def test_project():
data = np.array([[0, 0, 1, 0, 0], [0, 0, 1, 0, 0], [1, 1, 1, 1, 1],
[0, 0, 1, 0, 0], [0, 0, 1, 0, 0]],
dtype=np.int32)
geodict = {
'xmin': 50,
'xmax': 50.4,
'ymin': 50,
'ymax': 50.4,
'dx': 0.1,
'dy': 0.1,
'nx': 5,
'ny': 5
}
gd = GeoDict(geodict)
grid = GDALGrid(data, gd)
projstr = "+proj=utm +zone=40 +north +ellps=WGS84 +datum=WGS84 +units=m +no_defs "
newgrid = grid.project(projstr, method='nearest')
try:
tdir = tempfile.mkdtemp()
outfile = os.path.join(tdir, 'output.bil')
grid.save(outfile)
with rasterio.open(outfile) as src:
aff = get_affine(src)
data = src.read(1)
src_crs = CRS().from_string(GeoDict.DEFAULT_PROJ4).to_dict()
dst_crs = CRS().from_string(projstr).to_dict()
nrows, ncols = data.shape
left = aff.xoff
top = aff.yoff
right, bottom = aff * (ncols - 1, nrows - 1)
dst_transform, width, height = calculate_default_transform(
src_crs, dst_crs, ncols, nrows, left, bottom, right, top)
destination = np.zeros((height, width))
reproject(data,
destination,
src_transform=aff,
src_crs=src_crs,
dst_transform=dst_transform,
dst_crs=dst_crs,
src_nodata=src.nodata,
dst_nodata=np.nan,
resampling=Resampling.nearest)
x = 1
except:
pass
finally:
shutil.rmtree(tdir)
def test_project():
data = np.array([[0,0,1,0,0],
[0,0,1,0,0],
[1,1,1,1,1],
[0,0,1,0,0],
[0,0,1,0,0]],dtype=np.int32)
geodict = {'xmin':50,'xmax':50.4,'ymin':50,'ymax':50.4,'dx':0.1,'dy':0.1,'nx':5,'ny':5}
gd = GeoDict(geodict)
grid = GDALGrid(data,gd)
projstr = "+proj=utm +zone=40 +north +ellps=WGS84 +datum=WGS84 +units=m +no_defs "
newgrid = grid.project(projstr,method='nearest')
try:
tdir = tempfile.mkdtemp()
outfile = os.path.join(tdir,'output.bil')
grid.save(outfile)
with rasterio.open(outfile) as src:
aff = src.transform
data = src.read(1)
src_crs = CRS().from_string(GeoDict.DEFAULT_PROJ4).to_dict()
dst_crs = CRS().from_string(projstr).to_dict()
nrows,ncols = data.shape
left = aff.xoff
top = aff.yoff
right,bottom = aff * (ncols-1, nrows-1)
dst_transform,width,height = calculate_default_transform(src_crs,dst_crs,
ncols,nrows,
left,bottom,
right,top)
destination = np.zeros((height,width))
reproject(data,
destination,
src_transform=aff,
src_crs=src_crs,
dst_transform=dst_transform,
dst_crs=dst_crs,
src_nodata=src.nodata,
dst_nodata=np.nan,
resampling=Resampling.nearest)
x = 1
except:
pass
finally:
shutil.rmtree(tdir)
def test_project():
# test projecting a grid that wraps the 180 meridian
gd = GeoDict.createDictFromBox(175, -175, -5, 5, 1.0, 1.0)
ncells = gd.ny * gd.nx
data = np.arange(0.0, ncells).reshape(gd.ny, gd.nx)
grid = GDALGrid(data, gd)
projstr = "+proj=merc +lat_ts=55 +lon_0=180 +ellps=WGS84"
newgrid = grid.project(projstr, method='nearest')
proj = pyproj.Proj(projstr)
# what would the ul/lr corners be?
ulx, uly = proj(grid._geodict.xmin, grid._geodict.ymax)
lrx, lry = proj(grid._geodict.xmax, grid._geodict.ymin)
