVENTS['days']:
            EVENTS['days'].append(valid)
        ob.data['et_inch'] = distance(row['dailyet_qc'], 'MM').value('IN')
        ob.data['srad_mj'] = row['slrmj_tot_qc']
        # Someday check if this is apples to apples here
        ob.data['vector_avg_drct'] = row['winddir_d1_wvt_qc']
        if ob.data['max_tmpf'] is None:
            EVENTS['reprocess_temps'] = True
        if ob.data['srad_mj'] == 0 or np.isnan(ob.data['srad_mj']):
            LOG.info(
                "soilm_ingest.py station: %s ts: %s has 0 solar",
                nwsli, valid.strftime("%Y-%m-%d")
            )
            EVENTS['reprocess_solar'] = True
        if 'ws_mps_max' in df.columns:
            ob.data['max_sknt'] = speed(row['ws_mps_max_qc'],
                                        'MPS').value('KT')
        ob.data['avg_sknt'] = speed(row['ws_mps_s_wvt_qc'], 'MPS').value('KT')
        ob.save(acursor)

        processed += 1
    acursor.close()
    ACCESS.commit()
    return processed
예제 #27
0
    def test_vectorized(self):
        """See that heatindex and windchill can do lists"""
        temp = datatypes.temperature([0, 10], 'F')
        sknt = datatypes.speed([30, 40], 'MPH')
        val = meteorology.windchill(temp, sknt).value('F')
        self.assertAlmostEquals(val[0], -24.50, 2)

        t = datatypes.temperature([80.0, 90.0], 'F')
        td = datatypes.temperature([70.0, 60.0], 'F')
        hdx = meteorology.heatindex(t, td)
        self.assertAlmostEqual(hdx.value("F")[0], 83.93, 2)
예제 #28
0
파일: p82.py 프로젝트: akrherz/iem
def plotter(fdict):
    """ Go """
    import matplotlib
    matplotlib.use('agg')
    from pyiem.plot import calendar_plot
    pgconn = psycopg2.connect(database='iem', host='iemdb', user='******')
    cursor = pgconn.cursor(cursor_factory=psycopg2.extras.DictCursor)

    ctx = get_autoplot_context(fdict, get_description())
    station = ctx['station']
    varname = ctx['var']
    network = ctx['network']
    sdate = ctx['sdate']
    edate = ctx['edate']

    nt = NetworkTable(network)

    # Get Climatology
    cdf = read_sql("""SELECT to_char(valid, 'mmdd') as sday, high, low,
    precip from ncdc_climate81 WHERE station = %s
    """, psycopg2.connect(database='coop', host='iemdb', user='******'),
                   params=(nt.sts[station]['ncdc81'],), index_col='sday')

    cursor.execute("""
    SELECT day, max_tmpf, min_tmpf, max_dwpf, min_dwpf,
    pday, coalesce(avg_sknt, 0) as avg_sknt from summary s JOIN stations t
    on (t.iemid = s.iemid) WHERE s.day >= %s and s.day <= %s and
    t.id = %s and t.network = %s ORDER by day ASC
    """, (sdate, edate, station, network))
    rows = []
    data = {}
    for row in cursor:
        hd = row['max_tmpf'] - cdf.at[row[0].strftime("%m%d"), 'high']
        ld = row['min_tmpf'] - cdf.at[row[0].strftime("%m%d"), 'low']
        rows.append(dict(day=row['day'], max_tmpf=row['max_tmpf'],
                         avg_smph=speed(row['avg_sknt'], 'KT').value('MPH'),
                         min_dwpf=row['min_dwpf'], max_dwpf=row['max_dwpf'],
                         high_departure=hd, low_departure=ld,
                         min_tmpf=row['min_tmpf'], pday=row['pday']))
        data[row[0]] = {'val': safe(rows[-1], varname)}
        if varname == 'high_departure':
            data[row[0]]['color'] = 'b' if hd < 0 else 'r'
        elif varname == 'low_departure':
            data[row[0]]['color'] = 'b' if ld < 0 else 'r'
    df = pd.DataFrame(rows)

    title = ('[%s] %s Daily %s\n%s thru %s'
             ) % (station, nt.sts[station]['name'],
                  PDICT.get(varname), sdate.strftime("%-d %b %Y"),
                  edate.strftime("%-d %b %Y"))

    fig = calendar_plot(sdate, edate, data,
                        title=title)
    return fig, df
예제 #29
0
def plotter(fdict):
    """ Go """
    import matplotlib
    matplotlib.use('agg')
    from pyiem.plot import calendar_plot
    pgconn = psycopg2.connect(database='iem', host='iemdb', user='******')
    cursor = pgconn.cursor(cursor_factory=psycopg2.extras.DictCursor)

    ctx = get_autoplot_context(fdict, get_description())
    station = ctx['station']
    varname = ctx['var']
    network = ctx['network']
    sdate = ctx['sdate']
    edate = ctx['edate']

    nt = NetworkTable(network)

    # Get Climatology
    cdf = read_sql("""SELECT to_char(valid, 'mmdd') as sday, high, low,
    precip from ncdc_climate81 WHERE station = %s
    """, psycopg2.connect(database='coop', host='iemdb', user='******'),
                   params=(nt.sts[station]['ncdc81'],), index_col='sday')

    cursor.execute("""
    SELECT day, max_tmpf, min_tmpf, max_dwpf, min_dwpf,
    pday, coalesce(avg_sknt, 0) as avg_sknt from summary s JOIN stations t
    on (t.iemid = s.iemid) WHERE s.day >= %s and s.day <= %s and
    t.id = %s and t.network = %s ORDER by day ASC
    """, (sdate, edate, station, network))
    rows = []
    data = {}
    for row in cursor:
        hd = row['max_tmpf'] - cdf.at[row[0].strftime("%m%d"), 'high']
        ld = row['min_tmpf'] - cdf.at[row[0].strftime("%m%d"), 'low']
        rows.append(dict(day=row['day'], max_tmpf=row['max_tmpf'],
                         avg_smph=speed(row['avg_sknt'], 'KT').value('MPH'),
                         min_dwpf=row['min_dwpf'], max_dwpf=row['max_dwpf'],
                         high_departure=hd, low_departure=ld,
                         min_tmpf=row['min_tmpf'], pday=row['pday']))
        data[row[0]] = {'val': safe(rows[-1], varname)}
        if varname == 'high_departure':
            data[row[0]]['color'] = 'b' if hd < 0 else 'r'
        elif varname == 'low_departure':
            data[row[0]]['color'] = 'b' if ld < 0 else 'r'
    df = pd.DataFrame(rows)

