linewidth=0.5)
cindex = []
# loop thru b values
for b, n0 in zip(src_bval, src_n0):
if not isnan(n0):
idx = interp(b, [b_min, b_max], [0, ncolours - 1])
cindex.append(int(round(idx)))
# plt source zone boundary
drawshapepoly(m2,
plt,
sf,
cindex=cindex,
cmap=cmap,
ncolours=ncolours,
fillshape=True,
edgecolor='r',
lw=1.)
#labelpolygon(m2, plt, sf, 'CODE', value='CBGZ', col='k', fweight='normal', fsize=14, addOutline=False)
#x,y = m2(130., -35.35)
#plt.text(x, y, 'EBGZ', va='center', ha='center', fontsize=14)
xlim = ax.get_xlim()
xtxt = xlim[1] * 0.02
ylim = ax.get_ylim()
ytxt = ylim[1] * 0.02
plt.text(xtxt, ytxt, 'a)', fontsize=20, va='bottom', ha='left')
x, y = m(133.37-txtoff, -16.25+txtoff) plt.text(x, y, 'Daly Waters', size=14, ha='right', weight='normal', path_effects=path_effects) x, y = m(133.54, -17.55) plt.plot(x, y, 's', markerfacecolor='k', markeredgecolor='k', markeredgewidth=0.5, markersize=6, zorder=11000) x, y = m(133.54-txtoff, -17.55+txtoff) plt.text(x, y, 'Elliott', size=14, ha='right', weight='normal', path_effects=path_effects) """ ########################################################################################## # add shapefiles ########################################################################################## shpfile = '../NT/shapefiles/PetroleumTitles28August2019.shp' shpfile = 'PetroleumTitles28August2019.shp' sf = shapefile.Reader(shpfile) drawshapepoly(m, plt, sf, col='r', lw=0.75, alpha=0.5, fillshape=True) jsonfile = 'NSW_CSG_Boreholes.geojson' csg_data = return_csg_data(jsonfile) status = dictlist2array(csg_data, 'status') csg_lon = dictlist2array(csg_data, 'lon') csg_lat = dictlist2array(csg_data, 'lat') idx1 = where(status == 'Permanently Sealed') x, y = m(csg_lon[idx1], csg_lat[idx1]) plt.plot(x, y, 'ro', ms=7, label='Permanently Sealed') idx1 = where(status == 'Not Producing Gas') x, y = m(csg_lon[idx1], csg_lat[idx1]) plt.plot(x, y, 'o', c='orange', ms=7, label='Not Producing Gas')
year = cat.data['year'] idx = where((mags >= 3.0) & (year >= 1977))[0] x, y = m(lons[idx], lats[idx]) m.plot(x, y, 'o', ms=2, mfc='0.4', mec='0.4', zorder=1) idx = where((mags >= 5.6) & (year >= 1880))[0] x, y = m(lons[idx], lats[idx]) m.plot(x, y, 'o', ms=7, mfc='maroon', mec='w', mew=1, zorder=2) ########################################################################################## # add shapefiles ########################################################################################## shpfile = '../../Catalogue/Completeness_NSHA18/Leonard_17_mcomp_d.shp' sf = shapefile.Reader(shpfile) drawshapepoly(m, plt, sf, col='r', lw=2) # label shapes labelpolygon(m, plt, sf, 'NAME', fweight='normal', fsize=16, addOutline=True) # add subplot letter x, y = m(llcrnrlon + 1, urcrnrlat - 1) plt.text(x, y, '(a)', size=22, ha='left', va='top', weight='normal') ########################################################################################## # add 2nd axis ########################################################################################## ax = fig.add_subplot(122) plt.tick_params(labelsize=8)
cmap, zvals = cpt2colormap(cptfile, ncols + 1)
cmap = remove_last_cmap_colour(cmap)
cs = (cmap(arange(ncols)))
# load shape
import shapefile
shpfile = 'shapefiles/2021_nac_gmm_zones.shp'
sf = shapefile.Reader(shpfile)
shapes = sf.shapes()
zone_code = get_field_data(sf, 'CODE', 'str')
polygons = []
for poly in shapes:
polygons.append(Polygon(poly.points))
drawshapepoly(m, plt, sf, edgecolor='k', lw=2)
# get net IDs
netid = []
stas = []
unets = ['AU', 'GE', 'S1', 'II', 'IU', 'OA', '2O']
netsym = ['^', 'H', 'd', 's', 'v', 'p', 'D']
msize = [10, 10, 10, 8, 10, 10, 7]
# loop thru zones
i = 0
for j, poly in enumerate(polygons):
