1 | from asap.scantable import scantable |
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2 | from asap.parameters import rcParams |
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3 | from asap.logging import asaplog, asaplog_post_dec |
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4 | from asap.selector import selector |
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5 | from asap.asapplotter import new_asaplot |
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6 | from matplotlib import rc as rcp |
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7 | |
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8 | @asaplog_post_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 | compel: True forces to average overwrapped IFs. |
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29 | Example: |
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30 | # return a time averaged scan from scana and scanb |
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31 | # without using a mask |
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32 | scanav = average_time(scana,scanb) |
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33 | # or equivalent |
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34 | # scanav = average_time([scana, scanb]) |
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35 | # return the (time) averaged scan, i.e. the average of |
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36 | # all correlator cycles |
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37 | scanav = average_time(scan, scanav=True) |
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38 | """ |
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39 | scanav = False |
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40 | if kwargs.has_key('scanav'): |
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41 | scanav = kwargs.get('scanav') |
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42 | weight = 'tint' |
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43 | if kwargs.has_key('weight'): |
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44 | weight = kwargs.get('weight') |
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45 | mask = () |
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46 | if kwargs.has_key('mask'): |
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47 | mask = kwargs.get('mask') |
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48 | align = False |
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49 | if kwargs.has_key('align'): |
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50 | align = kwargs.get('align') |
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51 | compel = False |
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52 | if kwargs.has_key('compel'): |
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53 | compel = kwargs.get('compel') |
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54 | varlist = vars() |
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55 | if isinstance(args[0],list): |
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56 | lst = args[0] |
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57 | elif isinstance(args[0],tuple): |
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58 | lst = list(args[0]) |
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59 | else: |
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60 | lst = list(args) |
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61 | |
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62 | del varlist["kwargs"] |
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63 | varlist["args"] = "%d scantables" % len(lst) |
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64 | # need special formatting here for history... |
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65 | |
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66 | from asap._asap import stmath |
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67 | stm = stmath() |
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68 | for s in lst: |
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69 | if not isinstance(s,scantable): |
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70 | msg = "Please give a list of scantables" |
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71 | raise TypeError(msg) |
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72 | if scanav: scanav = "SCAN" |
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73 | else: scanav = "NONE" |
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74 | alignedlst = [] |
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75 | if align: |
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76 | refepoch = lst[0].get_time(0) |
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77 | for scan in lst: |
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78 | alignedlst.append(scan.freq_align(refepoch,insitu=False)) |
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79 | else: |
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80 | alignedlst = lst |
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81 | if weight.upper() == 'MEDIAN': |
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82 | # median doesn't support list of scantables - merge first |
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83 | merged = None |
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84 | if len(alignedlst) > 1: |
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85 | merged = merge(alignedlst) |
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86 | else: |
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87 | merged = alignedlst[0] |
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88 | s = scantable(stm._averagechannel(merged, 'MEDIAN', scanav)) |
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89 | del merged |
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90 | else: |
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91 | #s = scantable(stm._average(alignedlst, mask, weight.upper(), scanav)) |
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92 | s = scantable(stm._new_average(alignedlst, compel, mask, weight.upper(), scanav)) |
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93 | s._add_history("average_time",varlist) |
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94 | |
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95 | return s |
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96 | |
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97 | @asaplog_post_dec |
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98 | def quotient(source, reference, preserve=True): |
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99 | """ |
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100 | Return the quotient of a 'source' (signal) scan and a 'reference' scan. |
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101 | The reference can have just one scan, even if the signal has many. Otherwise |
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102 | they must have the same number of scans. |
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103 | The cursor of the output scan is set to 0 |
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104 | Parameters: |
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105 | source: the 'on' scan |
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106 | reference: the 'off' scan |
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107 | preserve: you can preserve (default) the continuum or |
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108 | remove it. The equations used are |
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109 | preserve: Output = Toff * (on/off) - Toff |
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110 | remove: Output = Toff * (on/off) - Ton |
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111 | """ |
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112 | varlist = vars() |
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113 | from asap._asap import stmath |
