Exemple #1
0
#  0 stress, 1 sleep, 2 diet, 3 exercise, 4 age, 5 gd.get_weight0
nd = 6

#
data_mat = np.zeros( ( nn, nd ), float )

#
for rr in xrange( nn ) :
	#
	stress, sleep, diet, exercise = 2 * nr.random( 4 ) - 1

	#
	age = young + nr.random() * ( old - young )

	#
	data_mat[ rr ] = stress, sleep, diet, exercise, age, gd.get_weight0( normal_w, stress, sleep, diet, exercise, w_var, age, young, old )



#
nq_list = [ 3 for xx in xrange(nd) ]

#
int_mat = gd.discretize_mat( data_mat, nq_list )
print int_mat[ :10 ]

#
mat_file = "../data/dummy_A_discrete_data0.tab"i
var_id_list = range( nd ) 

#
Exemple #2
0
#!/usr/bin/python
# -*- coding: utf-8 -*-

import numpy as np
import numpy.random as nr

import generate_data as gp


# DEBUG


gender = "m"
normal_w = 70
w_var = 5
age = 40


#
for rr in xrange( 10 ) :
	stress, sleep, diet, exercise = 2 * nr.random( 4 ) - 1
	#
	#stress = 0
	#sleep = 0
	#diet = 0
	#exercise = 0
	#
	print "stress %.2f, sleep %.2f, diet %.2f, exercise %.2f, weight %.2f" % ( stress, sleep, diet, exercise, gp.get_weight0( normal_w, stress, sleep, diet, exercise, w_var, age ) )
Exemple #3
0
#
for rr in xrange(n_data):
    #
    stress, sleep, diet, exercise = 2 * nr.random(4) - 1

    #
    age = young + nr.random() * (old - young)

    #
    data_mat[rr] = (
        stress,
        sleep,
        diet,
        exercise,
        age,
        gp.get_weight0(normal_w, stress, sleep, diet, exercise, w_var, age, young, old),
    )


#
print data_mat[:10]


#
nq = 4
print gp.get_quantile_limits0(data_mat[:, 0], nq)


#
nn = 20
nd = 4