| 1 | from asap import rcParams, print_log, selector
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| 2 | from numarray import logical_and
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| 3 |
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| 4 | class asapplotter:
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| 5 | """
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| 6 | The ASAP plotter.
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| 7 | By default the plotter is set up to plot polarisations
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| 8 | 'colour stacked' and scantables across panels.
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| 9 | Note:
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| 10 | Currenly it only plots 'spectra' not Tsys or
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| 11 | other variables.
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| 12 | """
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| 13 | def __init__(self, visible=None):
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| 14 | self._visible = rcParams['plotter.gui']
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| 15 | if visible is not None:
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| 16 | self._visible = visible
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| 17 | self._plotter = self._newplotter()
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| 18 |
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| 19 |
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| 20 | self._panelling = None
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| 21 | self._stacking = None
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| 22 | self.set_panelling()
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| 23 | self.set_stacking()
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| 24 | self._rows = None
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| 25 | self._cols = None
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| 26 | self._autoplot = False
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| 27 | self._minmaxx = None
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| 28 | self._minmaxy = None
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| 29 | self._datamask = None
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| 30 | self._data = None
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| 31 | self._lmap = None
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| 32 | self._title = None
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| 33 | self._ordinate = None
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| 34 | self._abcissa = None
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| 35 | self._abcunit = None
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| 36 | self._usermask = []
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| 37 | self._maskselection = None
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| 38 | self._selection = selector()
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| 39 | self._hist = rcParams['plotter.histogram']
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| 40 | from matplotlib import rc as mplrc
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| 41 | mplrc('legend',fontsize=8)
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| 42 |
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| 43 | def _translate(self, instr):
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| 44 | keys = "s b i p t".split()
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| 45 | if isinstance(instr, str):
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| 46 | for key in keys:
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| 47 | if instr.lower().startswith(key):
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| 48 | return key
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| 49 | return None
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| 50 |
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| 51 | def _newplotter(self):
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| 52 | if self._visible:
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| 53 | from asap.asaplotgui import asaplotgui as asaplot
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| 54 | else:
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| 55 | from asap.asaplot import asaplot
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| 56 | return asaplot()
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| 57 |
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| 58 |
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| 59 | def plot(self, scan=None):
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| 60 | """
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| 61 | Plot a scantable.
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| 62 | Parameters:
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| 63 | scan: a scantable
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| 64 | Note:
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| 65 | If a scantable was specified in a previous call
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| 66 | to plot, no argument has to be given to 'replot'
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| 67 | NO checking is done that the abcissas of the scantable
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| 68 | are consistent e.g. all 'channel' or all 'velocity' etc.
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| 69 | """
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| 70 | if self._plotter.is_dead:
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| 71 | self._plotter = self._newplotter()
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| 72 | self._plotter.hold()
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| 73 | self._plotter.clear()
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| 74 | from asap import scantable
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| 75 | if not self._data and not scan:
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| 76 | msg = "Input is not a scantable"
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| 77 | if rcParams['verbose']:
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| 78 | print msg
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| 79 | return
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| 80 | raise TypeError(msg)
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| 81 | if isinstance(scan, scantable):
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| 82 | if self._data is not None:
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| 83 | if scan != self._data:
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| 84 | self._data = scan
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| 85 | # reset
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| 86 | self._reset()
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| 87 | else:
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| 88 | self._data = scan
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| 89 | self._reset()
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| 90 | # ranges become invalid when unit changes
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| 91 | if self._abcunit and self._abcunit != self._data.get_unit():
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| 92 | self._minmaxx = None
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| 93 | self._minmaxy = None
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| 94 | self._abcunit = self._data.get_unit()
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| 95 | self._datamask = None
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| 96 | self._plot(self._data)
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| 97 | if self._minmaxy is not None:
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| 98 | self._plotter.set_limits(ylim=self._minmaxy)
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| 99 | self._plotter.release()
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| 100 | print_log()
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| 101 | return
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| 102 |
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| 103 | def set_mode(self, stacking=None, panelling=None):
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| 104 | """
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| 105 | Set the plots look and feel, i.e. what you want to see on the plot.