# what if we back-project?
newxmin, newymax = proj(newgrid._geodict.xmin,
newgrid._geodict.ymax, inverse=True)
newxmax, newymin = proj(newgrid._geodict.xmax,
newgrid._geodict.ymin, inverse=True)
x = 1
# test simple projection
data = np.array([[0, 0, 1, 0, 0],
[0, 0, 1, 0, 0],
[1, 1, 1, 1, 1],
[0, 0, 1, 0, 0],
[0, 0, 1, 0, 0]], dtype=np.int32)
geodict = {'xmin': 50, 'xmax': 50.4, 'ymin': 50,
'ymax': 50.4, 'dx': 0.1, 'dy': 0.1, 'nx': 5, 'ny': 5}
gd = GeoDict(geodict)
grid = GDALGrid(data, gd)
projstr = "+proj=utm +zone=40 +north +ellps=WGS84 +datum=WGS84 +units=m +no_defs "
newgrid = grid.project(projstr, method='nearest')
try:
tdir = tempfile.mkdtemp()
outfile = os.path.join(tdir, 'output.bil')
grid.save(outfile)
with rasterio.open(outfile) as src:
aff = get_affine(src)
data = src.read(1)
src_crs = CRS().from_string(GeoDict.DEFAULT_PROJ4).to_dict()
dst_crs = CRS().from_string(projstr).to_dict()
nrows, ncols = data.shape
left = aff.xoff
top = aff.yoff
right, bottom = aff * (ncols-1, nrows-1)
dst_transform, width, height = calculate_default_transform(src_crs, dst_crs,
ncols, nrows,
left, bottom,
right, top)
destination = np.zeros((height, width))
reproject(data,
destination,
src_transform=aff,
src_crs=src_crs,
dst_transform=dst_transform,
dst_crs=dst_crs,
src_nodata=src.nodata,
dst_nodata=np.nan,
resampling=Resampling.nearest)
x = 1
except:
pass
finally:
shutil.rmtree(tdir)
def makeTestData():
# make test layers
X = ['friction', 'slope', 'vs30', 'cti1', 'precip']
config = OrderedDict()
config.setdefault('logistic_models', {}).setdefault('test_model', {})
config['logistic_models']['test_model'].setdefault('shortref', 'Name et al. year')
config['logistic_models']['test_model'].setdefault('longref', 'full reference')
config['logistic_models']['test_model'].setdefault('layers', {})
config['logistic_models']['test_model'].setdefault('interpolations', {})
config['logistic_models']['test_model'].setdefault('terms', {})
config['logistic_models']['test_model'].setdefault('coefficients', {})['b0'] = 3.5
for k, items in enumerate(X):
coef = 'b%1d' % (k+1)
# make a GDALGrid object
testgrid = GDALGrid(eval(items), geodict)
# Save the file
if items == 'precip':
try:
os.mkdir('test_precip')
except:
pass
filename = 'test_precip/prec_Jan.bil' # Only make January for testing
else:
filename = 'test_%s.bil' % (items)
testgrid.save(filename, format='EHdr')
# add to test config file
config['logistic_models']['test_model']['layers'].update({items: {'file': filename.split('/')[0],
'units': units[k], 'longref': 'longref',
'shortref': 'shortref'}})
config['logistic_models']['test_model']['interpolations'].update({items: 'nearest'})
config['logistic_models']['test_model']['terms'].update({coef: terms[k]})
config['logistic_models']['test_model']['coefficients'].update({coef: coefficients[k]})
config['logistic_models']['test_model']['gfeype'] = 'landslide'
config['logistic_models']['test_model']['baselayer'] = 'slope'
config['logistic_models']['test_model']['slopemin'] = 5.
config['logistic_models']['test_model']['slopemax'] = 90.