if zone_code[j] == 'BS':
eqlo = []
im = m.imshow(rgb)
'''
##########################################################################################
# parse mag zones
##########################################################################################
import shapefile
from shapely.geometry import Point, Polygon
from mapping_tools import get_field_data, drawshapepoly, labelpolygon
shpfile = 'shapefile/australia_ml_regions.shp'
sf = shapefile.Reader(shpfile)
shapes = sf.shapes()
drawshapepoly(m, plt, sf, fillcolor='none', edgecolor='r', lw=2.5, zorder=0)
labelpolygon(m, plt, sf, 'ML_REGION', fsize=24, addOutline=True)
##########################################################################################
# add ficticious earthquakes
##########################################################################################
import matplotlib.patheffects as path_effects
data = loadtxt('ficticious_eq_locs.csv', delimiter=',')
x, y = m(data[:, 0], data[:, 1])
plt.plot(x,
y,
'*',
mfc='k',
mec='k',
mew=0,
m.fillcontinents(color='w', lake_color='0.8')
m.drawparallels(arange(-90., 90., grdsize),
labels=[0, 0, 0, 0],
fontsize=12,
dashes=[2, 2],
color='0.5',
linewidth=0.75)
m.drawmeridians(arange(0., 360., grdsize * 2),
labels=[0, 0, 0, 0],
fontsize=12,
dashes=[2, 2],
color='0.5',
linewidth=0.75)
# drow zones
drawshapepoly(m, plt, sf, lw=2.)
# find grd points inside zones
shla = []
shlo = []
for shape in shapes:
poly = Polygon(shape.points)
for slo, sla in zip(logrd, lagrd):
pt = Point(slo, sla)
if pt.within(poly):
shlo.append(slo)
shla.append(sla)
shlo = array(shlo)
shla = array(shla)
m.drawmeridians(arange(0., 360., 6.),
labels=[0, 0, 0, 1],
fontsize=16,
dashes=[2, 2],
color='0.5',
linewidth=0.75)
##########################################################################################
# add shapefiles
##########################################################################################
shpfile = '/Users/tallen/Documents/Geoscience_Australia/NSHA2018/source_models/zones/shapefiles/Leonard2008/source_model_leonard_2008.shp'
#shpfile = '/Users/tallen/Documents/Geoscience_Australia/NSHA2018/source_models/zones/shapefiles/Domains/Domains_Sep2011.shp'
#shpfile = '/Users/tallen/Documents/Geoscience_Australia/NSHA2018/source_models/zones/shapefiles/ARUP_Background/ARUP_background_source_model.shp'
shpfile = '/Users/tallen/Documents/Geoscience_Australia/NSHA2018/source_models/zones/shapefiles/NSHA13/NSHA13_regional_source_model_simplified.shp'
sfz = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sfz, col='blue', lw=1.75)
# label shapes
#labelpolygon(m, plt, sf, 'NAME', fweight='normal', fsize=16, addOutline=True)
##########################################################################################
# plt stress vectors
##########################################################################################
shpfile = '/Users/tallen/Documents/Geoscience_Australia/NSHA2018/source_models/zones/shapefiles/Other/SHMax_Rajabi_2016.shp'
sfv = shapefile.Reader(shpfile)
lat = get_field_data(sfv, 'LAT', 'float')
lon = get_field_data(sfv, 'LON', 'float')
shmax = get_field_data(sfv, 'SHMAX', 'float')
alpha=1.,
zorder=len(cat.data['magnitude']) + 1,
lw=2)
legh.append(h[0])
l = plt.legend(legh, ('MW 3.0', 'MW 5.0', 'MW 7.0'), loc=1, numpoints=1)
l.set_zorder(len(cat.data['magnitude']) + 5)
##########################################################################################
# add source zones
##########################################################################################
import shapefile
shpfile = '../sources/area_sources/2020_H_model/shapefiles/2020_H_model_slab.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sf, lw=2.)
