def MagTimePlot(Db, Mag0=[], Mag1=[],
Year0=[], Year1=[],
CompTable=[],
OutFile=[]):
if not Mag0:
Mag0 = min(Db.Extract('MagSize'))
if not Mag1:
Mag1 = max(Db.Extract('MagSize'))
if not Year0:
Year0 = min(Db.Extract('Year'))
if not Year1:
Year1 = max(Db.Extract('Year'))
DbS = Sel.MagRangeSelect(Db, Mag0, Mag1, Owrite=0, TopEdge=True)
DbS = Sel.TimeSelect(DbS, Year0, Year1, Owrite=0)
X = DbS.Extract('Year')
Y = DbS.Extract('MagSize')
plt.figure(figsize=(7, 4))
plt.plot(X, Y, 'o',markersize=3,
color=[0,0,0],
markeredgecolor=[0,0,0],
markeredgewidth=1.5)
# Plot completeness
if CompTable:
PlotCompTable(CompTable)
plt.gca().yaxis.grid(color='0.',linestyle='-')
plt.gca().xaxis.grid(color='0.65',linestyle='--')
plt.gca().xaxis.set_ticks_position('none')
plt.gca().yaxis.set_ticks_position('none')
plt.title('Time-Magnitude Distribution', fontsize=14, fontweight='bold')
plt.xlabel('Years', fontsize=14, fontweight='bold')
plt.ylabel('Magnitude', fontsize=14, fontweight='bold')
plt.axis([Year0, Year1, Mag0, Mag1])
# plt.tight_layout()
plt.show(block=False)
if OutFile:
plt.savefig(OutFile, bbox_inches='tight', dpi=150)
def GetEventRates(Db, CompTable, Area=1.):
"""
Method to compute observed annual rates (incremental and cumulative) from a given
completeness table. In this implementation, completeness is one window per
magnitude bin in M. Example:
CompTable = [[4.50, 0.25, 2000., 2013.],
[4.75, 0.25, 1980., 2013.],
[5.00, 0.25, 1970., 2013.],
[5.25, 0.25, 1960., 2013.],
[5.50, 0.50, 1950., 2013.],
[6.00, 1.50, 1901., 2013.]]
"""
Enum = []
Data = [[],[]]
for CT in CompTable:
MinM = CT[0]
MaxM = CT[0]+CT[1]
MinY = CT[2]
MaxY = CT[3]
# Catalogue selection (Magnitude-Year)
DbM = Sel.MagRangeSelect(Db, MinM, MaxM)
DbY = Sel.TimeSelect(DbM, MinY, MaxY)
# Computing incremental rates
RY = float(DbY.Size())/float(MaxY-MinY)
Enum.append(RY/float(Area))
# Data per magnitude bin
Data[0].append(DbY.Extract(Key='Year'))
Data[1].append(DbY.Extract(Key='MagSize'))
# Cumulative distribution
Ecum = np.cumsum(Enum[::-1])[::-1]
return Enum, Ecum, Data
def RateDensityPlot(Db, Mag0=[], Mag1=[], MBin=0.25,
Year0=[], Year1=[], Delta=2,
CompTable=[],
Normalise=True,
OutFile=[]):
if not Mag0:
Mag0 = min(Db.Extract('MagSize'))
if not Mag1:
Mag1 = max(Db.Extract('MagSize'))
MBins = np.arange(Mag0, Mag1+MBin, MBin)
if not Year0:
Year0 = min(Db.Extract('Year'))
if not Year1:
Year1 = max(Db.Extract('Year'))
YBins = np.arange(Year0, Year1+Delta, Delta)
Histo = np.zeros((np.size(MBins), np.size(YBins)))
# Catalogue selection (Magnitude-Year)
DbM = Sel.MagRangeSelect(Db, Mag0, Mag1, TopEdge=True)
DbY = Sel.TimeSelect(DbM, Year0, Year1)
M = DbY.Extract('MagSize')
Y = DbY.Extract('Year')
Hist = np.histogram2d(Y, M, bins=(YBins, MBins))[0]
Hist = np.transpose(Hist)
if Normalise:
for I in range(0,len(Hist)):
Max = np.max(Hist[I])
if Max > 0:
Hist[I] = Hist[I]/Max
# Plot
plt.figure(figsize=(7, 4))
plt.pcolormesh(YBins, MBins, Hist, cmap='Greys', vmin=0)
# Plot completeness
if CompTable:
PlotCompTable(CompTable)
plt.gca().xaxis.grid(color='0.65',linestyle='--')
plt.gca().yaxis.grid(color='0.',linestyle='-')
plt.gca().xaxis.set_ticks_position('none')
plt.gca().yaxis.set_ticks_position('none')
plt.title('Occurrence Rate Density', fontsize=14, fontweight='bold')
plt.xlabel('Years', fontsize=12, fontweight='bold')
plt.ylabel('Magnitude', fontsize=12, fontweight='bold')
plt.gca().xaxis.grid(color='0.65',linestyle='-')
plt.gca().yaxis.grid(color='0.65',linestyle='-')
plt.axis([Year0, Year1, Mag0, Mag1])
# plt.tight_layout()
plt.show(block=False)
if OutFile:
plt.savefig(OutFile, bbox_inches = 'tight', dpi = 150)
