1 | from asap.scantable import scantable |
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2 | from asap import rcParams |
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3 | from asap import print_log, print_log_dec |
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4 | from asap import selector |
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5 | from asap import asaplog |
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6 | from asap import asaplotgui |
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7 | |
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8 | @print_log_dec |
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9 | def average_time(*args, **kwargs): |
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10 | """ |
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11 | Return the (time) average of a scan or list of scans. [in channels only] |
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12 | The cursor of the output scan is set to 0 |
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13 | Parameters: |
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14 | one scan or comma separated scans or a list of scans |
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15 | mask: an optional mask (only used for 'var' and 'tsys' weighting) |
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16 | scanav: True averages each scan separately. |
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17 | False (default) averages all scans together, |
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18 | weight: Weighting scheme. |
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19 | 'none' (mean no weight) |
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20 | 'var' (1/var(spec) weighted) |
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21 | 'tsys' (1/Tsys**2 weighted) |
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22 | 'tint' (integration time weighted) |
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23 | 'tintsys' (Tint/Tsys**2) |
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24 | 'median' ( median averaging) |
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25 | align: align the spectra in velocity before averaging. It takes |
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26 | the time of the first spectrum in the first scantable |
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27 | as reference time. |
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28 | Example: |
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29 | # return a time averaged scan from scana and scanb |
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30 | # without using a mask |
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31 | scanav = average_time(scana,scanb) |
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32 | # or equivalent |
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33 | # scanav = average_time([scana, scanb]) |
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34 | # return the (time) averaged scan, i.e. the average of |
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35 | # all correlator cycles |
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36 | scanav = average_time(scan, scanav=True) |
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37 | """ |
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38 | scanav = False |
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39 | if kwargs.has_key('scanav'): |
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40 | scanav = kwargs.get('scanav') |
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41 | weight = 'tint' |
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42 | if kwargs.has_key('weight'): |
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43 | weight = kwargs.get('weight') |
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44 | mask = () |
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45 | if kwargs.has_key('mask'): |
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46 | mask = kwargs.get('mask') |
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47 | align = False |
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48 | if kwargs.has_key('align'): |
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49 | align = kwargs.get('align') |
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50 | compel = False |
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51 | if kwargs.has_key('compel'): |
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52 | compel = kwargs.get('compel') |
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53 | varlist = vars() |
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54 | if isinstance(args[0],list): |
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55 | lst = args[0] |
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56 | elif isinstance(args[0],tuple): |
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57 | lst = list(args[0]) |
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58 | else: |
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59 | lst = list(args) |
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60 | |
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61 | del varlist["kwargs"] |
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62 | varlist["args"] = "%d scantables" % len(lst) |
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63 | # need special formatting here for history... |
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64 | |
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65 | from asap._asap import stmath |
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66 | stm = stmath() |
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67 | for s in lst: |
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68 | if not isinstance(s,scantable): |
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69 | msg = "Please give a list of scantables" |
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70 | if rcParams['verbose']: |
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71 | #print msg |
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72 | asaplog.push(msg) |
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73 | print_log('ERROR') |
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74 | return |
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75 | else: |
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76 | raise TypeError(msg) |
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77 | if scanav: scanav = "SCAN" |
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78 | else: scanav = "NONE" |
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79 | alignedlst = [] |
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80 | if align: |
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81 | refepoch = lst[0].get_time(0) |
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82 | for scan in lst: |
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83 | alignedlst.append(scan.freq_align(refepoch,insitu=False)) |
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84 | else: |
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85 | alignedlst = lst |
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86 | if weight.upper() == 'MEDIAN': |
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87 | # median doesn't support list of scantables - merge first |
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88 | merged = None |
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89 | if len(alignedlst) > 1: |
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90 | merged = merge(alignedlst) |
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91 | else: |
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92 | merged = alignedlst[0] |
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93 | s = scantable(stm._averagechannel(merged, 'MEDIAN', scanav)) |
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94 | del merged |
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95 | else: |
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96 | #s = scantable(stm._average(alignedlst, mask, weight.upper(), scanav)) |
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97 | s = scantable(stm._new_average(alignedlst, compel, mask, weight.upper(), scanav)) |