    title = ('[%s] %s Daily %s\n%s thru %s'
             ) % (station, nt.sts[station]['name'],
                  PDICT.get(varname), sdate.strftime("%-d %b %Y"),
                  edate.strftime("%-d %b %Y"))

    fig = calendar_plot(sdate, edate, data,
                        title=title)
    return fig, df
예제 #30
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def do_windalerts(obs):
    """Iterate through the obs and do wind alerts where appropriate"""
    for sid in obs:
        # Problem sites with lightning issues
        if sid in [
                "RBFI4",
                "RTMI4",
                "RWII4",
                "RCAI4",
                "RDYI4",
                "RDNI4",
                "RCDI4",
                "RCII4",
                "RCLI4",
                "VCTI4",
                "RGAI4",
                "RAVI4",
        ]:
            continue
        ob = obs[sid]
        # screening
        if ob.get("gust") is None or ob["gust"] < 40:
            continue
        if np.isnan(ob["gust"]):
            continue
        smph = speed(ob["gust"], "KT").value("MPH")
        if smph < 50:
            continue
        if smph > 100:
            print(("process_rwis did not relay gust %.1f MPH from %s"
                   "") % (smph, sid))
            continue
        # Use a hacky tmp file to denote a wind alert that was sent
        fn = "/tmp/iarwis.%s.%s" % (sid, ob["valid"].strftime("%Y%m%d%H%M"))
        if os.path.isfile(fn):
            continue
        o = open(fn, "w")
        o.write(" ")
        o.close()
        lts = ob["valid"].astimezone(pytz.timezone("America/Chicago"))
        stname = NT.sts[sid]["name"]
        msg = ("At %s, a wind gust of %.1f mph (%.1f kts) was recorded "
               "at the %s (%s) Iowa RWIS station"
               "") % (lts.strftime("%I:%M %p %d %b %Y"), smph, ob["gust"],
                      stname, sid)
        mt = MIMEText(msg)
        mt["From"] = "*****@*****.**"
        # mt['To'] = '*****@*****.**'
        mt["To"] = "*****@*****.**"
        mt["Subject"] = "Iowa RWIS Wind Gust %.0f mph %s" % (smph, stname)
        s = smtplib.SMTP("mailhub.iastate.edu")
        s.sendmail(mt["From"], [mt["To"]], mt.as_string())
        s.quit()
예제 #31
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파일: ingest.py 프로젝트: akrherz/datateam
def googlesheet(siteid, sheetkey):
    """Harvest a google sheet, please"""
    rows = []
    config = util.get_config()
    sheets = util.get_sheetsclient(config, "td")
    f = sheets.spreadsheets().get(spreadsheetId=sheetkey, includeGridData=True)
    j = util.exponential_backoff(f.execute)
    for sheet in j['sheets']:
        # sheet_title = sheet['properties']['title']
        for griddata in sheet['data']:
            for row, rowdata in enumerate(griddata['rowData']):
                if 'values' not in rowdata:  # empty sheet
                    continue
                if row == 1:  # skip units
                    continue
                if row == 0:
                    header = []
                    for col, celldata in enumerate(rowdata['values']):
                        header.append(celldata['formattedValue'])
                    continue
                data = {}
                for col, celldata in enumerate(rowdata['values']):
                    data[header[col]] = fmt(celldata.get('formattedValue'))
                rows.append(data)
    df = pd.DataFrame(rows)
    print("googlesheet has columns: %s" % (repr(df.columns.values),))
    newcols = {}
    for k in df.columns:
        newcols[k] = XREF.get(k, k)
    df.rename(columns=newcols, inplace=True)
    df['valid'] = pd.to_datetime(df['valid'], errors='raise',
                                 format='%m/%d/%y %H:%M')
    df['valid'] = df['valid'] + datetime.timedelta(hours=TZREF[siteid])

    # do some conversions
    print("ALERT: doing windspeed unit conv")
    df['windspeed_mps'] = speed(df['windspeed_mps'].values, 'KMH').value('MPS')
    print("ALERT: doing windgustunit conv")
    df['windgust_mps'] = speed(df['windgust_mps'].values, 'KMH').value('MPS')
    return df
예제 #32
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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()
예제 #33
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def windrose(station, database='asos', months=np.arange(1, 13),
             hours=np.arange(0, 24), sts=datetime.datetime(1970, 1, 1),
             ets=datetime.datetime(2050, 1, 1), units="mph", nsector=36,
             justdata=False, rmax=None, cursor=None, sname=None,
             sknt=None, drct=None, valid=None, level=None, bins=[]):
    """Utility function that generates a windrose plot

    Args:
      station (str): station identifier to search database for
      database (str,optional): database name to look for data within
      months (list,optional): optional list of months to limit plot to
      hours (list,optional): optional list of hours to limit plot to
      sts (datetime,optional): start datetime
      ets (datetime,optional): end datetime
      units (str,optional): units to plot values as
      nsector (int,optional): number of bins to devide the windrose into
      justdata (boolean,optional): if True, write out the data only
      cursor (psycopg2.cursor,optional): provide a database cursor to run the
        query against.
      sname (str,optional): The name of this station, if not specified it will
        default to the ((`station`)) identifier
      sknt (list,optional): A list of wind speeds in knots already generated
      drct (list,optional): A list of wind directions (deg N) already generated
      valid (list,optional): A list of valid datetimes (with tzinfo set)
      level (int,optional): In case of RAOB, which level interests us (hPa)
      bins (list,optional): bins to use for the wind speed

    Returns:
      matplotlib.Figure instance or textdata
    """
    monthinfo = _get_timeinfo(months, 'month', 12)
    hourinfo = _get_timeinfo(hours, 'hour', 24)

    if sknt is None or drct is None:
        df = _get_data(station, cursor, database, sts, ets, monthinfo,
                       hourinfo, level)
    else:
        df = pd.DataFrame({'sknt': sknt, 'drct': drct, 'valid': valid})
    # Convert wind speed into the units we want here
    if df['sknt'].max() > 0:
        df['speed'] = speed(df['sknt'].values, 'KT').value(units.upper())
    if justdata:
        return _make_textresult(station, df, units, nsector, sname,
                                monthinfo, hourinfo, level,
                                bins)
    if len(df.index) < 5 or not df['sknt'].max() > 0:
        fig = plt.figure(figsize=(6, 7), dpi=80, facecolor='w', edgecolor='w')
        fig.text(0.17, 0.89, 'Not enough data available to generate plot')
        return fig