# Make test_shakegrid and test_uncert
eventDict = OrderedDict([('event_id', 'test'),
('lon', 0.5),
('lat', 0.5),
('event_timestamp', datetime(2000, 1, 5, 0, 30, 55)),
('event_network', 'na'),
('magnitude', 6.0),
('event_description', 'Test event'),
('depth', 5.0)])
shakeDict = OrderedDict([('process_timestamp',
datetime(2000, 1, 6, 20, 38, 19)),
('event_id', 'test'),
('shakemap_version', 2),
('code_version', '1 billion'),
('shakemap_event_type', 'TEST'),
('map_status', 'TEST'),
('shakemap_id', 'test'),
('shakemap_originator', 'na')])
uncertaintyDict = {}
layers1 = {'pga': pga, 'pgv': pgv}
shakegrid = ShakeGrid(layers1, geodict, eventDict, shakeDict, uncertaintyDict)
shakegrid.save('test_shakegrid.xml')
layers2 = {'stdpga': stdpga}
uncertgrid = ShakeGrid(layers2, geodict, eventDict, shakeDict, uncertaintyDict)
uncertgrid.save('test_uncert.xml')
C = ConfigObj(config)
C.filename = 'test.ini'
C.write()
return config
def makeTestData():
# make test layers and config files (model, and mapping)
Xmod = ['friction', 'slope', 'vs30', 'cti1', 'precip']
terms = ['friction', 'slope/100.', 'log(vs30)', 'cti1', 'precipMONTH']
coefficients = [0.3, 2.1, -0.5, 0.01, 1.0]
Xhaz = ['susceptibility']
Xgod = ['cohesion', 'friction', 'slope']
Xcla = ['cohesion', 'friction', 'slope', 'watertable']
configModel = OrderedDict()
configHazus = OrderedDict()
configGodt = OrderedDict()
configClassic = OrderedDict()
# Work on model configs
#LOGISTIC
configModel.setdefault('test_model', {})
configModel['test_model'].setdefault('shortref', 'Name et al. year')
configModel['test_model'].setdefault('longref', 'full reference')
configModel['test_model'].setdefault('layers', {})
configModel['test_model'].setdefault('interpolations', {})
configModel['test_model'].setdefault('terms', {})
configModel['test_model'].setdefault('coefficients', {})['b0'] = '3.5'
configModel['test_model'].setdefault(
'display_options', {
'lims': {
'model': 'np.linspace(0., 0.4, 10)'
},
'colors': {
'default': 'cm.inferno',
'alpha': '0.7',
'model': 'cm.jet'
},
'logscale': {
'model': 'False'
},
'maskthresholds': {
'model': '0.001'
}
})
configModel['test_model']['gfeype'] = 'landslide'
configModel['test_model']['baselayer'] = 'slope'
configModel['test_model']['slopemin'] = 5.
configModel['test_model']['slopemax'] = 90.
configModel['test_model']['display_options'].setdefault(
'pga', {
'lims': 'None',
'colors': 'cm.jet',
'logscale': 'True'
})
configModel['test_model']['display_options'].setdefault(
'pgv', {
'lims': 'None',
'colors': 'cm.jet',
'logscale': 'False'
})
# HAZUS
configHazus.setdefault('hazus', {})
configHazus['hazus'].setdefault('shortref', 'Name et al. year')
configHazus['hazus'].setdefault('longref', 'full reference')
configHazus['hazus']['gfeype'] = 'landslide'
configHazus['hazus'].setdefault('layers', {})
configHazus['hazus'].setdefault('parameters', {'dnthresh': 5.})
configHazus['hazus'].setdefault(
'display_options', {
'lims': {
'model': 'np.linspace(0., 0.4, 10)'
},
'colors': {
'default': 'cm.inferno',
'alpha': '0.7',
'model': 'cm.jet'
},
'logscale': {
'model': 'False'
},
'maskthresholds': {
'model': '0.001'
}
})
configHazus['hazus']['display_options'].setdefault('susceptibility', {
'lims': 'None',
'colors': 'cm.jet',
'logscale': 'True'
})
# GODT
configGodt.setdefault('godt_2008', {})
configGodt['godt_2008'].setdefault('shortref', 'Name et al. year')
configGodt['godt_2008'].setdefault('longref', 'full reference')
configGodt['godt_2008']['gfeype'] = 'landslide'