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98 | s._add_history("average_time",varlist) |
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99 | print_log() |
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100 | return s |
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101 | |
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102 | def quotient(source, reference, preserve=True): |
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103 | """ |
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104 | Return the quotient of a 'source' (signal) scan and a 'reference' scan. |
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105 | The reference can have just one scan, even if the signal has many. Otherwise |
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106 | they must have the same number of scans. |
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107 | The cursor of the output scan is set to 0 |
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108 | Parameters: |
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109 | source: the 'on' scan |
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110 | reference: the 'off' scan |
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111 | preserve: you can preserve (default) the continuum or |
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112 | remove it. The equations used are |
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113 | preserve: Output = Toff * (on/off) - Toff |
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114 | remove: Output = Toff * (on/off) - Ton |
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115 | """ |
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116 | varlist = vars() |
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117 | from asap._asap import stmath |
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118 | stm = stmath() |
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119 | stm._setinsitu(False) |
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120 | s = scantable(stm._quotient(source, reference, preserve)) |
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121 | s._add_history("quotient",varlist) |
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122 | print_log() |
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123 | return s |
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124 | |
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125 | @print_log_dec |
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126 | def dototalpower(calon, caloff, tcalval=0.0): |
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127 | """ |
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128 | Do calibration for CAL on,off signals. |
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129 | Adopted from GBTIDL dototalpower |
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130 | Parameters: |
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131 | calon: the 'cal on' subintegration |
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132 | caloff: the 'cal off' subintegration |
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133 | tcalval: user supplied Tcal value |
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134 | """ |
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135 | varlist = vars() |
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136 | from asap._asap import stmath |
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137 | stm = stmath() |
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138 | stm._setinsitu(False) |
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139 | s = scantable(stm._dototalpower(calon, caloff, tcalval)) |
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140 | s._add_history("dototalpower",varlist) |
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141 | print_log() |
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142 | return s |
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143 | |
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144 | @print_log_dec |
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145 | def dosigref(sig, ref, smooth, tsysval=0.0, tauval=0.0): |
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146 | """ |
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147 | Calculate a quotient (sig-ref/ref * Tsys) |
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148 | Adopted from GBTIDL dosigref |
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149 | Parameters: |
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150 | sig: on source data |
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151 | ref: reference data |
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152 | smooth: width of box car smoothing for reference |
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153 | tsysval: user specified Tsys (scalar only) |
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154 | tauval: user specified Tau (required if tsysval is set) |
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155 | """ |
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156 | varlist = vars() |
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157 | from asap._asap import stmath |
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158 | stm = stmath() |
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159 | stm._setinsitu(False) |
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160 | s = scantable(stm._dosigref(sig, ref, smooth, tsysval, tauval)) |
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161 | s._add_history("dosigref",varlist) |
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162 | print_log() |
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163 | return s |
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164 | |
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165 | @print_log_dec |
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166 | def calps(scantab, scannos, smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False): |
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167 | """ |
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168 | Calibrate GBT position switched data |
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169 | Adopted from GBTIDL getps |
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170 | Currently calps identify the scans as position switched data if they |
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171 | contain '_ps' in the source name. The data must contains 'CAL' signal |
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172 | on/off in each integration. To identify 'CAL' on state, the word, 'calon' |
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173 | need to be present in the source name field. |
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174 | (GBT MS data reading process to scantable automatically append these |
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175 | id names to the source names) |
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176 | |
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177 | Parameters: |
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178 | scantab: scantable |
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179 | scannos: list of scan numbers |
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180 | smooth: optional box smoothing order for the reference |
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181 | (default is 1 = no smoothing) |
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182 | tsysval: optional user specified Tsys (default is 0.0, |
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183 | use Tsys in the data) |
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184 | tauval: optional user specified Tau |
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185 | tcalval: optional user specified Tcal (default is 0.0, |
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186 | use Tcal value in the data) |
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187 | """ |
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188 | varlist = vars() |
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189 | # check for the appropriate data |
