| 1 | #!/usr/bin/python -tt
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| 2 | #
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| 3 | # Werner Lustermann, Dominik Neise
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| 4 | # ETH Zurich, TU Dortmund
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| 5 | #
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| 6 | # plotter.py
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| 7 |
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| 8 | import numpy as np
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| 9 | import matplotlib.pyplot as plt
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| 10 | import os.path
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| 11 | import sys
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| 12 |
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| 13 | # this class was formerly called Plotter in the depricated
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| 14 | # module plotter.py
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| 15 | class SimplePlotter(object):
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| 16 | """ simple x-y plot """
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| 17 | def __init__(self, name, x, style = 'b', xlabel='x', ylabel='y'):
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| 18 | """ initialize the object """
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| 19 |
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| 20 | self.name = name
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| 21 | self.fig = plt.figure()
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| 22 | self.line, = plt.plot(x, style)
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| 23 |
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| 24 | plt.title(name)
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| 25 | plt.xlabel(xlabel)
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| 26 | plt.ylabel(ylabel)
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| 27 | plt.grid(True)
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| 28 |
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| 29 | def __call__(self, ydata):
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| 30 | """ set ydata of plot """
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| 31 | plt.figure(self.fig.number)
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| 32 | plt.ylim( np.min(ydata), np.max(ydata) )
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| 33 | self.line.set_ydata(ydata)
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| 34 | plt.draw()
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| 35 |
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| 36 | class Plotter(object):
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| 37 | """ simple x-y plot """
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| 38 | def __init__(self, name, x=None, style = '.:', xlabel='x', ylabel='y', ion=True, grid=True, fname=None):
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| 39 | """ initialize the object """
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| 40 |
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| 41 | self.name = name
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| 42 | self.x = x
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| 43 | self.style = style
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| 44 | self.xlabel = xlabel
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| 45 | self.ylabel = ylabel
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| 46 |
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| 47 | #not sure if this should go here
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| 48 | if ion:
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| 49 | plt.ion()
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| 50 |
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| 51 | self.figure = plt.figure()
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| 52 | self.fig_id = self.figure.number
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| 53 |
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| 54 | plt.grid(grid)
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| 55 | self.fname = fname
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| 56 |
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| 57 | def __call__(self, ydata, label=None):
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| 58 | """ set ydata of plot """
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| 59 | style = self.style
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| 60 |
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| 61 | # make acitve and clear
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| 62 | plt.figure(self.fig_id)
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| 63 | plt.cla()
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| 64 |
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| 65 | # the following if else stuff is horrible,
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| 66 | # but I want all those possibilities, .... still working on it.
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| 67 |
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| 68 | # check if 1Dim oder 2Dim
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| 69 | ydata = np.array(ydata)
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| 70 | if ydata.ndim ==1:
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| 71 | if self.x==None:
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| 72 | plt.plot(ydata, self.style, label=label)
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| 73 | else:
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| 74 | plt.plot(self.x, ydata, self.style, label=label)
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| 75 | else:
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| 76 | for i in range(len(ydata)):
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| 77 | if self.x==None:
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| 78 | if label:
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| 79 | plt.plot(ydata[i], style, label=label[i])
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| 80 | else:
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| 81 | plt.plot(ydata[i], style)
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| 82 | else:
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| 83 | if label:
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| 84 | plt.plot(self.x, ydata[i], style, label=label[i])
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| 85 | else:
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| 86 | plt.plot(self.x, ydata[i], style)
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| 87 | plt.title(self.name)
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| 88 | plt.xlabel(self.xlabel)
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| 89 | plt.ylabel(self.ylabel)
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| 90 | if label:
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| 91 | plt.legend()
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| 92 |
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| 93 | if self.fname != None:
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| 94 | plt.savefig(self.fname)
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| 95 |
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| 96 | plt.draw()
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| 97 |
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| 98 |
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| 99 | class CamPlotter(object):
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| 100 | """ plotting data color-coded into FACT-camera """
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| 101 | def __init__(self, name, ion=True, grid=True, fname=None, map_file_path = '../map_dn.txt', vmin=None, vmax=None):
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| 102 | """ initialize the object """
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| 103 | path = os.path.abspath(__file__)
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| 104 | path = os.path.dirname(path)
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| 105 | map_file_path = os.path.join(path, map_file_path)
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| 106 | if not os.path.isfile(map_file_path):
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| 107 | print 'not able to find file:', map_file_path
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| 108 | sys.exit(-2)
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| 109 |
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| 110 | self.name = name
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| 111 | if ion:
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| 112 | plt.ion()
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| 113 |
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| 114 | chid, y,x,xe,ye,yh,xh,softid,hardid = np.loadtxt(map_file_path ,unpack=True)
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| 115 | self.xe = xe
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| 116 | self.ye = ye
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| 117 |
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| 118 | self.H = (6,0,30./180.*3.1415926)
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| 119 |
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| 120 | self.figure = plt.figure(figsize=(6, 6), dpi=80)
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| 121 | self.fig_id = self.figure.number
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| 122 |
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| 123 | self.grid = grid
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| 124 | self.fname = fname
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| 125 | self.vmin = vmin
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| 126 | self.vmax = vmax
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| 127 |
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| 128 | def __call__(self, data, mask=None):
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| 129 | # define some shortcuts
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| 130 | xe = self.xe
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| 131 | ye = self.ye
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| 132 | H = self.H
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| 133 | name = self.name
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| 134 | grid = self.grid
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| 135 | vmin = self.vmin
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| 136 | vmax = self.vmax
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| 137 |
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| 138 | # get the figure, clean it, and set it up nicely.