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114 | stm = stmath() |
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115 | stm._setinsitu(False) |
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116 | s = scantable(stm._quotient(source, reference, preserve)) |
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117 | s._add_history("quotient",varlist) |
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118 | return s |
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119 | |
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120 | @asaplog_post_dec |
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121 | def dototalpower(calon, caloff, tcalval=0.0): |
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122 | """ |
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123 | Do calibration for CAL on,off signals. |
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124 | Adopted from GBTIDL dototalpower |
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125 | Parameters: |
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126 | calon: the 'cal on' subintegration |
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127 | caloff: the 'cal off' subintegration |
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128 | tcalval: user supplied Tcal value |
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129 | """ |
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130 | varlist = vars() |
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131 | from asap._asap import stmath |
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132 | stm = stmath() |
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133 | stm._setinsitu(False) |
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134 | s = scantable(stm._dototalpower(calon, caloff, tcalval)) |
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135 | s._add_history("dototalpower",varlist) |
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136 | return s |
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137 | |
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138 | @asaplog_post_dec |
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139 | def dosigref(sig, ref, smooth, tsysval=0.0, tauval=0.0): |
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140 | """ |
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141 | Calculate a quotient (sig-ref/ref * Tsys) |
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142 | Adopted from GBTIDL dosigref |
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143 | Parameters: |
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144 | sig: on source data |
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145 | ref: reference data |
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146 | smooth: width of box car smoothing for reference |
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147 | tsysval: user specified Tsys (scalar only) |
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148 | tauval: user specified Tau (required if tsysval is set) |
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149 | """ |
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150 | varlist = vars() |
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151 | from asap._asap import stmath |
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152 | stm = stmath() |
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153 | stm._setinsitu(False) |
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154 | s = scantable(stm._dosigref(sig, ref, smooth, tsysval, tauval)) |
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155 | s._add_history("dosigref",varlist) |
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156 | return s |
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157 | |
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158 | @asaplog_post_dec |
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159 | def calps(scantab, scannos, smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False): |
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160 | """ |
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161 | Calibrate GBT position switched data |
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162 | Adopted from GBTIDL getps |
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163 | Currently calps identify the scans as position switched data if source |
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164 | type enum is pson or psoff. The data must contains 'CAL' signal |
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165 | on/off in each integration. To identify 'CAL' on state, the source type |
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166 | enum of poncal and poffcal need to be present. |
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167 | |
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168 | Parameters: |
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169 | scantab: scantable |
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170 | scannos: list of scan numbers |
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171 | smooth: optional box smoothing order for the reference |
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172 | (default is 1 = no smoothing) |
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173 | tsysval: optional user specified Tsys (default is 0.0, |
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174 | use Tsys in the data) |
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175 | tauval: optional user specified Tau |
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176 | tcalval: optional user specified Tcal (default is 0.0, |
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177 | use Tcal value in the data) |
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178 | verify: Verify calibration if true |
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179 | """ |
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180 | varlist = vars() |
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181 | # check for the appropriate data |
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182 | ## s = scantab.get_scan('*_ps*') |
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183 | ## if s is None: |
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184 | ## msg = "The input data appear to contain no position-switch mode data." |
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185 | ## raise TypeError(msg) |
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186 | s = scantab.copy() |
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187 | from asap._asap import srctype |
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188 | sel = selector() |
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189 | sel.set_types( srctype.pson ) |
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190 | try: |
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191 | scantab.set_selection( sel ) |
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192 | except Exception, e: |
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193 | msg = "The input data appear to contain no position-switch mode data." |
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194 | raise TypeError(msg) |
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195 | s.set_selection() |
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196 | sel.reset() |
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197 | ssub = s.get_scan(scannos) |
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198 | if ssub is None: |
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199 | msg = "No data was found with given scan numbers!" |
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200 | raise TypeError(msg) |
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201 | #ssubon = ssub.get_scan('*calon') |
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202 | #ssuboff = ssub.get_scan('*[^calon]') |
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203 | sel.set_types( [srctype.poncal,srctype.poffcal] ) |
