| 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(temperature, self._to_pascals(pressure), | 
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| 48 | humidity) | 
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| 49 | self.set_observatory_elevation(elevation) | 
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| 50 |  | 
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| 51 | def get_opacities(self, freq, elevation=None): | 
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| 52 | """Get the opacity value(s) for the fiven frequency(ies). | 
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| 53 | If no elevation is given the opacities for the zenith are returned. | 
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| 54 | If an elevation is specified refraction is also taken into account. | 
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| 55 | Parameters: | 
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| 56 | freq:       a frequency value in Hz, or a list of frequency values. | 
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| 57 | One opacity value per frequency is returned as a scalar | 
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| 58 | or list. | 
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| 59 | elevation:  the elevation at which to compute the opacity. If `None` | 
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| 60 | is given (default) the zenith opacity is returned. | 
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| 61 |  | 
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| 62 |  | 
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| 63 | """ | 
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| 64 | func = None | 
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| 65 | if isinstance(freq, (list, tuple)): | 
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| 66 | if elevation is None: | 
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| 67 | return self._atm.zenith_opacities(freq) | 
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| 68 | else: | 
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| 69 | elevation *= math.pi/180. | 
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| 70 | return self._atm.opacities(freq, elevation) | 
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| 71 | else: | 
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| 72 | if elevation is None: | 
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| 73 | return self._atm.zenith_opacity(freq) | 
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| 74 | else: | 
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| 75 | elevation *= math.pi/180. | 
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| 76 | return self._atm.opacity(freq, elevation) | 
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| 77 |  | 
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| 78 | def set_weather(self, temperature, pressure, humidity): | 
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| 79 | """Update the model using the given environmental parameters. | 
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| 80 | Parameters: | 
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| 81 | temperature:    air temperature at the observatory (K) | 
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| 82 | pressure:       air pressure at the sea level if the observatory | 
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| 83 | elevation is set to non-zero value (note, by | 
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| 84 | default is set to 700m) or at the observatory | 
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| 85 | ground level if the elevation is set to 0. (The | 
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| 86 | value is in Pascals or hPa, default 101325 Pa | 
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| 87 | humidity:       air humidity at the observatory (fractional), | 
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| 88 | default is 0.5 | 
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| 89 | """ | 
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| 90 | pressure = self._to_pascals(pressure) | 
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| 91 | self._atm.set_weather(temperature, pressure, humidity) | 
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| 92 |  | 
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| 93 | def set_observatory_elevation(self, elevation): | 
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| 94 | """Update the model using the given the observatory elevation | 
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| 95 | Parameters: | 
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| 96 | elevation:  the elevation at which to compute the opacity. If `None` | 
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| 97 | is given (default) the zenith opacity is returned. | 
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| 98 | """ | 
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| 99 | self._atm.set_observatory_elevation(elevation) | 
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| 100 |  | 
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| 101 |  | 
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| 102 | def _import_data(data): | 
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| 103 | if not isinstance(data, (list,tuple)): | 
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| 104 | if isinstance(data, scantable): | 
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| 105 | return data | 
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| 106 | elif isinstance(data, str): | 
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| 107 | return scantable(data) | 
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| 108 | tables = [] | 
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| 109 | for d in data: | 
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| 110 | if isinstance(d, scantable): | 
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| 111 | tables.append(d) | 
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| 112 | elif isinstance(d, str): | 
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| 113 | if os.path.exists(d): | 
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| 114 | tables.append(scantable(d)) | 
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| 115 | else: | 
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| 116 | raise IOError("Data file doesn't exists") | 
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| 117 | else: | 
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| 118 | raise TypeError("data is not a scantable or valid file") | 
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| 119 | return merge(tables) | 
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| 120 |  | 
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| 121 | def skydip(data, averagepol=True, tsky=300., plot=False, | 
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| 122 | temperature=288, pressure=101325., humidity=0.5): | 
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| 123 | """Determine the opacity from a set of 'skydip' obervations. | 
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| 124 | This can be any set of observations over a range of elevations, | 
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| 125 | but will ususally be a dedicated (set of) scan(s). | 
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| 126 | Return a list of 'n' opacities for 'n' IFs. In case of averagepol | 
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| 127 | being 'False' a list of 'n*m' elements where 'm' is the number of | 
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| 128 | polarisations, e.g. | 
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| 129 | nIF = 3, nPol = 2 => [if0pol0, if0pol1, if1pol0, if1pol1, if2pol0, if2pol1] | 
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| 130 |  | 
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| 131 | The opacity is determined by fitting a first order polynomial to: | 
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| 132 |  | 
