def interp(file_loc,mat_name):
"""
Function to accept matlab .mat file with tumor data and interpolate values onto mesh
"""
f_log.write("Interpolating "+mat_name+"...\n")
mat = sc_io_loadmat(file_loc)[mat_name]
mat = fliplr(mat.T)/theta # Needs to be adjusted to fit the mesh correctly; also scaled
x,y = mat.shape[0], mat.shape[1]
mat_interp = InterpolatedParameter(linspace(1,x,x),linspace(1,y,y),mat,degree=1)
return interpolate(mat_interp,V)
#########################################################################
# MAIN
# call the function with: python <this file>
########################################################################
output_dir = "./output/"
f_log = open(osjoin(output_dir, 'log.txt'), 'a')
rat_num = sys.argv[1]
rat_idx = int(sys.argv[2])
day_idx = int(sys.argv[3])
# Days data and time steps
input_dir = "../rat-data/rat" + rat_num + "/"
alldata = sc_io_loadmat("../rat-data/finaldata.mat", )
days = alldata['rat'][0][rat_idx][3][0]
days[:] = [x - days[0] for x in days]
day = days[day_idx]
steps = []
for i in range(1, len(days)):
steps.append(days[i] - days[i - 1])
# Constant inputs for optimization
D0 = 1.
gammaD = .5
k0 = 1.
beta = .5
theta = 50970. # carrying capacity - normalize cell data by this
mu = .42 # kPa, bulk shear modulus
nu = .45