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204 | ssub.set_selection( sel ) |
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205 | ssubon = ssub.copy() |
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206 | ssub.set_selection() |
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207 | sel.reset() |
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208 | sel.set_types( [srctype.pson,srctype.psoff] ) |
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209 | ssub.set_selection( sel ) |
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210 | ssuboff = ssub.copy() |
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211 | ssub.set_selection() |
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212 | sel.reset() |
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213 | if ssubon.nrow() != ssuboff.nrow(): |
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214 | msg = "mismatch in numbers of CAL on/off scans. Cannot calibrate. Check the scan numbers." |
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215 | raise TypeError(msg) |
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216 | cals = dototalpower(ssubon, ssuboff, tcalval) |
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217 | #sig = cals.get_scan('*ps') |
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218 | #ref = cals.get_scan('*psr') |
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219 | sel.set_types( srctype.pson ) |
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220 | cals.set_selection( sel ) |
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221 | sig = cals.copy() |
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222 | cals.set_selection() |
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223 | sel.reset() |
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224 | sel.set_types( srctype.psoff ) |
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225 | cals.set_selection( sel ) |
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226 | ref = cals.copy() |
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227 | cals.set_selection() |
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228 | sel.reset() |
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229 | if sig.nscan() != ref.nscan(): |
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230 | msg = "mismatch in numbers of on/off scans. Cannot calibrate. Check the scan numbers." |
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231 | raise TypeError(msg) |
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232 | |
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233 | #for user supplied Tsys |
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234 | if tsysval>0.0: |
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235 | if tauval<=0.0: |
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236 | msg = "Need to supply a valid tau to use the supplied Tsys" |
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237 | raise TypeError(msg) |
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238 | else: |
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239 | sig.recalc_azel() |
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240 | ref.recalc_azel() |
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241 | #msg = "Use of user specified Tsys is not fully implemented yet." |
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242 | #raise TypeError(msg) |
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243 | # use get_elevation to get elevation and |
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244 | # calculate a scaling factor using the formula |
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245 | # -> tsys use to dosigref |
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246 | |
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247 | #ress = dosigref(sig, ref, smooth, tsysval) |
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248 | ress = dosigref(sig, ref, smooth, tsysval, tauval) |
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249 | ### |
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250 | if verify: |
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251 | # get data |
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252 | import numpy |
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253 | precal={} |
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254 | postcal=[] |
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255 | keys=['ps','ps_calon','psr','psr_calon'] |
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256 | types=[srctype.pson,srctype.poncal,srctype.psoff,srctype.poffcal] |
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257 | ifnos=list(ssub.getifnos()) |
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258 | polnos=list(ssub.getpolnos()) |
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259 | sel=selector() |
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260 | for i in range(2): |
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261 | #ss=ssuboff.get_scan('*'+keys[2*i]) |
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262 | ll=[] |
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263 | for j in range(len(ifnos)): |
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264 | for k in range(len(polnos)): |
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265 | sel.set_ifs(ifnos[j]) |
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266 | sel.set_polarizations(polnos[k]) |
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267 | sel.set_types(types[2*i]) |
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268 | try: |
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269 | #ss.set_selection(sel) |
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270 | ssuboff.set_selection(sel) |
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271 | except: |
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272 | continue |
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273 | #ll.append(numpy.array(ss._getspectrum(0))) |
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274 | ll.append(numpy.array(ssuboff._getspectrum(0))) |
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275 | sel.reset() |
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276 | ssuboff.set_selection() |
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277 | precal[keys[2*i]]=ll |
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278 | #del ss |
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279 | #ss=ssubon.get_scan('*'+keys[2*i+1]) |
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280 | ll=[] |
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281 | for j in range(len(ifnos)): |
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282 | for k in range(len(polnos)): |
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283 | sel.set_ifs(ifnos[j]) |
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284 | sel.set_polarizations(polnos[k]) |
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285 | sel.set_types(types[2*i+1]) |
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286 | try: |
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287 | #ss.set_selection(sel) |
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288 | ssubon.set_selection(sel) |
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289 | except: |
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290 | continue |
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291 | #ll.append(numpy.array(ss._getspectrum(0))) |
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292 | ll.append(numpy.array(ssubon._getspectrum(0))) |
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293 | sel.reset() |
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294 | ssubon.set_selection() |
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295 | precal[keys[2*i+1]]=ll |
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296 | #del ss |
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297 | for j in range(len(ifnos)): |