configGodt['godt_2008'].setdefault('layers', {})
configGodt['godt_2008'].setdefault(
'parameters', {
'thick': '2.4',
'uwt': '15.7',
'nodata_cohesion': '1.0',
'nodata_friction': '26.',
'dnthresh': '5.',
'fsthresh': '1.01',
'acthresh': '0.05'
})
configGodt['godt_2008'].setdefault(
'display_options', {
'lims': {
'model': 'np.linspace(0., 0.4, 10)'
},
'colors': {
'default': 'cm.inferno',
'alpha': '0.7',
'model': 'cm.jet'
},
'logscale': {
'model': 'False'
},
'maskthresholds': {
'model': '0.001'
}
})
configGodt['godt_2008']['display_options'].setdefault(
'pga', {
'lims': 'None',
'colors': 'cm.jet',
'logscale': 'True'
})
# NEWMARK
configClassic.setdefault('classic_newmark', {})
configClassic['classic_newmark'].setdefault('shortref', 'Name et al. year')
configClassic['classic_newmark'].setdefault('longref', 'full reference')
configClassic['classic_newmark']['gfeype'] = 'landslide'
configClassic['classic_newmark'].setdefault('layers', {})
configClassic['classic_newmark'].setdefault(
'parameters', {
'thick': '2.4',
'uwt': '15.7',
'nodata_cohesion': '1.0',
'nodata_friction': '26.',
'dnthresh': '5.',
'fsthresh': '1.01',
'acthresh': '0.05',
'slopethresh': '5.',
'm': '0.5'
})
configClassic['classic_newmark'].setdefault(
'display_options', {
'lims': {
'model': 'np.linspace(0., 0.4, 10)'
},
'colors': {
'default': 'cm.inferno',
'alpha': '0.7',
'model': 'cm.jet'
},
'logscale': {
'model': 'False'
},
'maskthresholds': {
'model': '0.001'
}
})
configClassic['classic_newmark']['display_options'].setdefault(
'pga', {
'lims': 'None',
'colors': 'cm.jet',
'logscale': 'True'
})
for k, items in enumerate(Xmod):
coef = 'b%1d' % (k + 1)
# make a GDALGrid object
testgrid = GDALGrid(eval(items), geodict)
# Save the file
if items == 'precip':
try:
os.mkdir('test_precip')
except:
pass
filename = 'test_precip/prec_Jan.bil' # Only make January for testing
else:
filename = 'test_%s.bil' % (items)
testgrid.save(filename, format='EHdr')
# add to test config file
configModel['test_model']['layers'].update({
items: {
'file': filename.split('/')[0],
'units': units[items],
'longref': 'longref',
'shortref': 'shortref'
}
})
configModel['test_model']['interpolations'].update({items: 'nearest'})
configModel['test_model']['terms'].update({coef: terms[k]})
configModel['test_model']['coefficients'].update(
{coef: coefficients[k]})
configModel['test_model']['display_options']['lims'].update(
{items: 'None'})
configModel['test_model']['display_options']['colors'].update(
{items: 'None'})
configModel['test_model']['display_options']['logscale'].update(
{items: 'False'})
configModel['test_model']['display_options']['maskthresholds'].update(
{items: 'None'})
for k, items in enumerate(Xhaz):
# Save the file if not already saved
filename = 'test_%s.bil' % (items)
if items == 'susceptibility':
testgrid = GDALGrid(eval(items), susgeodict)
testgrid.save(filename, format='EHdr')
# add to test config file
configHazus['hazus']['layers'].update({
items: {
'file': filename,
'units': units[items],
'longref': 'longref',
'shortref': 'shortref'
}
})
configHazus['hazus']['display_options']['lims'].update({items: 'None'})
configHazus['hazus']['display_options']['colors'].update(
{items: 'None'})
configHazus['hazus']['display_options']['logscale'].update(
{items: 'False'})
configHazus['hazus']['display_options']['maskthresholds'].update(
{items: 'None'})
for k, items in enumerate(Xgod):
# make a GDALGrid object
if items == 'slope':