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190 | ## s = scantab.get_scan('*_ps*') |
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191 | ## if s is None: |
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192 | ## msg = "The input data appear to contain no position-switch mode data." |
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193 | ## if rcParams['verbose']: |
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194 | ## #print msg |
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195 | ## asaplog.push(msg) |
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196 | ## print_log('ERROR') |
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197 | ## return |
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198 | ## else: |
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199 | ## raise TypeError(msg) |
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200 | s = scantab.copy() |
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201 | from asap._asap import srctype |
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202 | sel = selector() |
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203 | sel.set_types( srctype.pson ) |
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204 | try: |
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205 | scantab.set_selection( sel ) |
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206 | except Exception, e: |
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207 | msg = "The input data appear to contain no position-switch mode data." |
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208 | if rcParams['verbose']: |
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209 | #print msg |
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210 | asaplog.push(msg) |
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211 | print_log('ERROR') |
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212 | return |
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213 | else: |
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214 | raise TypeError(msg) |
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215 | s.set_selection() |
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216 | sel.reset() |
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217 | ssub = s.get_scan(scannos) |
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218 | if ssub is None: |
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219 | msg = "No data was found with given scan numbers!" |
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220 | if rcParams['verbose']: |
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221 | #print msg |
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222 | asaplog.push(msg) |
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223 | print_log('ERROR') |
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224 | return |
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225 | else: |
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226 | raise TypeError(msg) |
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227 | #ssubon = ssub.get_scan('*calon') |
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228 | #ssuboff = ssub.get_scan('*[^calon]') |
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229 | sel.set_types( [srctype.poncal,srctype.poffcal] ) |
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230 | ssub.set_selection( sel ) |
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231 | ssubon = ssub.copy() |
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232 | ssub.set_selection() |
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233 | sel.reset() |
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234 | sel.set_types( [srctype.pson,srctype.psoff] ) |
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235 | ssub.set_selection( sel ) |
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236 | ssuboff = ssub.copy() |
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237 | ssub.set_selection() |
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238 | sel.reset() |
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239 | if ssubon.nrow() != ssuboff.nrow(): |
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240 | msg = "mismatch in numbers of CAL on/off scans. Cannot calibrate. Check the scan numbers." |
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241 | if rcParams['verbose']: |
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242 | #print msg |
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243 | asaplog.push(msg) |
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244 | print_log('ERROR') |
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245 | return |
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246 | else: |
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247 | raise TypeError(msg) |
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248 | cals = dototalpower(ssubon, ssuboff, tcalval) |
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249 | #sig = cals.get_scan('*ps') |
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250 | #ref = cals.get_scan('*psr') |
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251 | sel.set_types( srctype.pson ) |
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252 | cals.set_selection( sel ) |
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253 | sig = cals.copy() |
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254 | cals.set_selection() |
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255 | sel.reset() |
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256 | sel.set_types( srctype.psoff ) |
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257 | cals.set_selection( sel ) |
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258 | ref = cals.copy() |
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259 | cals.set_selection() |
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260 | sel.reset() |
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261 | if sig.nscan() != ref.nscan(): |
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262 | msg = "mismatch in numbers of on/off scans. Cannot calibrate. Check the scan numbers." |
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263 | if rcParams['verbose']: |
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264 | #print msg |
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265 | asaplog.push(msg) |
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266 | print_log('ERROR') |
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267 | return |
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268 | else: |
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269 | raise TypeError(msg) |
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270 | |
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271 | #for user supplied Tsys |
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272 | if tsysval>0.0: |
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273 | if tauval<=0.0: |
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274 | msg = "Need to supply a valid tau to use the supplied Tsys" |
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275 | if rcParams['verbose']: |
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276 | #print msg |
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277 | asaplog.push(msg) |
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278 | print_log('ERROR') |
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279 | return |
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280 | else: |
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281 | raise TypeError(msg) |
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282 | else: |
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283 | sig.recalc_azel() |
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284 | ref.recalc_azel() |
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285 | #msg = "Use of user specified Tsys is not fully implemented yet." |
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286 | #if rcParams['verbose']: |
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287 | # print msg |
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288 | # return |
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289 | #else: |