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298 | for k in range(len(polnos)): |
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299 | sel.set_ifs(ifnos[j]) |
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300 | sel.set_polarizations(polnos[k]) |
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301 | try: |
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302 | ress.set_selection(sel) |
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303 | except: |
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304 | continue |
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305 | postcal.append(numpy.array(ress._getspectrum(0))) |
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306 | sel.reset() |
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307 | ress.set_selection() |
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308 | del sel |
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309 | # plot |
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310 | asaplog.post() |
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311 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.') |
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312 | asaplog.post('WARN') |
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313 | p=new_asaplot() |
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314 | rcp('lines', linewidth=1) |
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315 | #nr=min(6,len(ifnos)*len(polnos)) |
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316 | nr=len(ifnos)*len(polnos) |
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317 | titles=[] |
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318 | btics=[] |
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319 | if nr<4: |
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320 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False) |
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321 | for i in range(2*nr): |
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322 | b=False |
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323 | if i >= 2*nr-2: |
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324 | b=True |
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325 | btics.append(b) |
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326 | elif nr==4: |
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327 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False) |
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328 | for i in range(2*nr): |
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329 | b=False |
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330 | if i >= 2*nr-4: |
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331 | b=True |
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332 | btics.append(b) |
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333 | elif nr<7: |
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334 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
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335 | for i in range(2*nr): |
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336 | if i >= 2*nr-4: |
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337 | b=True |
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338 | btics.append(b) |
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339 | else: |
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340 | asaplog.post() |
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341 | asaplog.push('Only first 6 [if,pol] pairs are plotted.') |
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342 | asaplog.post('WARN') |
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343 | nr=6 |
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344 | for i in range(2*nr): |
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345 | b=False |
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346 | if i >= 2*nr-4: |
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347 | b=True |
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348 | btics.append(b) |
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349 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
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350 | for i in range(nr): |
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351 | p.subplot(2*i) |
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352 | p.color=0 |
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353 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
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354 | titles.append(title) |
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355 | #p.set_axes('title',title,fontsize=40) |
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356 | ymin=1.0e100 |
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357 | ymax=-1.0e100 |
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358 | nchan=s.nchan(ifnos[int(i/len(polnos))]) |
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359 | edge=int(nchan*0.01) |
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360 | for j in range(4): |
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361 | spmin=min(precal[keys[j]][i][edge:nchan-edge]) |
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362 | spmax=max(precal[keys[j]][i][edge:nchan-edge]) |
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363 | ymin=min(ymin,spmin) |
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364 | ymax=max(ymax,spmax) |
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365 | for j in range(4): |
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366 | if i==0: |
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367 | p.set_line(label=keys[j]) |
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368 | else: |
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369 | p.legend() |
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370 | p.plot(precal[keys[j]][i]) |
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371 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
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372 | if not btics[2*i]: |
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373 | p.axes.set_xticks([]) |
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374 | p.subplot(2*i+1) |
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375 | p.color=0 |
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376 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
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377 | titles.append(title) |
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378 | #p.set_axes('title',title) |
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379 | p.legend() |
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380 | ymin=postcal[i][edge:nchan-edge].min() |
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381 | ymax=postcal[i][edge:nchan-edge].max() |
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382 | p.plot(postcal[i]) |
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383 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
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384 | if not btics[2*i+1]: |
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385 | p.axes.set_xticks([]) |
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386 | for i in range(2*nr): |
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387 | p.subplot(i) |
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388 | p.set_axes('title',titles[i],fontsize='medium') |
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389 | x=raw_input('Accept calibration ([y]/n): ' ) |
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390 | if x.upper() == 'N': |
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391 | p.quit() |
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392 | del p |
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393 | return scabtab |
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394 | p.quit() |
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395 | del p |
