# Basic characteristics of seismicity catalog
m0total = 1.0e16
max_m0 = math.pow(10.0, 18.0)
minM = -1.0
min_m0 = gr.calc_m0(minM)
slope = 1.0
# Define the Gutenberg-Richter relationship values
gr_obj = gr.GutenbergRichter(b=slope,
m0total=m0total,
max_m0=max_m0,
min_m0=min_m0)
gr_obj.calc_a()
# Make a plot of the chosen G-R relationship
maxM = gr.calc_Mw(max_m0)
Msamp = 0.25
Mws = np.arange(minM, maxM + Msamp, Msamp)
Ns = gr_obj.get_N(Mws)
max_dep = 2.0 #max depth in km, events will be uniform between 0 and max_dep
# Calculate probability of a given event per second
secday = 60.0 * 60.0 * 24.0
secyear = secday * 365.0
secmonth = secday * 30.0
Nsec = Ns / secyear
# Generate a couple months of catalog
catlength = 2.0 * secday
#(catalog, Nsc, Mwsc) = gr_obj.generate_catalog(catlength)
#(catalog2, Nsc2, Mwsc2) = gr_obj.generate_catalog(secmonth)
# Basic useful values
secday = 60.0 * 60.0 * 24.0
secyear = secday * 365.0
secmonth = secday * 30.0
# Determine if a catalog pickle file is included on command line
if (args.pklfile is not None): #Assumes argv[1] is pickle file
filename = args.pklfile
root = '.'.join(filename.split('.')[:-1])
with open(filename, 'rb') as f:
if python3:
gr_obj = pickle.load(f, encoding='latin1')
else:
gr_obj = pickle.load(f)
minM = gr.calc_Mw(gr_obj.min_m0)
maxM = gr.calc_Mw(gr_obj.max_m0)
Msamp = 0.25
Mws = np.arange(minM, maxM + Msamp, Msamp)
Ns = gr_obj.get_N(Mws)
setmin = True
if (args.minMw is not None):
min_Mw = args.minMw
else: # If no min_Mw argument is given
setmin = False
min_Mw = -999.0
else:
# Basic characteristics of seismicity catalog
m0total = 1.0e17
max_m0 = math.pow(10.0, 19.5)
max_m0=max_m0_lower,
min_m0=min_m0)
gr_obj_upper2.calc_a()
gr_obj_lower1 = gr.GutenbergRichter(b=slope,
m0total=m0total_lower,
max_m0=max_m0,
min_m0=min_m0)
gr_obj_lower1.calc_a()
gr_obj_lower2 = gr.GutenbergRichter(b=slope,
m0total=m0total_lower,
max_m0=max_m0_upper,
min_m0=min_m0)
gr_obj_lower2.calc_a()
# Make a plot of the chosen G-R relationship
maxM = gr.calc_Mw(max_m0)
minM = gr.calc_Mw(min_m0)
Msamp = 0.25
Mws = np.arange(minM, maxM + Msamp, Msamp)
Ns = gr_obj.get_N(Mws)
Ns_upper1 = gr_obj_upper1.get_N(Mws)
Ns_upper2 = gr_obj_upper2.get_N(Mws)
Ns_lower1 = gr_obj_lower1.get_N(Mws)
Ns_lower2 = gr_obj_lower2.get_N(Mws)
# max_dep = 2.0 #max depth in km, events will be uniform between 0 and max_dep
# Convert Ns to be for catalog duration
# Ns = Ns * TCycleYrs
# Ns_upper1 = Ns_upper1 * TCycleYrs
# Ns_upper2 = Ns_upper2 * TCycleYrs
# Ns_lower1 = Ns_lower1 * TCycleYrs