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| 106 | Parameters:
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| 107 | stacking: tell the plotter which variable to plot
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| 108 | as line color overlays (default 'pol')
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| 109 | panelling: tell the plotter which variable to plot
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| 110 | across multiple panels (default 'scan'
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| 111 | Note:
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| 112 | Valid modes are:
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| 113 | 'beam' 'Beam' 'b': Beams
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| 114 | 'if' 'IF' 'i': IFs
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| 115 | 'pol' 'Pol' 'p': Polarisations
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| 116 | 'scan' 'Scan' 's': Scans
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| 117 | 'time' 'Time' 't': Times
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| 118 | """
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| 119 | msg = "Invalid mode"
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| 120 | if not self.set_panelling(panelling) or \
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| 121 | not self.set_stacking(stacking):
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| 122 | if rcParams['verbose']:
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| 123 | print msg
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| 124 | return
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| 125 | else:
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| 126 | raise TypeError(msg)
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| 127 | if self._data: self.plot(self._data)
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| 128 | return
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| 129 |
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| 130 | def set_panelling(self, what=None):
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| 131 | mode = what
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| 132 | if mode is None:
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| 133 | mode = rcParams['plotter.panelling']
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| 134 | md = self._translate(mode)
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| 135 | if md:
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| 136 | self._panelling = md
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| 137 | self._title = None
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| 138 | return True
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| 139 | return False
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| 140 |
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| 141 | def set_layout(self,rows=None,cols=None):
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| 142 | """
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| 143 | Set the multi-panel layout, i.e. how many rows and columns plots
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| 144 | are visible.
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| 145 | Parameters:
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| 146 | rows: The number of rows of plots
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| 147 | cols: The number of columns of plots
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| 148 | Note:
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| 149 | If no argument is given, the potter reverts to its auto-plot
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| 150 | behaviour.
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| 151 | """
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| 152 | self._rows = rows
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| 153 | self._cols = cols
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| 154 | if self._data: self.plot(self._data)
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| 155 | return
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| 156 |
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| 157 | def set_stacking(self, what=None):
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| 158 | mode = what
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| 159 | if mode is None:
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| 160 | mode = rcParams['plotter.stacking']
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| 161 | md = self._translate(mode)
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| 162 | if md:
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| 163 | self._stacking = md
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| 164 | self._lmap = None
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| 165 | return True
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| 166 | return False
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| 167 |
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| 168 | def set_range(self,xstart=None,xend=None,ystart=None,yend=None):
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| 169 | """
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| 170 | Set the range of interest on the abcissa of the plot
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| 171 | Parameters:
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| 172 | [x,y]start,[x,y]end: The start and end points of the 'zoom' window
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| 173 | Note:
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| 174 | These become non-sensical when the unit changes.
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| 175 | use plotter.set_range() without parameters to reset
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| 176 |
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| 177 | """
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| 178 | if xstart is None and xend is None:
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| 179 | self._minmaxx = None
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| 180 | else:
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| 181 | self._minmaxx = [xstart,xend]
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| 182 | if ystart is None and yend is None:
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| 183 | self._minmaxy = None
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| 184 | else:
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| 185 | self._minmaxy = [ystart,yend]
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| 186 | if self._data: self.plot(self._data)
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| 187 | return
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| 188 |
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| 189 | def set_legend(self, mp=None, fontsize = None, mode = 0):
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| 190 | """
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| 191 | Specify a mapping for the legend instead of using the default
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| 192 | indices:
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| 193 | Parameters:
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| 194 | mp: a list of 'strings'. This should have the same length
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| 195 | as the number of elements on the legend and then maps
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| 196 | to the indeces in order. It is possible to uses latex
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| 197 | math expression. These have to be enclosed in r'',
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| 198 | e.g. r'$x^{2}$'
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| 199 | fontsize: The font size of the label (default None)
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| 200 | mode: where to display the legend
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| 201 | Any other value for loc else disables the legend:
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| 202 | 0: auto
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| 203 | 1: upper right
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| 204 | 2: upper left
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| 205 | 3: lower left
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| 206 | 4: lower right
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| 207 | 5: right
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| 208 | 6: center left
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| 209 | 7: center right
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| 210 | 8: lower center
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| 211 | 9: upper center
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| 212 | 10: center
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| 213 |
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| 214 | Example:
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| 215 | If the data has two IFs/rest frequencies with index 0 and 1
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| 216 | for CO and SiO:
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| 217 | plotter.set_stacking('i')
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| 218 | plotter.set_legend(['CO','SiO'])
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| 219 | plotter.plot()
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| 220 | plotter.set_legend([r'$^{12}CO$', r'SiO'])
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| 221 | """
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| 222 | self._lmap = mp
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| 223 | self._plotter.legend(mode)
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| 224 | if isinstance(fontsize, int):
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| 225 | from matplotlib import rc as rcp
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| 226 | rcp('legend', fontsize=fontsize)
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| 227 | if self._data:
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| 228 | self.plot(self._data)
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| 229 | return
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| 230 |
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| 231 | def set_title(self, title=None, fontsize=None):
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| 232 | """
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| 233 | Set the title of the plot. If multiple panels are plotted,
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| 234 | multiple titles have to be specified.