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| 139 | # maybe cleaning is not necessary and takes long, but
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| 140 | # I've got no time to test it at the moment.
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| 141 | plt.figure(self.fig_id)
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| 142 | plt.clf()
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| 143 | self.ax = self.figure.add_subplot(111, aspect='equal')
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| 144 | self.ax.axis([-22,22,-22,22])
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| 145 | self.ax.set_title(name)
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| 146 | self.ax.grid(grid)
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| 147 |
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| 148 | # throw data into numpy array for simplicity
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| 149 | data = np.array(data)
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| 150 |
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| 151 | #handle masked case specially
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| 152 | if mask!= None:
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| 153 | if len(mask)==0:
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| 154 | return
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| 155 |
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| 156 | elif mask.dtype == bool and data.ndim ==1 and len(mask)==1440:
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| 157 | length = mask.sum()
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| 158 | mask = np.where(mask)[0]
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| 159 | mxe = np.empty( length )
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| 160 | mye = np.empty( length )
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| 161 | mdata = np.empty( length )
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| 162 | for i,chid in enumerate(mask):
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| 163 | #print i , chid
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| 164 | mxe[i] = xe[chid]
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| 165 | mye[i] = ye[chid]
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| 166 | mdata[i] = data[chid]
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| 167 | #print 'mxe', mxe, 'len', len(mxe)
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| 168 | #print 'mye', mye, 'len', len(mye)
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| 169 | #print 'mxe', mdata, 'len', len(mdata)
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| 170 |
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| 171 | self.ax.axis([-22,22,-22,22])
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| 172 | self.ax.set_title(name)
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| 173 | self.ax.grid(grid)
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| 174 | # the next line is a stupid hack
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| 175 | # I plot invisible pixels, so that the axes show look ok.
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| 176 | # this must be possible differently, but I don't know how...
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| 177 | self.ax.scatter(xe,ye,s=25,alpha=0,marker=H)
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| 178 |
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| 179 | result = self.ax.scatter(mxe,mye,s=25,alpha=1.,
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| 180 | c=mdata, marker=H, linewidths=0., vmin=vmin, vmax=vmax)
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| 181 | self.figure.colorbar( result, shrink=0.8, pad=-0.04 )
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| 182 | plt.draw()
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| 183 |
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| 184 |
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| 185 | elif mask.dtype == int and data.ndim ==1:
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| 186 | length = len(mask)
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| 187 | mxe = np.empty( length )
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| 188 | mye = np.empty( length )
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| 189 | mdata = np.empty( length )
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| 190 | for i,chid in enumerate(mask):
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| 191 | mxe[i] = xe[chid]
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| 192 | mye[i] = ye[chid]
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| 193 | mdata[i] = data[chid]
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| 194 |
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| 195 | self.ax.axis([-22,22,-22,22])
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| 196 | self.ax.set_title(name)
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| 197 | self.ax.grid(grid)
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| 198 | # the next line is a stupid hack
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| 199 | # I plot invisible pixels, so that the axes show look ok.
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| 200 | # this must be possible differently, but I don't know how...