    return _make_plot(station, df, units, nsector, rmax, hours, months,
                      sname, level, bins)
예제 #34
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파일: raw2obs.py 프로젝트: stormchas4/iem
def do(ts):
    """ Do a UTC date's worth of data"""
    pgconn = get_dbconn("hads")
    table = ts.strftime("raw%Y_%m")
    sts = datetime.datetime(ts.year, ts.month, ts.day).replace(tzinfo=pytz.utc)
    ets = sts + datetime.timedelta(hours=24)
    df = read_sql(
        f"""
        SELECT station, valid, substr(key, 1, 3) as vname, value
        from {table} WHERE valid >= %s and valid < %s and
        substr(key, 1, 3) in ('USI', 'UDI', 'TAI', 'TDI')
        and value > -999
    """,
        pgconn,
        params=(sts, ets),
        index_col=None,
    )
    if df.empty:
        print("No data found for hads/raw2obs.py date: %s" % (ts, ))
        return

    pdf = pd.pivot_table(df,
                         values="value",
                         index=["station", "valid"],
                         columns="vname")
    if "USI" in pdf.columns:
        pdf["sknt"] = speed(pdf["USI"].values, "MPH").value("KT")

    table = ts.strftime("t%Y")
    data = StringIO()
    for (station, valid), row in pdf.iterrows():
        data.write(("%s\t%s\t%s\t%s\t%s\t%s\n") % (
            station,
            valid.strftime("%Y-%m-%d %H:%M:%S+00"),
            v(row.get("TAI")),
            v(row.get("TDI")),
            v(row.get("UDI")),
            v(row.get("sknt")),
        ))
    cursor = pgconn.cursor()
    cursor.execute(f"DELETE from {table} WHERE valid between %s and %s",
                   (sts, ets))
    data.seek(0)
    cursor.copy_from(
        data,
        table,
        columns=("station, valid", "tmpf", "dwpf", "drct", "sknt"),
        null="null",
    )
    cursor.close()
    pgconn.commit()
예제 #35
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def test_drct():
    """Conversion of u and v to direction"""
    r = meteorology.drct(datatypes.speed(np.array([10, 20]), 'KT'),
                         datatypes.speed(np.array([10, 20]),
                                         'KT')).value("DEG")
    assert r[0] == 225
    r = meteorology.drct(datatypes.speed(-10, 'KT'),
                         datatypes.speed(10, 'KT')).value("DEG")
    assert r == 135
    r = meteorology.drct(datatypes.speed(-10, 'KT'),
                         datatypes.speed(-10, 'KT')).value("DEG")
    assert r == 45
    r = meteorology.drct(datatypes.speed(10, 'KT'),
                         datatypes.speed(-10, 'KT')).value("DEG")
    assert r == 315
예제 #36
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 def test_drct(self):
     """Conversion of u and v to direction"""
     self.assertEquals(
         meteorology.drct(datatypes.speed(np.array([10, 20]), 'KT'),
                          datatypes.speed(np.array([10, 20]), 'KT')
                          ).value("DEG")[0], 225)
     self.assertEquals(meteorology.drct(datatypes.speed(-10, 'KT'),
                                        datatypes.speed(10, 'KT')
                                        ).value("DEG"), 135)
     self.assertEquals(meteorology.drct(datatypes.speed(-10, 'KT'),
                                        datatypes.speed(-10, 'KT')
                                        ).value("DEG"), 45)
     self.assertEquals(meteorology.drct(datatypes.speed(10, 'KT'),
                                        datatypes.speed(-10, 'KT')
                                        ).value("DEG"), 315)
예제 #37
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 def test_drct(self):
     """Conversion of u and v to direction"""
     self.assertEquals(
         meteorology.drct(datatypes.speed(np.array([10, 20]), 'KT'),
                          datatypes.speed(np.array([10, 20]),
                                          'KT')).value("DEG")[0], 225)
     self.assertEquals(
         meteorology.drct(datatypes.speed(-10, 'KT'),
                          datatypes.speed(10, 'KT')).value("DEG"), 135)
     self.assertEquals(
         meteorology.drct(datatypes.speed(-10, 'KT'),
                          datatypes.speed(-10, 'KT')).value("DEG"), 45)
     self.assertEquals(
         meteorology.drct(datatypes.speed(10, 'KT'),
                          datatypes.speed(-10, 'KT')).value("DEG"), 315)
예제 #38
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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()
예제 #39
0
파일: today_gust.py 프로젝트: trentford/iem
def main():
    """Go Main Go"""

    now = datetime.datetime.now()
    pgconn = get_dbconn('iem', user='******')
    icursor = pgconn.cursor()

    # Compute normal from the climate database
    sql = """
      select s.id, s.network,
      ST_x(s.geom) as lon, ST_y(s.geom) as lat,
      greatest(c.max_sknt, c.max_gust) as wind
      from summary_%s c, current c2, stations s
      WHERE s.iemid = c.iemid and c2.valid > 'TODAY' and c.day = 'TODAY'
      and c2.iemid = s.iemid
      and (s.network ~* 'ASOS' or s.network = 'AWOS') and s.country = 'US'
      ORDER by lon, lat
    """ % (now.year, )

    lats = []
    lons = []
    vals = []
    valmask = []
    icursor.execute(sql)
    for row in icursor:
        if row[4] == 0 or row[4] is None:
            continue
        lats.append(row[3])
        lons.append(row[2])
        vals.append(speed(row[4], 'KT').value('MPH'))
        valmask.append((row[1] in ['AWOS', 'IA_ASOS']))

    if len(vals) < 5 or True not in valmask:
        return

    clevs = np.arange(0, 40, 2)
    clevs = np.append(clevs, np.arange(40, 80, 5))
    clevs = np.append(clevs, np.arange(80, 120, 10))

    # Iowa
    pqstr = "plot ac %s summary/today_gust.png iowa_wind_gust.png png" % (
        now.strftime("%Y%m%d%H%M"), )
    mp = MapPlot(title="Iowa ASOS/AWOS Peak Wind Speed Reports",
                 subtitle="%s" % (now.strftime("%d %b %Y"), ),
                 sector='iowa')
    mp.contourf(lons, lats, vals, clevs, units='MPH')
    mp.plot_values(lons, lats, vals, '%.0f', valmask=valmask, labelbuffer=10)
    mp.drawcounties()
    mp.postprocess(pqstr=pqstr, view=False)
    mp.close()
예제 #40
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파일: run_metro.py 프로젝트: akrherz/metro
def make_rwis(i, j, initts, oldncout):
    """ Generate spinup file """
    i = i - IOFFSET
    j = j - JOFFSET

    o = open('rwis.xml', 'w')
    o.write("""<?xml version="1.0"?>
<observation>
 <header>
  <filetype>rwis-observation</filetype>
  <version>1.0</version>
  <road-station>oaa</road-station>
  </header>
  <measure-list>""")
    if oldncout is None:
        fake_rwis(o, initts)
        return

