1 | from scantable import scantable |
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2 | |
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3 | def average_time(*args, **kwargs): |
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4 | """ |
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5 | Return the (time) average of a scan or list of scans. [in channels only] |
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6 | Parameters: |
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7 | one scan or comma separated scans |
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8 | mask: an optional mask (only used for 'var' and 'tsys' weighting) |
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9 | scanav: False (default) averages all scans together, |
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10 | True averages each scan separately |
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11 | weight: Weighting scheme. 'none' (default), 'var' (variance |
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12 | weighted), 'tsys' |
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13 | Example: |
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14 | # return a time averaged scan from scana and scanb |
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15 | # without using a mask |
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16 | scanav = average_time(scana,scanb) |
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17 | # return the (time) averaged scan, i.e. the average of |
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18 | # all correlator cycles |
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19 | scanav = average_time(scan) |
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20 | |
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21 | """ |
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22 | scanAv = False |
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23 | if kwargs.has_key('scanav'): |
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24 | scanAv = kwargs.get('scanav') |
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25 | # |
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26 | weight = 'none' |
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27 | if kwargs.has_key('weight'): |
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28 | weight = kwargs.get('weight') |
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29 | # |
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30 | mask = () |
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31 | if kwargs.has_key('mask'): |
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32 | mask = kwargs.get('mask') |
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33 | # |
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34 | lst = tuple(args) |
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35 | from asap._asap import average as _av |
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36 | for s in lst: |
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37 | if not isinstance(s,scantable): |
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38 | print "Please give a list of scantables" |
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39 | return |
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40 | return scantable(_av(lst, mask, scanAv, weight)) |
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41 | |
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42 | def quotient(source, reference): |
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43 | """ |
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44 | Return the quotient of a 'source' scan and a 'reference' scan |
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45 | Parameters: |
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46 | source: the 'on' scan |
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47 | reference: the 'off' scan |
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48 | """ |
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49 | from asap._asap import quotient as _quot |
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50 | return scantable(_quot(source, reference)) |
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51 | |
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52 | def scale(scan, factor, insitu=False, all=True): |
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53 | """ |
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54 | Return a scan where all spectra are scaled by the give 'factor' |
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55 | Parameters: |
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56 | scan: a scantable |
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57 | factor: the scaling factor |
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58 | insitu: if False (default) a new scantable is returned. |
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59 | Otherwise, the scaling is done in-situ |
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60 | all: if True (default) apply to all spectra. Otherwise |
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61 | apply only to the selected (beam/pol/if)spectra only |
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62 | """ |
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63 | if not insitu: |
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64 | from asap._asap import scale as _scale |
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65 | return scantable(_scale(scan, factor, all)) |
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66 | else: |
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67 | from asap._asap import scale_insitu as _scale |
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68 | _scale(scan, factor, all) |
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69 | return |
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70 | |
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71 | |
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72 | def add(scan, offset, insitu=False, all=True): |
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73 | """ |
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74 | Return a scan where all spectra have the offset added |
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75 | Parameters: |
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76 | scan: a scantable |
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77 | offset: the offset |
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78 | insitu: if False (default) a new scantable is returned. |
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79 | Otherwise, the addition is done in-situ |
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80 | all: if True (default) apply to all spectra. Otherwise |
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81 | apply only to the selected (beam/pol/if)spectra only |
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82 | """ |
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83 | if not insitu: |
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84 | from asap._asap import add as _add |
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85 | return scantable(_add(scan, offset, all)) |
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86 | else: |
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87 | from asap._asap import add_insitu as _add |
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88 | _add(scan, offset, all) |
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89 | return |
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90 | |
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91 | def bin(scan, width=5, insitu=False): |
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92 | """ |
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93 | Return a scan where all spectra have been binned up |
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94 | width: The bin width (default=5) in pixels |
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95 | insitu: if False (default) a new scantable is returned. |
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96 | Otherwise, the addition is done in-situ |
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97 | """ |
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98 | if not insitu: |
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99 | from asap._asap import bin as _bin |
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100 | return scantable(_bin(scan, width)) |
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101 | else: |
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102 | from asap._asap import bin_insitu as _bin |
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103 | _bin(scan, width) |
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104 | return |
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105 | |
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106 | def average_pol(scan, mask=None, insitu=False): |
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107 | """ |
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108 | Average the Polarisations together. |
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109 | Parameters: |
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110 | scan: The scantable |
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111 | mask: An optional mask defining the region, where the |
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112 | averaging will be applied. The output will have all |
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113 | specified points masked. |
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114 | insitu: If False (default) a new scantable is returned. |
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115 | Otherwise, the averaging is done in-situ |
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116 | Example: |
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117 | polav = average_pols(myscan) |
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118 | """ |
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119 | if mask is None: |
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120 | mask = () |
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121 | if not insitu: |
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122 | from asap._asap import averagepol as _avpol |
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123 | return scantable(_avpol(scan, mask)) |
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124 | else: |
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125 | from asap._asap import averagepol_insitu as _avpol |
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126 | _avpol(scan, mask) |
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127 | return |
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128 | |
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129 | def smooth(scan, kernel="hanning", width=5.0, insitu=False, all=True): |
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130 | """ |
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131 | Smooth the spectrum by the specified kernel (conserving flux). |
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132 | Parameters: |
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133 | scan: The input scan |
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134 | kernel: The type of smoothing kernel. Select from |
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135 | 'hanning' (default), 'gaussian' and 'boxcar'. |
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136 | The first three characters are sufficient. |
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137 | width: The width of the kernel in pixels. For hanning this is |
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138 | ignored otherwise it defauls to 5 pixels. |
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139 | For 'gaussian' it is the Full Width Half |
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140 | Maximum. For 'boxcar' it is the full width. |
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141 | insitu: If False (default) a new scantable is returned. |
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142 | Otherwise, the scaling is done in-situ |
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143 | all: If True (default) apply to all spectra. Otherwise |
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144 | apply only to the selected (beam/pol/if)spectra only |
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145 | Example: |
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146 | none |
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147 | """ |
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148 | if not insitu: |
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149 | from asap._asap import smooth as _smooth |
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150 | return scantable(_smooth(scan,kernel,width,all)) |
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151 | else: |
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152 | from asap._asap import smooth_insitu as _smooth |
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153 | _smooth(scan,kernel,width,all) |
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154 | return |
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155 | |
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156 | def poly_baseline(scan, mask=None, order=0): |
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157 | """ |
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158 | Return a scan which has been baselined (all rows) by a polynomial. |
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159 | Parameters: |
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160 | scan: a scantable |
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161 | mask: an optional mask |
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162 | order: the order of the polynomial (default is 0) |
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163 | Example: |
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164 | # return a scan baselined by a third order polynomial, |
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165 | # not using a mask |
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166 | bscan = poly_baseline(scan, order=3) |
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167 | """ |
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168 | from asap.asapfitter import fitter |
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169 | if mask is None: |
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170 | from numarray import ones |
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171 | mask = tuple(ones(scan.nchan())) |
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172 | f = fitter() |
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173 | f._verbose(True) |
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174 | f.set_scan(scan, mask) |
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175 | f.set_function(poly=order) |
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176 | sf = f.auto_fit() |
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177 | return sf |
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