shpfile = '../sources/area_sources/2015_H_model/shapefiles/2015_H_merged_slab.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sf, lw=2., col='r', ls='--')
'''
##########################################################################################
# add cities
##########################################################################################
clat = [-37.814, -42.882, -35.282]
clon = [144.964, 147.324, 149.129]
cloc = ['Melbourne', 'Hobart', 'Canberra']
x, y = m(clon, clat)
plt.plot(x, y, 'o', markerfacecolor='maroon', markeredgecolor='w', markeredgewidth=2, markersize=14)
rgb = ls.shade(topodat.data, cmap=cmap, norm=norm)
im = m.imshow(rgb, alpha=1.)
##########################################################################################
# add basins
##########################################################################################
import matplotlib.patheffects as PathEffects
path_effects = [PathEffects.withStroke(linewidth=2.5, foreground="w")]
shpfile = '../2012_moe_earthquake/gis/gippslans_bass_basin_wgs84.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m,
plt,
sf,
col='r',
fillcolor='r',
edgecolor='r',
lw=0.75,
alpha=0.2,
fillshape=True)
# label polygons
x, y = m(146, -40.1)
plt.text(x,
y,
'Bass\nBasin',
size=12,
c='r',
ha='center',
va='top',
weight='normal',
triLats.append(reckon(dla, dlo, halfTriLen, daz + 180)[1])
# pt3 - assum equilateral triange
triHeight = sqrt(triLen**2 - halfTriLen**2)
arrowAng = adirn * 90.
triLons.append(reckon(dla, dlo, triHeight, daz - arrowAng)[0])
triLats.append(reckon(dla, dlo, triHeight, daz - arrowAng)[1])
xx, yy = m(triLons, triLats)
#plt.plot(xx, yy, 'o', c='r', lw=2, )
plt.fill(xx, yy, facecolor=acol, edgecolor='k', linewidth=0.5, alpha=1)
# add Flores-Wetar
shpfile = 'fault_geometries/flores-wetar.shp'
sf = shapefile.Reader(shpfile)
flolas = drawshapepoly(m, plt, sf, lw=1.5, polyline=True)
lons = flolas[0][0]
lats = flolas[0][1]
map_fault_dip_dirn(m,
plt,
lons,
lats,
discLen,
triLen,
fc='0.5',
ec='k',
lw=0.5,
invArrow=True)
##########################################################################################
# annotate text
mask_outside_polygons(polys, '0.9', plt)
# get lake ploygons
polygons = []
for polygon in m.lakepolygons:
poly = polygon.get_coords()
plt.fill(poly[:,0], poly[:,1], '0.9')
polygons.append(poly)
##########################################################################################
# finish off
##########################################################################################
# overlay domains
sf = shapefile.Reader('/Users/trev/Documents/Geoscience_Australia/NSHA2018/source_models/zones/shapefiles/Domains/Domains_Sep2011.shp')
drawshapepoly(m, plt, sf, lw=0.75, edgecolor='r', fillshape=False)
# set colorbar
plt.gcf().subplots_adjust(bottom=0.1)
cax = fig.add_axes([0.33,0.05,0.34,0.02]) # setup colorbar axes.