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290 | # raise TypeError(msg) |
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291 | # use get_elevation to get elevation and |
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292 | # calculate a scaling factor using the formula |
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293 | # -> tsys use to dosigref |
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294 | |
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295 | #ress = dosigref(sig, ref, smooth, tsysval) |
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296 | ress = dosigref(sig, ref, smooth, tsysval, tauval) |
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297 | ### |
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298 | if verify: |
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299 | # get data |
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300 | import numpy |
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301 | precal={} |
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302 | postcal=[] |
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303 | keys=['ps','ps_calon','psr','psr_calon'] |
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304 | types=[srctype.pson,srctype.poncal,srctype.psoff,srctype.poffcal] |
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305 | ifnos=list(ssub.getifnos()) |
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306 | polnos=list(ssub.getpolnos()) |
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307 | sel=selector() |
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308 | for i in range(2): |
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309 | #ss=ssuboff.get_scan('*'+keys[2*i]) |
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310 | ll=[] |
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311 | for j in range(len(ifnos)): |
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312 | for k in range(len(polnos)): |
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313 | sel.set_ifs(ifnos[j]) |
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314 | sel.set_polarizations(polnos[k]) |
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315 | sel.set_types(types[2*i]) |
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316 | try: |
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317 | #ss.set_selection(sel) |
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318 | ssuboff.set_selection(sel) |
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319 | except: |
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320 | continue |
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321 | #ll.append(numpy.array(ss._getspectrum(0))) |
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322 | ll.append(numpy.array(ssuboff._getspectrum(0))) |
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323 | sel.reset() |
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324 | ssuboff.set_selection() |
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325 | precal[keys[2*i]]=ll |
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326 | #del ss |
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327 | #ss=ssubon.get_scan('*'+keys[2*i+1]) |
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328 | ll=[] |
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329 | for j in range(len(ifnos)): |
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330 | for k in range(len(polnos)): |
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331 | sel.set_ifs(ifnos[j]) |
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332 | sel.set_polarizations(polnos[k]) |
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333 | sel.set_types(types[2*i+1]) |
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334 | try: |
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335 | #ss.set_selection(sel) |
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336 | ssubon.set_selection(sel) |
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337 | except: |
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338 | continue |
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339 | #ll.append(numpy.array(ss._getspectrum(0))) |
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340 | ll.append(numpy.array(ssubon._getspectrum(0))) |
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341 | sel.reset() |
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342 | ssubon.set_selection() |
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343 | precal[keys[2*i+1]]=ll |
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344 | #del ss |
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345 | for j in range(len(ifnos)): |
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346 | for k in range(len(polnos)): |
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347 | sel.set_ifs(ifnos[j]) |
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348 | sel.set_polarizations(polnos[k]) |
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349 | try: |
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350 | ress.set_selection(sel) |
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351 | except: |
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352 | continue |
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353 | postcal.append(numpy.array(ress._getspectrum(0))) |
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354 | sel.reset() |
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355 | ress.set_selection() |
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356 | del sel |
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357 | # plot |
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358 | print_log() |
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359 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.') |
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360 | print_log('WARN') |
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361 | p=asaplotgui.asaplotgui() |
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362 | #nr=min(6,len(ifnos)*len(polnos)) |
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363 | nr=len(ifnos)*len(polnos) |
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364 | titles=[] |
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365 | btics=[] |
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366 | if nr<4: |
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367 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False) |
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368 | for i in range(2*nr): |
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369 | b=False |
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370 | if i >= 2*nr-2: |
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371 | b=True |
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372 | btics.append(b) |
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373 | elif nr==4: |
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374 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False) |
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375 | for i in range(2*nr): |
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376 | b=False |
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377 | if i >= 2*nr-4: |
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378 | b=True |
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379 | btics.append(b) |
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380 | elif nr<7: |
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381 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
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382 | for i in range(2*nr): |
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383 | if i >= 2*nr-4: |
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384 | b=True |
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385 | btics.append(b) |
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386 | else: |
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387 | print_log() |
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388 | asaplog.push('Only first 6 [if,pol] pairs are plotted.') |
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389 | print_log('WARN') |
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390 | nr=6 |
