| 1 | import os
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| 2 | import math
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| 3 | from asap import scantable
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| 4 | from asap import merge
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| 5 | from asap import fitter
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| 6 | from asap import selector
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| 7 | from asap import rcParams
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| 8 | from asap._asap import atmosphere
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| 9 |
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| 10 |
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| 11 | class model(object):
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| 12 | def _to_pascals(self, val):
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| 13 | if val > 2000:
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| 14 | return val
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| 15 | return val*100
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| 16 |
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| 17 | def __init__(self, temperature=288, pressure=101325., humidity=0.5,
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| 18 | elevation=700.):
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| 19 | """
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| 20 | This class implements opacity/atmospheric brightness temperature model
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| 21 | equivalent to the model available in MIRIAD. The actual math is a
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| 22 | convertion of the Fortran code written by Bob Sault for MIRIAD.
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| 23 | It implements a simple model of the atmosphere and Liebe's model (1985)
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| 24 | of the complex refractive index of air.
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| 25 |
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| 26 | The model of the atmosphere is one with an exponential fall-off in
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| 27 | the water vapour content (scale height of 1540 m) and a temperature
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| 28 | lapse rate of 6.5 mK/m. Otherwise the atmosphere obeys the ideal gas
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| 29 | equation and hydrostatic equilibrium.
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| 30 |
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| 31 | Note, the model includes atmospheric lines up to 800 GHz, but was not
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| 32 | rigorously tested above 100 GHz and for instruments located at
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| 33 | a significant elevation. For high-elevation sites it may be necessary to
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| 34 | adjust scale height and lapse rate.
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| 35 |
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| 36 | Parameters:
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| 37 | temperature: air temperature at the observatory (K)
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| 38 | pressure: air pressure at the sea level if the observatory
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| 39 | elevation is set to non-zero value (note, by
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| 40 | default is set to 700m) or at the observatory
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| 41 | ground level if the elevation is set to 0. (The
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| 42 | value is in Pascals or hPa, default 101325 Pa
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| 43 | humidity: air humidity at the observatory (fractional),
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| 44 | default is 0.5
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| 45 | elevation: observatory elevation about sea level (in meters)
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| 46 | """
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| 47 | self._atm = atmosphere(temp, self._to_pascals(pressure), humidity)
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| 48 | self.set_observatory_elevation(elevation)
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| 49 |
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| 50 | def get_opacities(self, freq, elevation=None):
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| 51 | """Get the opacity value(s) for the fiven frequency(ies).
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| 52 | If no elevation is given the opacities for the zenith are returned.
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| 53 | If an elevation is specified refraction is also taken into account.
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| 54 | Parameters:
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| 55 | freq: a frequency value in Hz, or a list of frequency values.
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| 56 | One opacity value per frequency is returned as a scalar
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| 57 | or list.
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| 58 | elevation: the elevation at which to compute the opacity. If `None`
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| 59 | is given (default) the zenith opacity is returned.
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| 60 |
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| 61 |
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| 62 | """
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| 63 | func = None
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| 64 | if isinstance(freq, (list, tuple)):
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| 65 | if elevation is None:
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| 66 | return self._atm.zenith_opacities(freq)
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| 67 | else:
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| 68 | elevation *= math.pi/180.
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| 69 | return self._atm.opacities(freq, elevation)
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| 70 | else:
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| 71 | if elevation is None:
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| 72 | return self._atm.zenith_opacity(freq)
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| 73 | else:
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| 74 | elevation *= math.pi/180.
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| 75 | return self._atm.opacity(freq, elevation)
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| 76 |
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| 77 | def set_weather(self, temperature, pressure, humidity):
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| 78 | """Update the model using the given environmental parameters.
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| 79 | Parameters:
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| 80 | temperature: air temperature at the observatory (K)
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| 81 | pressure: air pressure at the sea level if the observatory
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| 82 | elevation is set to non-zero value (note, by
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| 83 | default is set to 700m) or at the observatory
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| 84 | ground level if the elevation is set to 0. (The
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| 85 | value is in Pascals or hPa, default 101325 Pa
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| 86 | humidity: air humidity at the observatory (fractional),
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| 87 | default is 0.5
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| 88 | """
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| 89 | pressure = self._to_pascals(pressure)
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| 90 | self._atm.set_weather(temperature, pressure, humidity)
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| 91 |
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| 92 | def set_observatory_elevation(self, elevation):
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| 93 | """Update the model using the given the observatory elevation
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| 94 | Parameters:
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| 95 | elevation: the elevation at which to compute the opacity. If `None`
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| 96 | is given (default) the zenith opacity is returned.
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| 97 | """
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| 98 | self._atm.set_observatory_elevation(el)
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| 99 |
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| 100 |
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| 101 | def _import_data(data):
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| 102 | if not isinstance(data, (list,tuple)):
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| 103 | if isinstance(data, scantable):
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| 104 | return data
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| 105 | elif isinstance(data, str):
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| 106 | return scantable(data)
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| 107 | tables = []
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| 108 | for d in data:
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| 109 | if isinstance(d, scantable):
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| 110 | tables.append(d)
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| 111 | elif isinstance(d, str):
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| 112 | if os.path.exists(d):
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| 113 | tables.append(scantable(d))
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| 114 | else:
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| 115 | raise IOError("Data file doesn't exists")
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| 116 | else:
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| 117 | raise TypeError("data is not a scantable or valid file")
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| 118 | return merge(tables)
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| 119 |
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| 120 | def skydip(data, averagepol=True, tsky=300., plot=False,
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| 121 | temperature=288, pressure=101325., humidity=0.5):
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| 122 | """Determine the opacity from a set of 'skydip' obervations.
