def calc_R_matrix (beta, gamma, alpha):
# calculate R matrix from beta value
# calc contact matrix C
#C = func.calc_contact_matrix(filename_germ_contact_data, filename_germ_pop_data, alpha)
q_c, q_a, p_c, p_a, _, _ = func.calc_p(filename_germ_within_group_contact_data, filename_germ_pop_data, filename_germ_all_contact_data)
C = func.calc_contact_matrix_pqa(p_c, p_a, q_c, q_a, alpha) # new calc of contact matrix
# assign components of C matrix
C_cc = C.item((0, 0))
C_ca = C.item((0, 1))
C_ac = C.item((1, 0))
C_aa = C.item((1, 1))
# multiply components of matrix C by alpha or (1-alpha)
mx_11 = (C_cc * alpha)
mx_12 = (C_ca * alpha)
mx_21 = (C_ac * (1 - alpha))
mx_22 = (C_aa * (1 - alpha))
# calc R matrix
# SB needs to check - might be (beta / (beta + gamma))
R = ((beta / gamma) * (np.matrix([[mx_11, mx_12], [mx_21, mx_22]])))
#R = ((beta / (beta + gamma)) * (np.matrix([[mx_11, mx_12], [mx_21, mx_22]])))
return C, R
filename_germ_all_contact_data = 'Dropbox/Anne_Bansal_lab/Contact_Data/all_ages_polymod_germany_contact_matrix_Mossong_2008.csv'
# READ Germany population data
filename_germ_pop_data = 'Dropbox/Anne_Bansal_lab/UNdata_Export_2008_Germany_Population.csv'
# DEFINE POPULATION PARAMETERS
year = 2010
alpha = pop_func.calc_alpha(year, dict_childpop, dict_adultpop)
d_metro_age_pop = pop_func.calc_metro_age_pop(filename_metropop, alpha)
ch_travelers_r = 0.0 # fraction of children who travel
ad_travelers_s = 1
# CONTACT MATRIX
q_c, q_a, p_c, p_a, _, _ = pop_func.calc_p(filename_germ_within_group_contact_data, filename_germ_pop_data, filename_germ_all_contact_data)
C = pop_func.calc_contact_matrix_pqa(p_c, p_a, q_c, q_a, alpha)
#print C
# DEFINE DISEASE PARAMETERS
R0 = 1.2
gamma = 0.5 # recovery rate based on (1/gamma) day infectious period
### UNIT TEST ###
unit_test = 'no_trans'
# NO TRANSMISSION #
#BETA = 0
beta = 0.0
num_metro_zeros = 1 # set how many metros to select patients from to start with
num_child_zeros = 1
num_adult_zeros = 0
time_end = 150
