Mercurial > ~darius > hgwebdir.cgi > beermon

annotate logplot.py @ 20:4792fbc1e255 default tip

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Random ignore crap.
author darius
date Tue, 29 Jan 2008 12:36:00 +0000
parents 9264a9cacfde
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
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1 #!/usr/bin/env python
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2
12
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3 import re, datetime, time, sys, cPickle, numpy
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4 import matplotlib
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5 import matplotlib.figure
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6 import matplotlib.backends.backend_agg
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7 import matplotlib.dates
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8
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9 daterestr = '([0-9]{4}/[0-9]{2}/[0-9]{2} [0-9]{2}:[0-9]{2}:[0-9]{2}): '
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10 targtre = re.compile(daterestr + 'target temperature - (-?[0-9]+\.[0-9]+)')
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11 templre = re.compile(daterestr + '(-?[0-9]+\.[0-9]+)\s+(-?[0-9]+\.[0-9]+)\s+(-?[0-9]+\.[0-9]+)\s+([a-z-]+)\s+([a-z-]+)')
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12 datefmt = '%Y/%m/%d %H:%M:%S'
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13 tz = matplotlib.pytz.timezone('Australia/Adelaide')
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14
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15 #start = time.mktime(time.strptime("2007/09/22 14:00:00", datefmt))
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16 start = None
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17 #end = time.mktime(time.strptime("2007/09/30 14:00:00", datefmt))
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18 end = None
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19
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20 def parselog(f, start, end, times, fermTemps, fridgeTemps, ambTemps, targetTemps, states):
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21 targetTemp = 18.0 # Have to guess this..
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22
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23 for line in f:
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24 # Log line?
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25 m = templre.match(line)
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26 if (m == None):
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27 # No, might be a target temp line
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28 m = targtre.match(line)
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29 if (m != None):
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30 # Parse date portion
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31 t = datetime.datetime(*time.strptime(m.group(1), datefmt)[0:6])
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32 if ((start != None and t < start) or (end != None and t > end)):
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33 continue
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34
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35 targetTemp = float(m.group(2))
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36 continue
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37 else:
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38 # Isn't anything, next!
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39 continue
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40
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41 # Parse date portion
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42 t = datetime.datetime(*time.strptime(m.group(1), datefmt)[0:6])
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43 if ((start != None and t < start) or (end != None and t > end)):
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44 continue
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45
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46 fermTemp = float(m.group(2))
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47 fridgeTemp = float(m.group(3))
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48 ambTemp = float(m.group(4))
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49 state = m.group(5)
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50
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51 # Convert to Gregorian days (float) because that is what matplotlib uses
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52 times.append(matplotlib.dates._to_ordinalf(t))
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53 fermTemps.append(fermTemp)
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54 fridgeTemps.append(fridgeTemp)
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55 ambTemps.append(ambTemp)
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56 targetTemps.append(targetTemp)
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57 if (state == 'heat'):
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58 states.append(10)
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59 elif (state == 'idle'):
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60 states.append(8)
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61 else:
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62 states.append(6)
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63
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64 return(times, fermTemps, fridgeTemps, ambTemps, targetTemps, states)
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65
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66 def doplot(times, fermTemps, fridgeTemps, ambTemps, targetTemps, states, outfile):
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67 assert(len(times) == len(fermTemps))
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68 assert(len(times) == len(fridgeTemps))
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69 assert(len(times) == len(ambTemps))
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70 assert(len(times) == len(targetTemps))
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71 assert(len(times) == len(states))
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72 nrec = len(times)
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73 print "nrec = %d" % (nrec)
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74 newsz = [1000]
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75 then = time.time()
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76 times = rebin(numpy.array(times), newsz)
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77 fermTemps = rebin(numpy.array(fermTemps), newsz)
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78 fridgeTemps = rebin(numpy.array(fridgeTemps), newsz)
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79 ambTemps = rebin(numpy.array(ambTemps), newsz)
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80 targetTemps = rebin(numpy.array(targetTemps), newsz)
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81 states = rebin(numpy.array(states, 'f'), newsz)
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82 now = time.time()
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83 print "Rebinning took %.2f msec" % ((now - then) * 1000)
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84
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85 title = "%s to %s (%d -> %d pts)" % (matplotlib.dates._from_ordinalf(times[0]).strftime(datefmt),
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86 matplotlib.dates._from_ordinalf(times[-1]).strftime(datefmt),
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87 nrec, len(times))
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88 print title
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89
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90 then = time.time()
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91 # A figure
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92 fig = matplotlib.figure.Figure(figsize = (9.0, 5.0))
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93
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94 # Create a plot, get some axes
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95 ax = fig.add_subplot(111)
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96
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97 # Plot the data onto the axes
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98 p = ax.plot(times, fermTemps, times, fridgeTemps, times, ambTemps, times, targetTemps, times, states, '.')