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| 123 | This can be any set of observations over a range of elevations,
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| 124 | but will ususally be a dedicated (set of) scan(s).
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| 125 | Return a list of 'n' opacities for 'n' IFs. In case of averagepol
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| 126 | being 'False' a list of 'n*m' elements where 'm' is the number of
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| 127 | polarisations, e.g.
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| 128 | nIF = 3, nPol = 2 => [if0pol0, if0pol1, if1pol0, if1pol1, if2pol0, if2pol1]
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| 129 |
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| 130 | The opacity is determined by fitting a first order polynomial to:
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| 131 |
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| 132 |
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| 133 | Tsys(airmass) = p0 + airmass*p1
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| 134 |
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| 135 | where
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| 136 |
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| 137 | airmass = 1/sin(elevation)
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| 138 |
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| 139 | tau = p1/Tsky
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| 140 |
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| 141 | Parameters:
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| 142 | data: a list of file names or scantables or a single
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| 143 | file name or scantable.
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| 144 | averagepol: Return the average of the opacities for the polarisations
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| 145 | This might be useful to set to 'False' if one polarisation
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| 146 | is corrupted (Mopra). If set to 'False', an opacity value
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| 147 | per polarisation is returned.
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| 148 | tksy: The sky temperature (default 300.0K). This might
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| 149 | be read from the data in the future.
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| 150 | plot: Plot each fit (airmass vs. Tsys). Default is 'False'
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| 151 | """
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| 152 | rcsave = rcParams['verbose']
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| 153 | rcParams['verbose'] = False
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| 154 | if plot:
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| 155 | from matplotlib import pylab
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| 156 | scan = _import_data(data)
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| 157 | f = fitter()
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| 158 | f.set_function(poly=1)
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| 159 | sel = selector()
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| 160 | basesel = scan.get_selection()
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| 161 | inos = scan.getifnos()
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| 162 | pnos = scan.getpolnos()
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| 163 | opacities = []
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| 164 | om = opacitymodel(temperature, pressure, humidity)
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| 165 | for ino in inos:
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| 166 | sel.set_ifs(ino)
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| 167 | opacity = []
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| 168 | fits = []
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| 169 | airms = []
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| 170 | tsyss = []
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| 171 | if plot:
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| 172 | pylab.cla()
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| 173 | pylab.ioff()
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| 174 | pylab.clf()
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| 175 | pylab.xlabel("Airmass")
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| 176 | pylab.ylabel(r"$T_{sys}$")
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| 177 | for pno in pnos:
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| 178 | sel.set_polarisations(pno)
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| 179 | scan.set_selection(basesel+sel)
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| 180 | freq = scan.get_coordinate(0).get_reference_value()/1e9
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| 181 | freqstr = "%0.4f GHz" % freq
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| 182 | tsys = scan.get_tsys()
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| 183 | elev = scan.get_elevation()
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| 184 | airmass = [ 1./math.sin(i) for i in elev ]
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| 185 | airms.append(airmass)
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| 186 | tsyss.append(tsys)
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| 187 | f.set_data(airmass, tsys)
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| 188 | f.fit()
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| 189 | fits.append(f.get_fit())
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| 190 | params = f.get_parameters()["params"]
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| 191 | opacity.append(params[1]/tsky)
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| 192 | if averagepol:
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| 193 | opacities.append(sum(opacity)/len(opacity))
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| 194 | else:
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| 195 | opacities += opacity
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| 196 | if plot:
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| 197 | colors = ['b','g','k']
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| 198 | n = len(airms)
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| 199 | for i in range(n):
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| 200 | pylab.plot(airms[i], tsyss[i], 'o', color=colors[i])
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| 201 | pylab.plot(airms[i], fits[i], '-', color=colors[i])
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| 202 | pylab.figtext(0.7,0.3-(i/30.0),
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| 203 | r"$\tau_{fit}=%0.2f$" % opacity[i],
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| 204 | color=colors[i])
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| 205 | if averagepol:
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| 206 | pylab.figtext(0.7,0.3-(n/30.0),
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| 207 | r"$\tau_{avg}=%0.2f$" % opacities[-1],
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| 208 | color='r')
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| 209 | n +=1
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| 210 | pylab.figtext(0.7,0.3-(n/30.0),
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| 211 | r"$\tau_{model}=%0.2f$" % om.get_opacities(freq*1e9),
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| 212 | color='grey')
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| 213 |
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| 214 | pylab.title("IF%d : %s" % (ino, freqstr))
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| 215 |
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| 216 | pylab.ion()
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| 217 | pylab.draw()
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| 218 | raw_input("Hit <return> for next fit...")
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| 219 | sel.reset()
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| 220 |
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| 221 | scan.set_selection(basesel)
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| 222 | rcParams['verbose'] = rcsave
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| 223 | if plot:
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| 224 | pylab.close()
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| 225 | return opacities
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