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391 | for i in range(2*nr): |
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392 | b=False |
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393 | if i >= 2*nr-4: |
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394 | b=True |
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395 | btics.append(b) |
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396 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
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397 | for i in range(nr): |
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398 | p.subplot(2*i) |
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399 | p.color=0 |
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400 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
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401 | titles.append(title) |
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402 | #p.set_axes('title',title,fontsize=40) |
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403 | ymin=1.0e100 |
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404 | ymax=-1.0e100 |
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405 | nchan=s.nchan() |
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406 | edge=int(nchan*0.01) |
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407 | for j in range(4): |
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408 | spmin=min(precal[keys[j]][i][edge:nchan-edge]) |
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409 | spmax=max(precal[keys[j]][i][edge:nchan-edge]) |
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410 | ymin=min(ymin,spmin) |
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411 | ymax=max(ymax,spmax) |
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412 | for j in range(4): |
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413 | if i==0: |
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414 | p.set_line(label=keys[j]) |
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415 | else: |
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416 | p.legend() |
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417 | p.plot(precal[keys[j]][i]) |
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418 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
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419 | if not btics[2*i]: |
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420 | p.axes.set_xticks([]) |
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421 | p.subplot(2*i+1) |
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422 | p.color=0 |
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423 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
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424 | titles.append(title) |
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425 | #p.set_axes('title',title) |
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426 | p.legend() |
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427 | ymin=postcal[i][edge:nchan-edge].min() |
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428 | ymax=postcal[i][edge:nchan-edge].max() |
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429 | p.plot(postcal[i]) |
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430 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
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431 | if not btics[2*i+1]: |
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432 | p.axes.set_xticks([]) |
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433 | for i in range(2*nr): |
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434 | p.subplot(i) |
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435 | p.set_axes('title',titles[i],fontsize='medium') |
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436 | x=raw_input('Accept calibration ([y]/n): ' ) |
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437 | if x.upper() == 'N': |
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438 | p.unmap() |
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439 | del p |
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440 | return scabtab |
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441 | p.unmap() |
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442 | del p |
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443 | ### |
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444 | ress._add_history("calps", varlist) |
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445 | print_log() |
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446 | return ress |
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447 | |
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448 | @print_log_dec |
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449 | def calnod(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False): |
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450 | """ |
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451 | Do full (but a pair of scans at time) processing of GBT Nod data |
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452 | calibration. |
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453 | Adopted from GBTIDL's getnod |
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454 | Parameters: |
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455 | scantab: scantable |
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456 | scannos: a pair of scan numbers, or the first scan number of the pair |
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457 | smooth: box car smoothing order |
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458 | tsysval: optional user specified Tsys value |
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459 | tauval: optional user specified tau value (not implemented yet) |
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460 | tcalval: optional user specified Tcal value |
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461 | """ |
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462 | varlist = vars() |
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463 | from asap._asap import stmath |
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464 | from asap._asap import srctype |
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465 | stm = stmath() |
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466 | stm._setinsitu(False) |
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467 | |
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468 | # check for the appropriate data |
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469 | ## s = scantab.get_scan('*_nod*') |
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470 | ## if s is None: |
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471 | ## msg = "The input data appear to contain no Nod observing mode data." |
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472 | ## if rcParams['verbose']: |
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473 | ## #print msg |
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474 | ## asaplog.push(msg) |
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475 | ## print_log('ERROR') |
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476 | ## return |
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477 | ## else: |
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478 | ## raise TypeError(msg) |
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479 | s = scantab.copy() |
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480 | sel = selector() |
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481 | sel.set_types( srctype.nod ) |
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482 | try: |
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483 | s.set_selection( sel ) |
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484 | except Exception, e: |
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485 | msg = "The input data appear to contain no Nod observing mode data." |
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486 | if rcParams['verbose']: |
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487 | #print msg |
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488 | asaplog.push(msg) |
