80 lines
2.7 KiB
Python
80 lines
2.7 KiB
Python
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#!/usr/bin/env python
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import sys
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import os
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from subprocess import *
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if len(sys.argv) <= 1:
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print('Usage: {0} training_file [testing_file]'.format(sys.argv[0]))
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raise SystemExit
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# svm, grid, and gnuplot executable files
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is_win32 = (sys.platform == 'win32')
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if not is_win32:
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svmscale_exe = "../svm-scale"
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svmtrain_exe = "../svm-train"
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svmpredict_exe = "../svm-predict"
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grid_py = "./grid.py"
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gnuplot_exe = "/usr/bin/gnuplot"
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else:
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# example for windows
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svmscale_exe = r"..\windows\svm-scale.exe"
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svmtrain_exe = r"..\windows\svm-train.exe"
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svmpredict_exe = r"..\windows\svm-predict.exe"
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gnuplot_exe = r"c:\tmp\gnuplot\binary\pgnuplot.exe"
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grid_py = r".\grid.py"
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assert os.path.exists(svmscale_exe),"svm-scale executable not found"
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assert os.path.exists(svmtrain_exe),"svm-train executable not found"
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assert os.path.exists(svmpredict_exe),"svm-predict executable not found"
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assert os.path.exists(gnuplot_exe),"gnuplot executable not found"
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assert os.path.exists(grid_py),"grid.py not found"
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train_pathname = sys.argv[1]
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assert os.path.exists(train_pathname),"training file not found"
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file_name = os.path.split(train_pathname)[1]
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scaled_file = file_name + ".scale"
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model_file = file_name + ".model"
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range_file = file_name + ".range"
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if len(sys.argv) > 2:
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test_pathname = sys.argv[2]
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file_name = os.path.split(test_pathname)[1]
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assert os.path.exists(test_pathname),"testing file not found"
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scaled_test_file = file_name + ".scale"
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predict_test_file = file_name + ".predict"
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cmd = '{0} -s "{1}" "{2}" > "{3}"'.format(svmscale_exe, range_file, train_pathname, scaled_file)
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print('Scaling training data...')
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Popen(cmd, shell = True, stdout = PIPE).communicate()
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cmd = '{0} -svmtrain "{1}" -gnuplot "{2}" "{3}"'.format(grid_py, svmtrain_exe, gnuplot_exe, scaled_file)
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print('Cross validation...')
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f = Popen(cmd, shell = True, stdout = PIPE).stdout
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line = ''
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while True:
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last_line = line
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line = f.readline()
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if not line: break
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c,g,rate = map(float,last_line.split())
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print('Best c={0}, g={1} CV rate={2}'.format(c,g,rate))
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cmd = '{0} -c {1} -g {2} "{3}" "{4}"'.format(svmtrain_exe,c,g,scaled_file,model_file)
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print('Training...')
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Popen(cmd, shell = True, stdout = PIPE).communicate()
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print('Output model: {0}'.format(model_file))
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if len(sys.argv) > 2:
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cmd = '{0} -r "{1}" "{2}" > "{3}"'.format(svmscale_exe, range_file, test_pathname, scaled_test_file)
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print('Scaling testing data...')
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Popen(cmd, shell = True, stdout = PIPE).communicate()
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cmd = '{0} "{1}" "{2}" "{3}"'.format(svmpredict_exe, scaled_test_file, model_file, predict_test_file)
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print('Testing...')
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Popen(cmd, shell = True).communicate()
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print('Output prediction: {0}'.format(predict_test_file))
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