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396 | ### |
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397 | ress._add_history("calps", varlist) |
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398 | return ress |
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399 | |
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400 | @asaplog_post_dec |
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401 | def calnod(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False): |
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402 | """ |
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403 | Do full (but a pair of scans at time) processing of GBT Nod data |
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404 | calibration. |
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405 | Adopted from GBTIDL's getnod |
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406 | Parameters: |
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407 | scantab: scantable |
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408 | scannos: a pair of scan numbers, or the first scan number of the pair |
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409 | smooth: box car smoothing order |
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410 | tsysval: optional user specified Tsys value |
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411 | tauval: optional user specified tau value (not implemented yet) |
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412 | tcalval: optional user specified Tcal value |
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413 | verify: Verify calibration if true |
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414 | """ |
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415 | varlist = vars() |
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416 | from asap._asap import stmath |
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417 | from asap._asap import srctype |
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418 | stm = stmath() |
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419 | stm._setinsitu(False) |
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420 | |
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421 | # check for the appropriate data |
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422 | ## s = scantab.get_scan('*_nod*') |
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423 | ## if s is None: |
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424 | ## msg = "The input data appear to contain no Nod observing mode data." |
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425 | ## raise TypeError(msg) |
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426 | s = scantab.copy() |
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427 | sel = selector() |
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428 | sel.set_types( srctype.nod ) |
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429 | try: |
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430 | s.set_selection( sel ) |
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431 | except Exception, e: |
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432 | msg = "The input data appear to contain no Nod observing mode data." |
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433 | raise TypeError(msg) |
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434 | sel.reset() |
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435 | del sel |
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436 | del s |
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437 | |
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438 | # need check correspondance of each beam with sig-ref ... |
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439 | # check for timestamps, scan numbers, subscan id (not available in |
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440 | # ASAP data format...). Assume 1st scan of the pair (beam 0 - sig |
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441 | # and beam 1 - ref...) |
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442 | # First scan number of paired scans or list of pairs of |
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443 | # scan numbers (has to have even number of pairs.) |
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444 | |
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445 | #data splitting |
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446 | scan1no = scan2no = 0 |
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447 | |
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448 | if len(scannos)==1: |
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449 | scan1no = scannos[0] |
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450 | scan2no = scannos[0]+1 |
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451 | pairScans = [scan1no, scan2no] |
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452 | else: |
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453 | #if len(scannos)>2: |
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454 | # msg = "calnod can only process a pair of nod scans at time." |
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455 | # raise TypeError(msg) |
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456 | # |
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457 | #if len(scannos)==2: |
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458 | # scan1no = scannos[0] |
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459 | # scan2no = scannos[1] |
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460 | pairScans = list(scannos) |
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461 | |
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462 | if tsysval>0.0: |
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463 | if tauval<=0.0: |
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464 | msg = "Need to supply a valid tau to use the supplied Tsys" |
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465 | raise TypeError(msg) |
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466 | else: |
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467 | scantab.recalc_azel() |
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468 | resspec = scantable(stm._donod(scantab, pairScans, smooth, tsysval,tauval,tcalval)) |
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469 | ### |
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470 | if verify: |
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471 | # get data |
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472 | import numpy |
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473 | precal={} |
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474 | postcal=[] |
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475 | keys=['','_calon'] |
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476 | types=[srctype.nod,srctype.nodcal] |
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477 | ifnos=list(scantab.getifnos()) |
---|
478 | polnos=list(scantab.getpolnos()) |
---|
479 | sel=selector() |
---|
480 | ss = scantab.copy() |
---|
481 | for i in range(2): |
---|
482 | #ss=scantab.get_scan('*'+keys[i]) |
---|
483 | ll=[] |
---|
484 | ll2=[] |
---|
485 | for j in range(len(ifnos)): |
---|
486 | for k in range(len(polnos)): |
---|
487 | sel.set_ifs(ifnos[j]) |
---|
488 | sel.set_polarizations(polnos[k]) |
---|
489 | sel.set_scans(pairScans[0]) |
---|
490 | sel.set_types(types[i]) |
---|
491 | try: |
---|
492 | ss.set_selection(sel) |
---|
493 | except: |
---|
494 | continue |
---|
495 | ll.append(numpy.array(ss._getspectrum(0))) |
---|
496 | sel.reset() |
---|
497 | ss.set_selection() |
---|
498 | sel.set_ifs(ifnos[j]) |
---|
499 | sel.set_polarizations(polnos[k]) |
---|
500 | sel.set_scans(pairScans[1]) |
---|
501 | sel.set_types(types[i]) |
---|
502 | try: |
---|
503 | ss.set_selection(sel) |
---|
504 | except: |
---|
505 | ll.pop() |
---|
506 | continue |
---|
507 | ll2.append(numpy.array(ss._getspectrum(0))) |
---|
508 | sel.reset() |
---|
