73 lines
1.8 KiB
Python
73 lines
1.8 KiB
Python
import sys
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import getopt
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import numpy as np
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import funcs as f
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def main(argv):
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inputfile = ''
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try:
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opts, args = getopt.getopt(argv, "hi:o:", ["ifile="])
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except getopt.GetoptError:
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print('main.py -i <inputfile>')
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sys.exit(2)
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for opt, arg in opts:
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if opt == '-h':
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print('main.py -i <inputfile>')
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sys.exit()
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elif opt in ("-i", "--ifile"):
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inputfile = arg
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if inputfile != '':
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print('Input file is', inputfile)
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else:
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print('no input file provided, see help (-h)\nexiting...')
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sys.exit(1)
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# d = f.load_d("./dat.csv")
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d = f.load_d(inputfile)
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# d = d.astype('float64')
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print(d.head())
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# data plots
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du = d['u']
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dy = d['y']
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f.plot_d(du, fname='u_input_plot')
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f.plot_d(dy, fname='y_input_plot', colour='green')
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# mean and variance
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mean_u = f.mean(d['u'])
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mean_y = f.mean(d['y'])
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variance_u = f.variance(d['u'])
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variance_y = f.variance(d['y'])
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hist_u = f.histogram(d['u'], fname='u_hist')
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hist_y = f.histogram(d['y'], fname='y_hist', colour='green')
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dist_u = f.distr_func(d['u'], fname='u_dist')
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dist_y = f.distr_func(d['y'], fname='y_dist', colour='green')
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cov = f.covar(d)
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std_dev_u = f.std_dev(d['u'])
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std_dev_y = f.std_dev(d['y'])
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cov_c = f.covar_coeff(cov, std_dev_u, std_dev_y)
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print("data covariance:\n", d.cov())
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# print the matrix.
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print(np.array([[variance_u, cov], [cov, variance_y]]))
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f.plot_autocorellation(dat=d['u'], fname='u_autocorellation')
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f.plot_autocorellation(dat=d['y'], fname='y_autocorellation', colour='green')
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f.plot_mutual_corellation(d1=d['u'], d2=d['y'], fname='mutual_corellation_uy')
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f.plot_autocovariance(dat=d['u'], fname='u_autocovariance')
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f.plot_autocovariance(dat=d['y'], fname='y_autocovariance', colour='green')
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f.plot_mutual_covariance(d1=d['u'], d2=d['y'], fname='mutual_covariance_uy')
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if __name__ == "__main__":
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main(sys.argv[1:])
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