Esempio n. 1
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def test_exception_maxalt():
    with pytest.raises(ValueError):
        aacgmv2.convert(60, 0, 2001, dtObj)
    with pytest.raises(ValueError):
        aacgmv2.convert(60, 0, [300, 2001], dtObj)

    # the following should not raise exceptions
    aacgmv2.convert(60, 0, 2001, dtObj, trace=True)
    aacgmv2.convert(60, 0, 2001, dtObj, allowtrace=True)
    aacgmv2.convert(60, 0, 2001, dtObj, badidea=True)
Esempio n. 2
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def f4():
    plt.figure(figsize=(6.88,6.74))
    #geographic coordinates
    ax1, projection1 = gcc.create_map(
        2, 2, 1, 'pol', 90, 50, 0, coastlines=False,useLT=True,
        dlat=10, lonticklabel=(1, 1, 1, 1))
    ax1.plot([45,45],[50,90], 'k--',transform=ccrs.PlateCarree())
    ax1.plot([225,225],[50,90], 'k--',transform=ccrs.PlateCarree())
    ax1.plot([105,105],[50,90], 'k--',transform=ccrs.PlateCarree())
    ax1.plot([285,285],[50,90], 'k--',transform=ccrs.PlateCarree())
    ax1.scatter(
        0, 90, color='r', transform=ccrs.PlateCarree(), zorder=10,
        label='North Pole')
    ax1.text(0,1,'(a)', transform = plt.gca().transAxes)
    plt.legend(loc=[0.5,1.1])

    ax2, projection2 = gcc.create_map(
        2, 2, 2, 'pol', -50, -90, 0, coastlines=False,useLT=True,
        dlat=10, lonticklabel=(1, 1, 1, 1))
    ax2.scatter(
        0, -90, color='b', transform=ccrs.PlateCarree(),label='South Pole')
    ax2.text(0,1,'(b)', transform = plt.gca().transAxes)
    plt.legend(loc=[-0.1,1.1])

    #geomagnetic coordinates
    ax3, projection3 = gcc.create_map(
        2, 2, 3, 'pol', 90, 50, 0, coastlines=False,useLT=True,
        dlat=10, lonticklabel=(1, 1, 1, 1))
    mlatn,mlonn = convert(90,0,0,date=dt.date(2002,3,21))
    for k in range(24):
        mltn = convert_mlt(mlonn[0],dtime=dt.datetime(2003,3,21,k))
        ax3.scatter(mltn*15,mlatn[0],color='r',transform=ccrs.PlateCarree())
    ax3.scatter(180,75,s=50,c='k',marker='x',transform=ccrs.PlateCarree())
    ax3.text(0,1,'(c)', transform = plt.gca().transAxes)

    ax4, projection4 = gcc.create_map(
        2, 2, 4, 'pol', -50, -90, 0, coastlines=False,useLT=True,
        dlat=10, lonticklabel=(1, 1, 1, 1))
    mlats,mlons = convert(-90,0,0,date=dt.date(2002,3,21))
    for k in range(24):
        mlts = convert_mlt(mlons[0],dtime=dt.datetime(2003,3,21,k))
        ax4.scatter(mlts*15,mlats[0],color='b',transform=ccrs.PlateCarree())
    ax4.scatter(180,-75,s=50,c='k',marker='x',transform=ccrs.PlateCarree())
    ax4.text(0,1,'(d)', transform = plt.gca().transAxes)
    plt.savefig(
        '/Users/guod/Documents/Pole_Density_MLT_Change/Figures/'
        '000_Pole_Feature.pdf')
    return
Esempio n. 3
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    def test_convert_list(self):
        """Test conversion for list input"""
        self.lat, self.lon = aacgmv2.convert([60], [0], [300], self.dtime)
        assert isinstance(self.lat, np.ndarray)
        assert isinstance(self.lon, np.ndarray)
        assert self.lat.shape == self.lon.shape and self.lat.shape == (1, )
        np.testing.assert_allclose(self.lat, [58.2258], rtol=1e-4)
        np.testing.assert_allclose(self.lon, [81.1685], rtol=1e-4)

        self.lat, self.lon = aacgmv2.convert([60, 61], [0, 0], [300, 300],
                                             self.dtime)
        assert isinstance(self.lat, np.ndarray)
        assert isinstance(self.lon, np.ndarray)
        assert self.lat.shape == self.lon.shape and self.lat.shape == (2, )
        np.testing.assert_allclose(self.lat, [58.2258, 59.3186], rtol=1e-4)
        np.testing.assert_allclose(self.lon, [81.1685, 81.6140], rtol=1e-4)
Esempio n. 4
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 def test_convert_location_failure(self):
     """Test conversion with a bad location"""
     self.lat, self.lon = aacgmv2.convert([0], [0], [0], self.dtime)
     assert isinstance(self.lat, np.ndarray)
     assert isinstance(self.lon, np.ndarray)
     assert self.lat.shape == self.lon.shape and self.lat.shape == (1, )
     assert np.all([np.isnan(self.lat), np.isnan(self.lon)])
Esempio n. 5
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 def test_convert_single_val(self):
     """Test conversion for a single value"""
     self.lat, self.lon = aacgmv2.convert(60, 0, 300, self.dtime)
     assert isinstance(self.lat, np.ndarray)
     assert isinstance(self.lon, np.ndarray)
     assert self.lat.shape == self.lon.shape and self.lat.shape == (1, )
     np.testing.assert_allclose(self.lat, [58.2258], rtol=1e-4)
     np.testing.assert_allclose(self.lon, [81.1685], rtol=1e-4)
Esempio n. 6
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 def test_convert_arr_single(self):
     """Test conversion for array input with one element"""
     self.lat, self.lon = aacgmv2.convert(np.array([60]), np.array([0]),
                                          np.array([300]), self.dtime)
     assert isinstance(self.lat, np.ndarray)
     assert isinstance(self.lon, np.ndarray)
     assert self.lat.shape == self.lon.shape and self.lat.shape == (1, )
     np.testing.assert_allclose(self.lat, [58.2258], rtol=1e-4)
     np.testing.assert_allclose(self.lon, [81.1685], rtol=1e-4)
Esempio n. 7
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 def test_convert_arr_mix(self):
     """Test conversion for an array and floats"""
     self.lat, self.lon = aacgmv2.convert(np.array([60, 61]), 0, 300,
                                          self.dtime)
     assert isinstance(self.lat, np.ndarray)
     assert isinstance(self.lon, np.ndarray)
     assert self.lat.shape == self.lon.shape and self.lat.shape == (2, )
     np.testing.assert_allclose(self.lat, [58.2258, 59.3186], rtol=1e-4)
     np.testing.assert_allclose(self.lon, [81.1685, 81.6140], rtol=1e-4)
Esempio n. 8
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    def test_warning_below_ground_convert(self):
        """ Test that a warning is issued if altitude is below zero"""
        import logbook
        lwarn = u"conversion not intended for altitudes < 0 km"

        with logbook.TestHandler() as handler:
            self.lat, self.lon = aacgmv2.convert([60], [0], [-1], self.dtime)
            assert handler.has_warning(lwarn)

        handler.close()
Esempio n. 9
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def get_flight_route(i,does_this_route_pass_through_arctic,airport_code,dest_airports):
    ### returns a pandas dataframe with the flight route info
    ### or returns None if the flight does not pass through the Arctic
    if not does_this_route_pass_through_arctic[i]:
        return None
    folderpath = 'gis_temp/'
    layername = airport_code+'-'+dest_airports.loc[i].code
    mag_lat = [dest_airports.loc[i].code+' mag lat']; mag_lon = [dest_airports.loc[i].code+' mag lon']
    gc_lat = [dest_airports.loc[i].code+' lat']; gc_lon = [dest_airports.loc[i].code+' lon']
    with open(folderpath+'/'+layername+'.geojson') as json_file:  
        data = json.load(json_file)
        if len(data['features'][0]['geometry']['coordinates'][0]) == 2:   #if everything is working as expected
            for j in range(len(data['features'][0]['geometry']['coordinates'][:])):
                lon,lat = data['features'][0]['geometry']['coordinates'][j]
                mg_lat,mg_lon = aacgmv2.convert(lat, lon, 10, date=date.today(), 
                                                  a2g=False, trace=False, allowtrace=False,
                                                  badidea=False, geocentric=False)
                mag_lat.append(mg_lat[0])
                mag_lon.append(mg_lon[0])
                gc_lat.append(lat)
                gc_lon.append(lon)
        else:    #anti-meridian crossing, they split the results into two groups so the len will be a lot longer
            for j in range(len(data['features'][0]['geometry']['coordinates'][0][:])):
                lon,lat = data['features'][0]['geometry']['coordinates'][0][j]
                mg_lat,mg_lon = aacgmv2.convert(lat, lon, 10, date=date.today(), 
                                                  a2g=False, trace=False, allowtrace=False,
                                                  badidea=False, geocentric=False)
                mag_lat.append(mg_lat[0])
                mag_lon.append(mg_lon[0])
                gc_lat.append(lat)
                gc_lon.append(lon)
            for j in range(len(data['features'][0]['geometry']['coordinates'][1][:])):
                lon,lat = data['features'][0]['geometry']['coordinates'][1][j]
                mg_lat,mg_lon = aacgmv2.convert(lat, lon, 10, date=date.today(), 
                                                  a2g=False, trace=False, allowtrace=False,
                                                  badidea=False, geocentric=False)
                mag_lat.append(mg_lat[0])
                mag_lon.append(mg_lon[0])
                gc_lat.append(lat)
                gc_lon.append(lon)
    df = pd.DataFrame.from_records([gc_lat,gc_lon,mag_lat,mag_lon])
    return df
Esempio n. 10
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def test_convert_result_values_shape():
    lat, lon = aacgmv2.convert(np.array([[60, 61, 62],
                                         [63, 64, 65]]),
                               0, 300, dtObj)
    aacgmv2._aacgmv2.setDateTime(*date)
    assert (lat[0, 0], lon[0, 0], 1) == aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, G2A)
    assert (lat[0, 1], lon[0, 1], 1) == aacgmv2._aacgmv2.aacgmConvert(61, 0, 300, G2A)
    assert (lat[0, 2], lon[0, 2], 1) == aacgmv2._aacgmv2.aacgmConvert(62, 0, 300, G2A)
    assert (lat[1, 0], lon[1, 0], 1) == aacgmv2._aacgmv2.aacgmConvert(63, 0, 300, G2A)
    assert (lat[1, 1], lon[1, 1], 1) == aacgmv2._aacgmv2.aacgmConvert(64, 0, 300, G2A)
    assert (lat[1, 2], lon[1, 2], 1) == aacgmv2._aacgmv2.aacgmConvert(65, 0, 300, G2A)
Esempio n. 11
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    def solar_conductance(self, dt, mlats, mlts, return_f107=False):
        """
        Estimate the solar conductance using methods from:
            Cousins, E. D. P., T. Matsuo, and A. D. Richmond (2015), Mapping
            high-latitude ionospheric electrodynamics with SuperDARN and AMPERE

            --which cites--

            Asgeir Brekke, Joran Moen, Observations of high latitude ionospheric conductances

            Maybe is not good for SZA for southern hemisphere? Don't know
            Going to use absolute value of latitude because that's what's done
            in Cousins IDL code.
        """
        # Find the closest hourly f107 value
        # to the current time to specifiy the conductance
        f107 = ovation_utilities.get_daily_f107(dt)
        if hasattr(self, '_f107'):
            log.warning(
                ('Warning: Overriding real F107 {0}'.format(f107) +
                 'with secret instance property _f107 {0}'.format(self._f107) +
                 'this is for debugging and will not' +
                 'produce accurate results for a particular date.'))
            f107 = self._f107