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489 | print_log('ERROR') |
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490 | return |
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491 | else: |
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492 | raise TypeError(msg) |
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493 | sel.reset() |
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494 | del sel |
---|
495 | del s |
---|
496 | |
---|
497 | # need check correspondance of each beam with sig-ref ... |
---|
498 | # check for timestamps, scan numbers, subscan id (not available in |
---|
499 | # ASAP data format...). Assume 1st scan of the pair (beam 0 - sig |
---|
500 | # and beam 1 - ref...) |
---|
501 | # First scan number of paired scans or list of pairs of |
---|
502 | # scan numbers (has to have even number of pairs.) |
---|
503 | |
---|
504 | #data splitting |
---|
505 | scan1no = scan2no = 0 |
---|
506 | |
---|
507 | if len(scannos)==1: |
---|
508 | scan1no = scannos[0] |
---|
509 | scan2no = scannos[0]+1 |
---|
510 | pairScans = [scan1no, scan2no] |
---|
511 | else: |
---|
512 | #if len(scannos)>2: |
---|
513 | # msg = "calnod can only process a pair of nod scans at time." |
---|
514 | # if rcParams['verbose']: |
---|
515 | # print msg |
---|
516 | # return |
---|
517 | # else: |
---|
518 | # raise TypeError(msg) |
---|
519 | # |
---|
520 | #if len(scannos)==2: |
---|
521 | # scan1no = scannos[0] |
---|
522 | # scan2no = scannos[1] |
---|
523 | pairScans = list(scannos) |
---|
524 | |
---|
525 | if tsysval>0.0: |
---|
526 | if tauval<=0.0: |
---|
527 | msg = "Need to supply a valid tau to use the supplied Tsys" |
---|
528 | if rcParams['verbose']: |
---|
529 | #print msg |
---|
530 | asaplog.push(msg) |
---|
531 | print_log('ERROR') |
---|
532 | return |
---|
533 | else: |
---|
534 | raise TypeError(msg) |
---|
535 | else: |
---|
536 | scantab.recalc_azel() |
---|
537 | resspec = scantable(stm._donod(scantab, pairScans, smooth, tsysval,tauval,tcalval)) |
---|
538 | ### |
---|
539 | if verify: |
---|
540 | # get data |
---|
541 | import numpy |
---|
542 | precal={} |
---|
543 | postcal=[] |
---|
544 | keys=['','_calon'] |
---|
545 | types=[srctype.nod,srctype.nodcal] |
---|
546 | ifnos=list(scantab.getifnos()) |
---|
547 | polnos=list(scantab.getpolnos()) |
---|
548 | sel=selector() |
---|
549 | ss = scantab.copy() |
---|
550 | for i in range(2): |
---|
551 | #ss=scantab.get_scan('*'+keys[i]) |
---|
552 | ll=[] |
---|
553 | ll2=[] |
---|
554 | for j in range(len(ifnos)): |
---|
555 | for k in range(len(polnos)): |
---|
556 | sel.set_ifs(ifnos[j]) |
---|
557 | sel.set_polarizations(polnos[k]) |
---|
558 | sel.set_scans(pairScans[0]) |
---|
559 | sel.set_types(types[i]) |
---|
560 | try: |
---|
561 | ss.set_selection(sel) |
---|
562 | except: |
---|
563 | continue |
---|
564 | ll.append(numpy.array(ss._getspectrum(0))) |
---|
565 | sel.reset() |
---|
566 | ss.set_selection() |
---|
567 | sel.set_ifs(ifnos[j]) |
---|
568 | sel.set_polarizations(polnos[k]) |
---|
569 | sel.set_scans(pairScans[1]) |
---|
570 | sel.set_types(types[i]) |
---|
571 | try: |
---|
572 | ss.set_selection(sel) |
---|
573 | except: |
---|
574 | ll.pop() |
---|
575 | continue |
---|
576 | ll2.append(numpy.array(ss._getspectrum(0))) |
---|
577 | sel.reset() |
---|
578 | ss.set_selection() |
---|
579 | key='%s%s' %(pairScans[0],keys[i]) |
---|
580 | precal[key]=ll |
---|
581 | key='%s%s' %(pairScans[1],keys[i]) |
---|
582 | precal[key]=ll2 |
---|
583 | #del ss |
---|
584 | keys=precal.keys() |
---|
585 | for j in range(len(ifnos)): |
---|
586 | for k in range(len(polnos)): |
---|
587 | sel.set_ifs(ifnos[j]) |
---|
588 | sel.set_polarizations(polnos[k]) |
---|
589 | sel.set_scans(pairScans[0]) |
---|
590 | try: |
---|
591 | resspec.set_selection(sel) |
---|
592 | except: |
---|
593 | continue |
---|
594 | postcal.append(numpy.array(resspec._getspectrum(0))) |
---|
595 | sel.reset() |
---|
596 | resspec.set_selection() |
---|
597 | del sel |
---|
598 | # plot |
---|
599 | print_log() |
---|
600 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.') |
---|
601 | print_log('WARN') |
---|
602 | p=asaplotgui.asaplotgui() |
---|
603 | #nr=min(6,len(ifnos)*len(polnos)) |
---|
604 | nr=len(ifnos)*len(polnos) |
---|
605 | titles=[] |
---|
606 | btics=[] |
---|
607 | if nr<4: |
---|
608 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False) |
---|
609 | for i in range(2*nr): |
---|
610 | b=False |
---|
611 | if i >= 2*nr-2: |
---|
612 | b=True |
---|
613 | btics.append(b) |
---|
614 | elif nr==4: |
---|
615 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False) |
---|
616 | for i in range(2*nr): |
---|
617 | b=False |
---|
618 | if i >= 2*nr-4: |
---|
619 | b=True |
---|
620 | btics.append(b) |
---|
621 | elif nr<7: |
---|
622 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
---|
623 | for i in range(2*nr): |
---|
624 | if i >= 2*nr-4: |
---|
625 | b=True |
---|
626 | btics.append(b) |
---|
627 | else: |
---|
628 | print_log() |
---|
629 | asaplog.push('Only first 6 [if,pol] pairs are plotted.') |
---|
630 | print_log('WARN') |
---|
631 | nr=6 |
---|
632 | for i in range(2*nr): |
---|
633 | b=False |
---|
634 | if i >= 2*nr-4: |
---|
635 | b=True |
---|
636 | btics.append(b) |
---|
637 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
---|
638 | for i in range(nr): |
---|
639 | p.subplot(2*i) |
---|
640 | p.color=0 |
---|
641 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
642 | titles.append(title) |
---|
643 | #p.set_axes('title',title,fontsize=40) |
---|
644 | ymin=1.0e100 |
---|
645 | ymax=-1.0e100 |
---|
646 | nchan=scantab.nchan() |
---|
647 | edge=int(nchan*0.01) |
---|
648 | for j in range(4): |
---|
649 | spmin=min(precal[keys[j]][i][edge:nchan-edge]) |
---|
650 | spmax=max(precal[keys[j]][i][edge:nchan-edge]) |
---|
651 | ymin=min(ymin,spmin) |
---|
652 | ymax=max(ymax,spmax) |
---|
653 | for j in range(4): |
---|
654 | if i==0: |
---|
655 | p.set_line(label=keys[j]) |
---|
656 | else: |
---|
657 | p.legend() |
---|
658 | p.plot(precal[keys[j]][i]) |
---|
659 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
660 | if not btics[2*i]: |
---|
661 | p.axes.set_xticks([]) |
---|
662 | p.subplot(2*i+1) |
---|
663 | p.color=0 |
---|
664 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
665 | titles.append(title) |
---|
666 | #p.set_axes('title',title) |
---|
667 | p.legend() |
---|
668 | ymin=postcal[i][edge:nchan-edge].min() |
---|
669 | ymax=postcal[i][edge:nchan-edge].max() |
---|
670 | p.plot(postcal[i]) |
---|
671 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
672 | if not btics[2*i+1]: |
---|
673 | p.axes.set_xticks([]) |
---|
674 | for i in range(2*nr): |
---|
675 | p.subplot(i) |
---|
676 | p.set_axes('title',titles[i],fontsize='medium') |
---|
677 | x=raw_input('Accept calibration ([y]/n): ' ) |
---|
678 | if x.upper() == 'N': |
---|
679 | p.unmap() |
---|
680 | del p |
---|
681 | return scabtab |
---|
682 | p.unmap() |
---|
683 | del p |
---|
684 | ### |
---|
685 | resspec._add_history("calnod",varlist) |
---|
686 | print_log() |
---|
687 | return resspec |
---|
688 | |
---|
689 | @print_log_dec |
---|
690 | def calfs(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False): |
---|
691 | """ |
---|
692 | Calibrate GBT frequency switched data. |
---|
693 | Adopted from GBTIDL getfs. |
---|
694 | Currently calfs identify the scans as frequency switched data if they |
---|
695 | contain '_fs' in the source name. The data must contains 'CAL' signal |
---|
696 | on/off in each integration. To identify 'CAL' on state, the word, 'calon' |
---|
697 | need to be present in the source name field. |
---|
698 | (GBT MS data reading via scantable automatically append these |
---|
699 | id names to the source names) |
---|
700 | |
---|
701 | Parameters: |
---|
702 | scantab: scantable |
---|
703 | scannos: list of scan numbers |
---|
704 | smooth: optional box smoothing order for the reference |
---|
705 | (default is 1 = no smoothing) |
---|
706 | tsysval: optional user specified Tsys (default is 0.0, |
---|
707 | use Tsys in the data) |
---|
708 | tauval: optional user specified Tau |
---|
709 | """ |
---|
710 | varlist = vars() |
---|
711 | from asap._asap import stmath |
---|
712 | from asap._asap import srctype |
---|
713 | stm = stmath() |
---|
714 | stm._setinsitu(False) |
