def fit_to_weibull(sim_file,beta_0,tau_0,event_range=None,magnitude_filter=None,section_filter=None):
from scipy import optimize
from pyvc import VCEvents,VCSimData
fitfunc = lambda p,x: weibull_one(x,p[0],p[1])
errfunc = lambda p,x,y: fitfunc(p,x) - y
p0 = [beta_0,tau_0]
with VCSimData() as sim_data:
# open the simulation data file
sim_data.open_file(sim_file)
# instantiate the vc classes passing in an instance of the VCSimData
# class
events = VCEvents(sim_data)
event_data = events.get_event_data(['event_number', 'event_year', 'event_magnitude', 'event_range_duration'], event_range=event_range, magnitude_filter=magnitude_filter, section_filter=section_filter)
intervals = np.array([ x - event_data['event_year'][n-1]
for n,x in enumerate(event_data['event_year'])
if n != 0
])
cumulative = {}
cumulative['x'] = np.sort(intervals)
cumulative['y'] = np.arange(float(intervals.size))/float(intervals.size)
p1,success = optimize.leastsq(errfunc,p0[:],args=(cumulative['x'],cumulative['y']))
print "\nBETA: {}".format(p1[0])
print "TAU : {}\n".format(p1[1])
def plot_number_area_data(sim_file, output_file=None, event_range=None):
from pyvc import *
from pyvc import vcplotutils
#Can't handle plot label if no event_range given
with VCSimData() as sim_data:
# open the simulation data file
sim_data.open_file(sim_file)
# instantiate the vc events class passing in an instance of the
# VCSimData class
events = VCEvents(sim_data)
# get the data
event_data = events.get_event_data(['event_number','event_area'], event_range=event_range)
start,end = event_range['filter']
duration = round(end-start)
#---------------------------------------------------------------------------
# Prepare the plot and do it.
#---------------------------------------------------------------------------
# initilize a dict to store the event counts and get the total number
# of events.
cum_num = {}
total_events = len(event_data['event_number'])
for num in range(total_events):
area = float(sorted(event_data['event_area'])[num])*float(pow(10,-6))
cum_num[area] = total_events - (num + 1)
sys.stdout.write("\nnumber of events : {}\n".format(total_events))
# dump the counts into x and y arrays for plotting. also, divide the count
# by the number of years so we get count per year.
x = []
y = []
for area in sorted(iter(cum_num)):
x.append(float(area))
y.append(float(cum_num[area]))
# create the line for b = 1
x_b1 = np.linspace(min(x),max(x),num=1000)
y_b1 = y[0]*x_b1[0]*(np.array(x_b1)**-1)
#sys.stdout.write(str(y_b1))
plt.title('Duration: {} years Total events: {}'.format(duration,total_events))
plt.plot(x_b1,y_b1,label='b=1',ls='-',lw=2,c='r')
plt.plot(x,y,'.',c='k')
plt.legend(loc='upper right')
plt.ylabel(r'$N (\geq A_r)$')
plt.xlabel(r'$A_r [km^2]$')
plt.xlim(-500,5500)
plt.ylim(-20,750)
plt.savefig(output_file,dpi=200)
# do the standard plot
"""vcplotutils.standard_plot(output_file, x, y,