509 | ss.set_selection() |
---|
510 | key='%s%s' %(pairScans[0],keys[i]) |
---|
511 | precal[key]=ll |
---|
512 | key='%s%s' %(pairScans[1],keys[i]) |
---|
513 | precal[key]=ll2 |
---|
514 | #del ss |
---|
515 | keys=precal.keys() |
---|
516 | for j in range(len(ifnos)): |
---|
517 | for k in range(len(polnos)): |
---|
518 | sel.set_ifs(ifnos[j]) |
---|
519 | sel.set_polarizations(polnos[k]) |
---|
520 | sel.set_scans(pairScans[0]) |
---|
521 | try: |
---|
522 | resspec.set_selection(sel) |
---|
523 | except: |
---|
524 | continue |
---|
525 | postcal.append(numpy.array(resspec._getspectrum(0))) |
---|
526 | sel.reset() |
---|
527 | resspec.set_selection() |
---|
528 | del sel |
---|
529 | # plot |
---|
530 | asaplog.post() |
---|
531 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.') |
---|
532 | asaplog.post('WARN') |
---|
533 | p=new_asaplot() |
---|
534 | rcp('lines', linewidth=1) |
---|
535 | #nr=min(6,len(ifnos)*len(polnos)) |
---|
536 | nr=len(ifnos)*len(polnos) |
---|
537 | titles=[] |
---|
538 | btics=[] |
---|
539 | if nr<4: |
---|
540 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False) |
---|
541 | for i in range(2*nr): |
---|
542 | b=False |
---|
543 | if i >= 2*nr-2: |
---|
544 | b=True |
---|
545 | btics.append(b) |
---|
546 | elif nr==4: |
---|
547 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False) |
---|
548 | for i in range(2*nr): |
---|
549 | b=False |
---|
550 | if i >= 2*nr-4: |
---|
551 | b=True |
---|
552 | btics.append(b) |
---|
553 | elif nr<7: |
---|
554 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
---|
555 | for i in range(2*nr): |
---|
556 | if i >= 2*nr-4: |
---|
557 | b=True |
---|
558 | btics.append(b) |
---|
559 | else: |
---|
560 | asaplog.post() |
---|
561 | asaplog.push('Only first 6 [if,pol] pairs are plotted.') |
---|
562 | asaplog.post('WARN') |
---|
563 | nr=6 |
---|
564 | for i in range(2*nr): |
---|
565 | b=False |
---|
566 | if i >= 2*nr-4: |
---|
567 | b=True |
---|
568 | btics.append(b) |
---|
569 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
---|
570 | for i in range(nr): |
---|
571 | p.subplot(2*i) |
---|
572 | p.color=0 |
---|
573 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
574 | titles.append(title) |
---|
575 | #p.set_axes('title',title,fontsize=40) |
---|
576 | ymin=1.0e100 |
---|
577 | ymax=-1.0e100 |
---|
578 | nchan=scantab.nchan(ifnos[int(i/len(polnos))]) |
---|
579 | edge=int(nchan*0.01) |
---|
580 | for j in range(4): |
---|
581 | spmin=min(precal[keys[j]][i][edge:nchan-edge]) |
---|
582 | spmax=max(precal[keys[j]][i][edge:nchan-edge]) |
---|
583 | ymin=min(ymin,spmin) |
---|
584 | ymax=max(ymax,spmax) |
---|
585 | for j in range(4): |
---|
586 | if i==0: |
---|
587 | p.set_line(label=keys[j]) |
---|
588 | else: |
---|
589 | p.legend() |
---|
590 | p.plot(precal[keys[j]][i]) |
---|
591 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
592 | if not btics[2*i]: |
---|
593 | p.axes.set_xticks([]) |
---|
594 | p.subplot(2*i+1) |
---|
595 | p.color=0 |
---|
596 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
597 | titles.append(title) |
---|
598 | #p.set_axes('title',title) |
---|
599 | p.legend() |
---|
600 | ymin=postcal[i][edge:nchan-edge].min() |
---|
601 | ymax=postcal[i][edge:nchan-edge].max() |
---|
602 | p.plot(postcal[i]) |
---|
603 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
604 | if not btics[2*i+1]: |
---|
605 | p.axes.set_xticks([]) |
---|
606 | for i in range(2*nr): |
---|
607 | p.subplot(i) |
---|
608 | p.set_axes('title',titles[i],fontsize='medium') |
---|
609 | x=raw_input('Accept calibration ([y]/n): ' ) |
---|
610 | if x.upper() == 'N': |
---|
611 | p.quit() |
---|
612 | del p |
---|
613 | return scabtab |
---|
614 | p.quit() |
---|
615 | del p |
---|
616 | ### |
---|
617 | resspec._add_history("calnod",varlist) |
---|
618 | return resspec |
---|
619 | |
---|
620 | @asaplog_post_dec |
---|
621 | def calfs(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False): |
---|
622 | """ |
---|
623 | Calibrate GBT frequency switched data. |
---|
624 | Adopted from GBTIDL getfs. |
---|
625 | Currently calfs identify the scans as frequency switched data if source |
---|
626 | type enum is fson and fsoff. The data must contains 'CAL' signal |
---|
627 | on/off in each integration. To identify 'CAL' on state, the source type |
---|
628 | enum of foncal and foffcal need to be present. |
---|
629 | |
---|
630 | Parameters: |
---|
631 | scantab: scantable |
---|
632 | scannos: list of scan numbers |
---|
633 | smooth: optional box smoothing order for the reference |
---|
634 | (default is 1 = no smoothing) |
---|
635 | tsysval: optional user specified Tsys (default is 0.0, |
---|
636 | use Tsys in the data) |
---|
637 | tauval: optional user specified Tau |
---|
638 | verify: Verify calibration if true |
---|
639 | """ |
---|
640 | varlist = vars() |
---|
641 | from asap._asap import stmath |
---|
642 | from asap._asap import srctype |
---|
643 | stm = stmath() |
---|
644 | stm._setinsitu(False) |
---|
645 | |
---|
646 | # check = scantab.get_scan('*_fs*') |
---|
647 | # if check is None: |
---|
648 | # msg = "The input data appear to contain no Nod observing mode data." |
---|
649 | # raise TypeError(msg) |
---|
650 | s = scantab.get_scan(scannos) |
---|
651 | del scantab |
---|
652 | |
---|
653 | resspec = scantable(stm._dofs(s, scannos, smooth, tsysval,tauval,tcalval)) |
---|
654 | ### |
---|
655 | if verify: |
---|
656 | # get data |
---|
657 | ssub = s.get_scan(scannos) |
---|
658 | #ssubon = ssub.get_scan('*calon') |
---|
659 | #ssuboff = ssub.get_scan('*[^calon]') |
---|
660 | sel = selector() |
---|
661 | sel.set_types( [srctype.foncal,srctype.foffcal] ) |
---|
662 | ssub.set_selection( sel ) |
---|
663 | ssubon = ssub.copy() |
---|
664 | ssub.set_selection() |
---|
665 | sel.reset() |
---|
666 | sel.set_types( [srctype.fson,srctype.fsoff] ) |
---|
667 | ssub.set_selection( sel ) |
---|
668 | ssuboff = ssub.copy() |
---|
669 | ssub.set_selection() |
---|
670 | sel.reset() |
---|
671 | import numpy |
---|
672 | precal={} |
---|
673 | postcal=[] |
---|
674 | keys=['fs','fs_calon','fsr','fsr_calon'] |
---|
675 | types=[srctype.fson,srctype.foncal,srctype.fsoff,srctype.foffcal] |
---|
676 | ifnos=list(ssub.getifnos()) |
---|
677 | polnos=list(ssub.getpolnos()) |
---|
678 | for i in range(2): |
---|
679 | #ss=ssuboff.get_scan('*'+keys[2*i]) |
---|
680 | ll=[] |
---|
681 | for j in range(len(ifnos)): |
---|
682 | for k in range(len(polnos)): |
---|
683 | sel.set_ifs(ifnos[j]) |
---|
684 | sel.set_polarizations(polnos[k]) |
---|
685 | sel.set_types(types[2*i]) |
---|
686 | try: |
---|
687 | #ss.set_selection(sel) |
---|
688 | ssuboff.set_selection(sel) |
---|
689 | except: |
---|
690 | continue |
---|
691 | ll.append(numpy.array(ss._getspectrum(0))) |
---|
692 | sel.reset() |
---|
693 | #ss.set_selection() |
---|
694 | ssuboff.set_selection() |
---|
695 | precal[keys[2*i]]=ll |
---|
696 | #del ss |
---|
697 | #ss=ssubon.get_scan('*'+keys[2*i+1]) |
---|
698 | ll=[] |
---|
699 | for j in range(len(ifnos)): |
---|
700 | for k in range(len(polnos)): |
---|
701 | sel.set_ifs(ifnos[j]) |
---|
702 | sel.set_polarizations(polnos[k]) |
---|
703 | sel.set_types(types[2*i+1]) |
---|
704 | try: |
---|
705 | #ss.set_selection(sel) |
---|
706 | ssubon.set_selection(sel) |
---|
707 | except: |
---|
708 | continue |
---|
709 | ll.append(numpy.array(ss._getspectrum(0))) |
---|
710 | sel.reset() |
---|
711 | #ss.set_selection() |
---|
712 | ssubon.set_selection() |
---|
713 | precal[keys[2*i+1]]=ll |
---|
714 | #del ss |
---|
715 | #sig=resspec.get_scan('*_fs') |
---|
716 | #ref=resspec.get_scan('*_fsr') |
---|
717 | sel.set_types( srctype.fson ) |
---|
718 | resspec.set_selection( sel ) |
---|
719 | sig=resspec.copy() |
---|
720 | resspec.set_selection() |
---|
721 | sel.reset() |
---|
722 | sel.set_type( srctype.fsoff ) |
---|
723 | resspec.set_selection( sel ) |
---|
724 | ref=resspec.copy() |
---|
725 | resspec.set_selection() |
---|
726 | sel.reset() |
---|
727 | for k in range(len(polnos)): |
---|
728 | for j in range(len(ifnos)): |
---|
729 | sel.set_ifs(ifnos[j]) |
---|
730 | sel.set_polarizations(polnos[k]) |