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| 235 | Example:
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| 236 | # two panels are visible on the plotter
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| 237 | plotter.set_title(["First Panel","Second Panel"])
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| 238 | """
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| 239 | self._title = title
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| 240 | if isinstance(fontsize, int):
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| 241 | from matplotlib import rc as rcp
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| 242 | rcp('axes', titlesize=fontsize)
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| 243 | if self._data: self.plot(self._data)
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| 244 | return
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| 245 |
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| 246 | def set_ordinate(self, ordinate=None, fontsize=None):
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| 247 | """
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| 248 | Set the y-axis label of the plot. If multiple panels are plotted,
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| 249 | multiple labels have to be specified.
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| 250 | Parameters:
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| 251 | ordinate: a list of ordinate labels. None (default) let
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| 252 | data determine the labels
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| 253 | Example:
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| 254 | # two panels are visible on the plotter
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| 255 | plotter.set_ordinate(["First Y-Axis","Second Y-Axis"])
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| 256 | """
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| 257 | self._ordinate = ordinate
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| 258 | if isinstance(fontsize, int):
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| 259 | from matplotlib import rc as rcp
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| 260 | rcp('axes', labelsize=fontsize)
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| 261 | rcp('ytick', labelsize=fontsize)
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| 262 | if self._data: self.plot(self._data)
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| 263 | return
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| 264 |
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| 265 | def set_abcissa(self, abcissa=None, fontsize=None):
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| 266 | """
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| 267 | Set the x-axis label of the plot. If multiple panels are plotted,
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| 268 | multiple labels have to be specified.
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| 269 | Parameters:
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| 270 | abcissa: a list of abcissa labels. None (default) let
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| 271 | data determine the labels
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| 272 | Example:
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| 273 | # two panels are visible on the plotter
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| 274 | plotter.set_ordinate(["First X-Axis","Second X-Axis"])
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| 275 | """
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| 276 | self._abcissa = abcissa
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| 277 | if isinstance(fontsize, int):
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| 278 | from matplotlib import rc as rcp
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| 279 | rcp('axes', labelsize=fontsize)
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| 280 | rcp('xtick', labelsize=fontsize)
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| 281 | if self._data: self.plot(self._data)
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| 282 | return
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| 283 |
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| 284 | def set_colors(self, colormap):
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| 285 | """
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| 286 | Set the colors to be used. The plotter will cycle through
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| 287 | these colors when lines are overlaid (stacking mode).
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| 288 | Parameters:
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| 289 | colormap: a list of colour names
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| 290 | Example:
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| 291 | plotter.set_colors("red green blue")
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| 292 | # If for example four lines are overlaid e.g I Q U V
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| 293 | # 'I' will be 'red', 'Q' will be 'green', U will be 'blue'
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| 294 | # and 'V' will be 'red' again.
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| 295 | """
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| 296 | if isinstance(colormap,str):
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| 297 | colormap = colormap.split()
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| 298 | self._plotter.palette(0,colormap=colormap)
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| 299 | if self._data: self.plot(self._data)
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| 300 |
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| 301 | def set_histogram(self, hist=True, linewidth=None):
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| 302 | """
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| 303 | Enable/Disable histogram-like plotting.