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| 201 | self.ax.scatter(xe,ye,s=25,alpha=0,marker=H)
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| 202 |
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| 203 | result = self.ax.scatter(mxe,mye,s=25,alpha=1.,
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| 204 | c=mdata, marker=H, linewidths=0., vmin=vmin, vmax=vmax)
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| 205 | self.figure.colorbar( result, shrink=0.8, pad=-0.04 )
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| 206 | plt.draw()
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| 207 |
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| 208 | else:
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| 209 | print "there is a mask, but I don't know how to treat it!!!"
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| 210 | sys.exit(-1)
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| 211 | else: # i.e. when mask is None
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| 212 | # handle 1D and 2D case differently
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| 213 | if data.ndim == 1 and len(data)==1440:
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| 214 | result = self.ax.scatter(xe,ye,s=25,alpha=1,
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| 215 | c=data, marker=H, linewidths=0., vmin=vmin, vmax=vmax)
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| 216 | self.figure.colorbar( result, shrink=0.8, pad=-0.04 )
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| 217 | plt.draw()
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| 218 |
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| 219 | elif data.ndim == 2 and data.shape[0] == 2 and data.shape[1] <=1440:
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| 220 | # I assume the first row of data, contains the CHIDs
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| 221 | # and the 2nd row contains the actual data.
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| 222 | chids = data[0]
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| 223 | # check if there are double chids in chids
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| 224 | if len(chids)!=len(set(chids)):
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| 225 | print 'warning: there are doubled chids in input data',
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| 226 | print 'you might want to plot something else, but I plot it anyway...'
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| 227 | print chids
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| 228 | data = data[1]
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| 229 | # now I have to mask the xe, and ye vectors accordingly
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| 230 | mxe = np.empty( len(chids) )
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| 231 | mye = np.empty( len(chids) )
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| 232 | for i,chid in enumerate(chids):
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| 233 | mxe[i] = xe[chid]
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| 234 | mye[i] = ye[chid]
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| 235 |
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| 236 | # check if I did it right
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| 237 | if len(mxe)!=len(data) or len(mye)!=len(data):
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| 238 | print 'the masking did not work:'
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| 239 | print 'len(mxe)', len(mxe)
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| 240 | print 'len(mye)', len(mye)
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| 241 | print 'len(data)', len(data)
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| 242 |
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| 243 | self.ax.axis([-22,22,-22,22])
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| 244 | self.ax.set_title(name)
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| 245 | self.ax.grid(grid)
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| 246 | # the next line is a stupid hack
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| 247 | # I plot invisible pixels, so that the axes show look ok.
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| 248 | # this must be possible differently, but I don't know how...
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| 249 | self.ax.scatter(xe,ye,s=25,alpha=0,marker=H)
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| 250 |
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| 251 | result = self.ax.scatter(mxe,mye,s=25,alpha=1.,
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| 252 | c=data, marker=H, linewidths=0., vmin=vmin, vmax=vmax)
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| 253 | self.figure.colorbar( result, shrink=0.8, pad=-0.04 )
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| 254 | plt.draw()
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| 255 |
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| 256 | else:
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| 257 | print 'CamPlotter call input data has bad format'
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| 258 | print 'data.ndim', data.ndim
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| 259 | print 'data.shape', data.shape
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| 260 | print 'data:----------------------------------'
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| 261 | print data
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| 262 |
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| 263 |
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| 264 |
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| 265 |
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| 266 | class HistPlotter(object):
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| 267 |
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| 268 | def __init__(self, name, bins, range, grid=True, ion=True):
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| 269 | """ initialize the object """
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| 270 | self.bins = bins
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| 271 | self.range = range
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| 272 | self.name = name
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| 273 | self.figure = plt.figure()
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| 274 | self.fig_id = self.figure.number
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| 275 | self.grid = grid
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| 276 |
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| 277 | if ion:
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| 278 | plt.ion()
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| 279 |
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| 280 | def __call__(self, ydata, label=None, log=False):
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| 281 | plt.figure(self.fig_id)
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| 282 | plt.cla()
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| 283 |
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| 284 | bins = self.bins
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| 285 | range = self.range
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| 286 | grid = self.grid
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| 287 |
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| 288 | ydata = np.array(ydata)
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| 289 |
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| 290 | if ydata.ndim > 1:
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| 291 | ydata = ydata.flatten()
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| 292 | if label:
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| 293 | plt.hist(ydata, bins, range, label=label, log=log)
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| 294 | plt.legend()
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| 295 | else:
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| 296 | plt.hist(ydata, bins, range, log=log)
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| 297 |
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| 298 | plt.title(self.name)
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| 299 |
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| 300 | plt.draw()
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| 301 |
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| 302 | def _test_SimplePlotter():
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| 303 | """ test of maintaining two independant plotter instances """
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| 304 | plt.ion()
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| 305 |
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| 306 | x = np.linspace(0., 10.)