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| 133 |  | 
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| 134 | Tsys(airmass) = p0 + airmass*p1 | 
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| 135 |  | 
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| 136 | where | 
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| 137 |  | 
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| 138 | airmass = 1/sin(elevation) | 
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| 139 |  | 
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| 140 | tau =  p1/Tsky | 
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| 141 |  | 
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| 142 | Parameters: | 
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| 143 | data:       a list of file names or scantables or a single | 
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| 144 | file name or scantable. | 
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| 145 | averagepol: Return the average of the opacities for the polarisations | 
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| 146 | This might be useful to set to 'False' if one polarisation | 
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| 147 | is corrupted (Mopra). If set to 'False', an opacity value | 
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| 148 | per polarisation is returned. | 
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| 149 | tksy:       The sky temperature (default 300.0K). This might | 
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| 150 | be read from the data in the future. | 
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| 151 | plot:       Plot each fit (airmass vs. Tsys). Default is 'False' | 
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| 152 | """ | 
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| 153 | rcsave = rcParams['verbose'] | 
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| 154 | rcParams['verbose'] = False | 
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| 155 | if plot: | 
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| 156 | from matplotlib import pylab | 
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| 157 | scan = _import_data(data) | 
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| 158 | f = fitter() | 
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| 159 | f.set_function(poly=1) | 
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| 160 | sel = selector() | 
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| 161 | basesel = scan.get_selection() | 
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| 162 | inos = scan.getifnos() | 
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| 163 | pnos = scan.getpolnos() | 
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| 164 | opacities = [] | 
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| 165 | om = model(temperature, pressure, humidity) | 
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| 166 | for ino in inos: | 
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| 167 | sel.set_ifs(ino) | 
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| 168 | opacity = [] | 
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| 169 | fits = [] | 
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| 170 | airms = [] | 
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| 171 | tsyss = [] | 
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| 172 | if plot: | 
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| 173 | pylab.cla() | 
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| 174 | pylab.ioff() | 
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| 175 | pylab.clf() | 
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| 176 | pylab.xlabel("Airmass") | 
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| 177 | pylab.ylabel(r"$T_{sys}$") | 
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| 178 | for pno in pnos: | 
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| 179 | sel.set_polarisations(pno) | 
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| 180 | scan.set_selection(basesel+sel) | 
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| 181 | freq = scan.get_coordinate(0).get_reference_value()/1e9 | 
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| 182 | freqstr = "%0.4f GHz" % freq | 
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| 183 | tsys = scan.get_tsys() | 
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| 184 | elev = scan.get_elevation() | 
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| 185 | airmass = [ 1./math.sin(i) for i in elev ] | 
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| 186 | airms.append(airmass) | 
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| 187 | tsyss.append(tsys) | 
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| 188 | f.set_data(airmass, tsys) | 
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| 189 | f.fit() | 
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| 190 | fits.append(f.get_fit()) | 
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| 191 | params = f.get_parameters()["params"] | 
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| 192 | opacity.append(params[1]/tsky) | 
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| 193 | if averagepol: | 
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| 194 | opacities.append(sum(opacity)/len(opacity)) | 
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| 195 | else: | 
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| 196 | opacities += opacity | 
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| 197 | if plot: | 
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| 198 | colors = ['b','g','k'] | 
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| 199 | n = len(airms) | 
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| 200 | for i in range(n): | 
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| 201 | pylab.plot(airms[i], tsyss[i], 'o', color=colors[i]) | 
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| 202 | pylab.plot(airms[i], fits[i], '-', color=colors[i]) | 
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| 203 | pylab.figtext(0.7,0.3-(i/30.0), | 
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| 204 | r"$\tau_{fit}=%0.2f$" % opacity[i], | 
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| 205 | color=colors[i]) | 
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| 206 | if averagepol: | 
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| 207 | pylab.figtext(0.7,0.3-(n/30.0), | 
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| 208 | r"$\tau_{avg}=%0.2f$" % opacities[-1], | 
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| 209 | color='r') | 
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| 210 | n +=1 | 
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| 211 | pylab.figtext(0.7,0.3-(n/30.0), | 
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| 212 | r"$\tau_{model}=%0.2f$" % om.get_opacities(freq*1e9), | 
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| 213 | color='grey') | 
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| 214 |  | 
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| 215 | pylab.title("IF%d : %s" % (ino, freqstr)) | 
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| 216 |  | 
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| 217 | pylab.ion() | 
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| 218 | pylab.draw() | 
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| 219 | raw_input("Hit <return> for next fit...") | 
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| 220 | sel.reset() | 
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| 221 |  | 
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| 222 | scan.set_selection(basesel) | 
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| 223 | rcParams['verbose'] = rcsave | 
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| 224 | if plot: | 
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| 225 | pylab.close() | 
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| 226 | return opacities | 
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