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| 304 | Parameters:
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| 305 | hist: True (default) or False. The fisrt default
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| 306 | is taken from the .asaprc setting
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| 307 | plotter.histogram
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| 308 | """
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| 309 | self._hist = hist
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| 310 | if isinstance(linewidth, float) or isinstance(linewidth, int):
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| 311 | from matplotlib import rc as rcp
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| 312 | rcp('lines', linewidth=linewidth)
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| 313 | if self._data: self.plot(self._data)
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| 314 |
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| 315 | def set_linestyles(self, linestyles=None, linewidth=None):
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| 316 | """
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| 317 | Set the linestyles to be used. The plotter will cycle through
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| 318 | these linestyles when lines are overlaid (stacking mode) AND
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| 319 | only one color has been set.
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| 320 | Parameters:
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| 321 | linestyles: a list of linestyles to use.
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| 322 | 'line', 'dashed', 'dotted', 'dashdot',
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| 323 | 'dashdotdot' and 'dashdashdot' are
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| 324 | possible
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| 325 |
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| 326 | Example:
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| 327 | plotter.set_colors("black")
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| 328 | plotter.set_linestyles("line dashed dotted dashdot")
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| 329 | # If for example four lines are overlaid e.g I Q U V
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| 330 | # 'I' will be 'solid', 'Q' will be 'dashed',
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| 331 | # U will be 'dotted' and 'V' will be 'dashdot'.
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| 332 | """
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| 333 | if isinstance(linestyles,str):
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| 334 | linestyles = linestyles.split()
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| 335 | self._plotter.palette(color=0,linestyle=0,linestyles=linestyles)
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| 336 | if isinstance(linewidth, float) or isinstance(linewidth, int):
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| 337 | from matplotlib import rc as rcp
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| 338 | rcp('lines', linewidth=linewidth)
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| 339 | if self._data: self.plot(self._data)
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| 340 |
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| 341 | def set_font(self, family=None, style=None, weight=None, size=None):
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| 342 | """
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| 343 | Set font properties.
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| 344 | Parameters:
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| 345 | family: one of 'sans-serif', 'serif', 'cursive', 'fantasy', 'monospace'
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| 346 | style: one of 'normal' (or 'roman'), 'italic' or 'oblique'
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| 347 | weight: one of 'normal or 'bold'
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| 348 | size: the 'general' font size, individual elements can be adjusted
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| 349 | seperately
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| 350 | """
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| 351 | from matplotlib import rc as rcp
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| 352 | if isinstance(family, str):
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| 353 | rcp('font', family=family)
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| 354 | if isinstance(style, str):
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| 355 | rcp('font', style=style)
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| 356 | if isinstance(weight, str):
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| 357 | rcp('font', weight=weight)
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| 358 | if isinstance(size, float) or isinstance(size, int):
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| 359 | rcp('font', size=size)
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| 360 | if self._data: self.plot(self._data)
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| 361 |
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| 362 | def save(self, filename=None, orientation=None, dpi=None):
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| 363 | """
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| 364 | Save the plot to a file. The know formats are 'png', 'ps', 'eps'.
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| 365 | Parameters:
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| 366 | filename: The name of the output file. This is optional
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| 367 | and autodetects the image format from the file
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| 368 | suffix. If non filename is specified a file
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| 369 | called 'yyyymmdd_hhmmss.png' is created in the
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| 370 | current directory.
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| 371 | orientation: optional parameter for postscript only (not eps).
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| 372 | 'landscape', 'portrait' or None (default) are valid.
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| 373 | If None is choosen for 'ps' output, the plot is
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| 374 | automatically oriented to fill the page.
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| 375 | dpi: The dpi of the output non-ps plot
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| 376 | """
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| 377 | self._plotter.save(filename,orientation,dpi)
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| 378 | return
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| 379 |
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| 380 |
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| 381 | def set_mask(self, mask=None, selection=None):
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| 382 | """
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| 383 | Set a plotting mask for a specific polarization.
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| 384 | This is useful for masking out "noise" Pangle outside a source.