        # print "F10.7 = %f" % (f107)

        # Convert from magnetic to geocentric using the AACGMv2 python library
        flatmlats, flatmlts = mlats.flatten(), mlts.flatten()
        flatmlons = aacgmv2.convert_mlt(flatmlts, dt, m2a=True)
        try:
            glats, glons = aacgmv2.convert(flatmlats,
                                           flatmlons,
                                           110. * np.ones_like(flatmlats),
                                           date=dt,
                                           a2g=True,
                                           geocentric=False)
        except AttributeError:
            # convert method was deprecated
            glats, glons, r = aacgmv2.convert_latlon_arr(flatmlats,
                                                         flatmlons,
                                                         110.,
                                                         dt,
                                                         method_code='A2G')

        sigp, sigh = brekke_moen_solar_conductance(dt, glats, glons, f107)

        sigp_unflat = sigp.reshape(mlats.shape)
        sigh_unflat = sigh.reshape(mlats.shape)

        if return_f107:
            return sigp_unflat, sigh_unflat, f107
        else:
            return sigp_unflat, sigh_unflat
Esempio n. 12
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def test_output_type():
    lat, lon = aacgmv2.convert(60, 0, 300, dtObj)
    print(type(lat))
    print(lat.shape)
    print(lat.size)
    assert isinstance(lat, np.ndarray)
    assert isinstance(lon, np.ndarray)

    lat, lon = aacgmv2.convert([60], [0], [300], dtObj)
    assert isinstance(lat, np.ndarray)
    assert isinstance(lon, np.ndarray)

    lat, lon = aacgmv2.convert([60, 61], [0, 0], [300, 300], dtObj)
    assert isinstance(lat, np.ndarray)
    assert isinstance(lon, np.ndarray)

    lat, lon = aacgmv2.convert([60, 61, 62], 0, 300, dtObj)
    assert isinstance(lat, np.ndarray)
    assert isinstance(lon, np.ndarray)

    lat, lon = aacgmv2.convert(np.array([60, 61, 62]), 0, 300, dtObj)
    assert isinstance(lat, np.ndarray)
    assert isinstance(lon, np.ndarray)

    lat, lon = aacgmv2.convert(np.array([[60, 61, 62], [63, 64, 65]]), 0, 300, dtObj)
    assert isinstance(lat, np.ndarray)
    assert isinstance(lon, np.ndarray)
Esempio n. 13
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 def test_convert_mult_array_mix(self):
     """Test conversion for a multi-dim array and floats"""
     self.lat, self.lon = aacgmv2.convert(
         np.array([[60, 61, 62], [63, 64, 65]]), 0, 300, self.dtime)
     assert isinstance(self.lat, np.ndarray)
     assert isinstance(self.lon, np.ndarray)
     assert self.lat.shape == self.lon.shape and self.lat.shape == (2, 3)
     np.testing.assert_allclose(
         self.lat,
         [[58.2258, 59.3186, 60.4040], [61.4820, 62.5528, 63.6164]],
         rtol=1e-4)
     np.testing.assert_allclose(
         self.lon,
         [[81.1685, 81.6140, 82.0872], [82.5909, 83.1286, 83.7039]],
         rtol=1e-4)
Esempio n. 14
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def test_output_shape_size():
    lat, lon = aacgmv2.convert(60, 0, 300, dtObj)
    assert lat.shape == tuple()
    assert lon.shape == tuple()
    assert lat.size == 1
    assert lon.size == 1

    lat, lon = aacgmv2.convert([60], [0], [300], dtObj)
    assert lat.shape == (1,)
    assert lon.shape == (1,)
    assert lat.size == 1
    assert lon.size == 1

    lat, lon = aacgmv2.convert([60, 61], [0, 0], [300, 300], dtObj)
    assert lat.shape == (2,)
    assert lon.shape == (2,)
    assert lat.size == 2
    assert lon.size == 2

    lat, lon = aacgmv2.convert([60, 61, 62], 0, 300, dtObj)
    assert lat.shape == (3,)
    assert lon.shape == (3,)
    assert lat.size == 3
    assert lon.size == 3

    lat, lon = aacgmv2.convert(np.array([60, 61, 62]), 0, 300, dtObj)
    assert lat.shape == (3,)
    assert lon.shape == (3,)
    assert lat.size == 3
    assert lon.size == 3

    lat, lon = aacgmv2.convert(np.array([[60, 61, 62],
                                         [63, 64, 65]]),
                               0, 300, dtObj)
    assert lat.shape == (2, 3)
    assert lon.shape == (2, 3)
    assert lat.size == 6
    assert lon.size == 6
Esempio n. 15
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def test_convert_result_values_badidea():
    lat, lon = aacgmv2.convert(60, 0, [300, 5000], dtObj, badidea=True)
    aacgmv2._aacgmv2.setDateTime(*date)
    assert (lat[0], lon[0], 1) == aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, BADIDEA)
    assert (lat[1], lon[1], 1) == aacgmv2._aacgmv2.aacgmConvert(60, 0, 5000, BADIDEA)
Esempio n. 16
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def test_convert_result_values_geocentric():
    lat_p, lon_p = aacgmv2.convert(60, 0, 300, dtObj, geocentric=True)
    aacgmv2._aacgmv2.setDateTime(*date)
    lat_c, lon_c, _ = aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, GEOCENTRIC)
    assert lat_p == lat_c
    assert lon_p == lon_c
Esempio n. 17
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def test_convert_result_values_A2G_trace():
    lat_p, lon_p = aacgmv2.convert(60, 0, 300, dtObj, a2g=True, trace=True)
    aacgmv2._aacgmv2.setDateTime(*date)
    lat_c, lon_c, _ = aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, A2G | TRACE)
    assert lat_p == lat_c
    assert lon_p == lon_c
Esempio n. 18
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def test_convert_result_values_allowtrace():
    lat, lon = aacgmv2.convert(60, 0, [300, 5000], dtObj, allowtrace=True)
    aacgmv2._aacgmv2.setDateTime(*date)
    assert (lat[0], lon[0], 1) == aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, ALLOWTRACE)
    assert (lat[1], lon[1], 1) == aacgmv2._aacgmv2.aacgmConvert(60, 0, 5000, ALLOWTRACE)
Esempio n. 19
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def figure2_3(run=1):
    plt.close('all')
    plt.figure(figsize=(8.28, 9.25))
    if run==1:
        g = g1
    else:
        g = g2
    rholevels = [np.linspace(8, 16, 21)*1e-10, np.linspace(1,4,21)*1e-11,
                 np.linspace(0.5, 8,21)*1e-13]
    rhoticks = [np.arange(8, 17, 2)*1e-10, np.arange(1,5,1)*1e-11,
                np.arange(1, 9, 2)*1e-13]
    templevels = [np.linspace(600, 800, 21), np.linspace(900,1500,21),
                 np.linspace(900, 1500,21)]
    tempticks = [np.arange(600, 900, 100), np.arange(900,1600,200),
                np.arange(900, 1600, 200)]
    labels =[('(a)','(b)','(c)'), ('(d)','(e)','(f)'), ('(g)','(h)','(i)')]
    qlat, qlon = convert(-90, 0, 0, date=dt.date(2003,3,22), a2g=True)
    for ialt, alt in enumerate([150, 300, 600]):
        alt_ind = np.argmin(np.abs(g['Altitude'][0, 0, 2:-2]/1000-alt))+2
        alt_str = '%6.0f' % (g['Altitude'][0, 0, alt_ind]/1000)
        ax, projection = gcc.create_map(
            3, 3, ialt+1, 'polar', nlat=nlat, slat=slat, dlat=10,
            centrallon=g3ca.calculate_centrallon(g, 'polar',  useLT=True),
            coastlines=False, lonticklabel=[1,1,1,1])

        # density
        lon0, lat0, zdata0 = g3ca.contour_data('Rho', g, alt=alt)
        fp = (lat0[:,0]>slat) & (lat0[:,0]<nlat)
        lon0, lat0, zdata0 = lon0[fp, :], lat0[fp,:], zdata0[fp,:]
        hc = ax.contourf(
            lon0, lat0, zdata0, rholevels[ialt], transform=ccrs.PlateCarree(),
            cmap='jet', extend='both')
        gcapos = ax.get_position()
        axcb = [
            gcapos.x0, gcapos.y0+0.028, gcapos.width, gcapos.height/20]
        axcb = plt.axes(axcb)
        hcb = plt.colorbar(
            hc, cax=axcb, extendrect=True, ticks=rhoticks[ialt],
            orientation='horizontal')

        # wind
        lon0, lat0, ewind, nwind = g3ca.vector_data(g, 'neutral', alt=alt)
        lon0, lat0, ewind, nwind = g3ca.convert_vector(
            lon0, lat0, ewind, nwind, plot_type='polar', projection=projection)
        hq = ax.quiver(
            lon0, lat0, ewind, nwind, scale=1000, scale_units='inches',
            regrid_shape=20)
        ax.quiverkey(hq, 0.97, 0.92, 500, '500 m/s')

        ax.scatter(qlon, qlat, color='k', transform=ccrs.PlateCarree())
        ax.scatter(
            0, -90, color='w', s=30, transform=ccrs.PlateCarree(), zorder=1000)

        ax.set_title('%s km' % alt_str, y=1.08)

        if ialt == 0:
            plt.text(
                -0.2, 0.5, r'$\rho$ and wind', rotation=90,
                transform=ax.transAxes, verticalalignment='center')
        plt.text(0, 0.9, labels[0][ialt],transform=ax.transAxes,color='r')

        #----------------------------------------------------------------------
        ax, projection = gcc.create_map(
            3, 3, ialt+4, 'polar', nlat=nlat, slat=slat, dlat=10,
            centrallon=g3ca.calculate_centrallon(g, 'polar',  useLT=True),
            coastlines=False, lonticklabel=[1,1,1,1])
        # temperature
        lon0, lat0, zdata0 = g3ca.contour_data('Temperature', g, alt=alt)
        fp = (lat0[:,0]>slat) & (lat0[:,0]<nlat)
        lon0, lat0, zdata0 = lon0[fp, :], lat0[fp,:], zdata0[fp,:]
        hc = ax.contourf(
            lon0, lat0, zdata0, templevels[ialt], transform=ccrs.PlateCarree(),
            cmap='jet', extend='both')
        gcapos = ax.get_position()
        axcb = [
            gcapos.x0, gcapos.y0-0.017, gcapos.width, gcapos.height/20]
        axcb = plt.axes(axcb)
        hcb = plt.colorbar(
            hc, cax=axcb, extendrect=True, ticks=tempticks[ialt],
            orientation='horizontal')

        ax.scatter(qlon, qlat, color='k', transform=ccrs.PlateCarree())
        ax.scatter(
            0, -90, color='w', s=30, transform=ccrs.PlateCarree(), zorder=1000)

        if ialt == 0:
            plt.text(
                -0.2, 0.5, 'Temperature (K)', rotation=90,
                transform=ax.transAxes, verticalalignment='center')
        plt.text(0, 0.9, labels[1][ialt],transform=ax.transAxes,color='r')
        #----------------------------------------------------------------------
        ax, projection = gcc.create_map(
            3, 3, ialt+7, 'polar', nlat=nlat, slat=slat, dlat=10,
            centrallon=g3ca.calculate_centrallon(g, 'polar',  useLT=True),
            coastlines=False, lonticklabel=[1,1,1,1])
        # ion drift
        lon0, lat0, ewind, nwind = g3ca.vector_data(g, 'ion', alt=alt)
        lon0, lat0, ewind, nwind = g3ca.convert_vector(
            lon0, lat0, ewind, nwind, plot_type='polar', projection=projection)
        if run == 2:
            ewind, nwind = 0.1*ewind, 0.1*nwind
        hq = ax.quiver(
            lon0, lat0, ewind, nwind, scale=1000, scale_units='inches',
            regrid_shape=20)
        ax.quiverkey(hq, 0.97, 0.92, 500, '500 m/s')
        ax.scatter(qlon, qlat, color='k', transform=ccrs.PlateCarree())
        ax.scatter(
            0, -90, color='w', s=30, transform=ccrs.PlateCarree(), zorder=1000)

        if ialt == 0:
            plt.text(
                -0.2, 0.5, 'Ion Drift', rotation=90,
                transform=ax.transAxes, verticalalignment='center')
        plt.text(0, 0.9, labels[2][ialt],transform=ax.transAxes,color='r')
    plt.subplots_adjust(wspace=0.25, hspace=0.25, top=0.95, bottom=0.05)