norm = colors.Normalize(vmin=b_min, vmax=b_max)
cb = colorbar.ColorbarBase(cax, cmap=cmap, norm=norm, orientation='horizontal', alpha=1.0)
# set cb labels
#linticks = array([0.01, 0.03, 0.1, 0.3 ])
ticks = arange(b_min, b_max+0.1, 0.1)
cb.set_ticks(ticks)
labels = [str('%0.1f' % x) for x in ticks]
#cb.set_ticklabels(labels, fontsize=10)
cb.ax.set_xticklabels(labels, fontsize=10)
b_min = 0.8
b_max = 1.3
cindex = []
# loop thru b values
for b, n0 in zip(src_bval, src_n0):
if not isnan(n0):
idx = interp(b, [b_min, b_max], [0, ncolours-1])
cindex.append(int(round(idx)))
# get cmap
cmap = plt.get_cmap('YlOrRd', ncolours)
# plt source zone boundary
drawshapepoly(m2, plt, sf, cindex=cindex, cmap=cmap, ncolours=ncolours, fillshape=True)
labelpolygon(m2, plt, sf, 'CODE', value='CBGZ', col='k', fweight='normal', fsize=14, addOutline=False)
x,y = m2(130., -35.35)
plt.text(x, y, 'EBGZ', va='center', ha='center', fontsize=14)
xlim = ax.get_xlim()
xtxt = xlim[1] * 0.02
ylim = ax.get_ylim()
ytxt = ylim[1] * 0.02
plt.text(xtxt, ytxt, 'a)', fontsize=17, va='bottom', ha='left')
# label polygons
#labelpolygon(m2, plt, sf, 'CODE')
###############################################################################
World_Topo_Map
ESRI_Imagery_World_2D - good sat image
NatGeo_World_Map - nice road map - hard to read
'''
##########################################################################################
# add cities
##########################################################################################
numCities = 10
#annotate_cities(numCities, plt, m, marker='s')
##########################################################################################
# add earthquakes
##########################################################################################
'''
shpfile = '../NT/shapefiles/PetroleumTitles28August2019.shp'
shpfile = 'PetroleumTitles28August2019.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sf, col='r',lw=0.75, alpha=0.5, fillshape = True)
'''
#gadat = parse_ga_event_query('earthquakes_export_2012-16_250.edit.csv')
gadat = parse_ga_event_query('2014-2016_earthquakes_export.edit.csv')
la = dictlist2array(gadat, 'lat')
lo = dictlist2array(gadat, 'lon')
mag = dictlist2array(gadat, 'mag_ml')
x, y = m(lo, la)
scatter = plt.scatter(x,
y,
s=-75 + mag * 80,
# get lake ploygons
polygons = []
for polygon in m.lakepolygons:
poly = polygon.get_coords()
plt.fill(poly[:, 0], poly[:, 1], 'lightskyblue')
polygons.append(poly)
##########################################################################################
# add source zones
##########################################################################################
import shapefile
shpfile = 'SECan_H2.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sf, lw=1.5, col='r')
'''
shpfile = 'swcan_crustal.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sf, lw=2., col='b', ls='--', polyline=True)
shpfile = 'swcan_slab.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sf, lw=2., col='k', ls='-', polyline=True)
'''
# set legend
m.plot([0, 0], [10, 10], 'r-', lw=1.5, label='Shallow Area Sources')
plt.legend(loc=1, fontsize=16)
'''
# label thrusts
x, y = m(-132.5, 52.5)
def map_haz(fig, plt, haz_map_file, sitelon, sitelat, **kwargs):
'''
kwargs:
shpfile: path to area source - is a list of files
resolution: c (crude), l (low), i (intermediate), h (high), f (full)
mbuffer: map buffer in degrees
'''
from openquake.nrmllib.hazard.parsers import GMFScenarioParser
from mpl_toolkits.basemap import Basemap
from numpy import arange, array, log10, mean, mgrid, percentile
from matplotlib.mlab import griddata
from matplotlib import colors, colorbar, cm
from os import path
from mapping_tools import drawshapepoly, labelpolygon
import shapefile
# set kwargs
drawshape = False
res = 'c'
mbuff = -0.3
keys = ['shapefile', 'resolution', 'mbuffer']
for key in keys:
if key in kwargs:
if key == 'shapefile':
shpfile = kwargs[key]
drawshape = True
if key == 'resolution':
res = kwargs[key]
if key == 'mbuffer':
mbuff = kwargs[key]
gmfsp = GMFScenarioParser(haz_map_file).parse()
metadata, values = parse_nrml_hazard_map(haz_map_file)
hazvals = []
latlist = []
lonlist = []
for val in values:
lonlist.append(val[0])
latlist.append(val[1])
hazvals.append(val[2])
# get map bounds
llcrnrlat = min(latlist) - mbuff / 2.
