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3 | <title>Mopra 2005 Workshop - Data reduction tutorial worksheet</title> |
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27 | </head> |
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28 | <body> |
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29 | <div> |
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30 | <h1 class=custom> |
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31 | Introduction |
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32 | </h1> |
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33 | <div class=main align=center> |
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34 | This is a short tutorial on how to use ASAP for simple on of dual IF |
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35 | observations. It is highly customisable via ".aipsrc" parameters. It |
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36 | can read rpfits,sdfits and measurement sets, and export to sdfits, ms, |
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37 | ASCII and image fits. ASAP provides a lot more functionality, such as |
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38 | frequency alignment, averaging which can't be presented here. |
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39 | </div> |
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40 | <h1 class=custom> |
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41 | Part I - Reduction |
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42 | </h1> |
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43 | <div class=main align=center> |
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44 | To start ASAP type the follwing at the *nix command line prompt |
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45 | <div class=shell> |
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46 | <pre> |
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47 | localhost> asap |
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48 | </pre> |
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49 | </div> |
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50 | To get the list of available commands in asap type: |
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51 | <div class=code><pre> |
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52 | commands() |
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53 | </pre></div> |
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54 | Help can be accessed by using <em>help</em>: |
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55 | <div class=code><pre> |
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56 | help(scantable) |
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57 | help(scantable.summary) |
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58 | </pre></div> |
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59 | To start we are reading in the data into a scantable, which can be accessed via th variable <em>s</em>. After reading in we have a look at the data. |
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60 | <div class=code><pre> |
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61 | s = scantable("2005-05-08_0350.rpf") |
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62 | s.summary() |
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63 | </pre></div> |
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64 | We can plot the scan now. First we set up the plotter to plot "IF" as stcked colours and "time" across panels. Then we issue th plot command. |
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65 | <div class=code><pre> |
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66 | plotter.set_mode("IF","time") |
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67 | plotter.plot(s) # plot s |
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68 | </pre></div> |
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69 | Now we can build the quotient. This applies the quotient to both IFs. |
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70 | <div class=code><pre> |
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71 | q = auto_quotient() |
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72 | plotter.plot(q) # plot q |
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73 | </pre></div> |
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74 | Now we can set some information anbout the velocity setup. We set the rest frequencies for 13Co and SiO and want to operate in "LSRK". |
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75 | <div class=code><pre> |
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76 | restfreqs = [110.201,86.243] # 13CO-1/0, SiO the two IF |
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77 | q.set_restfreqs(restfreqs,"GHz") # set the restfrequencies, as not in data |
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78 | q.set_unit("km/s") # set the unit to be used from now on |
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79 | q.set_freqframe("LSRK") # set frequency frame |
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80 | plotter.plot() # replot, should show velocity now |
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81 | </pre></div> |
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82 | Now we can subtract a baseline. ASAP can do this automatically if ther is good S/N and the lines aren't too broad. |
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83 | <div class=code><pre> |
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84 | q.auto_poly_baseline() # determine and subtract a poly baseline automatically |
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85 | plotter.plot() # replot |
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86 | </pre></div> |
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87 | We can zoom in on the spectrum and format the title and legend. ASAP accepts LATEX math expressions. |
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88 | <div class=code><pre> |
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89 | plotter.set_range(-35,35) # zoom in bit |
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90 | plotter.set_legend([r"$^{13}CO(1\leftarrow 0)$",r"$SiO$"]) # make nice latex IF labels |
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91 | plotter.set_title(['Mopra Tutorial 2005']) # set the title |
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92 | </pre></div> |
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93 | Now convert Brightness temperature to Flux density. |
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94 | <div class=code><pre> |
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95 | q.convert_flux() # K -> Jy |
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96 | plotter.plot() |
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97 | </pre></div> |
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98 | This "final" plot can be saved now as "png", "ps" or "eps" |
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99 | <div class=code><pre> |
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100 | plotter.save("tutorial.png") |
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101 | plotter.save("tutorial.eps") |
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102 | </pre></div> |
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103 | We can also do some stats on the spectra. We select a line free region first, which get applied to the statistics. |
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104 | <div class=code><pre> |
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105 | msk = q.create_mask([-70,20], [20,70]) # line free region - two windows |
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106 | rms = q.stats("rms",msk) |
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107 | med = q.stats("median",msk) |
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108 | </pre></div> |
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109 | </div> |
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110 | <h1 class=custom> |
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111 | Part II - Fitting |
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112 | </h1> |
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113 | <div class=main align=center> |
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114 | This part shows how easy it is to fit gaussian line profiles. |
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115 | <div class=code><pre> |
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116 | f = fitter() |
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117 | </pre></div> |
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118 | We start with the first spectrum (IF=0) bys setting the selection. We want to fit two gaussian components. |
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119 | <div class=code><pre> |
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120 | sel = selector() |
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121 | sel.set_ifs(0) |
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122 | q.set_selection(sel) |
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123 | f.set_scan(q) |
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124 | f.set_function(gauss=2) # fit two gaussians |
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125 | f.fit() |
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126 | f.plot( |
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127 | </pre></div> |
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128 | The second IFs spectrum is more complex. We select it and fit seven gaussians to it. Here we also plot residuals, the individual components and the fit parameters. |
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129 | <div class=code><pre> |
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130 | sel.set_ifs(1) |
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131 | q.set_selection(sel) |
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132 | f.set_function(gauss=7) |
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133 | f.fit() |
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134 | f.plot(residual=True) |
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135 | f.plot(components=[0,1,2,3,4,5,6,-1]) |
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136 | f.plot(components=[0,1,2,3,4,5,6,-1],plotparms=True) |
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137 | </pre></div> |
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138 | </div> |
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139 | <h1 class=custom> |
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140 | Appendix |
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141 | </h1> |
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142 | <div class=main align=center> |
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143 | More info can be found on the ASAP homepage |
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144 | <a href="http://www.atnf.csiro.au/computing/software/asap"> |
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145 | http://www.atnf.csiro.au/computing/software/asap</a> |
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146 | </div> |
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147 | </body> |
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148 | </html> |
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