    if run==1:
        plt.savefig(savepath+'Figure2.eps')
        plt.savefig(savepath+'Figure2.jpeg')
    else:
        plt.savefig(savepath+'Figure3.eps')
        plt.savefig(savepath+'Figure3.jpeg')
    return
Esempio n. 20
0
def figure5_7(alt=150):
    times = pd.to_datetime([
        '2003-03-22 00:00:00', '2003-03-22 00:30:00', '2003-03-22 01:00:00',
        '2003-03-22 02:00:00', '2003-03-22 03:00:00', '2003-03-22 06:00:00'])
    plt.close('all')
    plt.figure(figsize=(9.5, 9.25))
    xtitle = [
        r'$-\nabla\cdot w$', r'$-\nabla\cdot u$',
        r'$-\frac{w\cdot\nabla\rho}{\rho}$',
        r'$-\frac{u\cdot\nabla\rho}{\rho}$',
        r'$\frac{\partial \rho}{\rho\partial t}$',
        r'$\delta\rho$ (%)']
    ylabel = times.strftime('%H:%M')
    qlat, qlon = convert(-90, 0, 0, date=dt.date(2003,3,22), a2g=True)
    for itime, time in enumerate(times):
        strtime = time.strftime('%y%m%d_%H%M')
        fn1 = glob.glob(
            '/home/guod/simulation_output/momentum_analysis/'\
            'run_no_shrink_iondrift_4_1/data/3DALL_t%s*.bin' % strtime)
        fn2 = glob.glob(
            '/home/guod/simulation_output/momentum_analysis/'\
            'run_shrink_iondrift_4_c1/data/3DALL_t%s*.bin' % strtime)
        g1 = gitm.read(fn1[0])
        g2 = gitm.read(fn2[0])

        lon1 = g1['Longitude']
        lat1 = g1['Latitude']
        alt1 = g1['Altitude']
        Re = 6371*1000 # Earth radius, unit: m
        RR = Re+alt1
        omega = 2*pi/(24*3600)
        rho1 = np.array(g1['Rho'])
        nwind1 = g1['V!Dn!N (north)']
        ewind1 = g1['V!Dn!N (east)'] + omega*RR*np.cos(lat1)
        uwind1 = g1['V!Dn!N (up)']
        div_rhov1 = \
            (cr.calc_div_hozt(lon1, lat1, alt1, rho1*nwind1, rho1*ewind1)\
            +cr.calc_div_vert(alt1, rho1*uwind1))/rho1
        vert_divv1 = cr.calc_div_vert(alt1, uwind1)
        hozt_divv1 = cr.calc_div_hozt(lon1, lat1, alt1, nwind1, ewind1)
        vert_vgradrho1 = uwind1*cr.calc_rusanov_alts_ausm(alt1,rho1)/rho1
        hozt_vgradrho1 = \
            (nwind1*cr.calc_rusanov_lats(lat1,alt1,rho1)\
            +ewind1*cr.calc_rusanov_lons(lon1,lat1,alt1,rho1))/rho1

        dc1 = [
            vert_divv1, hozt_divv1, vert_vgradrho1, hozt_vgradrho1,
            div_rhov1, rho1]

        lon2 = g2['Longitude']
        lat2 = g2['Latitude']
        alt2 = g2['Altitude']
        Re = 6371*1000 # Earth radius, unit: m
        RR = Re+alt2
        omega = 2*pi/(24*3600)
        rho2 = g2['Rho']
        nwind2 = g2['V!Dn!N (north)']
        ewind2 = g2['V!Dn!N (east)'] + omega*RR*np.cos(lat2)
        uwind2 = g2['V!Dn!N (up)']
        div_rhov2 = \
            (cr.calc_div_hozt(lon2, lat2, alt2, rho2*nwind2, rho2*ewind2)\
            +cr.calc_div_vert(alt2, rho2*uwind2))/rho2
        vert_divv2 = cr.calc_div_vert(alt2, uwind2)
        hozt_divv2 = cr.calc_div_hozt(lon2, lat2, alt2, nwind2, ewind2)
        vert_vgradrho2 = uwind2*cr.calc_rusanov_alts_ausm(alt2,rho2)/rho2
        hozt_vgradrho2 = \
            (nwind2*cr.calc_rusanov_lats(lat2,alt2,rho2)\
            +ewind2*cr.calc_rusanov_lons(lon2,lat2,alt2,rho2))/rho2

        dc2 = [
            vert_divv2, hozt_divv2, vert_vgradrho2, hozt_vgradrho2,
            div_rhov2, rho2]

        alt_ind = np.argmin(np.abs(alt1[0, 0, :]/1000-alt))
        alt_str = '%6.0f' % (alt1[0, 0, alt_ind]/1000)

        for idc in range(6):
            lonticklabel = [0, 0, 0, 0]
            if idc == 0:
                lonticklabel[3] = lonticklabel[-1]+1
            if idc == 5:
                lonticklabel[1] = lonticklabel[-1]+1
            if itime == 0:
                lonticklabel[0] = lonticklabel[-2]+1
            if itime == 5:
                lonticklabel[2] = lonticklabel[-2]+1
            ax, projection = gcc.create_map(
                6, 6, itime*6+idc+1, 'polar', nlat=nlat, slat=slat, dlat=10,
                centrallon=g3ca.calculate_centrallon(g1, 'polar',  useLT=True),
                coastlines=False, lonticklabel=lonticklabel)
            g1['temp'] = -(dc1[idc] - dc2[idc])
            if idc==5:
                g1['temp'] = 100*(dc1[idc] - dc2[idc])/dc2[idc]
            lon0, lat0, zdata0 = g3ca.contour_data('temp', g1, alt=alt)
            fp = (lat0[:,0]>slat) & (lat0[:,0]<nlat)
            lon0, lat0, zdata0 = lon0[fp, :], lat0[fp,:], zdata0[fp,:]
            levels = np.linspace(-8,8,21)*1e-5
            if idc==5:
                levels = np.linspace(-30,30,21)
            hc = ax.contourf(
                lon0, lat0, zdata0, levels,
                transform=ccrs.PlateCarree(), cmap='seismic', extend='both')
            # wind difference
            alt_ind = np.argmin(np.abs(alt1[0, 0, :]/1000-alt))
            alt_str = '%6.0f' % (alt1[0, 0, alt_ind]/1000)
            lon1, lat1, ewind1, nwind1 = g3ca.vector_data(
                g1, 'neutral', alt=alt)
            lon2, lat2, ewind2, nwind2 = g3ca.vector_data(
                g2, 'neutral', alt=alt)
            lon0, lat0 = lon1, lat1
            lon0, lat0, ewind0, nwind0 = g3ca.convert_vector(
                    lon0, lat0, ewind1-ewind2, nwind1-nwind2,
                    plot_type='polar', projection=projection)
            hq = ax.quiver(
                    lon0, lat0, ewind0, nwind0, scale=1500,
                    scale_units='inches', regrid_shape=20, headwidth=5)
            ax.scatter(
                qlon, qlat, s=10, color='k', transform=ccrs.PlateCarree())
            ax.scatter(
                0, -90, color='w', s=10, transform=ccrs.PlateCarree(),
                zorder=1000)
            if idc==0:
                plt.text(
                    -0.3, 0.5, ylabel[itime], rotation=90,
                    transform=ax.transAxes, verticalalignment='center')
            if itime==0:
                plt.title(xtitle[idc], y=1.15, fontsize=14)
                texts = ['(a)', '(b)', '(c)', '(d)', '(e)', '(f)']
                plt.text(0.05,1,texts[idc],transform=plt.gca().transAxes,
                         color='r')
            if itime==5:
                axp = ax.get_position()
                cax = [axp.x0, axp.y0-0.03, axp.x1-axp.x0, 1/20*(axp.y1-axp.y0)]
                cax = plt.axes(cax)
                ticks = np.arange(-8e-5, 8.1e-5, 4e-5) if idc<5 else \
                        np.arange(-30, 31, 15)
                hcb = plt.colorbar(
                    hc, cax=cax, extendrect=True, orientation='horizontal',
                    ticks=ticks)
                if idc<5:
                    hcb.formatter.set_powerlimits((0,0))
                    hcb.update_ticks()
    plt.subplots_adjust(wspace=0, hspace=0)
    if alt==300:
        plt.savefig(savepath+'Figure5.eps')
        plt.savefig(savepath+'Figure5.jpeg')
    if alt==600:
        plt.savefig(savepath+'Figure7.eps')
        plt.savefig(savepath+'Figure7.jpeg')
    return
Esempio n. 21
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def geo2mag(lat, lon, alt):
    #Latitudes range from -90 to 90.
    #Longitudes range from -180 to 180. (Maybe, who knows --  http://ccmc.gsfc.nasa.gov/requests/instant/ranges.php
    #Verified with http://ccmc.gsfc.nasa.gov/requests/instant/instant1.php?model=AACGM&type=1
    mlat, mlon = convert(lat, lon, alt, None)
    return mlat
Esempio n. 22
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def test_exception_lat90():
    with pytest.raises(ValueError):
        aacgmv2.convert(91, 0, 300, dtObj)
    with pytest.raises(ValueError):
        aacgmv2.convert(-91, 0, 300, dtObj)
    with pytest.raises(ValueError):
        aacgmv2.convert([60, 91], 0, 300, dtObj)
    with pytest.raises(ValueError):
        aacgmv2.convert([60, -91], 0, 300, dtObj)

    # the following should not raise exceptions
    aacgmv2.convert(90, 0, 300, dtObj)
    aacgmv2.convert(-90, 0, 300, dtObj)
Esempio n. 23
0
def f4():
    plt.figure(figsize=(6.88, 6.74))
    #geographic coordinates
    ax1, projection1 = gcc.create_map(2,
                                      2,
                                      1,
                                      'pol',
                                      90,
                                      50,
                                      0,
                                      coastlines=False,
                                      useLT=True,
                                      dlat=10,
                                      lonticklabel=(1, 1, 1, 1))
    ax1.plot([45, 45], [50, 90], 'k--', transform=ccrs.PlateCarree())
    ax1.plot([225, 225], [50, 90], 'k--', transform=ccrs.PlateCarree())
    ax1.plot([105, 105], [50, 90], 'k--', transform=ccrs.PlateCarree())
    ax1.plot([285, 285], [50, 90], 'k--', transform=ccrs.PlateCarree())
    ax1.scatter(0,
                90,
                color='r',
                transform=ccrs.PlateCarree(),
                zorder=10,
                label='North Pole')
    ax1.text(0, 1, '(a)', transform=plt.gca().transAxes)
    plt.legend(loc=[0.5, 1.1])

    ax2, projection2 = gcc.create_map(2,
                                      2,
                                      2,
                                      'pol',
                                      -50,
                                      -90,
                                      0,
                                      coastlines=False,
                                      useLT=True,
                                      dlat=10,
                                      lonticklabel=(1, 1, 1, 1))
    ax2.scatter(0,
                -90,
                color='b',
                transform=ccrs.PlateCarree(),
                label='South Pole')
    ax2.text(0, 1, '(b)', transform=plt.gca().transAxes)
    plt.legend(loc=[-0.1, 1.1])