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99 ax.set_title(title, weight = 'bold')
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100 ax.set_autoscale_on(True)
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101
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102 # Add a formatter
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103 hoursFmt = matplotlib.dates.DateFormatter('%d %b\n%H:%M')
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104 ax.xaxis.set_major_formatter(hoursFmt)
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105
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106 # Prettify it
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107 ax.grid(True)
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108 ax.set_xlabel('Date')
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109 ax.set_ylabel('Temperature(C)')
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110
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111 # Set the legend
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112 legend = ax.legend((p[0], p[1], p[2], p[3], p[4]), ('Fermenter', 'Fridge', 'Ambient', 'Target', 'State'), 'lower left')
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113
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114 # Render the figure
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115 canvas = matplotlib.backends.backend_agg.FigureCanvasAgg(fig)
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116 canvas.print_figure(outfile, dpi = 96)
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117 now = time.time()
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118 print "Plotting took %.2f msec" % ((now - then) * 1000)
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119
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120 def main():
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121 logf = open(sys.argv[1], 'r')
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122 outfile = sys.argv[1][:-3] + 'png'
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123
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124 try:
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125 # Try reading the pickled data
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126 p = cPickle.Unpickler(open("data.pck", "r"))
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127 then = time.time()
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128 times, fermTemps, fridgeTemps, ambTemps, targetTemps, states, offs = p.load()
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129 now = time.time()
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130 print "Unpickle took %.2f msec" % ((now - then) * 1000)
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131 # Seek up to the last place we parsed
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132 logf.seek(offs)
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133 del p
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134 print "Parsed pickle OK"
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135
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136 except (IOError, cPickle.UnpicklingError, ValueError):
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137 # Either the pickle doesn't exist, or it's invalid, start anew
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138 print "Can't read pickle, starting from scratch"
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139 times = []
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140 fermTemps = []
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141 fridgeTemps = []
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142 ambTemps = []
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143 states = []
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144 targetTemps = []
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145
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146 then = time.time()
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147 parselog(logf, start, end, times, fermTemps, fridgeTemps, ambTemps, targetTemps, states)
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148 now = time.time()
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149 print "Parselog took %.2f msec" % ((now - then) * 1000)
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150
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151 # Write the pickle back out
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152 p = cPickle.Pickler(open("data.pck", "w"), protocol = -1)
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153 then = time.time()
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154 p.dump((times, fermTemps, fridgeTemps, ambTemps, targetTemps, states, logf.tell()))
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155 now = time.time()
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156 print "Pickle took %.2f msec" % ((now - then) * 1000)
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157 del p
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158
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159 # Do the plot
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160 doplot(times, fermTemps, fridgeTemps, ambTemps, targetTemps, states, outfile)
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161
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162 def rebin(a, newshape):
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163 '''Rebin an array to a new shape.
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164 '''
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165 assert len(a.shape) == len(newshape)
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166
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167 slices = [slice(0, old, float(old)/new) for old,new in zip(a.shape,newshape) ]
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168 coordinates = numpy.mgrid[slices]
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169 indices = coordinates.astype('i') #choose the biggest smaller integer index
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170 return a[tuple(indices)]
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171
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172 if __name__ == "__main__":
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173 main()