urcrnrlat = max(latlist) + mbuff / 2.
llcrnrlon = min(lonlist) - mbuff
urcrnrlon = max(lonlist) + mbuff
lon_0 = mean([llcrnrlon, urcrnrlon])
lat_1 = percentile([llcrnrlat, urcrnrlat], 25)
lat_2 = percentile([llcrnrlat, urcrnrlat], 75)
m = Basemap(llcrnrlon=llcrnrlon,llcrnrlat=llcrnrlat, \
urcrnrlon=urcrnrlon,urcrnrlat=urcrnrlat,
projection='lcc',lat_1=lat_1,lat_2=lat_2,lon_0=lon_0,
resolution=res,area_thresh=1000.)
m.drawcoastlines(linewidth=0.5, color='k')
m.drawcountries()
# draw parallels and meridians.
m.drawparallels(arange(-90., 90., 1.),
labels=[1, 0, 0, 0],
fontsize=10,
dashes=[2, 2],
color='0.5',
linewidth=0.5)
m.drawmeridians(arange(0., 360., 1.),
labels=[0, 0, 0, 1],
fontsize=10,
dashes=[2, 2],
color='0.5',
linewidth=0.5)
# make regular grid
N = 150j
extent = (min(lonlist), max(lonlist), min(latlist), max(latlist))
xs, ys = mgrid[extent[0]:extent[1]:N, extent[2]:extent[3]:N]
resampled = griddata(array(lonlist), array(latlist), log10(array(hazvals)),
xs, ys)
#############################################################################
# transform grid to basemap
# get 1D lats and lons for map transform
lons = ogrid[extent[0]:extent[1]:N]
lats = ogrid[extent[2]:extent[3]:N]
# transform to map projection
if max(lonlist) - min(lonlist) < 1:
transspace = 500
elif max(lonlist) - min(lonlist) < 5:
transspace = 1000
elif max(lonlist) - min(lonlist) < 10:
transspace = 2000
else:
transspace = 5000
nx = int((m.xmax - m.xmin) / transspace) + 1
ny = int((m.ymax - m.ymin) / transspace) + 1
transhaz = m.transform_scalar(resampled.T, lons, lats, nx, ny)
m.imshow(transhaz,
cmap='Spectral_r',
extent=extent,
vmin=-2,
vmax=log10(2.),
zorder=0)
# plot site
xx, yy = m(sitelon, sitelat)
plt.plot(xx, yy, '*', ms=20, mec='k', mew=2.0, mfc="None")
# superimpose area source shapefile
if drawshape == True:
for shp in shpfile:
sf = shapefile.Reader(shp)
drawshapepoly(m, plt, sf, col='k', lw=1.5, polyline=True)
labelpolygon(m, plt, sf, 'CODE', fsize=14)
# set colourbar
# set cb for final fig
plt.gcf().subplots_adjust(bottom=0.1)
cax = fig.add_axes([0.6, 0.05, 0.25, 0.02]) # setup colorbar axes.
norm = colors.Normalize(vmin=-2, vmax=log10(2.))