testgrid = GDALGrid(eval('slopeGodt'), geodict)
else:
testgrid = GDALGrid(eval(items), geodict)
# Save the file
filename = 'test_%s.bil' % (items)
word = 'file'
if items == 'slope':
word = 'filepath'
try:
os.mkdir('test_slope_quantiles_godt')
except:
pass
for j, slp in enumerate(slopequants):
filename = 'test_slope_quantiles_godt/slope%s.bil' % (
slopequantnames[j]) # Only make January for testing
temp = GDALGrid(eval('slopeGodt') * slopequants[j], geodict)
temp.save(filename, format='EHdr')
filename = 'test_slope_quantiles_godt'
elif items == 'cohesion':
testgrid.save(filename, format='EHdr')
# add to test config file
configGodt['godt_2008']['layers'].update({
items: {
word: filename,
'units': units[items],
'longref': 'longref',
'shortref': 'shortref'
}
})
configGodt['godt_2008']['display_options']['lims'].update(
{items: 'None'})
configGodt['godt_2008']['display_options']['colors'].update(
{items: 'None'})
configGodt['godt_2008']['display_options']['logscale'].update(
{items: 'False'})
configGodt['godt_2008']['display_options']['maskthresholds'].update(
{items: 'None'})
for k, items in enumerate(Xcla):
# make a GDALGrid object
testgrid = GDALGrid(eval(items), geodict)
# Save the file
filename = 'test_%s.bil' % (items)
if items == 'watertable':
testgrid.save(filename, format='EHdr')
# add to test config file
configClassic['classic_newmark']['layers'].update({
items: {
'file': filename,
'units': units[items],
'longref': 'longref',
'shortref': 'shortref'
}
})
configClassic['classic_newmark']['display_options']['lims'].update(
{items: 'None'})
configClassic['classic_newmark']['display_options']['colors'].update(
{items: 'None'})
configClassic['classic_newmark']['display_options']['logscale'].update(
{items: 'False'})
configClassic['classic_newmark']['display_options'][
'maskthresholds'].update({items: 'None'})
# Make test_shakegrid and test_uncert
eventDict = OrderedDict([
('event_id', 'test'), ('lon', 0.5), ('lat', 0.5),
('event_timestamp', datetime(2000, 1, 5, 0, 30, 55)),
('event_network', 'na'), ('magnitude', 6.0),
('event_description', 'Test event'), ('depth', 5.0)
])
shakeDict = OrderedDict([('process_timestamp',
datetime(2000, 1, 6, 20, 38, 19)),
('event_id', 'test'), ('shakemap_version', 2),
('code_version', '1 billion'),
('shakemap_event_type', 'TEST'),
('map_status', 'TEST'), ('shakemap_id', 'test'),
('shakemap_originator', 'na')])
uncertaintyDict = {}
layers1 = {'pga': pga, 'pgv': pgv}
shakegrid = ShakeGrid(layers1, geodict, eventDict, shakeDict,
uncertaintyDict)
shakegrid.save('test_shakegrid.xml')
layers2 = {'stdpga': stdpga, 'stdpgv': stdpgv}
uncertgrid = ShakeGrid(layers2, geodict, eventDict, shakeDict,
uncertaintyDict)
uncertgrid.save('test_uncert.xml')
layers3 = {'pga': pga1, 'pgv': pgv1}
shakegrid = ShakeGrid(layers3, geodict1, eventDict, shakeDict,
uncertaintyDict)
shakegrid.save('test_shakegrid_bounds.xml')
C = ConfigObj(configModel)
C.filename = 'testconfig_logimodel.ini'
C.write()
C = ConfigObj(configHazus)
C.filename = 'testconfig_hazus.ini'
C.write()
C = ConfigObj(configClassic)
C.filename = 'testconfig_classic.ini'
C.write()
C = ConfigObj(configGodt)
C.filename = 'testconfig_godt.ini'
C.write()
configMap = OrderedDict({
'dem': {
'file': 'None'
},
'roads': {
'file': 'None'
},
'cities': {
'file': 'None'
},
'ocean': {
'file': 'None'
},
'colors': {
'roadcolor': '808080',
'countrycolor': '474747',
'watercolor': 'B8EEFF'
}
})
C = ConfigObj(configMap)
C.filename = 'testconfig_map.ini'
C.write()