    ts0 = find_initts(oldncout)
    # at Air Temp in C
    tmpc = dt.temperature(oldncout.variables['tmpk'][:, i, j], 'K').value('C')
    # td Dew point in C
    dwpc = dt.temperature(oldncout.variables['dwpk'][:, i, j], 'K').value('C')
    # pi presence of precipitation 0: No -- 1: Yes
    # ws wind speed in km / hr
    ws = dt.speed(oldncout.variables['wmps'][:, i, j], 'MPS').value('KMH')
    # sc condition code  1=DryCond 2=Wet 3=Ice 4=MixWaterSnow
    #                    5=dew 6=Meltsnow 7=Frost 8=Ice
    # Was set to 33 for SSI ?
    icond = oldncout.variables['icond'][:, i, j]
    # st road surface temp
    bridgec = dt.temperature(
        oldncout.variables['bdeckt'][:, i, j], 'K').value('C')
    # sst sub surface temp
    subsfc = dt.temperature(
        oldncout.variables['subsfct'][:, i, j], 'K').value('C')
    t1 = initts + datetime.timedelta(hours=12)
    for tstep in range(4, len(oldncout.dimensions['time']), 4):
        ts = ts0 + datetime.timedelta(
                                minutes=int(oldncout.variables['time'][tstep]))
        if ts > t1:
            break
        o.write("""<measure><observation-time>%s</observation-time>
<at>%.2f</at><td>%.2f</td><pi>0</pi><ws>%.2f</ws><sc>%s</sc><st>%.2f</st>
<sst>%.2f</sst></measure>
      """ % (ts.strftime("%Y-%m-%dT%H:%MZ"), tmpc[tstep], dwpc[tstep],
             ws[tstep], icond[tstep], bridgec[tstep], subsfc[tstep]))

    o.write("</measure-list></observation>")
    o.close()
예제 #41
0
파일: p138.py 프로젝트: akrherz/iem
def plotter(fdict):
    """ Go """
    import matplotlib
    matplotlib.use('agg')
    import matplotlib.pyplot as plt
    pgconn = psycopg2.connect(database='asos', host='iemdb', user='******')
    ctx = get_autoplot_context(fdict, get_description())

    station = ctx['zstation']
    network = ctx['network']
    units = ctx['units']

    nt = NetworkTable(network)

    df = read_sql("""
        select date_trunc('hour', valid) as ts, avg(sknt) as sknt,
        max(drct) as drct from alldata
        WHERE station = %s and sknt is not null and drct is not null
        GROUP by ts
        """, pgconn, params=(station, ), parse_dates=('ts',),
                  index_col=None)
    sknt = speed(df['sknt'].values, 'KT')
    drct = direction(df['drct'].values, 'DEG')
    df['u'], df['v'] = [x.value('MPS') for x in meteorology.uv(sknt, drct)]
    df['month'] = df['ts'].dt.month
    grp = df[['month', 'u', 'v', 'sknt']].groupby('month').mean()
    grp['u_%s' % (units,)] = speed(grp['u'].values, 'KT').value(units.upper())
    grp['v_%s' % (units,)] = speed(grp['u'].values, 'KT').value(units.upper())
    grp['sped_%s' % (units,)] = speed(grp['sknt'].values,
                                      'KT').value(units.upper())
    drct = meteorology.drct(speed(grp['u'].values, 'KT'),
                            speed(grp['v'].values, 'KT'))
    grp['drct'] = drct.value('DEG')
    maxval = grp['sped_%s' % (units,)].max()
    (fig, ax) = plt.subplots(1, 1)
    ax.barh(grp.index.values, grp['sped_%s' % (units,)].values,
            align='center')
    ax.set_xlabel("Average Wind Speed [%s]" % (UNITS[units],))
    ax.set_yticks(grp.index.values)
    ax.set_yticklabels(calendar.month_abbr[1:])
    ax.grid(True)
    ax.set_xlim(0, maxval * 1.2)
    for mon, row in grp.iterrows():
        ax.text(maxval * 1.1, mon, drct2text(row['drct']), ha='center',
                va='center', bbox=dict(color='white'))
        ax.text(row['sped_%s' % (units,)] * 0.98, mon,
                "%.1f" % (row['sped_%s' % (units,)],), ha='right',
                va='center', bbox=dict(color='white',
                                       boxstyle='square,pad=0.03',))
    ax.set_ylim(12.5, 0.5)
    ax.set_title(("[%s] %s [%s-%s]\nMonthly Average Wind Speed and"
                  " Vector Average Direction"
                  ) % (station, nt.sts[station]['name'],
                       df['ts'].min().year,
                       df['ts'].max().year))

    return fig, grp
예제 #42
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def do(valid, frame):
    """ Generate plot for a given timestamp """

    cursor.execute(
        """select turbineid, power, ST_x(geom), ST_y(geom), yaw,
    windspeed 
     from sampled_data s JOIN turbines t on (t.id = s.turbineid) 
     WHERE valid = %s and power is not null and yaw is not null
     and windspeed is not null""", (valid, ))
    lons = []
    lats = []
    vals = []
    u = []
    v = []
    for row in cursor:
        lons.append(row[2])
        lats.append(row[3])
        vals.append(row[1])
        a, b = uv(speed(row[5], 'MPS'), direction(row[4], 'deg'))
        u.append(a.value('MPS'))
        v.append(b.value('MPS'))
    vals = np.array(vals)
    avgv = np.average(vals)
    vals2 = vals - avgv
    print valid, min(vals2), max(vals2)
    (fig, ax) = plt.subplots(1, 1)

    cmap = plt.cm.get_cmap('RdYlBu_r')
    cmap.set_under('white')

    cmap.set_over('black')
    clevs = np.arange(-300, 301, 50)
    norm = mpcolors.BoundaryNorm(clevs, cmap.N)
    ax.quiver(lons, lats, u, v, zorder=1)
    ax.scatter(lons,
               lats,
               c=vals2,
               vmin=-500,
               vmax=500,
               cmap=cmap,
               s=100,
               zorder=2)
    ax.set_title(
        "Pomeroy Farm Turbine Power [kW] Diff from Farm Avg (1min sampled dataset)\nValid: %s"
        % (valid.strftime("%d %b %Y %I:%M %p")))
    make_colorbar(clevs, norm, cmap)
    fig.savefig('power_movie/frame%05i.png' % (frame, ))

    plt.close()
예제 #43
0
def computeOthers(d):
    r = {}
    # Need something to compute other values needed for output
    for sid in d.keys():
        ob = d[sid]
        ob["ticks"] = calendar.timegm(ob['utc_valid'].timetuple())
        if ob['sknt'] is not None:
            ob["sped"] = ob["sknt"] * 1.17
        if ob.get('tmpf') is not None and ob.get('dwpf') is not None:
            tmpf = temperature(ob['tmpf'], 'F')
            dwpf = temperature(ob['dwpf'], 'F')
            ob["relh"] = meteorology.relh(tmpf, dwpf).value('%')
        else:
            ob['relh'] = None
        if ob['relh'] == 'M':
            ob['relh'] = None