    #geomagnetic coordinates
    ax3, projection3 = gcc.create_map(2,
                                      2,
                                      3,
                                      'pol',
                                      90,
                                      50,
                                      0,
                                      coastlines=False,
                                      useLT=True,
                                      dlat=10,
                                      lonticklabel=(1, 1, 1, 1))
    mlatn, mlonn = convert(90, 0, 0, date=dt.date(2002, 3, 21))
    for k in range(24):
        mltn = convert_mlt(mlonn[0], dtime=dt.datetime(2003, 3, 21, k))
        ax3.scatter(mltn * 15,
                    mlatn[0],
                    color='r',
                    transform=ccrs.PlateCarree())
    ax3.scatter(180, 75, s=50, c='k', marker='x', transform=ccrs.PlateCarree())
    ax3.text(0, 1, '(c)', transform=plt.gca().transAxes)

    ax4, projection4 = gcc.create_map(2,
                                      2,
                                      4,
                                      'pol',
                                      -50,
                                      -90,
                                      0,
                                      coastlines=False,
                                      useLT=True,
                                      dlat=10,
                                      lonticklabel=(1, 1, 1, 1))
    mlats, mlons = convert(-90, 0, 0, date=dt.date(2002, 3, 21))
    for k in range(24):
        mlts = convert_mlt(mlons[0], dtime=dt.datetime(2003, 3, 21, k))
        ax4.scatter(mlts * 15,
                    mlats[0],
                    color='b',
                    transform=ccrs.PlateCarree())
    ax4.scatter(180,
                -75,
                s=50,
                c='k',
                marker='x',
                transform=ccrs.PlateCarree())
    ax4.text(0, 1, '(d)', transform=plt.gca().transAxes)
    plt.savefig('/Users/guod/Documents/Pole_Density_MLT_Change/Figures/'
                '000_Pole_Feature.pdf')
    return
Esempio n. 24
0
def plot_06ut_18ut(ns='SH', alt=150, tf=[1, 0, 0, 0, 0, 0]):
    # 0:rho and wind; 1: diff rho and wind; 2:ion drag; 3:vni; 4:ion convection
    # 5:ion density; 6:electron density;
    path = '/home/guod/simulation_output/momentum_analysis/run_shrink_dipole_1_c1/UA/data'
    fn1 = path + '/3DALL_t030322_060002.bin'
    fn2 = path + '/3DALL_t030322_180002.bin'
    g11 = [gitm.read(fn1), gitm.read(fn2)]  # shrink, dipole
    #print(g11[0]['Altitude'][0,0,np.argmin(np.abs(g11[0]['Altitude'][0,0,:]-150*1000))])

    path = '/home/guod/simulation_output/momentum_analysis/run_shrink_igrf_1_c1/UA/data'
    fn1 = path + '/3DALL_t030322_060002.bin'
    fn2 = path + '/3DALL_t030322_180003.bin'
    g12 = [gitm.read(fn1), gitm.read(fn2)]  # shrink, igrf

    path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_dipole_1_1/UA/data'
    fn1 = path + '/3DALL_t030322_060000.bin'
    fn2 = path + '/3DALL_t030322_180001.bin'
    g21 = [gitm.read(fn1), gitm.read(fn2)]  # no shrink, diple

    path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_igrf_1_1/UA/data'
    fn1 = path + '/3DALL_t030322_060001.bin'
    fn2 = path + '/3DALL_t030322_180002.bin'
    g22 = [gitm.read(fn1), gitm.read(fn2)]  # no shrink, igrf

    if ns == 'SH':
        nlat, slat = -50, -90
    elif ns == 'NH':
        nlat, slat = 90, 50
    glats, glons = convert(-90, 0, 0, date=dt.date(2003, 1, 1), a2g=True)
    glatn, glonn = convert(90, 0, 0, date=dt.date(2003, 1, 1), a2g=True)
    fign = ['(a)', '(b)', '(c)', '(d)']
    # Rho and wind
    if tf[0]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            ax, projection, hc, hq = plot_polar_contour_vector(
                2,
                2,
                k + 1,
                gtemp[k % 2],
                nlat,
                slat,
                alt,
                contour=True,
                zstr='Rho',
                vector=True,
                neuion='neu',
                useLT=True,
                coastlines=False,
                levels=np.linspace(0.8e-9, 1.6e-9, 21))
            if k in [0, 1]:
                ax.scatter(glons,
                           glats,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
                ax.scatter(glonn,
                           glatn,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
            ax.scatter(0,
                       90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            ax.scatter(0,
                       -90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            if k in [0, 1]:
                plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k == 0 else 'Dipole'
                plt.text(-0.2,
                         0.5,
                         text,
                         fontsize=14,
                         verticalalignment='center',
                         transform=plt.gca().transAxes,
                         rotation=90)
            plt.text(0, 1, fign[k], fontsize=14, transform=plt.gca().transAxes)
        plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(hc[0],
                     cax=cax,
                     orientation='horizontal',
                     ticks=np.arange(0.8e-9, 1.7e-9, 0.2e-9))
        cax.set_xlabel(r'$\rho (kg/m^3)$')
        plt.quiverkey(hq[0], 0.5, 0.12, 500, '500m/s', coordinates='figure')
        plt.savefig(savepath + '2' + ns + 'RhoWind.jpeg')
        plt.savefig(savepath + '2' + ns + 'RhoWind.eps')

    # ion drag
    if tf[1]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            calc_rhoi(gtemp[0])
            calc_rhoi(gtemp[1])
            gtemp[0]['iondrag'] = \
                gtemp[0]['rhoi']/gtemp[0]['Rho']*gtemp[0]['Collision(in)']*\
                np.sqrt((gtemp[0]['V!Di!N (east)']-gtemp[0]['V!Dn!N (east)'])**2 +\
                        (gtemp[0]['V!Di!N (north)']-gtemp[0]['V!Dn!N (north)'])**2)
            gtemp[1]['iondrag'] = \
                gtemp[1]['rhoi']/gtemp[1]['Rho']*gtemp[1]['Collision(in)']*\
                np.sqrt((gtemp[1]['V!Di!N (east)']-gtemp[1]['V!Dn!N (east)'])**2 +\
                        (gtemp[1]['V!Di!N (north)']-gtemp[1]['V!Dn!N (north)'])**2)
            ax, projection, hc, hq = plot_polar_contour_vector(
                2,
                2,
                k + 1,
                gtemp[k % 2],
                nlat,
                slat,
                alt,
                contour=True,
                zstr='iondrag',
                vector=False,
                neuion='neu',
                useLT=True,
                coastlines=False,
                levels=np.linspace(0, 0.05, 21))
            if k in [0, 1]:
                ax.scatter(glons,
                           glats,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
                ax.scatter(glonn,
                           glatn,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
            ax.scatter(0,
                       90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            ax.scatter(0,
                       -90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            if k in [0, 1]:
                plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k == 0 else 'Dipole'
                plt.text(-0.2,
                         0.5,
                         text,
                         fontsize=14,
                         verticalalignment='center',
                         transform=plt.gca().transAxes,
                         rotation=90)
        plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(hc[0],
                     cax=cax,
                     orientation='horizontal',
                     ticks=np.arange(0, 0.051, 0.01))
        cax.set_xlabel(r'Ion Drag $(m/s^2)$')
        plt.savefig(savepath + '3' + ns + 'IonDrag.jpeg')
        plt.savefig(savepath + '3' + ns + 'IonDrag.eps')

    # vni
    if tf[2]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            calc_rhoi(gtemp[0])
            calc_rhoi(gtemp[1])
            gtemp[0]['vni'] = \
                gtemp[0]['rhoi']/gtemp[0]['Rho']*gtemp[0]['Collision(in)']
            gtemp[1]['vni'] = \
                gtemp[1]['rhoi']/gtemp[1]['Rho']*gtemp[1]['Collision(in)']
            ax, projection, hc, hq = plot_polar_contour_vector(
                2,
                2,
                k + 1,
                gtemp[k % 2],
                nlat,
                slat,
                alt,
                contour=True,
                zstr='vni',
                vector=False,
                neuion='neu',
                useLT=True,
                coastlines=False,
                levels=np.linspace(0, 0.0002, 21))
            if k in [0, 1]:
                ax.scatter(glons,
                           glats,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
                ax.scatter(glonn,
                           glatn,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
            ax.scatter(0,
                       90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            ax.scatter(0,
                       -90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            if k in [0, 1]:
                plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k == 0 else 'Dipole'
                plt.text(-0.2,
                         0.5,
                         text,
                         fontsize=14,
                         verticalalignment='center',
                         transform=plt.gca().transAxes,
                         rotation=90)
        plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(hc[0],
                     cax=cax,
                     orientation='horizontal',
                     ticks=np.arange(0, 0.00021, 0.0001))
        cax.set_xlabel(r'$\nu_{ni}$ $(s^{-1})$')
        plt.savefig(savepath + '4' + ns + 'vni.jpeg')
        plt.savefig(savepath + '4' + ns + 'vni.eps')

    # ion convection
    if tf[3]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            gtemp[0]['vi'] = np.sqrt(gtemp[0]['V!Di!N (east)']**2 +
                                     gtemp[0]['V!Di!N (north)']**2)
            gtemp[1]['vi'] = np.sqrt(gtemp[1]['V!Di!N (east)']**2 +
                                     gtemp[1]['V!Di!N (north)']**2)
            ax, projection, hc, hq = plot_polar_contour_vector(
                2,
                2,
                k + 1,
                gtemp[k % 2],
                nlat,
                slat,
                alt,
                contour=True,
                zstr='vi',
                vector=True,
                neuion='ion',
                useLT=True,
                coastlines=False,
                levels=np.linspace(0, 1000, 21))
            if k in [0, 1]:
                ax.scatter(glons,
                           glats,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
                ax.scatter(glonn,
                           glatn,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
            ax.scatter(0,
                       90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            ax.scatter(0,
                       -90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            if k in [0, 1]:
                plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k == 0 else 'Dipole'
                plt.text(-0.2,
                         0.5,
                         text,
                         fontsize=14,
                         verticalalignment='center',
                         transform=plt.gca().transAxes,
                         rotation=90)
        plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(hc[0],
                     cax=cax,
                     orientation='horizontal',
                     ticks=np.arange(0, 1001, 200))
        cax.set_xlabel(r'Vi (m/s)')
        plt.savefig(savepath + '5' + ns + 'IonV.jpeg')
        plt.savefig(savepath + '5' + ns + 'IonV.eps')

    # ion density
    if tf[4]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            calc_rhoi(gtemp[0])
            calc_rhoi(gtemp[1])
            ax, projection, hc, hq = plot_polar_contour_vector(
                2,
                2,
                k + 1,
                gtemp[k % 2],
                nlat,
                slat,
                alt,
                contour=True,
                zstr='rhoi',
                vector=False,
                neuion='neu',
                useLT=True,
                coastlines=False,
                levels=np.linspace(0, 12e-15, 21))
            if k in [0, 1]:
                ax.scatter(glons,
                           glats,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
                ax.scatter(glonn,
                           glatn,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
            ax.scatter(0,
                       90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            ax.scatter(0,
                       -90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            if k in [0, 1]:
                plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k == 0 else 'Dipole'
                plt.text(-0.2,
                         0.5,
                         text,
                         fontsize=14,
                         verticalalignment='center',
                         transform=plt.gca().transAxes,
                         rotation=90)
        plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(hc[0],
                     cax=cax,
                     orientation='horizontal',
                     ticks=np.arange(0, 12.1e-15, 3e-15))
        cax.set_xlabel(r'$\rho_i$ $(kg/m^3)$')
        plt.savefig(savepath + '6' + ns + 'Rhoi.jpeg')
        plt.savefig(savepath + '6' + ns + 'Rhoi.eps')

