def run_viewshed_by_cpu(tid, obs, dem, output,
vis_basename='vis', maxdst=None, obselevation=None):
# Create GRASS GIS location
loc_name = 'loc_' + str(tid)
gbase = run_grass(output, location=loc_name, srs=dem)
# Start GRASS GIS Session
import grass.script as grass
import grass.script.setup as gsetup
gsetup.init(gbase, output, loc_name, 'PERMANENT')
from glass.g.it.rst import rst_to_grs, grs_to_rst
from glass.g.rst.surf import grs_viewshed
# Send DEM to GRASS GIS
grs_dem = rst_to_grs(dem, 'grs_dem', as_cmd=True)
# Produce Viewshed for each point in obs
for idx, row in obs.iterrows():
vrst = grs_viewshed(
grs_dem, (row.geometry.x, row.geometry.y),
'{}_{}'.format(vis_basename, str(row[obs_id])),
max_dist=maxdst, obs_elv=obselevation
)
frst = grs_to_rst(vrst, os.path.join(output, vrst + '.tif'))
def grscliprst(in_rst, clip_ext, outrst):
"""
Clip Raster using GRASS GIS
"""
import os
from glass.pys.oss import fprop
from glass.g.wenv.grs import run_grass
from glass.g.wenv.grs import rst_to_region
from glass.g.prop.prj import get_epsg
# Get EPSG From Raster
EPSG = get_epsg(in_rst)
if not EPSG:
raise ValueError(
'Cannot get EPSG code of Extent Template File ({})'.format(in_rst))
workspace = os.path.dirname(outrst)
loc = 'loc_' + fprop(outrst, 'fn')
# Create GRASS GIS Session
gbase = run_grass(workspace, location=loc, srs=EPSG)
import grass.script.setup as gsetup
gsetup.init(gbase, workspace, loc, 'PERMANENT')
# GRASS GIS modules
from glass.g.it.rst import rst_to_grs, grs_to_rst, grs_to_mask
# Add data to GRASS GIS
rst = rst_to_grs(in_rst, fprop(in_rst, 'fn'), as_cmd=True)
clip = rst_to_grs(clip_ext, fprop(clip_ext, 'fn'), as_cmd=True)
# Set New region
rst_to_region(clip)
# Set Mask
grs_to_mask(clip)
# Export result
return grs_to_rst(rst, outrst)
def run_slope(tid, inrsts, outfolder, oname, percentage):
"""
Thread function
"""
iirsts = inrsts.mdt.tolist()
# Create GRASS GIS Location
loc_name = f'thread_{str(tid)}'
gbase = run_grass(
outfolder, location=loc_name, srs=iirsts[0]
)
# Start GRASS GIS Session
import grass.script as grass
import grass.script.setup as gsetup
gsetup.init(gbase, outfolder, loc_name, 'PERMANENT')
from glass.g.it.rst import rst_to_grs, grs_to_rst
from glass.g.rst.surf import slope
from glass.g.wenv.grs import rst_to_region
for rst in iirsts:
# Import data
mdt = rst_to_grs(rst, fprop(rst, 'fn'))
# Set region
rst_to_region(mdt)
# Get ID in name
mdt_id = re.search(r'\d+', mdt).group()
# Get slope
if percentage:
slope_perc = slope(
mdt, f"pp_{oname}_{mdt_id}",
data='percent'
)
slope_degr = slope(
mdt, f"{oname}_{mdt_id}", data='degrees'
)
# Export
if percentage:
grs_to_rst(slope_perc, os.path.join(
percentage, slope_degr + '.tif'
))
grs_to_rst(slope_degr, os.path.join(
outfolder, slope_degr + '.tif'
))
def rsts_to_shps(rstfolder, outfolder, rsttemplate):
"""
Rasters in folder to Shapefile
this script uses GRASS GIS
"""
import os
from glass.pys.oss import lst_ff, fprop
from glass.g.wenv.grs import run_grass
# List Raster Files
rsts = lst_ff(rstfolder, file_format='tif')
# Start GRASS GIS Session
loc = 'convrst'
grsbase = run_grass(outfolder, location=loc, srs=rsttemplate)
import grass.script.setup as gsetup
gsetup.init(grsbase, outfolder, loc, 'PERMANENT')
from glass.g.it.rst import rst_to_grs
from glass.g.it.shp import grs_to_shp
for rst in rsts:
grs_rst = rst_to_grs(rst, fprop(rst, 'fn'), as_cmd=True)
# to polygon
grs_shp = rst_to_polyg(grs_rst,
grs_rst + "_shp",
rstColumn="value",
gisApi='grasscmd')
grs_to_shp(grs_shp, os.path.join(outfolder, grs_rst + '.shp'), 'area')
return outfolder
def raster_based(osmdata, nomenclature, refRaster, lulcRst,
overwrite=None, dataStore=None, roadsAPI='POSTGIS'):
"""
Convert OSM Data into Land Use/Land Cover Information
An raster based approach.