---|
731 | try: |
---|
732 | sig.set_selection(sel) |
---|
733 | postcal.append(numpy.array(sig._getspectrum(0))) |
---|
734 | except: |
---|
735 | ref.set_selection(sel) |
---|
736 | postcal.append(numpy.array(ref._getspectrum(0))) |
---|
737 | sel.reset() |
---|
738 | resspec.set_selection() |
---|
739 | del sel |
---|
740 | # plot |
---|
741 | asaplog.post() |
---|
742 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.') |
---|
743 | asaplog.post('WARN') |
---|
744 | p=new_asaplot() |
---|
745 | rcp('lines', linewidth=1) |
---|
746 | #nr=min(6,len(ifnos)*len(polnos)) |
---|
747 | nr=len(ifnos)/2*len(polnos) |
---|
748 | titles=[] |
---|
749 | btics=[] |
---|
750 | if nr>3: |
---|
751 | asaplog.post() |
---|
752 | asaplog.push('Only first 3 [if,pol] pairs are plotted.') |
---|
753 | asaplog.post('WARN') |
---|
754 | nr=3 |
---|
755 | p.set_panels(rows=nr,cols=3,nplots=3*nr,ganged=False) |
---|
756 | for i in range(3*nr): |
---|
757 | b=False |
---|
758 | if i >= 3*nr-3: |
---|
759 | b=True |
---|
760 | btics.append(b) |
---|
761 | for i in range(nr): |
---|
762 | p.subplot(3*i) |
---|
763 | p.color=0 |
---|
764 | 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)]) |
---|
765 | titles.append(title) |
---|
766 | #p.set_axes('title',title,fontsize=40) |
---|
767 | ymin=1.0e100 |
---|
768 | ymax=-1.0e100 |
---|
769 | nchan=s.nchan(ifnos[2*int(i/len(polnos))]) |
---|
770 | edge=int(nchan*0.01) |
---|
771 | for j in range(4): |
---|
772 | spmin=min(precal[keys[j]][i][edge:nchan-edge]) |
---|
773 | spmax=max(precal[keys[j]][i][edge:nchan-edge]) |
---|
774 | ymin=min(ymin,spmin) |
---|
775 | ymax=max(ymax,spmax) |
---|
776 | for j in range(4): |
---|
777 | if i==0: |
---|
778 | p.set_line(label=keys[j]) |
---|
779 | else: |
---|
780 | p.legend() |
---|
781 | p.plot(precal[keys[j]][i]) |
---|
782 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
783 | if not btics[3*i]: |
---|
784 | p.axes.set_xticks([]) |
---|
785 | p.subplot(3*i+1) |
---|
786 | p.color=0 |
---|
787 | title='sig data IF%s POL%s' % (ifnos[2*int(i/len(polnos))],polnos[i%len(polnos)]) |
---|
788 | titles.append(title) |
---|
789 | #p.set_axes('title',title) |
---|
790 | p.legend() |
---|
791 | ymin=postcal[2*i][edge:nchan-edge].min() |
---|
792 | ymax=postcal[2*i][edge:nchan-edge].max() |
---|
793 | p.plot(postcal[2*i]) |
---|
794 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
795 | if not btics[3*i+1]: |
---|
796 | p.axes.set_xticks([]) |
---|
797 | p.subplot(3*i+2) |
---|
798 | p.color=0 |
---|
799 | title='ref data IF%s POL%s' % (ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)]) |
---|
800 | titles.append(title) |
---|
801 | #p.set_axes('title',title) |
---|
802 | p.legend() |
---|
803 | ymin=postcal[2*i+1][edge:nchan-edge].min() |
---|
804 | ymax=postcal[2*i+1][edge:nchan-edge].max() |
---|
805 | p.plot(postcal[2*i+1]) |
---|
806 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
---|
807 | if not btics[3*i+2]: |
---|
808 | p.axes.set_xticks([]) |
---|
809 | for i in range(3*nr): |
---|
810 | p.subplot(i) |
---|
811 | p.set_axes('title',titles[i],fontsize='medium') |
---|
812 | x=raw_input('Accept calibration ([y]/n): ' ) |
---|
813 | if x.upper() == 'N': |
---|
814 | p.quit() |
---|
815 | del p |
---|
816 | return scabtab |
---|
817 | p.quit() |
---|
818 | del p |
---|
819 | ### |
---|
820 | resspec._add_history("calfs",varlist) |
---|
821 | return resspec |
---|
822 | |
---|
823 | @asaplog_post_dec |
---|
824 | def merge(*args): |
---|
825 | """ |
---|
826 | Merge a list of scanatables, or comma-sperated scantables into one |
---|
827 | scnatble. |
---|
828 | Parameters: |
---|
829 | A list [scan1, scan2] or scan1, scan2. |
---|
830 | Example: |
---|
831 | myscans = [scan1, scan2] |
---|
832 | allscans = merge(myscans) |
---|
833 | # or equivalent |
---|
834 | sameallscans = merge(scan1, scan2) |
---|
835 | """ |
---|
836 | varlist = vars() |
---|
837 | if isinstance(args[0],list): |
---|
838 | lst = tuple(args[0]) |
---|
839 | elif isinstance(args[0],tuple): |
---|
840 | lst = args[0] |
---|
841 | else: |
---|
842 | lst = tuple(args) |
---|
843 | varlist["args"] = "%d scantables" % len(lst) |
---|
844 | # need special formatting her for history... |
---|
845 | from asap._asap import stmath |
---|
846 | stm = stmath() |
---|
847 | for s in lst: |
---|
848 | if not isinstance(s,scantable): |
---|
849 | msg = "Please give a list of scantables" |
---|
850 | raise TypeError(msg) |
---|
851 | s = scantable(stm._merge(lst)) |
---|
852 | s._add_history("merge", varlist) |
---|
853 | return s |
---|
854 | |
---|
855 | @asaplog_post_dec |
---|
856 | def calibrate( scantab, scannos=[], calmode='none', verify=None ): |
---|
857 | """ |
---|
858 | Calibrate data. |
---|
859 | |
---|
860 | Parameters: |
---|
861 | scantab: scantable |
---|
862 | scannos: list of scan number |
---|
863 | calmode: calibration mode |
---|
864 | verify: verify calibration |
---|
865 | """ |
---|
866 | import re |
---|
867 | antname = scantab.get_antennaname() |
---|
868 | if ( calmode == 'nod' ): |
---|
869 | asaplog.push( 'Calibrating nod data.' ) |
---|
870 | scal = calnod( scantab, scannos=scannos, verify=verify ) |
---|
871 | elif ( calmode == 'quotient' ): |
---|
872 | asaplog.push( 'Calibrating using quotient.' ) |
---|
873 | scal = scantab.auto_quotient( verify=verify ) |
---|
874 | elif ( calmode == 'ps' ): |
---|
875 | asaplog.push( 'Calibrating %s position-switched data.' % antname ) |
---|
876 | if ( antname.find( 'APEX' ) != -1 ): |
---|
877 | scal = apexcal( scantab, scannos, calmode, verify ) |
---|
878 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 |
---|
879 | or re.match('DV[0-9][0-9]$',antname) is not None |
---|
880 | or re.match('PM[0-9][0-9]$',antname) is not None |
---|
881 | or re.match('CM[0-9][0-9]$',antname) is not None |
---|
882 | or re.match('DA[0-9][0-9]$',antname) is not None ): |
---|
883 | scal = almacal( scantab, scannos, calmode, verify ) |
---|
884 | else: |
---|
885 | scal = calps( scantab, scannos=scannos, verify=verify ) |
---|
886 | elif ( calmode == 'fs' or calmode == 'fsotf' ): |
---|
887 | asaplog.push( 'Calibrating %s frequency-switched data.' % antname ) |
---|
888 | if ( antname.find( 'APEX' ) != -1 ): |
---|
889 | scal = apexcal( scantab, scannos, calmode, verify ) |
---|
890 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 ): |
---|
891 | scal = almacal( scantab, scannos, calmode, verify ) |
---|
892 | else: |
---|
893 | scal = calfs( scantab, scannos=scannos, verify=verify ) |
---|
894 | elif ( calmode == 'otf' ): |
---|
895 | asaplog.push( 'Calibrating %s On-The-Fly data.' % antname ) |
---|
896 | scal = almacal( scantab, scannos, calmode, verify ) |
---|
897 | else: |
---|
898 | asaplog.push( 'No calibration.' ) |
---|
899 | scal = scantab.copy() |
---|
900 | |
---|
901 | return scal |
---|
902 | |
---|
903 | def apexcal( scantab, scannos=[], calmode='none', verify=False ): |
---|
904 | """ |
---|
905 | Calibrate APEX data |
---|
906 | |
---|
907 | Parameters: |
---|
908 | scantab: scantable |
---|
909 | scannos: list of scan number |
---|
910 | calmode: calibration mode |
---|
911 | |
---|
912 | verify: verify calibration |
---|
913 | """ |
---|
914 | from asap._asap import stmath |
---|
915 | stm = stmath() |
---|
916 | antname = scantab.get_antennaname() |
---|
917 | selection=selector() |
---|
918 | selection.set_scans(scannos) |
---|
919 | orig = scantab.get_selection() |
---|
920 | scantab.set_selection(orig+selection) |
---|
921 | ## ssub = scantab.get_scan( scannos ) |
---|
922 | ## scal = scantable( stm.cwcal( ssub, calmode, antname ) ) |
---|
923 | scal = scantable( stm.cwcal( scantab, calmode, antname ) ) |
---|
924 | scantab.set_selection(orig) |
---|
925 | return scal |
---|
926 | |
---|
927 | def almacal( scantab, scannos=[], calmode='none', verify=False ): |
---|
928 | """ |
---|
929 | Calibrate ALMA data |
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930 | |
---|
931 | Parameters: |
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932 | scantab: scantable |
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933 | scannos: list of scan number |