    #  electron density
    if tf[5]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            calc_rhoi(gtemp[0])
            calc_rhoi(gtemp[1])
            ax, projection, hc, hq = plot_polar_contour_vector(
                2,
                2,
                k + 1,
                gtemp[k % 2],
                nlat,
                slat,
                alt,
                contour=True,
                zstr='e-',
                vector=False,
                neuion='neu',
                useLT=True,
                coastlines=False,
                levels=np.linspace(0, 0.9e12, 21))
            if k in [0, 1]:
                ax.scatter(glons,
                           glats,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
                ax.scatter(glonn,
                           glatn,
                           transform=ccrs.PlateCarree(),
                           s=55,
                           c='k')
            ax.scatter(0,
                       90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            ax.scatter(0,
                       -90,
                       transform=ccrs.PlateCarree(),
                       s=55,
                       c='w',
                       zorder=100)
            if k in [0, 1]:
                plt.title('UT: ' + gtemp[k % 2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k == 0 else 'Dipole'
                plt.text(-0.2,
                         0.5,
                         text,
                         fontsize=14,
                         verticalalignment='center',
                         transform=plt.gca().transAxes,
                         rotation=90)
        plt.subplots_adjust(bottom=0.13, top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(hc[0],
                     cax=cax,
                     orientation='horizontal',
                     ticks=np.arange(0, 0.31e12, 0.1e12))
        cax.set_xlabel(r'Ne ($m^{-3}$)')
        # plt.savefig(savepath+'7'+ns+'Ne.jpeg')
        # plt.savefig(savepath+'7'+ns+'Ne.eps')
    return
Esempio n. 25
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 def test_convert_lat_failure(self):
     """Test error return for co-latitudes above 90 for an array"""
     with pytest.raises(AssertionError):
         aacgmv2.convert([91, 60, -91], 0, 300, self.dtime)
Esempio n. 26
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def figure1():
    plt.close('all')
    fig = plt.figure(figsize=(5.41, 8.54))
    ax = fig.add_subplot(111, projection='3d')

    levels = [np.linspace(6.1e-10, 17.8e-10,21), np.linspace(1.1e-10, 2.7e-10, 21),
              np.linspace(1.3e-11, 3.9e-11,21), np.linspace(2.6e-12, 9.503e-12,21),
              np.linspace(4.3e-13, 2.71e-12,21), np.linspace(7.4e-14, 8.2e-13,21)]
    olat = -40
    olatr = np.abs(olat)/180*pi

    glats, glons = convert(-90,0,0,date=dt.date(2003,3,22), a2g=True)
    glats, glons = glats/180*pi, glons/180*pi

    artalt = [10, 200, 380, 540, 680, 820]
    realalt = [150, 200, 300, 400, 500, 600]
    for ik, alt in enumerate([150, 200, 300, 400, 500, 600]):
        lon0, lat0, rho1 = g3ca.contour_data('Rho', g1, alt=alt)
        lat0, lon0 = lat0/180*pi, lon0/180*pi
        ilat = lat0[:, 0]<=olat/180*pi
        lat0, lon0, rho1 = lat0[ilat,:], lon0[ilat,:], rho1[ilat,:]
        r = lat0+pi/2
        theta = lon0
        x = r*np.cos(theta)
        x = -x # for sorthern hemisphere
        y = r*np.sin(theta)
        v = rho1
        print (np.min(v), np.max(v))
        ax.contourf(
            x, y, v, zdir='z', offset=artalt[ik], levels=levels[ik],
            cmap='jet', zorder=100)
        ax.scatter(
            -(glats+pi/2)*np.cos(glons), (glats+pi/2)*np.sin(glons),
            artalt[ik], s=50, c='k', zorder=200)
        for rtick in np.arange(10,50,10)/180*pi:
            thetatick = np.arange(0, 2*pi, 0.01)
            xtick = rtick*np.cos(thetatick)
            ytick = rtick*np.sin(thetatick)
            hp = ax.plot(
                xtick,ytick, artalt[ik], color='0.7',linestyle=':',
                zorder = 300, linewidth=0.8)
    plt.subplots_adjust(top=1,bottom=0)
    ax.set_xlim(-olatr, olatr)
    ax.set_ylim(-olatr, olatr)
    ax.set_zlim(0,800)
    ax.axis('off')

    for ik, alt in enumerate(artalt):
        ialt = np.argmin(np.abs(g1['Altitude'][0,0,:]/1000-realalt[ik]))
        ax.plot([-olatr, -olatr+0.1], [-olatr, -olatr], alt, color='k')
        ax.text(-olatr-0.1, -olatr, alt,
                '%.0f km'%(g1['Altitude'][0,0,ialt]/1000),
                verticalalignment='center')
    ax.plot([-olatr, -olatr], [-olatr, -olatr], [artalt[0], artalt[-1]], color='k')

    ax.text(-olatr-0.3, 0, artalt[-1], '06', horizontalalignment='center',
            zdir='x', zorder=1000)
    ax.text(0, -olatr-0.3, artalt[-1], '00', horizontalalignment='center',
            zdir='x', zorder=1000)
    ax.text(olatr+0.3, 0, artalt[-1], '18', horizontalalignment='center',
            zdir='x', zorder=1000)
    ax.text(0, olatr+0.3, artalt[-1], '12', horizontalalignment='center',
            zdir='x', zorder=1000)
    plt.show()
    return
Esempio n. 27
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def figure4():
    plt.close('all')
    plt.figure(figsize=(8.28, 9.25))
    labels =[('(a)','(b)','(c)'), ('(d)','(e)','(f)'), ('(g)','(h)','(i)')]
    qlat, qlon = convert(-90, 0, 0, date=dt.date(2003,3,22), a2g=True)
    ylim = [[0.6e-9,1.6e-9], [1.5e-11, 4e-11], [1e-13, 9e-13]]
    for ialt, alt in enumerate([150, 300, 600]):
        alt_ind = np.argmin(np.abs(g1['Altitude'][0, 0, 2:-2]/1000-alt))+2
        alt_str = '%6.0f' % (g1['Altitude'][0, 0, alt_ind]/1000)
        rho1, rho2 = g1['Rho'], g2['Rho']
        rhod = 100*(rho1-rho2)/rho2
        lats, lons  = g1['Latitude'], g1['Longitude']

        #----------------------------------------------------------------------
        ax, projection = gcc.create_map(
            3, 3, ialt+1, 'polar', nlat=nlat, slat=slat, dlat=10,
            centrallon=g3ca.calculate_centrallon(g1, 'polar',  useLT=True),
            coastlines=False, lonticklabel=[1,1,1,1])

        # density difference
        lon1, lat1, zdata1 = g3ca.contour_data('Rho', g1, alt=alt)
        lon2, lat2, zdata2 = g3ca.contour_data('Rho', g2, alt=alt)
        fp = (lat1[:,0]>slat) & (lat1[:,0]<nlat)
        lon0, lat0 = lon1[fp, :], lat1[fp,:]
        zdata0 = (100*(zdata1-zdata2)/zdata2)[fp, :]
        print(zdata0.min())
        hc = ax.contourf(
            lon0, lat0, zdata0, np.linspace(-30,30,21),
            transform=ccrs.PlateCarree(), cmap='seismic', extend='both')
        # colorbar
        gcapos = ax.get_position()
        axcb = [
            gcapos.x0, gcapos.y0+0.035, gcapos.width, gcapos.height/20]
        axcb = plt.axes(axcb)
        hcb = plt.colorbar(
            hc, cax=axcb, extendrect=True, ticks=np.arange(-30, 31, 15),
            orientation='horizontal')

        # wind difference
        lon1, lat1, ewind1, nwind1 = g3ca.vector_data(g1, 'neutral', alt=alt)
        lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2, 'neutral', alt=alt)
        lon0, lat0 = lon1, lat1
        lon0, lat0, ewind0, nwind0 = g3ca.convert_vector(
                lon0, lat0, ewind1-ewind2, nwind1-nwind2, plot_type='polar',
                projection=projection)
        hq = ax.quiver(
                lon0, lat0, ewind0, nwind0, scale=1000, scale_units='inches',
                regrid_shape=20, headwidth=5)
        ax.quiverkey(hq, 0.97, 0.92, 500, '500 m/s')

        # magnetic pole
        ax.scatter(qlon, qlat, color='k', transform=ccrs.PlateCarree())
        ax.scatter(
            0, -90, color='w', s=30, transform=ccrs.PlateCarree(), zorder=1000)

        latt1 = [-90, nlat]
        lont1 = [15*(12-ut), 15*(12-ut)]
        ax.plot(lont1, latt1, transform = ccrs.PlateCarree(), c='g')
        latt1 = [-90, nlat]
        lont1 = [15*(0-ut), 15*(0-ut)]
        ax.plot(lont1, latt1, transform = ccrs.PlateCarree(), c='g')
        ax.set_title('%s km' % alt_str, y=1.07)
        if ialt==0:
            ax.text(-0.2, 0.5, r'$\delta \rho$ (%)',
                    transform=ax.transAxes,rotation=90, fontsize=14,
                    verticalalignment='center', horizontalalignment='center')
        plt.text(
            0.05, 0.9, labels[0][ialt],transform=ax.transAxes,color='r')

        #----------------------------------------------------------------------
        # density in run1 and run2
        plt.subplot(3,3,ialt+7)
        ilat = (lats[0,:,0]/pi*180<nlat) &(lats[0,:,0]/pi*180>slat)
        lt = 12
        ilt = np.argmin(np.abs(g1['LT'][2:-2,0,0]-lt))+2
        plt.plot(
            180+lats[ilt,ilat,alt_ind]/pi*180,rho1[ilt,ilat,alt_ind], 'r',
            label = 'Run 1')
        plt.plot(
            180+lats[ilt,ilat,alt_ind]/pi*180,rho2[ilt,ilat,alt_ind], 'b',
            label = 'Run 2')
        plt.legend(loc='upper center')
        lat_1, rho_11, rho_12, rho_1d = \
            180+lats[ilt,2,alt_ind]/pi*180, rho1[ilt,2, alt_ind], \
            rho2[ilt,2, alt_ind], rhod[ilt,2,alt_ind]

        lt = 0
        ilt = np.argmin(np.abs(g1['LT'][2:-2,0,0]-lt))+2
        plt.plot(-lats[ilt,ilat,alt_ind]/pi*180,rho1[ilt,ilat,alt_ind], 'r')
        plt.plot(-lats[ilt,ilat,alt_ind]/pi*180,rho2[ilt,ilat,alt_ind], 'b')
        lat_2, rho_21, rho_22, rho_2d = \
            -lats[ilt,2,alt_ind]/pi*180, rho1[ilt,2, alt_ind], \
            rho2[ilt,2, alt_ind], rhod[ilt,2,alt_ind]

        plt.plot([lat_1,lat_2], [rho_11,rho_21], 'r')
        plt.plot([lat_1,lat_2], [rho_12,rho_22], 'b')
        plt.grid('on')

        plt.xlim([-nlat,180+nlat])
        plt.ylim(ylim[ialt])
        plt.xticks(np.arange(-nlat,181+nlat,30),
            np.concatenate(
                [np.arange(nlat,-90,-30), np.arange(-90,nlat+1,30)]))

        if ialt==0:
            plt.ylabel(r'$\rho$ (kg/m$^3$)', fontsize=14)
        plt.xlabel('Latitude')
        plt.text(
            0.05, 0.9, labels[2][ialt],transform=plt.gca().transAxes,color='r')

        #----------------------------------------------------------------------
        # density difference
        plt.subplot(3,3,ialt+4)
        lt = 12
        ilt = np.argmin(np.abs(g1['LT'][2:-2,0,0]-lt))+2
        plt.plot(
            180+lats[ilt,ilat,alt_ind]/pi*180,rhod[ilt,ilat,alt_ind], 'k')

        lt = 0
        ilt = np.argmin(np.abs(g1['LT'][2:-2,0,0]-lt))+2
        plt.plot(
            -lats[ilt,ilat,alt_ind]/pi*180,rhod[ilt,ilat,alt_ind], 'k')
        plt.plot([lat_1,lat_2], [rho_1d,rho_2d], 'k')

        plt.grid('on')

        plt.xlim([-nlat,180+nlat])
        plt.xticks(np.arange(-nlat,181+nlat,30),
            np.concatenate(
                [np.arange(nlat,-90,-30), np.arange(-90,nlat+1,30)]))
        plt.ylim(-35, 5)
        plt.yticks(np.arange(-30, 0.1, 10))
        if ialt==0:
            plt.ylabel(r'$\delta\rho$ (%)', fontsize=14)
        plt.xlabel('Latitude')
        plt.text(
            0.05, 0.9, labels[1][ialt],transform=plt.gca().transAxes,color='r')

    plt.subplots_adjust(wspace=0.25, hspace=0.25, top=0.95, bottom=0.05)
    plt.savefig(savepath+'Figure4.eps')
    plt.savefig(savepath+'Figure4.jpeg')
    return
Esempio n. 28
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def test_warning_below_ground():
    with pytest.warns(UserWarning):
        aacgmv2.convert(60, 0, -1, dtObj)
    with pytest.warns(UserWarning):
        aacgmv2.convert(60, 0, [300, -1], dtObj)
Esempio n. 29
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 def test_convert_maxalt_failure(self):
     """For an array, test failure for an altitude too high for
     coefficients"""
     with pytest.raises(ValueError):
         aacgmv2.convert([60], [0], [2001], self.dtime)
Esempio n. 30
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def readDay(hemiSN,
            dt,
            deltaT=2,
            fileType='grdex',
            src=None,
            fileName=None,
            custType='grdex',
            noCache=False):
    """Read one day and hemisphere of SuperDARN data
	