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| 385 | Parameters:
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| 386 | mask: a mask from scantable.create_mask
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| 387 | selection: the spectra to apply the mask to.
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| 388 | Example:
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| 389 | select = selector()
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| 390 | select.setpolstrings("Pangle")
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| 391 | plotter.set_mask(mymask, select)
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| 392 | """
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| 393 | if not self._data:
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| 394 | msg = "Can only set mask after a first call to plot()"
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| 395 | if rcParams['verbose']:
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| 396 | print msg
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| 397 | return
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| 398 | else:
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| 399 | raise RuntimeError(msg)
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| 400 | if len(mask):
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| 401 | if isinstance(mask, list) or isinstance(mask, tuple):
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| 402 | self._usermask = array(mask)
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| 403 | else:
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| 404 | self._usermask = mask
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| 405 | if mask is None and selection is None:
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| 406 | self._usermask = []
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| 407 | self._maskselection = None
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| 408 | if isinstance(selection, selector):
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| 409 | self._maskselection = {'b': selection.get_beams(),
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| 410 | 's': selection.get_scans(),
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| 411 | 'i': selection.get_ifs(),
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| 412 | 'p': selection.get_pols(),
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| 413 | 't': [] }
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| 414 | else:
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| 415 | self._maskselection = None
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| 416 | self.plot(self._data)
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| 417 |
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| 418 | def _slice_indeces(self, data):
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| 419 | mn = self._minmaxx[0]
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| 420 | mx = self._minmaxx[1]
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| 421 | asc = data[0] < data[-1]
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| 422 | start=0
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| 423 | end = len(data)-1
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| 424 | inc = 1
|
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| 425 | if not asc:
|
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| 426 | start = len(data)-1
|
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| 427 | end = 0
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| 428 | inc = -1
|
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| 429 | # find min index
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| 430 | while start > 0 and data[start] < mn:
|
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| 431 | start+= inc
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| 432 | # find max index
|
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| 433 | while end > 0 and data[end] > mx:
|
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| 434 | end-=inc
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| 435 | if end > 0: end +=1
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| 436 | if start > end:
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| 437 | return end,start
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| 438 | return start,end
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| 439 |
|
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| 440 | def _reset(self):
|
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| 441 | self._usermask = []
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| 442 | self._usermaskspectra = None
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| 443 | self.set_selection(None, False)
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| 444 |
|
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| 445 | def _plot(self, scan):
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| 446 | savesel = scan.get_selection()
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| 447 | sel = savesel + self._selection
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| 448 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
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| 449 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
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| 450 | order = [d0[self._panelling],d0[self._stacking]]
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| 451 | sel.set_order(order)
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| 452 | scan.set_selection(sel)
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| 453 | d = {'b': scan.getbeam, 's': scan.getscan,
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| 454 | 'i': scan.getif, 'p': scan.getpol, 't': scan._gettime }
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| 455 |
|
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| 456 | polmodes = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
|
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| 457 | n,nstack = self._get_selected_n(scan)
|
|---|
| 458 | maxpanel, maxstack = 16,8
|
|---|
| 459 | if n > maxpanel or nstack > maxstack:
|
|---|
| 460 | from asap import asaplog
|
|---|
| 461 | msg ="Scan to be plotted contains more than %d selections.\n" \
|
|---|
| 462 | "Selecting first %d selections..." % (maxpanel,maxpanel)
|
|---|
| 463 | asaplog.push(msg)
|
|---|
| 464 | print_log()
|
|---|
| 465 | n = min(n,maxpanel)
|
|---|
| 466 | nstack = min(nstack,maxstack)
|
|---|
| 467 |
|
|---|
| 468 | if n > 1:
|
|---|
| 469 | ganged = rcParams['plotter.ganged']
|
|---|
| 470 | if self._rows and self._cols:
|
|---|
| 471 | n = min(n,self._rows*self._cols)
|
|---|
| 472 | self._plotter.set_panels(rows=self._rows,cols=self._cols,
|
|---|
| 473 | nplots=n,ganged=ganged)
|
|---|
| 474 | else:
|
|---|
| 475 | self._plotter.set_panels(rows=n,cols=0,nplots=n,ganged=ganged)
|
|---|
| 476 | else:
|
|---|
| 477 | self._plotter.set_panels()
|
|---|
| 478 | r=0
|
|---|
| 479 | nr = scan.nrow()
|
|---|
| 480 | a0,b0 = -1,-1
|
|---|
| 481 | allxlim = []
|
|---|
| 482 | allylim = []
|
|---|
| 483 | newpanel=True
|
|---|
| 484 | panelcount,stackcount = 0,0
|
|---|
| 485 | while r < nr:
|
|---|
| 486 | a = d[self._panelling](r)
|
|---|
| 487 | b = d[self._stacking](r)
|
|---|
| 488 | if a > a0 and panelcount < n:
|
|---|
| 489 | if n > 1:
|
|---|
| 490 | self._plotter.subplot(panelcount)
|
|---|
| 491 | self._plotter.palette(0)
|
|---|
| 492 | #title
|
|---|
| 493 | xlab = self._abcissa and self._abcissa[panelcount] \
|
|---|
| 494 | or scan._getabcissalabel()
|
|---|
| 495 | ylab = self._ordinate and self._ordinate[panelcount] \
|
|---|
| 496 | or scan._get_ordinate_label()
|
|---|
| 497 | self._plotter.set_axes('xlabel',xlab)
|
|---|
| 498 | self._plotter.set_axes('ylabel',ylab)
|
|---|
| 499 | lbl = self._get_label(scan, r, self._panelling, self._title)
|
|---|
| 500 | if isinstance(lbl, list) or isinstance(lbl, tuple):
|
|---|
| 501 | if 0 <= panelcount < len(lbl):
|
|---|
| 502 | lbl = lbl[panelcount]
|
|---|
| 503 | else:
|
|---|
| 504 | # get default label
|
|---|
| 505 | lbl = self._get_label(scan, r, self._panelling, None)
|
|---|
| 506 | self._plotter.set_axes('title',lbl)
|
|---|
| 507 | newpanel = True
|
|---|
| 508 | stackcount =0
|
|---|
| 509 | panelcount += 1
|
|---|
| 510 | if (b > b0 or newpanel) and stackcount < nstack:
|
|---|
| 511 | y = []
|
|---|