        if (ob.get('tmpf') is not None and ob.get('dwpf') is not None and
                ob.get('sped') is not None):
            tmpf = temperature(ob['tmpf'], 'F')
            dwpf = temperature(ob['dwpf'], 'F')
            sknt = speed(ob['sped'], 'MPH')
            ob["feel"] = meteorology.feelslike(tmpf, dwpf, sknt).value("F")
        else:
            ob['feel'] = None
        if ob['feel'] == 'M':
            ob['feel'] = None

        ob["altiTend"] = 'S'
        ob["drctTxt"] = util.drct2text(ob["drct"])
        if ob["max_drct"] is None:
            ob["max_drct"] = 0
        ob["max_drctTxt"] = util.drct2text(ob["max_drct"])
        ob["20gu"] = 0
        if ob['gust'] is not None:
            ob["gmph"] = ob["gust"] * 1.17
        if ob['max_gust'] is not None:
            ob["max_sped"] = ob["max_gust"] * 1.17
        else:
            ob['max_sped'] = 0
        ob['pday'] = 0 if ob['pday'] is None else ob['pday']
        ob['pmonth'] = 0 if ob['pmonth'] is None else ob['pmonth']
        ob["gtim"] = "0000"
        ob["gtim2"] = "12:00 AM"
        if ob["max_gust_ts"] is not None and ob["max_gust_ts"] != "null":
            ob["gtim"] = ob["max_gust_ts"].strftime("%H%M")
            ob["gtim2"] = ob["max_gust_ts"].strftime("%-I:%M %p")
        r[sid] = ob
    return r
예제 #44
0
def computeOthers(d):
    r = {}
    # Need something to compute other values needed for output
    for sid in d.keys():
        ob = d[sid]
        ob["ticks"] = calendar.timegm(ob['utc_valid'].timetuple())
        if ob['sknt'] is not None:
            ob["sped"] = ob["sknt"] * 1.17
        if ob.get('tmpf') is not None and ob.get('dwpf') is not None:
            tmpf = temperature(ob['tmpf'], 'F')
            dwpf = temperature(ob['dwpf'], 'F')
            ob["relh"] = meteorology.relh(tmpf, dwpf).value('%')
        else:
            ob['relh'] = None
        if ob['relh'] == 'M':
            ob['relh'] = None

        if (ob.get('tmpf') is not None and ob.get('dwpf') is not None and
                ob.get('sped') is not None):
            tmpf = temperature(ob['tmpf'], 'F')
            dwpf = temperature(ob['dwpf'], 'F')
            sknt = speed(ob['sped'], 'MPH')
            ob["feel"] = meteorology.feelslike(tmpf, dwpf, sknt).value("F")
        else:
            ob['feel'] = None
        if ob['feel'] == 'M':
            ob['feel'] = None

        ob["altiTend"] = 'S'
        ob["drctTxt"] = util.drct2text(ob["drct"])
        if ob["max_drct"] is None:
            ob["max_drct"] = 0
        ob["max_drctTxt"] = util.drct2text(ob["max_drct"])
        ob["20gu"] = 0
        if ob['gust'] is not None:
            ob["gmph"] = ob["gust"] * 1.17
        if ob['max_gust'] is not None:
            ob["max_sped"] = ob["max_gust"] * 1.17
        else:
            ob['max_sped'] = 0
        ob['pday'] = 0 if ob['pday'] is None else ob['pday']
        ob['pmonth'] = 0 if ob['pmonth'] is None else ob['pmonth']
        ob["gtim"] = "0000"
        ob["gtim2"] = "12:00 AM"
        if ob["max_gust_ts"] is not None and ob["max_gust_ts"] != "null":
            ob["gtim"] = ob["max_gust_ts"].strftime("%H%M")
            ob["gtim2"] = ob["max_gust_ts"].strftime("%-I:%M %p")
        r[sid] = ob
    return r
예제 #45
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def windrose(station, database='asos', months=np.arange(1, 13),
             hours=np.arange(0, 24), sts=datetime.datetime(1970, 1, 1),
             ets=datetime.datetime(2050, 1, 1), units="mph", nsector=36,
             justdata=False, rmax=None, cursor=None, sname=None,
             sknt=None, drct=None, level=None, bins=[]):
    """Utility function that generates a windrose plot

    Args:
      station (str): station identifier to search database for
      database (str,optional): database name to look for data within
      months (list,optional): optional list of months to limit plot to
      hours (list,optional): optional list of hours to limit plot to
      sts (datetime,optional): start datetime
      ets (datetime,optional): end datetime
      units (str,optional): units to plot values as
      nsector (int,optional): number of bins to devide the windrose into
      justdata (boolean,optional): if True, write out the data only
      cursor (psycopg2.cursor,optional): provide a database cursor to run the
        query against.
      sname (str,optional): The name of this station, if not specified it will
        default to the ((`station`)) identifier
      sknt (list,optional): A list of wind speeds in knots already generated
      drct (list,optional): A list of wind directions (deg N) already generated
      level (int,optional): In case of RAOB, which level interests us (hPa)
      bins (list,optional): bins to use for the wind speed

    Returns:
      matplotlib.Figure instance or textdata
    """
    monthinfo = _get_timeinfo(months, 'month', 12)
    hourinfo = _get_timeinfo(hours, 'hour', 24)

    if sknt is None or drct is None:
        (sknt, drct, minvalid, maxvalid) = _get_data(station, cursor, database,
                                                     sts, ets, monthinfo,
                                                     hourinfo, level)
    sknt = speed(sknt, 'KT').value(units.upper())
    if justdata:
        return _make_textresult(station, sknt, drct, units, nsector, sname,
                                minvalid, maxvalid, monthinfo, hourinfo, level,
                                bins)
    if len(sknt) < 5 or np.max(sknt) < 1:
        fig = plt.figure(figsize=(6, 7), dpi=80, facecolor='w', edgecolor='w')
        fig.text(0.17, 0.89, 'Not enough data available to generate plot')
        return fig