	(All of these other options are passed through just_sam to DavitPy)
	
	Parameters
	----------
        hemiSN: N or S
	dt : TYPE
	    Description
	deltaT : int, optional
	    Description
	fileType : str, optional
	    Description
	src : None, optional
	    Description
	fileName : None, optional
	    Description
	custType : str, optional
	    Description
	noCache : bool, optional
	    Description
	
	Returns
	-------
	TYPE
	    Description
	"""
    #import davitpy.models.aacgm as aacgm

    #def _sdGridLoad(sTime,eTime,deltaT,hemi,fileType,src,fileName,custType,noCache,estd=False,TWidth=None):

    #SAM uses different hemisphere naming convention
    if hemiSN is 'N':
        hemi = 'north'
    elif hemiSN is 'S':
        hemi = 'south'

    #Load in data in 2 minute chunks
    sdList = _sdGridLoad(dt,
                         dt + datetime.timedelta(days=1),
                         deltaT,
                         hemi,
                         fileType,
                         src,
                         fileName,
                         custType,
                         noCache,
                         estd=False,
                         TWidth=None)

    #Split out data into numpy arrays
    #Each sdI is a griddata object from pydarn.sdio.sdDataTypes
    startdts, enddts = [], []
    mlats, mlons, mltlons, vels, verrs, azms, rids = [], [], [], [], [], [], []
    eloss, eerrs = [], []  #Electric fields will be compute inplace
    bigrfs = []

    for sdI in sdList:
        if sdI.vector.mlat is None or sdI.vector.mlon is None:
            print sdI.vector
            continue

        startdts.append(sdI.sTime)
        enddts.append(sdI.eTime)
        mlat = np.asarray(sdI.vector.mlat)
        mlats.append(mlat)
        #Do in-band MLT conversion
        mlon = np.asarray(sdI.vector.mlon)
        y, M, d = sdI.sTime.year, sdI.sTime.month, sdI.sTime.day
        h, m, s = sdI.sTime.hour, sdI.sTime.minute, sdI.sTime.second
        # mltDef = aacgm.mltFromYmdhms(y,M,d,h,m,s,0.0) * 15.
        # mltDef is the rotation that needs to be applied,
        # and lon is the AACGM longitude.
        # use modulo so new longitude is between 0 & 360
        # mlt_lon = np.mod((mlon + mltDef), 360.)

        mlt_lon = aacgmv2.convert_mlt(mlon, sdI.sTime, False)  ## sishen added
        mlons.append(mlon)  #Actual mlon
        mltlons.append(mlt_lon)  #MLT in degrees
        #Convert to electric field
        vel = np.asarray(sdI.vector.velmedian)
        verr = np.asarray(sdI.vector.velsd)
        vels.append(vel)
        verrs.append(verr)

        # Where do superDARN returns come from?
        approx_alt = 300.

        #Could use either Apex-Python or AACGMv2 package
        #for magnetic to geocentric conversion
        gdlat, gdlon = aacgmv2.convert(mlat,
                                       mlon,
                                       approx_alt,
                                       date=sdI.sTime,
                                       a2g=True)
        #gdlat,gdlon = ac.apex2geo(mlat,mlon,approx_alt)
        Be, Bn, Bu = igrfpy.getmainfield(sdI.sTime,
                                         gdlat,
                                         gdlon,
                                         np.ones_like(gdlat) * approx_alt,
                                         geocentric=False,
                                         silent=True)
        Bu = np.abs(np.array(Bu))  # It returns lists

        # Convert SuperDARN Vlos to E-field
        # (Should be using IGRF...just using constant instead)
        # Will change after compare with SAM
        #Bconst = 0.5e-4

        bigrfs.append(Bu * 1.0e-9)
        eloss.append(vel * Bu * 1.0e-9)
        eerrs.append(verr * Bu * 1.0e-9)

        azms.append(np.asarray(sdI.vector.kvect))  #degrees
        rids.append(np.asarray(sdI.vector.stid))  #station id num

    return (startdts, enddts, mlats, mlons, mltlons, vels, verrs, eloss, eerrs,
            azms, rids, bigrfs)
Esempio n. 31
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 def test_convert_datetime_date(self):
     """Test conversion with date and datetime input"""
     self.lat, self.lon = aacgmv2.convert([60], [0], [300], self.ddate)
     np.testing.assert_allclose(self.lat, [58.2258], rtol=1e-4)
     np.testing.assert_allclose(self.lon, [81.1685], rtol=1e-4)
Esempio n. 32
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def test_forbidden():
    mlat, mlon = aacgmv2.convert(7, 0, 0)
    assert np.isnan(mlat)
    assert np.isnan(mlon)
Esempio n. 33
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def test_convert_result_values_G2A_coeff():
    lat_p, lon_p = aacgmv2.convert(60, 0, 300, dtObj)
    aacgmv2._aacgmv2.setDateTime(*date)
    lat_c, lon_c, _ = aacgmv2._aacgmv2.aacgmConvert(60, 0, 300, G2A)
    assert lat_p == lat_c
    assert lon_p == lon_c
Esempio n. 34
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def plot_06ut_18ut(ns='SH',alt=150,tf=[1,0,0,0,0,0]):
    # 0:rho and wind; 1: diff rho and wind; 2:ion drag; 3:vni; 4:ion convection
    # 5:ion density; 6:electron density;
    path = '/home/guod/simulation_output/momentum_analysis/run_shrink_dipole_1_c1/UA/data'
    fn1 = path+'/3DALL_t030322_060002.bin'
    fn2 = path+'/3DALL_t030322_180002.bin'
    g11 = [gitm.read(fn1), gitm.read(fn2)] # shrink, dipole
    #print(g11[0]['Altitude'][0,0,np.argmin(np.abs(g11[0]['Altitude'][0,0,:]-150*1000))])

    path = '/home/guod/simulation_output/momentum_analysis/run_shrink_igrf_1_c1/UA/data'
    fn1 = path+'/3DALL_t030322_060002.bin'
    fn2 = path+'/3DALL_t030322_180003.bin'
    g12 = [gitm.read(fn1), gitm.read(fn2)] # shrink, igrf

    path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_dipole_1_1/UA/data'
    fn1 = path+'/3DALL_t030322_060000.bin'
    fn2 = path+'/3DALL_t030322_180001.bin'
    g21 = [gitm.read(fn1), gitm.read(fn2)] # no shrink, diple

    path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_igrf_1_1/UA/data'
    fn1 = path+'/3DALL_t030322_060001.bin'
    fn2 = path+'/3DALL_t030322_180002.bin'
    g22 = [gitm.read(fn1), gitm.read(fn2)] # no shrink, igrf

    if ns == 'SH':
        nlat, slat = -50, -90
    elif ns == 'NH':
        nlat, slat = 90, 50
    glats, glons = convert(-90, 0, 0, date=dt.date(2003,1,1), a2g=True)
    glatn, glonn = convert(90, 0, 0, date=dt.date(2003,1,1), a2g=True)
    fign=['(a)','(b)','(c)','(d)']
    # Rho and wind
    if tf[0]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            ax, projection, hc, hq = plot_polar_contour_vector(
                2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='Rho',
                vector=True, neuion='neu', useLT=True, coastlines=False,
                levels=np.linspace(0.8e-9, 1.6e-9, 21))
            if k in [0, 1]:
                ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
                ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
            ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            if k in [0, 1]:
                plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k==0 else 'Dipole'
                plt.text(
                    -0.2, 0.5, text, fontsize=14, verticalalignment='center',
                    transform=plt.gca().transAxes, rotation=90)
            plt.text(
                0, 1, fign[k], fontsize=14, transform=plt.gca().transAxes)
        plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(
            hc[0], cax=cax, orientation='horizontal',
            ticks=np.arange(0.8e-9, 1.7e-9, 0.2e-9))
        cax.set_xlabel(r'$\rho (kg/m^3)$')
        plt.quiverkey(hq[0], 0.5,0.12, 500, '500m/s',coordinates='figure')
        plt.savefig(savepath+'2'+ns+'RhoWind.jpeg')
        plt.savefig(savepath+'2'+ns+'RhoWind.eps')

    # ion drag
    if tf[1]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            calc_rhoi(gtemp[0])
            calc_rhoi(gtemp[1])
            gtemp[0]['iondrag'] = \
                gtemp[0]['rhoi']/gtemp[0]['Rho']*gtemp[0]['Collision(in)']*\
                np.sqrt((gtemp[0]['V!Di!N (east)']-gtemp[0]['V!Dn!N (east)'])**2 +\
                        (gtemp[0]['V!Di!N (north)']-gtemp[0]['V!Dn!N (north)'])**2)
            gtemp[1]['iondrag'] = \
                gtemp[1]['rhoi']/gtemp[1]['Rho']*gtemp[1]['Collision(in)']*\
                np.sqrt((gtemp[1]['V!Di!N (east)']-gtemp[1]['V!Dn!N (east)'])**2 +\
                        (gtemp[1]['V!Di!N (north)']-gtemp[1]['V!Dn!N (north)'])**2)
            ax, projection, hc, hq = plot_polar_contour_vector(
                2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='iondrag',
                vector=False, neuion='neu', useLT=True, coastlines=False,
                levels=np.linspace(0, 0.05, 21))
            if k in [0, 1]:
                ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
                ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
            ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            if k in [0, 1]:
                plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k==0 else 'Dipole'
                plt.text(
                    -0.2, 0.5, text, fontsize=14, verticalalignment='center',
                    transform=plt.gca().transAxes, rotation=90)
        plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(
            hc[0], cax=cax, orientation='horizontal',
            ticks=np.arange(0, 0.051, 0.01))
        cax.set_xlabel(r'Ion Drag $(m/s^2)$')
        plt.savefig(savepath+'3'+ns+'IonDrag.jpeg')
        plt.savefig(savepath+'3'+ns+'IonDrag.eps')

    # vni
    if tf[2]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            calc_rhoi(gtemp[0])
            calc_rhoi(gtemp[1])
            gtemp[0]['vni'] = \
                gtemp[0]['rhoi']/gtemp[0]['Rho']*gtemp[0]['Collision(in)']
            gtemp[1]['vni'] = \
                gtemp[1]['rhoi']/gtemp[1]['Rho']*gtemp[1]['Collision(in)']
            ax, projection, hc, hq = plot_polar_contour_vector(
                2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='vni',
                vector=False, neuion='neu', useLT=True, coastlines=False,
                levels=np.linspace(0, 0.0002, 21))
            if k in [0, 1]:
                ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
                ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
            ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            if k in [0, 1]:
                plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k==0 else 'Dipole'
                plt.text(
                    -0.2, 0.5, text, fontsize=14, verticalalignment='center',
                    transform=plt.gca().transAxes, rotation=90)
        plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(
            hc[0], cax=cax, orientation='horizontal',
            ticks=np.arange(0, 0.00021, 0.0001))
        cax.set_xlabel(r'$\nu_{ni}$ $(s^{-1})$')
        plt.savefig(savepath+'4'+ns+'vni.jpeg')
        plt.savefig(savepath+'4'+ns+'vni.eps')