| 512 | if len(polmodes):
|
|---|
| 513 | y = scan._getspectrum(r, polmodes[scan.getpol(r)])
|
|---|
| 514 | else:
|
|---|
| 515 | y = scan._getspectrum(r)
|
|---|
| 516 | m = scan._getmask(r)
|
|---|
| 517 | if self._maskselection and len(self._usermask) == len(m):
|
|---|
| 518 | if d[self._stacking](r) in self._maskselection[self._stacking]:
|
|---|
| 519 | m = logical_and(m, self._usermask)
|
|---|
| 520 | x = scan._getabcissa(r)
|
|---|
| 521 | from matplotlib.numerix import ma, logical_not, array
|
|---|
| 522 | y = ma.masked_array(y,mask=logical_not(array(m,copy=False)))
|
|---|
| 523 | if self._minmaxx is not None:
|
|---|
| 524 | s,e = self._slice_indeces(x)
|
|---|
| 525 | x = x[s:e]
|
|---|
| 526 | y = y[s:e]
|
|---|
| 527 | if len(x) > 1024 and rcParams['plotter.decimate']:
|
|---|
| 528 | fac = len(x)/1024
|
|---|
| 529 | x = x[::fac]
|
|---|
| 530 | y = y[::fac]
|
|---|
| 531 | llbl = self._get_label(scan, r, self._stacking, self._lmap)
|
|---|
| 532 | if isinstance(llbl, list) or isinstance(llbl, tuple):
|
|---|
| 533 | if 0 <= stackcount < len(llbl):
|
|---|
| 534 | # use user label
|
|---|
| 535 | llbl = llbl[stackcount]
|
|---|
| 536 | else:
|
|---|
| 537 | # get default label
|
|---|
| 538 | llbl = self._get_label(scan, r, self._stacking, None)
|
|---|
| 539 | self._plotter.set_line(label=llbl)
|
|---|
| 540 | plotit = self._plotter.plot
|
|---|
| 541 | if self._hist: plotit = self._plotter.hist
|
|---|
| 542 | if len(x) > 0: plotit(x,y)
|
|---|
| 543 | xlim= self._minmaxx or [min(x),max(x)]
|
|---|
| 544 | allxlim += xlim
|
|---|
| 545 | ylim= self._minmaxy or [ma.minimum(y),ma.maximum(y)]
|
|---|
| 546 | allylim += ylim
|
|---|
| 547 | stackcount += 1
|
|---|
| 548 | # last in colour stack -> autoscale x
|
|---|
| 549 | if stackcount == nstack:
|
|---|
| 550 | allxlim.sort()
|
|---|
| 551 | self._plotter.axes.set_xlim([allxlim[0],allxlim[-1]])
|
|---|
| 552 | # clear
|
|---|
| 553 | allxlim =[]
|
|---|
| 554 |
|
|---|
| 555 | newpanel = False
|
|---|
| 556 | a0=a
|
|---|
| 557 | b0=b
|
|---|
| 558 | # ignore following rows
|
|---|
| 559 | if (panelcount == n) and (stackcount == nstack):
|
|---|
| 560 | # last panel -> autoscale y if ganged
|
|---|
| 561 | if rcParams['plotter.ganged']:
|
|---|
| 562 | allylim.sort()
|
|---|
| 563 | self._plotter.set_limits(ylim=[allylim[0],allylim[-1]])
|
|---|
| 564 | break
|
|---|
| 565 | r+=1 # next row
|
|---|
| 566 | #reset the selector to the scantable's original
|
|---|
| 567 | scan.set_selection(savesel)
|
|---|
| 568 |
|
|---|
| 569 | def set_selection(self, selection=None, refresh=True):
|
|---|
| 570 | self._selection = isinstance(selection,selector) and selection or selector()
|
|---|
| 571 | d0 = {'s': 'SCANNO', 'b': 'BEAMNO', 'i':'IFNO',
|
|---|
| 572 | 'p': 'POLNO', 'c': 'CYCLENO', 't' : 'TIME' }
|
|---|
| 573 | order = [d0[self._panelling],d0[self._stacking]]
|
|---|
| 574 | self._selection.set_order(order)
|
|---|
| 575 | if self._data and refresh: self.plot(self._data)
|
|---|
| 576 |
|
|---|
| 577 | def _get_selected_n(self, scan):
|
|---|
| 578 | d1 = {'b': scan.nbeam, 's': scan.nscan,
|
|---|
| 579 | 'i': scan.nif, 'p': scan.npol, 't': scan.ncycle }
|
|---|
| 580 | d2 = { 'b': len(self._selection.get_beams()),
|
|---|
| 581 | 's': len(self._selection.get_scans()),
|
|---|
| 582 | 'i': len(self._selection.get_ifs()),
|
|---|
| 583 | 'p': len(self._selection.get_pols()),
|
|---|
| 584 | 't': len(self._selection.get_cycles()) }
|
|---|
| 585 | n = d2[self._panelling] or d1[self._panelling]()
|
|---|
| 586 | nstack = d2[self._stacking] or d1[self._stacking]()
|
|---|
| 587 | return n,nstack
|
|---|
| 588 |
|
|---|
| 589 | def _get_label(self, scan, row, mode, userlabel=None):
|
|---|
| 590 | pms = dict(zip(self._selection.get_pols(),self._selection.get_poltypes()))
|
|---|
| 591 | if len(pms):
|
|---|
| 592 | poleval = scan._getpollabel(scan.getpol(row),pms[scan.getpol(row)])
|
|---|
| 593 | else:
|
|---|
| 594 | poleval = scan._getpollabel(scan.getpol(row),scan.poltype())
|
|---|
| 595 | d = {'b': "Beam "+str(scan.getbeam(row)),
|
|---|
| 596 | 's': scan._getsourcename(row),
|
|---|
| 597 | 'i': "IF"+str(scan.getif(row)),
|
|---|
| 598 | 'p': poleval,
|
|---|
| 599 | 't': scan._gettime(row) }
|
|---|
| 600 | return userlabel or d[mode]
|
|---|