    return _make_plot(station, sknt, drct, units, nsector, rmax, hours, months,
                      sname, minvalid, maxvalid, level, bins)
예제 #46
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def grid_day(nc, ts):
    """
    """
    offset = iemre.daily_offset(ts)
    print(('cal hi/lo for %s [idx:%s]') % (ts, offset))
    sql = """
       SELECT ST_x(s.geom) as lon, ST_y(s.geom) as lat, s.state,
       s.name, s.id as station,
       (CASE WHEN pday >= 0 then pday else null end) as precipdata,
       (CASE WHEN max_tmpf > -50 and max_tmpf < 130
           then max_tmpf else null end) as highdata,
       (CASE WHEN min_tmpf > -50 and min_tmpf < 95
           then min_tmpf else null end) as lowdata,
       (CASE WHEN max_dwpf > -50 and max_dwpf < 130
           then max_dwpf else null end) as highdwpf,
       (CASE WHEN min_dwpf > -50 and min_dwpf < 95
           then min_dwpf else null end) as lowdwpf,
        (CASE WHEN avg_sknt >= 0 and avg_sknt < 100
         then avg_sknt else null end) as avgsknt
       from summary_%s c, stations s WHERE day = '%s' and
       s.network in ('IA_ASOS', 'MN_ASOS', 'WI_ASOS', 'IL_ASOS', 'MO_ASOS',
        'KS_ASOS', 'NE_ASOS', 'SD_ASOS', 'ND_ASOS', 'KY_ASOS', 'MI_ASOS',
        'OH_ASOS', 'AWOS') and c.iemid = s.iemid
        """ % (ts.year, ts.strftime("%Y-%m-%d"))
    df = read_sql(sql, pgconn)

    if len(df.index) > 4:
        res = generic_gridder(df, 'highdata')
        nc.variables['high_tmpk'][offset] = datatypes.temperature(
                                                res, 'F').value('K')
        res = generic_gridder(df, 'lowdata')
        nc.variables['low_tmpk'][offset] = datatypes.temperature(
                                            res, 'F').value('K')
        hres = generic_gridder(df, 'highdwpf')
        lres = generic_gridder(df, 'lowdwpf')
        nc.variables['avg_dwpk'][offset] = datatypes.temperature(
                                            (hres + lres) / 2., 'F').value('K')
        res = generic_gridder(df, 'avgsknt')
        res = np.where(res < 0, 0, res)
        nc.variables['wind_speed'][offset] = datatypes.speed(
                                            res, 'KT').value('MPS')
    else:
        print "%s has %02i entries, FAIL" % (ts.strftime("%Y-%m-%d"),
                                             cursor.rowcount)
예제 #47
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def test_drct():
    """Conversion of u and v to direction"""
    r = meteorology.drct(
        datatypes.speed(np.array([10, 20]), 'KT'),
        datatypes.speed(np.array([10, 20]), 'KT')
    ).value("DEG")
    assert r[0] == 225
    r = meteorology.drct(
        datatypes.speed(-10, 'KT'),
        datatypes.speed(10, 'KT')
    ).value("DEG")
    assert r == 135
    r = meteorology.drct(
        datatypes.speed(-10, 'KT'),
        datatypes.speed(-10, 'KT')
    ).value("DEG")
    assert r == 45
    r = meteorology.drct(
        datatypes.speed(10, 'KT'),
        datatypes.speed(-10, 'KT')
    ).value("DEG")
    assert r == 315
예제 #48
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def do_windalerts(obs):
    """Iterate through the obs and do wind alerts where appropriate"""
    for sid in obs:
        # Problem sites with lightning issues
        if sid in ['RBFI4', 'RTMI4', 'RWII4', 'RCAI4', 'RDYI4',
                   'RDNI4', 'RCDI4', 'RCII4', 'RCLI4']:
            continue
        ob = obs[sid]
        # screening
        if ob.get('gust', 0) < 40:
            continue
        if np.isnan(ob['gust']):
            continue
        smph = speed(ob['gust'], 'KT').value('MPH')
        if smph < 50:
            continue
        if smph > 100:
            print(('process_rwis did not relay gust %.1f MPH from %s'
                  '') % (smph, sid))
            continue
        # Use a hacky tmp file to denote a wind alert that was sent
        fn = "/tmp/iarwis.%s.%s" % (sid, ob['valid'].strftime("%Y%m%d%H%M"))
        if os.path.isfile(fn):
            continue
        o = open(fn, 'w')
        o.write(" ")
        o.close()
        lts = ob['valid'].astimezone(pytz.timezone("America/Chicago"))
        stname = NT.sts[sid]['name']
        msg = ("At %s, a wind gust of %.1f mph (%.1f kts) was recorded "
               "at the %s (%s) Iowa RWIS station"
               "") % (lts.strftime("%I:%M %p %d %b %Y"), smph, ob['gust'],
                      stname, sid)
        mt = MIMEText(msg)
        mt['From'] = '*****@*****.**'
        # mt['To'] = '*****@*****.**'
        mt['To'] = '*****@*****.**'
        mt['Subject'] = 'Iowa RWIS Wind Gust %.0f mph %s' % (smph, stname)
        s = smtplib.SMTP('mailhub.iastate.edu')
        s.sendmail(mt['From'], [mt['To']], mt.as_string())
        s.quit()
예제 #49
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def do(valid, frame):
    """ Generate plot for a given timestamp """
    
    cursor.execute("""select turbineid, power, ST_x(geom), ST_y(geom), yaw,
    windspeed 
     from sampled_data s JOIN turbines t on (t.id = s.turbineid) 
     WHERE valid = %s and power is not null and yaw is not null
     and windspeed is not null""", (valid,))
    lons = []
    lats = []
    vals = []
    u = []
    v = []
    for row in cursor:
        lons.append(row[2])
        lats.append(row[3])
        vals.append(row[1])
        a,b = uv(speed(row[5], 'MPS'), direction(row[4], 'deg'))
        u.append( a.value('MPS') )
        v.append( b.value('MPS') )
    vals = np.array(vals)
    avgv = np.average(vals)
    vals2 = vals - avgv
    print valid, min(vals2), max(vals2)
    (fig, ax) = plt.subplots(1,1)

    cmap = plt.cm.get_cmap('RdYlBu_r')
    cmap.set_under('white')
    
    cmap.set_over('black')
    clevs = np.arange(-300,301,50)
    norm = mpcolors.BoundaryNorm(clevs, cmap.N)
    ax.quiver(lons, lats, u, v, zorder=1)
    ax.scatter(lons, lats, c=vals2, vmin=-500, vmax=500,
               cmap=cmap, s=100, zorder=2)
    ax.set_title("Pomeroy Farm Turbine Power [kW] Diff from Farm Avg (1min sampled dataset)\nValid: %s" % (
                                                        valid.strftime("%d %b %Y %I:%M %p")))
    make_colorbar(clevs, norm, cmap)
    fig.savefig('power_movie/frame%05i.png' % (frame,))