---|
715 | |
---|
716 | # check = scantab.get_scan('*_fs*') |
---|
717 | # if check is None: |
---|
718 | # msg = "The input data appear to contain no Nod observing mode data." |
---|
719 | # if rcParams['verbose']: |
---|
720 | # print msg |
---|
721 | # return |
---|
722 | # else: |
---|
723 | # raise TypeError(msg) |
---|
724 | s = scantab.get_scan(scannos) |
---|
725 | del scantab |
---|
726 | |
---|
727 | resspec = scantable(stm._dofs(s, scannos, smooth, tsysval,tauval,tcalval)) |
---|
728 | ### |
---|
729 | if verify: |
---|
730 | # get data |
---|
731 | ssub = s.get_scan(scannos) |
---|
732 | #ssubon = ssub.get_scan('*calon') |
---|
733 | #ssuboff = ssub.get_scan('*[^calon]') |
---|
734 | sel = selector() |
---|
735 | sel.set_types( [srctype.foncal,srctype.foffcal] ) |
---|
736 | ssub.set_selection( sel ) |
---|
737 | ssubon = ssub.copy() |
---|
738 | ssub.set_selection() |
---|
739 | sel.reset() |
---|
740 | sel.set_types( [srctype.fson,srctype.fsoff] ) |
---|
741 | ssub.set_selection( sel ) |
---|
742 | ssuboff = ssub.copy() |
---|
743 | ssub.set_selection() |
---|
744 | sel.reset() |
---|
745 | import numpy |
---|
746 | precal={} |
---|
747 | postcal=[] |
---|
748 | keys=['fs','fs_calon','fsr','fsr_calon'] |
---|
749 | types=[srctype.fson,srctype.foncal,srctype.fsoff,srctype.foffcal] |
---|
750 | ifnos=list(ssub.getifnos()) |
---|
751 | polnos=list(ssub.getpolnos()) |
---|
752 | for i in range(2): |
---|
753 | #ss=ssuboff.get_scan('*'+keys[2*i]) |
---|
754 | ll=[] |
---|
755 | for j in range(len(ifnos)): |
---|
756 | for k in range(len(polnos)): |
---|
757 | sel.set_ifs(ifnos[j]) |
---|
758 | sel.set_polarizations(polnos[k]) |
---|
759 | sel.set_types(types[2*i]) |
---|
760 | try: |
---|
761 | #ss.set_selection(sel) |
---|
762 | ssuboff.set_selection(sel) |
---|
763 | except: |
---|
764 | continue |
---|
765 | ll.append(numpy.array(ss._getspectrum(0))) |
---|
766 | sel.reset() |
---|
767 | #ss.set_selection() |
---|
768 | ssuboff.set_selection() |
---|
769 | precal[keys[2*i]]=ll |
---|
770 | #del ss |
---|
771 | #ss=ssubon.get_scan('*'+keys[2*i+1]) |
---|
772 | ll=[] |
---|
773 | for j in range(len(ifnos)): |
---|
774 | for k in range(len(polnos)): |
---|
775 | sel.set_ifs(ifnos[j]) |
---|
776 | sel.set_polarizations(polnos[k]) |
---|
777 | sel.set_types(types[2*i+1]) |
---|
778 | try: |
---|
779 | #ss.set_selection(sel) |
---|
780 | ssubon.set_selection(sel) |
---|
781 | except: |
---|
782 | continue |
---|
783 | ll.append(numpy.array(ss._getspectrum(0))) |
---|
784 | sel.reset() |
---|
785 | #ss.set_selection() |
---|
786 | ssubon.set_selection() |
---|
787 | precal[keys[2*i+1]]=ll |
---|
788 | #del ss |
---|
789 | #sig=resspec.get_scan('*_fs') |
---|
790 | #ref=resspec.get_scan('*_fsr') |
---|
791 | sel.set_types( srctype.fson ) |
---|
792 | resspec.set_selection( sel ) |
---|
793 | sig=resspec.copy() |
---|
794 | resspec.set_selection() |
---|
795 | sel.reset() |
---|
796 | sel.set_type( srctype.fsoff ) |
---|
797 | resspec.set_selection( sel ) |
---|
798 | ref=resspec.copy() |
---|
799 | resspec.set_selection() |
---|
800 | sel.reset() |
---|
801 | for k in range(len(polnos)): |
---|
802 | for j in range(len(ifnos)): |
---|
803 | sel.set_ifs(ifnos[j]) |
---|
804 | sel.set_polarizations(polnos[k]) |
---|
805 | try: |
---|
806 | sig.set_selection(sel) |
---|
807 | postcal.append(numpy.array(sig._getspectrum(0))) |
---|
808 | except: |
---|
809 | ref.set_selection(sel) |
---|
810 | postcal.append(numpy.array(ref._getspectrum(0))) |
---|
811 | sel.reset() |
---|
812 | resspec.set_selection() |
---|
813 | del sel |
---|
814 | # plot |
---|
815 | print_log() |
---|
816 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.') |
---|
817 | print_log('WARN') |
---|
818 | p=asaplotgui.asaplotgui() |
---|
819 | #nr=min(6,len(ifnos)*len(polnos)) |
---|
820 | nr=len(ifnos)/2*len(polnos) |
---|
821 | titles=[] |
---|
822 | btics=[] |
---|
823 | if nr>3: |
---|
824 | print_log() |
---|
825 | asaplog.push('Only first 3 [if,pol] pairs are plotted.') |
---|
826 | print_log('WARN') |
---|
827 | nr=3 |
---|
828 | p.set_panels(rows=nr,cols=3,nplots=3*nr,ganged=False) |
---|
829 | for i in range(3*nr): |
---|
830 | b=False |
---|
831 | if i >= 3*nr-3: |
---|
832 | b=True |
---|
833 | btics.append(b) |
---|
834 | for i in range(nr): |
---|
835 | p.subplot(3*i) |
---|
836 | p.color=0 |
---|
837 | title='raw data IF%s,%s POL%s' % (ifnos[2*int(i/len(polnos))],ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)]) |
---|
838 | titles.append(title) |
---|
839 | #p.set_axes('title',title,fontsize=40) |
---|
840 | ymin=1.0e100 |
---|
841 | ymax=-1.0e100 |
---|
842 | nchan=s.nchan() |
---|
843 | edge=int(nchan*0.01) |
---|
844 | for j in range(4): |
---|
845 | spmin=min(precal[keys[j]][i][edge:nchan-edge]) |
---|
846 | spmax=max(precal[keys[j]][i][edge:nchan-edge]) |
---|
847 | ymin=min(ymin,spmin) |
---|
848 | ymax=max(ymax,spmax) |
---|
849 | for j in range(4): |
---|
850 | if i==0: |
---|
851 | p.set_line(label=keys[j]) |
---|
852 | else: |
---|
853 | p.legend() |
---|
854 | p.plot(precal[keys[j]][i]) |
---|
855 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
856 | if not btics[3*i]: |
---|
857 | p.axes.set_xticks([]) |
---|
858 | p.subplot(3*i+1) |
---|
859 | p.color=0 |
---|
860 | title='sig data IF%s POL%s' % (ifnos[2*int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
861 | titles.append(title) |
---|
862 | #p.set_axes('title',title) |
---|
863 | p.legend() |
---|
864 | ymin=postcal[2*i][edge:nchan-edge].min() |
---|
865 | ymax=postcal[2*i][edge:nchan-edge].max() |
---|
866 | p.plot(postcal[2*i]) |
---|
867 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
868 | if not btics[3*i+1]: |
---|
869 | p.axes.set_xticks([]) |
---|
870 | p.subplot(3*i+2) |
---|
871 | p.color=0 |
---|
872 | title='ref data IF%s POL%s' % (ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)]) |
---|
873 | titles.append(title) |
---|
874 | #p.set_axes('title',title) |
---|
875 | p.legend() |
---|
876 | ymin=postcal[2*i+1][edge:nchan-edge].min() |
---|
877 | ymax=postcal[2*i+1][edge:nchan-edge].max() |
---|
878 | p.plot(postcal[2*i+1]) |
---|
879 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
880 | if not btics[3*i+2]: |
---|
881 | p.axes.set_xticks([]) |
---|
882 | for i in range(3*nr): |
---|
883 | p.subplot(i) |
---|
884 | p.set_axes('title',titles[i],fontsize='medium') |
---|
885 | x=raw_input('Accept calibration ([y]/n): ' ) |
---|
886 | if x.upper() == 'N': |
---|
887 | p.unmap() |
---|
888 | del p |
---|
889 | return scabtab |
---|
890 | p.unmap() |
---|
891 | del p |
---|
892 | ### |
---|
893 | resspec._add_history("calfs",varlist) |
---|
894 | print_log() |
---|
895 | return resspec |
---|
896 | |
---|
897 | @print_log_dec |
---|
898 | def merge(*args): |
---|
899 | """ |
---|
900 | Merge a list of scanatables, or comma-sperated scantables into one |
---|
901 | scnatble. |
---|
902 | Parameters: |
---|
903 | A list [scan1, scan2] or scan1, scan2. |
---|
904 | Example: |
---|
905 | myscans = [scan1, scan2] |
---|
906 | allscans = merge(myscans) |
---|
907 | # or equivalent |
---|
908 | sameallscans = merge(scan1, scan2) |
---|
909 | """ |
---|
910 | varlist = vars() |
---|
911 | if isinstance(args[0],list): |
---|
912 | lst = tuple(args[0]) |
---|
913 | elif isinstance(args[0],tuple): |
---|
914 | lst = args[0] |
---|
915 | else: |
---|
916 | lst = tuple(args) |
---|
917 | varlist["args"] = "%d scantables" % len(lst) |
---|
918 | # need special formatting her for history... |
---|
919 | from asap._asap import stmath |
---|
920 | stm = stmath() |
---|
921 | for s in lst: |
---|
922 | if not isinstance(s,scantable): |
---|
923 | msg = "Please give a list of scantables" |
---|
924 | if rcParams['verbose']: |
---|
925 | #print msg |
---|
926 | asaplog.push(msg) |
---|
927 | print_log('ERROR') |
---|
928 | return |
---|
929 | else: |
---|
930 | raise TypeError(msg) |
---|
931 | s = scantable(stm._merge(lst)) |
---|
932 | s._add_history("merge", varlist) |
---|
933 | print_log() |
---|
934 | return s |
---|
935 | |
---|
936 | def calibrate( scantab, scannos=[], calmode='none', verify=None ): |
---|
937 | """ |
---|
938 | Calibrate data. |
---|
939 | |
---|
940 | Parameters: |
---|
941 | scantab: scantable |
---|
942 | scannos: list of scan number |
---|
943 | calmode: calibration mode |
---|
944 | verify: verify calibration |