    # ion convection
    if tf[3]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            gtemp[0]['vi'] = np.sqrt(
                gtemp[0]['V!Di!N (east)']**2 + gtemp[0]['V!Di!N (north)']**2)
            gtemp[1]['vi'] = np.sqrt(
                gtemp[1]['V!Di!N (east)']**2 + gtemp[1]['V!Di!N (north)']**2)
            ax, projection, hc, hq = plot_polar_contour_vector(
                2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='vi',
                vector=True, neuion='ion', useLT=True, coastlines=False,
                levels=np.linspace(0, 1000, 21))
            if k in [0, 1]:
                ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
                ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
            ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            if k in [0, 1]:
                plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k==0 else 'Dipole'
                plt.text(
                    -0.2, 0.5, text, fontsize=14, verticalalignment='center',
                    transform=plt.gca().transAxes, rotation=90)
        plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(
            hc[0], cax=cax, orientation='horizontal',
            ticks=np.arange(0, 1001, 200))
        cax.set_xlabel(r'Vi (m/s)')
        plt.savefig(savepath+'5'+ns+'IonV.jpeg')
        plt.savefig(savepath+'5'+ns+'IonV.eps')

    # ion density
    if tf[4]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            calc_rhoi(gtemp[0])
            calc_rhoi(gtemp[1])
            ax, projection, hc, hq = plot_polar_contour_vector(
                2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='rhoi',
                vector=False, neuion='neu', useLT=True, coastlines=False,
                levels=np.linspace(0, 12e-15, 21))
            if k in [0, 1]:
                ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
                ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
            ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            if k in [0, 1]:
                plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k==0 else 'Dipole'
                plt.text(
                    -0.2, 0.5, text, fontsize=14, verticalalignment='center',
                    transform=plt.gca().transAxes, rotation=90)
        plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(
            hc[0], cax=cax, orientation='horizontal',
            ticks=np.arange(0, 12.1e-15, 3e-15))
        cax.set_xlabel(r'$\rho_i$ $(kg/m^3)$')
        plt.savefig(savepath+'6'+ns+'Rhoi.jpeg')
        plt.savefig(savepath+'6'+ns+'Rhoi.eps')

    #  electron density
    if tf[5]:
        plt.figure(1, figsize=(8, 7.55))
        for k in range(4):
            gtemp = g22 if k in [0, 1] else g21
            calc_rhoi(gtemp[0])
            calc_rhoi(gtemp[1])
            ax, projection, hc, hq = plot_polar_contour_vector(
                2, 2, k+1, gtemp[k%2], nlat, slat, alt, contour=True, zstr='e-',
                vector=False, neuion='neu', useLT=True, coastlines=False,
                levels=np.linspace(0, 0.9e12, 21))
            if k in [0, 1]:
                ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=55, c='k')
                ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=55, c='k')
            ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=55, c='w',zorder=100)
            if k in [0, 1]:
                plt.title('UT: '+gtemp[k%2]['time'].strftime('%H'), y=1.05)
            if k in [0, 2]:
                text = 'IGRF' if k==0 else 'Dipole'
                plt.text(
                    -0.2, 0.5, text, fontsize=14, verticalalignment='center',
                    transform=plt.gca().transAxes, rotation=90)
        plt.subplots_adjust(bottom=0.13,top=0.93, wspace=0.15, hspace=0.15)
        cax = plt.axes([0.3, 0.08, 0.4, 0.02])
        plt.colorbar(
            hc[0], cax=cax, orientation='horizontal',
            ticks=np.arange(0, 0.31e12, 0.1e12))
        cax.set_xlabel(r'Ne ($m^{-3}$)')
        # plt.savefig(savepath+'7'+ns+'Ne.jpeg')
        # plt.savefig(savepath+'7'+ns+'Ne.eps')
    return
Esempio n. 35
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def figure5_7_refer(alt=300):
    times = pd.to_datetime([
        '2003-03-22 00:00:00', '2003-03-22 00:30:00', '2003-03-22 01:00:00',
        '2003-03-22 02:00:00', '2003-03-22 03:00:00', '2003-03-22 06:00:00'])
    plt.close('all')
    plt.figure(figsize=(3, 9.25))
    ylabel = times.strftime('%H:%M')
    qlat, qlon = convert(-90, 0, 0, date=dt.date(2003,3,22), a2g=True)
    for itime, time in enumerate(times):
        strtime = time.strftime('%y%m%d_%H%M')
        fn1 = glob.glob(
            '/home/guod/simulation_output/momentum_analysis/'\
            'run_no_shrink_iondrift_4_1/data/3DALL_t%s*.bin' % strtime)
        fn2 = glob.glob(
            '/home/guod/simulation_output/momentum_analysis/'\
            'run_shrink_iondrift_4_c1/data/3DALL_t%s*.bin' % strtime)
        g1 = gitm.read(fn1[0])
        g2 = gitm.read(fn2[0])

        lon1, lat1, alt1, T1 = \
            g1['Longitude'], g1['Latitude'], g1['Altitude'], g1['Temperature']
        lon2, lat2, alt2, T2 = \
            g2['Longitude'], g2['Latitude'], g2['Altitude'], g2['Temperature']

        alt_ind = np.argmin(np.abs(alt1[0, 0, :]/1000-alt))
        alt_str = '%6.0f' % (alt1[0, 0, alt_ind]/1000)

        lonticklabel=[0, 1, 0, 1]
        if itime == 0:
            lonticklabel[0] = 1
        if itime == 5:
            lonticklabel[2] = 1
        ax, projection = gcc.create_map(
            6, 1, itime+1, 'polar', nlat=nlat, slat=slat, dlat=10,
            centrallon=g3ca.calculate_centrallon(g1, 'polar',  useLT=True),
            coastlines=False, lonticklabel=lonticklabel)
        g1['temp'] = T1-T2
        lon0, lat0, zdata0 = g3ca.contour_data('temp', g1, alt=alt)
        fp = (lat0[:,0]>slat) & (lat0[:,0]<nlat)
        lon0, lat0, zdata0 = lon0[fp, :], lat0[fp,:], zdata0[fp,:]
        hc = ax.contourf(
            lon0, lat0, zdata0, levels=np.linspace(-60, 60, 21),
            transform=ccrs.PlateCarree(), cmap='seismic', extend='both')

        # wind difference
        lon1, lat1, ewind1, nwind1 = g3ca.vector_data(
            g1, 'neutral', alt=alt)
        lon2, lat2, ewind2, nwind2 = g3ca.vector_data(
            g2, 'neutral', alt=alt)
        lon0, lat0 = lon1, lat1
        lon0, lat0, ewind0, nwind0 = g3ca.convert_vector(
                lon0, lat0, ewind1-ewind2, nwind1-nwind2,
                plot_type='polar', projection=projection)
        hq = ax.quiver(
                lon0, lat0, ewind0, nwind0, scale=1500,
                scale_units='inches', regrid_shape=20, headwidth=5)
        ax.scatter(
            qlon, qlat, s=10, color='k', transform=ccrs.PlateCarree())
        ax.scatter(
            0, -90, color='w', s=10, transform=ccrs.PlateCarree(),
            zorder=1000)
        plt.text(
            -0.3, 0.5, ylabel[itime], rotation=90,
            transform=ax.transAxes, verticalalignment='center')
        if itime==0:
            plt.title(r'$T_d$ (K)', y=1.15)
        if itime==5:
            axp = ax.get_position()
            cax = [axp.x0, axp.y0-0.03, axp.x1-axp.x0, 1/20*(axp.y1-axp.y0)]
            cax = plt.axes(cax)
            ticks = np.arange(-60, 61, 20)
            hcb = plt.colorbar(
                hc, cax=cax, extendrect=True, orientation='horizontal',
                ticks=ticks)
    plt.subplots_adjust(wspace=0, hspace=0)
    plt.show()
    return
Esempio n. 36
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def test_convert_datetime_date():
    lat_1, lon_1 = aacgmv2.convert(60, 0, 300, dt.date(2013, 12, 1))
    lat_2, lon_2 = aacgmv2.convert(60, 0, 300, dt.datetime(2013, 12, 1, 0, 0, 0))
    assert lat_1 == lat_2
    assert lon_1 == lon_2
Esempio n. 37
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 def test_convert_time_failure(self):
     """Test conversion with a bad time"""
     with pytest.raises(AssertionError):
         self.lat, self.lon = aacgmv2.convert([60], [0], [300], None)
Esempio n. 38
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                                  lonticklabel=(1, 1, 1, 1))
ax2.scatter(0, -90, color='b', transform=ccrs.PlateCarree())

#geomagnetic coordinates
ax3, projection3 = gcc.create_map(2,
                                  2,
                                  3,
                                  'pol',
                                  90,
                                  50,
                                  0,
                                  coastlines=False,
                                  useLT=True,
                                  dlat=10,
                                  lonticklabel=(1, 1, 1, 1))
mlatn, mlonn = convert(90, 0, 0, date=dt.date(2002, 3, 21))
for k in range(24):
    mltn = convert_mlt(mlonn[0], dtime=dt.datetime(2003, 3, 21, k))
    ax3.scatter(mltn * 15, mlatn[0], color='r', transform=ccrs.PlateCarree())
ax3.scatter(180, 75, s=50, c='k', marker='x', transform=ccrs.PlateCarree())

ax4, projection4 = gcc.create_map(2,
                                  2,
                                  4,
                                  'pol',
                                  -50,
                                  -90,
                                  0,
                                  coastlines=False,
                                  useLT=True,
                                  dlat=10,
Esempio n. 39
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g2 = gitm.read(path2)
fig = plt.figure(figsize=(5.41, 8.54))
ax = fig.add_subplot(111, projection='3d')

levels = [
    np.linspace(6.1e-10, 17.8e-10, 21),
    np.linspace(1.1e-10, 2.7e-10, 21),
    np.linspace(1.3e-11, 3.9e-11, 21),
    np.linspace(2.6e-12, 9.503e-12, 21),
    np.linspace(4.3e-13, 2.71e-12, 21),
    np.linspace(7.4e-14, 8.2e-13, 21)
]
olat = -40
olatr = np.abs(olat) / 180 * np.pi

glats, glons = convert(-90, 0, 0, date=dt.date(2003, 3, 22), a2g=True)
glats, glons = glats / 180 * pi, glons / 180 * pi

artalt = [10, 200, 380, 540, 680, 820]
realalt = [150, 200, 300, 400, 500, 600]
for ik, alt in enumerate([150, 200, 300, 400, 500, 600]):
    lon0, lat0, rho1 = g3ca.contour_data('Rho', g1, alt=alt)
    lon0, lat0, rho2 = g3ca.contour_data('Rho', g2, alt=alt)
    lat0, lon0 = lat0 / 180 * pi, lon0 / 180 * pi
    ilat = lat0[:, 0] <= olat / 180 * np.pi
    lat0, lon0, rho1, rho2 = \
        lat0[ilat,:], lon0[ilat,:], rho1[ilat,:], rho2[ilat,:]
    r = lat0 + pi / 2
    theta = lon0
    x = r * np.cos(theta)
    x = -x  # for sorthern hemisphere
Esempio n. 40
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File: thesis.py Progetto: guodj/work
        dlat=10, lonticklabel=(1, 1, 1, 1))
ax1.plot([45,45],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.plot([225,225],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.plot([105,105],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.plot([285,285],[50,90], 'k--',transform=ccrs.PlateCarree())
ax1.scatter(0, 90, color='r', transform=ccrs.PlateCarree(), zorder=10)
ax2, projection2 = gcc.create_map(
        2, 2, 2, 'pol', -50, -90, 0, coastlines=False,useLT=True,
        dlat=10, lonticklabel=(1, 1, 1, 1))
ax2.scatter(0, -90, color='b', transform=ccrs.PlateCarree())

