def complex_arr(arr1, arr2):
nb1 = np.size(arr1)
nb2 = np.size(arr2)
if nb1 == nb2:
out_arr = np.zeros(nb1, complex)
out_arr.real = arr1
out_arr.imag = arr2
if nb1 != nb2 and nb1 == 1:
out_arr = np.zeros(nb2, complex)
i = np.arange(1, nb2 + 1) / np.arange(1, nb2 + 1)
out_arr.real = i * arr1
out_arr.imag = arr2
if nb1 != nb2 and nb2 == 1:
out_arr = np.zeros(nb1, complex)
i = np.arange(1, nb1 + 1) / np.arange(1, nb1 + 1)
out_arr.real = arr1
out_arr.imag = i * arr2
if nb1 == 1 and nb2 == 1:
out_arr = np.eros(nb1, complex)
out_arr.real = arr1
out_arr.imag = arr2
return np.array(out_arr)
def complex_arr(arr1,arr2):
nb1 = np.size(arr1)
nb2 = np.size(arr2)
if nb1 == nb2:
out_arr = np.zeros(nb1,complex)
out_arr.real=arr1
out_arr.imag=arr2
if nb1!=nb2 and nb1==1:
out_arr = np.zeros(nb2,complex)
i = np.arange(1,nb2+1)/np.arange(1,nb2+1)
out_arr.real=i*arr1
out_arr.imag=arr2
if nb1!=nb2 and nb2==1:
out_arr = np.zeros(nb1,complex)
i = np.arange(1,nb1+1)/np.arange(1,nb1+1)
out_arr.real=arr1
out_arr.imag=i*arr2
if nb1==1 and nb2==1:
out_arr = np.eros(nb1,complex)
out_arr.real=arr1
out_arr.imag=arr2
return np.array(out_arr)
def WW2000(mcval, mags, binsize):
"""Wiemer and Wyss (2000) method for determining a and b values."""
mags = mags[~np.isnan(mags)]
mags = np.around(mags, 1)
mc_vec = np.arange(mcval - 1.5, mcval + 1.5 + binsize / 2., binsize)
max_mag = max(mags)
corr = binsize / 2.
bvalue = np.zeros(len(mc_vec))
std_dev = np.zeros(len(mc_vec))
avalue = np.zeros(len(mc_vec))
rval = np.eros(len(mc_vec))
for idx in range(len(mc_vec)):
mval = mags[mags >= mc_vec[idx] - 0.001]
mag_bins_edges = np.arange(mc_vec[idx] - binsize / 2.,
max_mag + binsize, binsize)
mag_bins_centers = np.arange(mc_vec[idx], max_mag + binsize / 2.,
binsize)
cdf = np.zeros(len(mag_bins_centers))
for jdx in range(len(cdf)):
cdf[jdx] = np.count_nonzero(
~np.isnan(mags[mags >= mag_bins_centers[jdx] - 0.001]))
bvalue[idx] = np.log10(np.exp(1)) / (np.average(mval) -
(mc_vec[idx] - corr))
std_dev[idx] = bvalue[idx] / sqrt(cdf[0])
avalue[idx] = np.log10(len(mval)) + bvalue[idx] * mc_vec[idx]
log_l = avalue[idx] - bvalue[idx] * mag_bins_centers
lval = 10.**log_l
bval, _ = np.histogram(mval, mag_bins_edges)
sval = abs(np.diff(lval))
rval[idx] = (sum(abs(bval[:-1] - sval)) / len(mval)) * 100
ind = np.where(rval <= 10)[0]
if len(ind) != 0:
idx = ind[0]
else:
idx = list(rval).index(min(rval))
mcval = mc_vec[idx]
bvalue = bvalue[idx]
avalue = avalue[idx]
std_dev = std_dev[idx]
mag_bins = np.arange(o, max_mag + binsize / 2., binsize)
lval = 10.**(avalue - bvalue * mag_bins)
return mcval, bvalue, avalue, lval, mag_bins, std_dev