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934 | calmode: calibration mode |
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935 | |
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936 | verify: verify calibration |
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937 | """ |
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938 | from asap._asap import stmath |
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939 | stm = stmath() |
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940 | selection=selector() |
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941 | selection.set_scans(scannos) |
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942 | orig = scantab.get_selection() |
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943 | scantab.set_selection(orig+selection) |
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944 | ## ssub = scantab.get_scan( scannos ) |
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945 | ## scal = scantable( stm.almacal( ssub, calmode ) ) |
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946 | scal = scantable( stm.almacal( scantab, calmode ) ) |
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947 | scantab.set_selection(orig) |
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948 | return scal |
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949 | |
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950 | @asaplog_post_dec |
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951 | def splitant(filename, outprefix='',overwrite=False): |
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952 | """ |
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953 | Split Measurement set by antenna name, save data as a scantables, |
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954 | and return a list of filename. |
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955 | Notice this method can only be available from CASA. |
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956 | Prameter |
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957 | filename: the name of Measurement set to be read. |
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958 | outprefix: the prefix of output scantable name. |
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959 | the names of output scantable will be |
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960 | outprefix.antenna1, outprefix.antenna2, .... |
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961 | If not specified, outprefix = filename is assumed. |
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962 | overwrite If the file should be overwritten if it exists. |
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963 | The default False is to return with warning |
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964 | without writing the output. USE WITH CARE. |
---|
965 | |
---|
966 | """ |
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967 | # Import the table toolkit from CASA |
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968 | from casac import casac |
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969 | from asap.scantable import is_ms |
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970 | tb = casac.table() |
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971 | # Check the input filename |
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972 | if isinstance(filename, str): |
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973 | import os.path |
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974 | filename = os.path.expandvars(filename) |
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975 | filename = os.path.expanduser(filename) |
---|
976 | if not os.path.exists(filename): |
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977 | s = "File '%s' not found." % (filename) |
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978 | raise IOError(s) |
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979 | # check if input file is MS |
---|
980 | #if not os.path.isdir(filename) \ |
---|
981 | # or not os.path.exists(filename+'/ANTENNA') \ |
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982 | # or not os.path.exists(filename+'/table.f1'): |
---|
983 | if not is_ms(filename): |
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984 | s = "File '%s' is not a Measurement set." % (filename) |
---|
985 | raise IOError(s) |
---|
986 | else: |
---|
987 | s = "The filename should be string. " |
---|
988 | raise TypeError(s) |
---|
989 | # Check out put file name |
---|
990 | outname='' |
---|
991 | if len(outprefix) > 0: prefix=outprefix+'.' |
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992 | else: |
---|
993 | prefix=filename.rstrip('/') |
---|
994 | # Now do the actual splitting. |
---|
995 | outfiles=[] |
---|
996 | tb.open(tablename=filename,nomodify=True) |
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997 | ant1=tb.getcol('ANTENNA1',0,-1,1) |
---|
998 | #anttab=tb.getkeyword('ANTENNA').split()[-1] |
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999 | anttab=tb.getkeyword('ANTENNA').lstrip('Table: ') |
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1000 | tb.close() |
---|
1001 | #tb.open(tablename=filename+'/ANTENNA',nomodify=True) |
---|
1002 | tb.open(tablename=anttab,nomodify=True) |
---|
1003 | nant=tb.nrows() |
---|
1004 | antnames=tb.getcol('NAME',0,nant,1) |
---|
1005 | tb.close() |
---|
1006 | tmpname='asapmath.splitant.tmp' |
---|
1007 | for antid in set(ant1): |
---|
1008 | tb.open(tablename=filename,nomodify=True) |
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1009 | tbsel=tb.query('ANTENNA1 == %s && ANTENNA2 == %s'%(antid,antid),tmpname) |
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1010 | scan=scantable(tmpname,average=False,getpt=True,antenna=int(antid)) |
---|
1011 | outname=prefix+antnames[antid]+'.asap' |
---|
1012 | scan.save(outname,format='ASAP',overwrite=overwrite) |
---|
1013 | tbsel.close() |
---|
1014 | tb.close() |
---|
1015 | del tbsel |
---|
1016 | del scan |
---|
1017 | outfiles.append(outname) |
---|
1018 | os.system('rm -rf '+tmpname) |
---|
1019 | del tb |
---|
1020 | return outfiles |
---|
1021 | |
---|
1022 | @asaplog_post_dec |
---|
1023 | def _array2dOp( scan, value, mode="ADD", tsys=False, insitu=None): |
---|
1024 | """ |
---|
1025 | This function is workaround on the basic operation of scantable |
---|
1026 | with 2 dimensional float list. |
---|
1027 | |
---|
1028 | scan: scantable operand |
---|
1029 | value: float list operand |
---|
1030 | mode: operation mode (ADD, SUB, MUL, DIV) |
---|
1031 | tsys: if True, operate tsys as well |
---|
1032 | insitu: if False, a new scantable is returned. |
---|
1033 | Otherwise, the array operation is done in-sitsu. |
---|
1034 | """ |
---|
1035 | if insitu is None: insitu = rcParams['insitu'] |
---|
1036 | nrow = scan.nrow() |
---|
1037 | s = None |
---|
1038 | from asap._asap import stmath |
---|
1039 | stm = stmath() |
---|
1040 | stm._setinsitu(insitu) |
---|
1041 | if len( value ) == 1: |
---|
1042 | s = scantable( stm._arrayop( scan, value[0], mode, tsys ) ) |
---|
1043 | elif len( value ) != nrow: |
---|
1044 | raise ValueError( 'len(value) must be 1 or conform to scan.nrow()' ) |
---|
1045 | else: |
---|
1046 | from asap._asap import stmath |
---|
1047 | if not insitu: |
---|
1048 | s = scan.copy() |
---|
1049 | else: |
---|
1050 | s = scan |
---|
1051 | # insitu must be True as we go row by row on the same data |
---|
1052 | stm._setinsitu( True ) |
---|
1053 | basesel = s.get_selection() |
---|
1054 | # generate a new selector object based on basesel |
---|
1055 | sel = selector(basesel) |
---|
1056 | for irow in range( nrow ): |
---|
1057 | sel.set_rows( irow ) |
---|
1058 | s.set_selection( sel ) |
---|
1059 | if len( value[irow] ) == 1: |
---|
1060 | stm._unaryop( s, value[irow][0], mode, tsys ) |
---|
1061 | else: |
---|
1062 | #stm._arrayop( s, value[irow], mode, tsys, 'channel' ) |
---|
1063 | stm._arrayop( s, value[irow], mode, tsys ) |
---|
1064 | s.set_selection(basesel) |
---|
1065 | return s |
---|