#geomagnetic coordinates
ax3, projection3 = gcc.create_map(
        2, 2, 3, 'pol', 90, 50, 0, coastlines=False,useLT=True,
        dlat=10, lonticklabel=(1, 1, 1, 1))
mlatn,mlonn = convert(90,0,0,date=dt.date(2002,3,21))
for k in range(24):
    mltn = convert_mlt(mlonn[0],dtime=dt.datetime(2003,3,21,k))
    ax3.scatter(mltn*15,mlatn[0],color='r',transform=ccrs.PlateCarree())
ax3.scatter(180,75,s=50,c='k',marker='x',transform=ccrs.PlateCarree())

ax4, projection4 = gcc.create_map(
        2, 2, 4, 'pol', -50, -90, 0, coastlines=False,useLT=True,
        dlat=10, lonticklabel=(1, 1, 1, 1))
mlats,mlons = convert(-90,0,0,date=dt.date(2002,3,21))
for k in range(24):
    mlts = convert_mlt(mlons[0],dtime=dt.datetime(2003,3,21,k))
    ax4.scatter(mlts*15,mlats[0],color='b',transform=ccrs.PlateCarree())
ax4.scatter(180,-75,s=50,c='k',marker='x',transform=ccrs.PlateCarree())
plt.savefig('/Users/guod/Documents/Thesis/006SciFig/work3_001.eps')
#plt.show()
Esempio n. 41
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def plot_rho_wind_ut(ns='SH', alt=150):
    path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_igrf_1_1/data'
    fn01 = path+'/3DALL_t030323_000000.bin'
    fn02 = path+'/3DALL_t030323_030000.bin'
    fn03 = path+'/3DALL_t030323_060001.bin'
    fn04 = path+'/3DALL_t030323_090002.bin'
    fn05 = path+'/3DALL_t030323_120000.bin'
    fn06 = path+'/3DALL_t030323_150001.bin'
    fn07 = path+'/3DALL_t030323_180000.bin'
    fn08 = path+'/3DALL_t030323_210002.bin'
    fn09 = path+'/3DALL_t030324_000000.bin'
    fn2 = [fn01, fn02, fn03, fn04, fn05, fn06, fn07, fn08, fn09]

    if ns=='SH':
        nlat, slat = -50, -90
    elif ns=='NH':
        nlat, slat = 90, 50
    glats, glons = convert(-90, 0, 0, date=dt.date(2003,1,1), a2g=True)
    glatn, glonn = convert(90, 0, 0, date=dt.date(2003,1,1), a2g=True)
    fig1 = plt.figure(1, figsize=(5.28,8.49))
    titf = ['(a)','(b)','(c)','(d)','(e)','(f)','(g)','(h)']
    for k in range(8):
        g2 = gitm.read(fn2[k])

        title = 'UT: '+g2['time'].strftime('%H')

        lon2, lat2, rho2 = g3ca.contour_data('Rho', g2, alt=alt)
        ilat2 = (lat2[:,0]>=slat) & (lat2[:,0]<=nlat)
        min_div_mean = \
            np.min(rho2[ilat2, :]) / \
            (np.mean(rho2[ilat2, :]*np.cos(lat2[ilat2, :]/180*np.pi)) /\
            np.mean(np.cos(lat2[ilat2,:]/180*np.pi)))
        print(ns,':  ',100*(min_div_mean-1))

        lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2,'neu',alt=alt)

        if k ==0:
            lonticklabel = [1, 0, 0, 1]
        elif k==1:
            lonticklabel = [1, 1, 0, 0]
        elif k in [2, 4]:
            lonticklabel = [0, 0, 0, 1]
        elif k in [3, 5]:
            lonticklabel = [0, 1, 0, 0]
        elif k==6:
            lonticklabel = [0, 0, 1, 1]
        elif k==7:
            lonticklabel = [0, 1, 1, 0]
        olat=False if k<7 else True

        # No shrink
        plt.figure(1)
        centrallon = g3ca.calculate_centrallon(g2, 'pol', useLT=True)
        ax, projection = gcc.create_map(
            4,2,k+1, 'pol', nlat, slat, centrallon, coastlines=False,
            dlat=10, useLT=True, lonticklabel=lonticklabel, olat=olat)
        hc1 = ax.contourf(lon2, lat2, rho2, np.linspace(0.8e-9, 1.6e-9),
            transform=ccrs.PlateCarree(),cmap='jet', extend='both')
        lon9, lat9, ewind9, nwind9 = g3ca.convert_vector(
            lon2, lat2, ewind2, nwind2, 'pol', projection)
        hq1 = ax.quiver(
            lon9,lat9,ewind9,nwind9,scale=1500,scale_units='inches',
            regrid_shape=20)
        ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=35, c='k')
        ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=35, c='k')
        ax.scatter(0, 90, transform=ccrs.PlateCarree(), s=35, c='w', zorder=100)
        ax.scatter(0, -90, transform=ccrs.PlateCarree(), s=35, c='w', zorder=100)
        plt.title(titf[k]+' '+title,x=0,y=0.93)

    plt.figure(1)
    plt.subplots_adjust(
        hspace=0.01, wspace=0.01, left=0.05, right=0.95, top=0.95, bottom=0.12)
    cax = plt.axes([0.25,0.07,0.5,0.02])
    hcb = plt.colorbar(
        hc1,cax=cax,orientation='horizontal',ticks=np.arange(0.8,1.7,0.2)*1e-9)
    hcb.set_label(r'$\rho$ (kg/$m^3$)')
    plt.quiverkey(hq1, 0.5,0.12, 500, '500m/s',coordinates='figure')
    plt.savefig(savepath+'1'+ns+'AllUT.eps')
    plt.savefig(savepath+'1'+ns+'AllUT.jpeg')

    return
Esempio n. 42
0
def plot_rho_wind_ut(ns='SH', alt=150):
    path = '/home/guod/simulation_output/momentum_analysis/run_no_shrink_igrf_1_1/data'
    fn01 = path + '/3DALL_t030323_000000.bin'
    fn02 = path + '/3DALL_t030323_030000.bin'
    fn03 = path + '/3DALL_t030323_060001.bin'
    fn04 = path + '/3DALL_t030323_090002.bin'
    fn05 = path + '/3DALL_t030323_120000.bin'
    fn06 = path + '/3DALL_t030323_150001.bin'
    fn07 = path + '/3DALL_t030323_180000.bin'
    fn08 = path + '/3DALL_t030323_210002.bin'
    fn09 = path + '/3DALL_t030324_000000.bin'
    fn2 = [fn01, fn02, fn03, fn04, fn05, fn06, fn07, fn08, fn09]

    if ns == 'SH':
        nlat, slat = -50, -90
    elif ns == 'NH':
        nlat, slat = 90, 50
    glats, glons = convert(-90, 0, 0, date=dt.date(2003, 1, 1), a2g=True)
    glatn, glonn = convert(90, 0, 0, date=dt.date(2003, 1, 1), a2g=True)
    fig1 = plt.figure(1, figsize=(5.28, 8.49))
    titf = ['(a)', '(b)', '(c)', '(d)', '(e)', '(f)', '(g)', '(h)']
    for k in range(8):
        g2 = gitm.read(fn2[k])

        title = 'UT: ' + g2['time'].strftime('%H')

        lon2, lat2, rho2 = g3ca.contour_data('Rho', g2, alt=alt)
        ilat2 = (lat2[:, 0] >= slat) & (lat2[:, 0] <= nlat)
        min_div_mean = \
            np.min(rho2[ilat2, :]) / \
            (np.mean(rho2[ilat2, :]*np.cos(lat2[ilat2, :]/180*np.pi)) /\
            np.mean(np.cos(lat2[ilat2,:]/180*np.pi)))
        print(ns, ':  ', 100 * (min_div_mean - 1))

        lon2, lat2, ewind2, nwind2 = g3ca.vector_data(g2, 'neu', alt=alt)

        if k == 0:
            lonticklabel = [1, 0, 0, 1]
        elif k == 1:
            lonticklabel = [1, 1, 0, 0]
        elif k in [2, 4]:
            lonticklabel = [0, 0, 0, 1]
        elif k in [3, 5]:
            lonticklabel = [0, 1, 0, 0]
        elif k == 6:
            lonticklabel = [0, 0, 1, 1]
        elif k == 7:
            lonticklabel = [0, 1, 1, 0]
        olat = False if k < 7 else True

        # No shrink
        plt.figure(1)
        centrallon = g3ca.calculate_centrallon(g2, 'pol', useLT=True)
        ax, projection = gcc.create_map(4,
                                        2,
                                        k + 1,
                                        'pol',
                                        nlat,
                                        slat,
                                        centrallon,
                                        coastlines=False,
                                        dlat=10,
                                        useLT=True,
                                        lonticklabel=lonticklabel,
                                        olat=olat)
        hc1 = ax.contourf(lon2,
                          lat2,
                          rho2,
                          np.linspace(0.8e-9, 1.6e-9),
                          transform=ccrs.PlateCarree(),
                          cmap='jet',
                          extend='both')
        lon9, lat9, ewind9, nwind9 = g3ca.convert_vector(
            lon2, lat2, ewind2, nwind2, 'pol', projection)
        hq1 = ax.quiver(lon9,
                        lat9,
                        ewind9,
                        nwind9,
                        scale=1500,
                        scale_units='inches',
                        regrid_shape=20)
        ax.scatter(glons, glats, transform=ccrs.PlateCarree(), s=35, c='k')
        ax.scatter(glonn, glatn, transform=ccrs.PlateCarree(), s=35, c='k')
        ax.scatter(0,
                   90,
                   transform=ccrs.PlateCarree(),
                   s=35,
                   c='w',
                   zorder=100)
        ax.scatter(0,
                   -90,
                   transform=ccrs.PlateCarree(),
                   s=35,
                   c='w',
                   zorder=100)
        plt.title(titf[k] + ' ' + title, x=0, y=0.93)

    plt.figure(1)
    plt.subplots_adjust(hspace=0.01,
                        wspace=0.01,
                        left=0.05,
                        right=0.95,
                        top=0.95,
                        bottom=0.12)
    cax = plt.axes([0.25, 0.07, 0.5, 0.02])
    hcb = plt.colorbar(hc1,
                       cax=cax,
                       orientation='horizontal',
                       ticks=np.arange(0.8, 1.7, 0.2) * 1e-9)
    hcb.set_label(r'$\rho$ (kg/$m^3$)')
    plt.quiverkey(hq1, 0.5, 0.12, 500, '500m/s', coordinates='figure')
    plt.savefig(savepath + '1' + ns + 'AllUT.eps')
    plt.savefig(savepath + '1' + ns + 'AllUT.jpeg')

    return
Esempio n. 43
0
path1 = '/home/guod/simulation_output/momentum_analysis/'+\
        'run_shrink_iondrift_4_c1/data/3DALL_t030322_060000.bin'
path2 = '/home/guod/simulation_output/momentum_analysis/'+\
        'run_no_shrink_iondrift_4_1/data/3DALL_t030322_060000.bin'
g1 = gitm.read(path1)
g2 = gitm.read(path2)
fig = plt.figure(figsize=(5.41, 8.54))
ax = fig.add_subplot(111, projection='3d')

levels = [np.linspace(6.1e-10, 17.8e-10,21), np.linspace(1.1e-10, 2.7e-10, 21),
          np.linspace(1.3e-11, 3.9e-11,21), np.linspace(2.6e-12, 9.503e-12,21),
          np.linspace(4.3e-13, 2.71e-12,21), np.linspace(7.4e-14, 8.2e-13,21)]
olat = -40
olatr = np.abs(olat)/180*np.pi

glats, glons = convert(-90,0,0,date=dt.date(2003,3,22), a2g=True)
glats, glons = glats/180*pi, glons/180*pi

artalt = [10, 200, 380, 540, 680, 820]
realalt = [150, 200, 300, 400, 500, 600]
for ik, alt in enumerate([150, 200, 300, 400, 500, 600]):
    lon0, lat0, rho1 = g3ca.contour_data('Rho', g1, alt=alt)
    lon0, lat0, rho2 = g3ca.contour_data('Rho', g2, alt=alt)
    lat0, lon0 = lat0/180*pi, lon0/180*pi
    ilat = lat0[:, 0]<=olat/180*np.pi
    lat0, lon0, rho1, rho2 = \
        lat0[ilat,:], lon0[ilat,:], rho1[ilat,:], rho2[ilat,:]
    r = lat0+pi/2
    theta = lon0
    x = r*np.cos(theta)
    x = -x # for sorthern hemisphere