    plt.close()
예제 #50
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def test_vectorized():
    """See that heatindex and windchill can do lists"""
    temp = datatypes.temperature([0, 10], 'F')
    sknt = datatypes.speed([30, 40], 'MPH')
    val = meteorology.windchill(temp, sknt).value('F')
    assert abs(val[0] - -24.50) < 0.01

    t = datatypes.temperature([80.0, 90.0], 'F')
    td = datatypes.temperature([70.0, 60.0], 'F')
    hdx = meteorology.heatindex(t, td)
    assert abs(hdx.value("F")[0] - 83.93) < 0.01

    tmpf = np.array([80., 90.]) * units('degF')
    dwpf = np.array([70., 60.]) * units('degF')
    smps = np.array([10., 20.]) * units('meter per second')
    feels = meteorology.mcalc_feelslike(tmpf, dwpf, smps)
    assert abs(feels.to(units("degF")).magnitude[0] - 83.15) < 0.01

    tmpf = masked_array([80., np.nan], units('degF'), mask=[False, True])
    feels = meteorology.mcalc_feelslike(tmpf, dwpf, smps)
    assert abs(feels.to(units("degF")).magnitude[0] - 83.15) < 0.01
    assert feels.mask[1]
예제 #51
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def sendWindAlert(txn, iemid, v, d, t, clean_metar):
    """
    Send a wind alert please
    """
    speed = datatypes.speed(v, 'KT')
    print "ALERTING for [%s]" % (iemid,)
    txn.execute("""SELECT wfo, state, name, ST_x(geom) as lon,
           ST_y(geom) as lat, network from stations
           WHERE id = '%s' """ % (iemid, ))
    if txn.rowcount == 0:
        print "I not find WFO for sid: %s " % (iemid,)
        return
    row = txn.fetchone()
    wfo = row['wfo']
    if wfo is None or wfo == '':
        log.msg("Unknown WFO for id: %s, skipping WindAlert" % (iemid,))
        return
    st = row['state']
    nm = row['name']

    extra = ""
    if clean_metar.find("$") > 0:
        extra = "(Caution: Maintenance Check Indicator)"

    jtxt = ("%s,%s (%s) ASOS %s reports gust of %.0f knots (%.1f mph) "
            "from %s @ %s\n%s"
            ) % (nm, st, iemid, extra, speed.value('KT'), speed.value('MPH'),
                 drct2dirTxt(d), t.strftime("%H%MZ"), clean_metar)
    xtra = {'channels': wfo,
            'lat': str(row['lat']),
            'long': str(row['lon'])}

    xtra['twitter'] = ("%s,%s (%s) ASOS reports gust of %.1f knots "
                       "(%.1f mph) from %s @ %s"
                       ) % (nm, st, iemid, speed.value('KT'),
                            speed.value('MPH'), drct2dirTxt(d),
                            t.strftime("%H%MZ"))
    jabber.sendMessage(jtxt, "<p>%s</p>" % (jtxt,), xtra)
예제 #52
0
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()
예제 #53
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def grid_wind(rs):
    """
    Grid winds based on u and v components
    @param rs array of dicts
    @return uwnd, vwnd
    """
    lats = []
    lons = []
    udata = []
    vdata = []
    for row in rs:
        if row["sknt"] is None or row["drct"] is None:
            continue
        # mps
        (u, v) = meteorology.uv(dt.speed(row["sknt"], "KT"), dt.direction(row["drct"], "DEG"))
        if v is not None:
            lats.append(nt.sts[row["station"]]["lat"])
            lons.append(nt.sts[row["station"]]["lon"])
            vdata.append(v.value("MPS"))
            udata.append(u.value("MPS"))

    if len(vdata) < 4:
        print "No wind data at all"
        return None

    xi, yi = np.meshgrid(iemre.XAXIS, iemre.YAXIS)
    nn = NearestNDInterpolator((lons, lats), np.array(udata))
    ugrid = nn(xi, yi)
    nn = NearestNDInterpolator((lons, lats), np.array(vdata))
    vgrid = nn(xi, yi)
    if ugrid is not None:
        ugt = ugrid
        vgt = vgrid
        return ugt, vgt
    else:
        return None, None
예제 #54
0
 def wind_message(self):
     """Convert this into a Jabber style message"""
     drct = 0
     sknt = 0
     time = self.time.replace(tzinfo=pytz.UTC)
     if self.wind_gust:
         sknt = self.wind_gust.value("KT")
         if self.wind_dir:
             drct = self.wind_dir.value()
     if self.wind_speed_peak:
         v1 = self.wind_speed_peak.value("KT")
         d1 = self.wind_dir_peak.value()
         t1 = self.peak_wind_time.replace(tzinfo=pytz.UTC)
         if v1 > sknt:
             sknt = v1
             drct = d1
             time = t1
     key = "%s;%s;%s" % (self.station_id, sknt, time)
     if key not in WIND_ALERTS:
         WIND_ALERTS[key] = 1
         speed = datatypes.speed(sknt, 'KT')
         return ("gust of %.0f knots (%.1f mph) from %s @ %s"
                 ) % (speed.value('KT'), speed.value('MPH'),
                      drct2text(drct), time.strftime("%H%MZ"))
예제 #55
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def do_daily(fn):
    df = pd.read_table(fn, sep=' ')
    df['sknt'] = speed(df['WINDSPEED'], 'MPS').value('KT')
    df['high'] = temperature(df['TMAX'], 'C').value('F')
    df['low'] = temperature(df['TMIN'], 'C').value('F')
    df['pday'] = distance(df['PRECIP'], 'MM').value('IN')
    df['date'] = df[['YEAR', 'MONTH', 'DAY']].apply(lambda x:
                                                    datetime.date(x[0], x[1],
                                                                  x[2]),
                                                    axis=1)
    print("fn: %s valid: %s - %s" % (fn, df['date'].min(), df['date'].max()))
    cursor = pgconn.cursor()
    cursor.execute("""DELETE from weather_data_daily where station = 'DPAC'
    and valid >= %s and valid <= %s""", (df['date'].min(), df['date'].max()))
    if cursor.rowcount > 0:
        print("Deleted %s rows" % (cursor.rowcount, ))
    for i, row in df.iterrows():
        cursor.execute("""INSERT into weather_data_daily
        (station, valid, high, low, precip, sknt) VALUES ('DPAC',
        %s, %s, %s, %s, %s)""", (row['date'], row['high'], row['low'],
                                 row['pday'], row['sknt']))
    print("Inserted %s rows..." % (i + 1, ))
    cursor.close()
    pgconn.commit()
예제 #56
0
def do_hourly(fn):
    df = pd.read_table(fn, sep=' ')
    df['sknt'] = speed(df['WINDSPEED'], 'MPS').value('KT')
    df['tmpf'] = temperature(df['TAIR'], 'C').value('F')
    df['precip'] = distance(df['PREC'], 'MM').value('IN')
    df['valid'] = df[['YEAR', 'MONTH', 'DAY', 'HOUR']].apply(lambda x:
                                                             d(*x),
                                                             axis=1)
    print("fn: %s valid: %s - %s" % (fn, df['valid'].min(),
                                     df['valid'].max()))
    cursor = pgconn.cursor()
    cursor.execute("""DELETE from weather_data_obs where station = 'DPAC'
    and valid >= %s and valid <= %s""", (df['valid'].min(), df['valid'].max()))
    if cursor.rowcount > 0:
        print("Deleted %s rows" % (cursor.rowcount, ))
    for i, row in df.iterrows():
        cursor.execute("""INSERT into weather_data_obs
        (station, valid, tmpf, sknt, precip, srad) VALUES ('DPAC',
        %s, %s, %s, %s, %s)""", (row['valid'].strftime("%Y-%m-%d %H:%M-05"),
                                 row['tmpf'], row['sknt'],
                                 row['precip'], row['RADIATION']))
    print("Inserted %s rows..." % (i + 1, ))
    cursor.close()
    pgconn.commit()
예제 #57
0
  and c2.iemid = s.iemid
  and (s.network ~* 'ASOS' or s.network = 'AWOS') and s.country = 'US'
  ORDER by lon, lat
""" % (now.year,)