---|
945 | """ |
---|
946 | antname = scantab.get_antennaname() |
---|
947 | if ( calmode == 'nod' ): |
---|
948 | asaplog.push( 'Calibrating nod data.' ) |
---|
949 | print_log() |
---|
950 | scal = calnod( scantab, scannos=scannos, verify=verify ) |
---|
951 | elif ( calmode == 'quotient' ): |
---|
952 | asaplog.push( 'Calibrating using quotient.' ) |
---|
953 | print_log() |
---|
954 | scal = scantab.auto_quotient( verify=verify ) |
---|
955 | elif ( calmode == 'ps' ): |
---|
956 | asaplog.push( 'Calibrating %s position-switched data.' % antname ) |
---|
957 | print_log() |
---|
958 | if ( antname.find( 'APEX' ) != -1 ): |
---|
959 | scal = apexcal( scantab, scannos, calmode, verify ) |
---|
960 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 ): |
---|
961 | scal = almacal( scantab, scannos, calmode, verify ) |
---|
962 | else: |
---|
963 | scal = calps( scantab, scannos=scannos, verify=verify ) |
---|
964 | elif ( calmode == 'fs' or calmode == 'fsotf' ): |
---|
965 | asaplog.push( 'Calibrating %s frequency-switched data.' % antname ) |
---|
966 | print_log() |
---|
967 | if ( antname.find( 'APEX' ) != -1 ): |
---|
968 | scal = apexcal( scantab, scannos, calmode, verify ) |
---|
969 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 ): |
---|
970 | scal = almacal( scantab, scannos, calmode, verify ) |
---|
971 | else: |
---|
972 | scal = calfs( scantab, scannos=scannos, verify=verify ) |
---|
973 | elif ( calmode == 'otf' ): |
---|
974 | asaplog.push( 'Calibrating %s On-The-Fly data.' % antname ) |
---|
975 | print_log() |
---|
976 | scal = almacal( scantab, scannos, calmode, verify ) |
---|
977 | else: |
---|
978 | asaplog.push( 'No calibration.' ) |
---|
979 | scal = scantab.copy() |
---|
980 | |
---|
981 | return scal |
---|
982 | |
---|
983 | def apexcal( scantab, scannos=[], calmode='none', verify=False ): |
---|
984 | """ |
---|
985 | Calibrate APEX data |
---|
986 | |
---|
987 | Parameters: |
---|
988 | scantab: scantable |
---|
989 | scannos: list of scan number |
---|
990 | calmode: calibration mode |
---|
991 | |
---|
992 | verify: verify calibration |
---|
993 | """ |
---|
994 | from asap._asap import stmath |
---|
995 | stm = stmath() |
---|
996 | antname = scantab.get_antennaname() |
---|
997 | ssub = scantab.get_scan( scannos ) |
---|
998 | scal = scantable( stm.cwcal( ssub, calmode, antname ) ) |
---|
999 | return scal |
---|
1000 | |
---|
1001 | def almacal( scantab, scannos=[], calmode='none', verify=False ): |
---|
1002 | """ |
---|
1003 | Calibrate ALMA data |
---|
1004 | |
---|
1005 | Parameters: |
---|
1006 | scantab: scantable |
---|
1007 | scannos: list of scan number |
---|
1008 | calmode: calibration mode |
---|
1009 | |
---|
1010 | verify: verify calibration |
---|
1011 | """ |
---|
1012 | from asap._asap import stmath |
---|
1013 | stm = stmath() |
---|
1014 | ssub = scantab.get_scan( scannos ) |
---|
1015 | scal = scantable( stm.almacal( ssub, calmode ) ) |
---|
1016 | return scal |
---|
1017 | |
---|
1018 | def splitant(filename, outprefix='',overwrite=False): |
---|
1019 | """ |
---|
1020 | Split Measurement set by antenna name, save data as a scantables, |
---|
1021 | and return a list of filename. |
---|
1022 | Notice this method can only be available from CASA. |
---|
1023 | Prameter |
---|
1024 | filename: the name of Measurement set to be read. |
---|
1025 | outprefix: the prefix of output scantable name. |
---|
1026 | the names of output scantable will be |
---|
1027 | outprefix.antenna1, outprefix.antenna2, .... |
---|
1028 | If not specified, outprefix = filename is assumed. |
---|
1029 | overwrite If the file should be overwritten if it exists. |
---|
1030 | The default False is to return with warning |
---|
1031 | without writing the output. USE WITH CARE. |
---|
1032 | |
---|
1033 | """ |
---|
1034 | # Import the table toolkit from CASA |
---|
1035 | try: |
---|
1036 | import casac |
---|
1037 | except ImportError: |
---|
1038 | if rcParams['verbose']: |
---|
1039 | #print "failed to load casa" |
---|
1040 | print_log() |
---|
1041 | asaplog.push("failed to load casa") |
---|
1042 | print_log('ERROR') |
---|
1043 | else: raise |
---|
1044 | return False |
---|
1045 | try: |
---|
1046 | tbtool = casac.homefinder.find_home_by_name('tableHome') |
---|
1047 | tb = tbtool.create() |
---|
1048 | tb2 = tbtool.create() |
---|
1049 | except: |
---|
1050 | if rcParams['verbose']: |
---|
1051 | #print "failed to load a table tool:\n", e |
---|
1052 | print_log() |
---|
1053 | asaplog.push("failed to load table tool") |
---|
1054 | print_log('ERROR') |
---|
1055 | else: raise |
---|
1056 | return False |
---|
1057 | # Check the input filename |
---|
1058 | if isinstance(filename, str): |
---|
1059 | import os.path |
---|
1060 | filename = os.path.expandvars(filename) |
---|
1061 | filename = os.path.expanduser(filename) |
---|
1062 | if not os.path.exists(filename): |
---|
1063 | s = "File '%s' not found." % (filename) |
---|
1064 | if rcParams['verbose']: |
---|
1065 | print_log() |
---|
1066 | asaplog.push(s) |
---|
1067 | print_log('ERROR') |
---|
1068 | return |
---|
1069 | raise IOError(s) |
---|
1070 | # check if input file is MS |
---|
1071 | if not os.path.isdir(filename) \ |
---|
1072 | or not os.path.exists(filename+'/ANTENNA') \ |
---|
1073 | or not os.path.exists(filename+'/table.f1'): |
---|
1074 | s = "File '%s' is not a Measurement set." % (filename) |
---|
1075 | if rcParams['verbose']: |
---|
1076 | print_log() |
---|
1077 | asaplog.push(s) |
---|
1078 | print_log('ERROR') |
---|
1079 | return |
---|
1080 | raise IOError(s) |
---|
1081 | else: |
---|
1082 | s = "The filename should be string. " |
---|
1083 | if rcParams['verbose']: |
---|
1084 | print_log() |
---|
1085 | asaplog.push(s) |
---|
1086 | print_log('ERROR') |
---|
1087 | return |
---|
1088 | raise TypeError(s) |
---|
1089 | # Check out put file name |
---|
1090 | outname='' |
---|
1091 | if len(outprefix) > 0: prefix=outprefix+'.' |
---|
1092 | else: |
---|
1093 | prefix=filename.rstrip('/') |
---|
1094 | # Now do the actual splitting. |
---|
1095 | outfiles=[] |
---|
1096 | tb.open(tablename=filename+'/ANTENNA',nomodify=True) |
---|
1097 | nant=tb.nrows() |
---|
1098 | antnames=tb.getcol('NAME',0,nant,1) |
---|
1099 | antpos=tb.getcol('POSITION',0,nant,1).transpose() |
---|
1100 | tb.close() |
---|
1101 | tb.open(tablename=filename,nomodify=True) |
---|
1102 | ant1=tb.getcol('ANTENNA1',0,-1,1) |
---|
1103 | tb.close() |
---|
1104 | for antid in set(ant1): |
---|
1105 | scan=scantable(filename,average=False,getpt=True,antenna=int(antid)) |
---|
1106 | outname=prefix+antnames[antid]+'.asap' |
---|
1107 | scan.save(outname,format='ASAP',overwrite=overwrite) |
---|
1108 | del scan |
---|
1109 | outfiles.append(outname) |
---|
1110 | del tb, tb2 |
---|
1111 | return outfiles |
---|
1112 | |
---|
1113 | def _array2dOp( scan, value, mode="ADD", tsys=False ): |
---|
1114 | """ |
---|
1115 | This function is workaround on the basic operation of scantable |
---|
1116 | with 2 dimensional float list. |
---|
1117 | |
---|
1118 | scan: scantable operand |
---|
1119 | value: float list operand |
---|
1120 | mode: operation mode (ADD, SUB, MUL, DIV) |
---|
1121 | tsys: if True, operate tsys as well |
---|
1122 | """ |
---|
1123 | nrow = scan.nrow() |
---|
1124 | s = None |
---|
1125 | if len( value ) == 1: |
---|
1126 | from asap._asap import stmath |
---|
1127 | stm = stmath() |
---|
1128 | s = scantable( stm._arrayop( scan.copy(), value[0], mode, tsys ) ) |
---|
1129 | del stm |
---|
1130 | elif len( value ) != nrow: |
---|
1131 | asaplog.push( 'len(value) must be 1 or conform to scan.nrow()' ) |
---|
1132 | print_log( 'ERROR' ) |
---|
1133 | else: |
---|
1134 | from asap._asap import stmath |
---|
1135 | stm = stmath() |
---|
1136 | # insitu must be True |
---|
1137 | stm._setinsitu( True ) |
---|
1138 | s = scan.copy() |
---|
1139 | sel = selector() |
---|
1140 | for irow in range( nrow ): |
---|
1141 | sel.set_rows( irow ) |
---|
1142 | s.set_selection( sel ) |
---|
1143 | if len( value[irow] ) == 1: |
---|
1144 | stm._unaryop( s, value[irow][0], mode, tsys ) |
---|
1145 | else: |
---|
1146 | stm._arrayop( s, value[irow], mode, tsys, 'channel' ) |
---|
1147 | s.set_selection() |
---|
1148 | sel.reset() |
---|
1149 | del sel |
---|
1150 | del stm |
---|
1151 | return s |
---|
1152 | |
---|
1153 | |
---|
1154 | |
---|