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| 307 | plot1 = SimplePlotter('plot1', x, 'r')
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| 308 | print 'plot1.fig.number: ', plot1.fig.number
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| 309 | plot2 = SimplePlotter('plot2', x, 'g.')
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| 310 | print 'plot2.fig.number: ', plot2.fig.number
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| 311 |
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| 312 | plot1(np.sin(x) * 7.)
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| 313 | plot2(x*x)
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| 314 |
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| 315 | raw_input('next')
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| 316 |
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| 317 | plot1(np.cos(x) * 3.)
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| 318 | plot2(x)
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| 319 |
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| 320 | raw_input('next')
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| 321 |
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| 322 |
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| 323 | def _test_Plotter():
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| 324 | """ test of maintaining two independant plotter instances
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| 325 | with different examples for init and call
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| 326 | """
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| 327 | x = np.linspace(0., 2*np.pi , 100)
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| 328 | plot1 = Plotter('plot1', x, 'r.:')
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| 329 | plot2 = Plotter('plot2')
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| 330 |
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| 331 | y1 = np.sin(x) * 7
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| 332 | plot1(y1)
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| 333 |
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| 334 | number_of_graphs_in_plot2 = 3
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| 335 | no = number_of_graphs_in_plot2 # short form
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| 336 |
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| 337 | # this is where you do your analysis...
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| 338 | y2 = np.empty( (no, len(x)) ) # prepare some space
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| 339 | y2_labels = [] # prepare labels
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| 340 | for k in range(no):
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| 341 | y2[k] = np.sin( (k+1)*x )
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| 342 | y2_labels.append('sin(%d*x)' % (k+1) )
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| 343 |
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| 344 | # plot the result of your analysis
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| 345 | plot2(y2, y2_labels)
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| 346 | raw_input('next') # do not forget this line, or your graph is lost
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| 347 |
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| 348 | plot1(np.cos(x) * 3.)
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| 349 | plot2.name += ' without labels!!!' # changing titles 'on the fly' is possible
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| 350 | plot2(y2)
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| 351 | raw_input('next') # DO NOT forget
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| 352 |
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| 353 |
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| 354 | def _test_CamPlotter():
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| 355 | """ test of CamPlotter """
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| 356 |
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| 357 | c1 = np.array(range(20))
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| 358 | chids1 = np.empty( len(c1) , dtype=int)
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| 359 | for i in range(len(chids1)-2):
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| 360 | chids1[i] = np.random.randint(1440)
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| 361 | chids1[-1] = 15
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| 362 | chids1[-2] = 15
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| 363 |
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| 364 | c2 = np.linspace(0., 1., num=1440)
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| 365 | plot1 = CamPlotter('plot1')
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| 366 | plot2 = CamPlotter('plot2')
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| 367 |
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| 368 | plot1( (chids1,c1) )
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| 369 | plot2(c2)
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| 370 | raw_input('next')
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| 371 |
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| 372 | def _test_HistPlotter():
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| 373 | """ test of the HistPlotter """
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| 374 | plt.ion()
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| 375 |
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| 376 | data = np.random.randn(1000)
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| 377 | hp = HistPlotter('test hist plotter',34, (-5,4))
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| 378 |
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| 379 | hp(data, 'test-label')
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| 380 | raw_input('next')
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| 381 |
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| 382 | if __name__ == '__main__':
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| 383 | """ test the class """
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| 384 | print ' testing SimplePlotter'
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| 385 | _test_SimplePlotter()
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| 386 | print ' testing Plotter'
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| 387 | _test_Plotter()
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| 388 | print 'testing CamPlotter ... testing what happens if doubled IDs in mask'
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| 389 | _test_CamPlotter()
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| 390 | print 'testing basic HistPlotter functionality'
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| 391 | _test_HistPlotter()
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| 392 | |
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