cb = colorbar.ColorbarBase(cax,
cmap=cm.Spectral_r,
norm=norm,
orientation='horizontal')
# set cb labels
#linticks = array([0.01, 0.03, 0.1, 0.3 ])
logticks = arange(-2, log10(2.), 0.25)
cb.set_ticks(logticks)
labels = [str('%0.2f' % 10**x) for x in logticks]
cb.set_ticklabels(labels)
# get map probabiltiy from filename
mprob = path.split(haz_map_file)[-1].split('_')[-1].split('-')[0]
probstr = str(int(float(mprob) * 100))
# set colourbar title
if metadata['statistics'] == 'mean':
titlestr = ''.join((metadata['imt'], ' ', metadata['sa_period'], ' s ', \
probstr,'% in ',metadata['investigation_time'][0:-2], \
' Year Mean Hazard (g)'))
#cb.set_ticklabels(labels)
cb.set_label(titlestr, fontsize=12)
return plt
mfc='k',
markersize=(-10 + lm * 5),
alpha=1.,
zorder=len(mag) + 1,
lw=2)
legh.append(h[0])
l = plt.legend(legh, ('MW 4.0', 'MW 5.0', 'MW 6.0'), loc=2, numpoints=1)
l.set_zorder(len(mag) + 5)
##########################################################################################
# add domains
##########################################################################################
shpfile = '/nas/active/ops/community_safety/ehp/georisk_earthquake/modelling/sandpits/tallen/NSHA2018/source_models/zones/shapefiles/Domains/Domains_Sep2011.shp'
sfz = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sfz, edgecolor='r', col='r', lw=1., zorder=1)
##########################################################################################
# make map inset
##########################################################################################
from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
axins = zoomed_inset_axes(ax, 0.115, loc=1)
m2 = Basemap(projection='merc',\
llcrnrlon=109,llcrnrlat=-45, \
urcrnrlon=156,urcrnrlat=-9,\
rsphere=6371200.,resolution='l',area_thresh=10000)
m2.drawmapboundary(fill_color='0.8')
m2.fillcontinents(color='w', lake_color='0.8') #, zorder=0)
x, y = m(0, 0)
h = m.plot(x, y, 'ko', mfc='k', markersize=(-4 + lm*3.2), alpha=1., zorder=len(cat.data['magnitude'])+1, lw=2)
legh.append(h[0])
l = plt.legend(legh, ('MW 3.0', 'MW 5.0', 'MW 7.0'), loc=1, numpoints=1)
l.set_zorder(len(cat.data['magnitude'])+5)
'''
##########################################################################################
# add source zones
##########################################################################################
import shapefile
shpfile = 'swcan_shallow_area.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sf, lw=1.5, col='r')
shpfile = 'swcan_crustal.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sf, lw=2., col='b', ls='--', polyline=True)
shpfile = 'swcan_slab.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sf, lw=2., col='k', ls='-', polyline=True)
# set legend
m.plot([0,0],[10, 10], 'r-', lw=1.5, label='Shallow Area Sources')
m.plot([0,0],[10, 10], 'b--', lw=2.0, label='Transform Fault Sources')
m.plot([0,0],[10, 10], 'k-', lw=2.5, label='Thrust Fault Sources')
plt.legend(loc=1, fontsize=16)
data = loadtxt('scenario_lat_lons.csv', delimiter=',')
x, y = m(data[:, 1], data[:, 0])
plt.plot(x,
y,
'*',
mfc='r',
mec='k',
mew=0.25,
markersize=8,
label='Scenario Localities')
'''
path_effect=[path_effects.withStroke(linewidth=3, foreground='w')]
x, y = m(data[:,0]+0.75, data[:,1]+0.5)
for i in range(0, len(x)):
plt.text(x[i], y[i], 'E'+str(i+1), fontsize=14, c='b', \
va='bottom', ha='left', style='italic', path_effects=path_effect)
'''
plt.legend(loc=3, fontsize=14, numpoints=1)
# add neotectonic domains
shpfile = '/nas/active/ops/community_safety/ehp/georisk_earthquake/modelling/sandpits/tallen/NSHA2018/source_models/zones/shapefiles/Domains/Domains_Sep2011.shp'
sf = shapefile.Reader(shpfile)
drawshapepoly(m, plt, sf, col='k', lw=.5)
plt.savefig('scenario_locations.png',
format='png',
dpi=300,
bbox_inches='tight')
#plt.savefig('neac_ml_zones.svg', format='svg', bbox_inches='tight')
plt.show()