lats = []
lons = []
vals = []
valmask = []
icursor.execute(sql)
for row in icursor:
    if row[4] == 0 or row[4] is None:
        continue
    lats.append(row[3])
    lons.append(row[2])
    vals.append(speed(row[4], 'KT').value('MPH'))
    valmask.append((row[1] in ['AWOS', 'IA_ASOS']))

if len(vals) < 5 or True not in valmask:
    sys.exit(0)

clevs = numpy.arange(0, 40, 2)
clevs = numpy.append(clevs, numpy.arange(40, 80, 5))
clevs = numpy.append(clevs, numpy.arange(80, 120, 10))

# Iowa
pqstr = "plot ac %s summary/today_gust.png iowa_wind_gust.png png" % (
        now.strftime("%Y%m%d%H%M"), )
m = MapPlot(title="Iowa ASOS/AWOS Peak Wind Speed Reports",
            subtitle="%s" % (now.strftime("%d %b %Y"), ),
            sector='iowa')
예제 #58
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파일: network2wxc.py 프로젝트: akrherz/iem
    heat = "M"
    if tmpf != "M" and dwpf != "M":
        t = temperature(nc.variables['temperature'][idx], 'K')
        d = temperature(nc.variables['dewpoint'][idx], 'K')
        relh = meteorology.relh(t, d).value("%")
        heat = "%5.1f" % (meteorology.heatindex(t, d).value("F"),)
    drct = s2( nc.variables['windDir'][idx])
    smps = s2( nc.variables['windSpeed'][idx])
    sped = "M"
    if smps != "M":
        sped = "%5.1f" % (nc.variables['windSpeed'][idx] * 2.23694,)

    wcht = "M"
    if tmpf != "M" and sped != "M":
        t = temperature(nc.variables['temperature'][idx], 'K')
        sped = speed( nc.variables['windSpeed'][idx], 'MPS')
        wcht = "%5.1f" % (meteorology.windchill(t, sped).value("F"),) 

    ts = indices[sid]['ts']

    out.write("%5.5s %25.25s %8.4f %10.4f %02i %02i %5s %5s %5s %5s %5s %5s\n" % (sid, name, latitude,
                                                   longitude, ts.hour,
                                                   ts.minute, tmpf, dwpf,
                                                   drct, sped, heat, wcht))

nc.close()
out.close()
pqstr = "data c 000000000000 wxc/wxc_%s.txt bogus txt" % (network.lower(),)
subprocess.call("/home/ldm/bin/pqinsert -p '%s' %s" % (
                            pqstr, wxcfn), shell=True)
os.remove(wxcfn)
예제 #59
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"""
http://www.isws.illinois.edu/warm/datatype.asp
"""
import pandas as pd
import datetime
from pyiem.datatypes import speed
import psycopg2
pgconn = psycopg2.connect(database='sustainablecorn', host='iemdb')

station = 'SEPAC'
fn = 'sepac.xlsx'

df = pd.read_excel(fn)
print df.columns
df['sknt'] = speed(pd.to_numeric(df['Wind Speed(mph)'], errors='coerse'),
                   'MPH').value('KT')
df['high'] = pd.to_numeric(df['Maximum Air Temperature(degF)'], errors='coerse')
df['low'] = pd.to_numeric(df['Minimum Air Temperature(degF)'], errors='coerse')
df['pday'] = df['Precipitation(inch)']
df['srad'] = df['Solar Radiation(MJsqm)']

print("fn: %s valid: %s - %s" % (fn, df['date'].min(), df['date'].max()))
cursor = pgconn.cursor()
cursor.execute("""DELETE from weather_data_daily where station = %s
    and valid >= %s and valid <= %s
    """, (station, df['date'].min(), df['date'].max()))
if cursor.rowcount > 0:
    print("Deleted %s rows" % (cursor.rowcount, ))

for i, row in df.iterrows():
    cursor.execute("""INSERT into weather_data_daily
예제 #60
0
파일: hourly_climo.py 프로젝트: akrherz/DEV
# air temperature, RH, Radiation, WS, and precipitation
df2 = read_sql("""SELECT
  extract(month from valid) as month,
  extract(hour from valid + '10 minutes'::interval) as hour,
  extract(day from valid + '10 minutes'::interval) as day,
  c800 from hourly
  WHERE station = 'A130209' and extract(month from valid) in (10, 11)
  """, pgconn, index_col=None)

gdf2 = df2.groupby(by=['month', 'day', 'hour']).mean()

print(("MONTH,DAY,HOUR,AIRTEMP[C],"
       "RELHUMID[%],RADIATION[kC/m2],WINDSPEED[MPS],PRECIP[MM]"))
for month in (10, 11):
    for day in range(1, 32):
        if day == 31 and month == 11:
            continue
        for hour in range(24):
            print(("%s,%s,%s,%.2f,%.2f,%.2f,%.2f,%.2f"
                   ) % (month, day, hour,
                        temperature(gdf.at[(month, day, hour),
                                           'tmpf'], 'F').value('C'),
                        gdf.at[(month, day, hour), 'relh'],
                        gdf2.at[(month, day, hour), 'c800'],
                        speed(gdf.at[(month, day, hour), 'sknt'],
                              'KT').value('MPS'),
                        distance(gdf.at[(month, day, hour), 'p01i'],
                                 'IN').value('MM')
                        ))