TODO: Add detailed description
"""
# ************************************************************************ #
# Python Modules from Reference Packages #
# ************************************************************************ #
import datetime; import os; import pandas; import copy
# ************************************************************************ #
# glass dependencies #
# ************************************************************************ #
from glass.pys.oss import mkdir, fprop
from glass.g.prop import check_isRaster
from glass.g.prop.prj import get_rst_epsg
from glass.g.wenv.grs import run_grass
if roadsAPI == 'POSTGIS':
from glass.ng.sql.db import create_db
from glass.g.it.db import osm_to_psql
from glass.ete.osm2lulc.mod2 import roads_sqdb
from glass.ng.sql.bkup import dump_db
from glass.ng.sql.db import drop_db
else:
from glass.g.it.osm import osm_to_sqdb
from glass.ete.osm2lulc.mod2 import grs_rst_roads
from glass.ete.osm2lulc.utils import osm_project, add_lulc_to_osmfeat, osmlulc_rsttbl
from glass.ete.osm2lulc.utils import get_ref_raster
from glass.ete.osm2lulc.mod1 import grs_rst
from glass.ete.osm2lulc.m3_4 import rst_area
from glass.ete.osm2lulc.mod5 import basic_buffer
from glass.ete.osm2lulc.mod6 import rst_pnt_to_build
# ************************************************************************ #
# Global Settings #
# ************************************************************************ #
# Check if input parameters exists!
if not os.path.exists(os.path.dirname(lulcRst)):
raise ValueError('{} does not exist!'.format(os.path.dirname(lulcRst)))
if not os.path.exists(osmdata):
raise ValueError('File with OSM DATA ({}) does not exist!'.format(osmdata))
if not os.path.exists(refRaster):
raise ValueError('File with reference area ({}) does not exist!'.format(refRaster))
# Check if Nomenclature is valid
nomenclature = "URBAN_ATLAS" if nomenclature != "URBAN_ATLAS" and \
nomenclature != "CORINE_LAND_COVER" and \
nomenclature == "GLOBE_LAND_30" else nomenclature
time_a = datetime.datetime.now().replace(microsecond=0)
workspace = os.path.join(os.path.dirname(
lulcRst), 'osmtolulc') if not dataStore else dataStore
# Check if workspace exists
if os.path.exists(workspace):
if overwrite:
mkdir(workspace)
else:
raise ValueError('Path {} already exists'.format(workspace))
else:
mkdir(workspace)
# Get Ref Raster
refRaster, epsg = get_ref_raster(refRaster, workspace, cellsize=2)
from glass.ete.osm2lulc import PRIORITIES, osmTableData, LEGEND
__priorites = PRIORITIES[nomenclature]
__legend = LEGEND[nomenclature]
time_b = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# Convert OSM file to SQLITE DB or to POSTGIS DB #
# ************************************************************************ #
if roadsAPI == 'POSTGIS':
osm_db = create_db(fprop(
osmdata, 'fn', forceLower=True), overwrite=True)
osm_db = osm_to_psql(osmdata, osm_db)
else:
osm_db = osm_to_sqdb(osmdata, os.path.join(workspace, 'osm.sqlite'))
time_c = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# Add Lulc Classes to OSM_FEATURES by rule #
# ************************************************************************ #
add_lulc_to_osmfeat(osm_db, osmTableData, nomenclature, api=roadsAPI)
time_d = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# Transform SRS of OSM Data #
# ************************************************************************ #
osmTableData = osm_project(
osm_db, epsg, api=roadsAPI,
isGlobeLand=None if nomenclature != 'GLOBE_LAND_30' else True
)
time_e = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# Start a GRASS GIS Session #
# ************************************************************************ #
grass_base = run_grass(
workspace, grassBIN='grass78', location='grloc', srs=epsg)
import grass.script as grass
import grass.script.setup as gsetup
gsetup.init(grass_base, workspace, 'grloc', 'PERMANENT')
# ************************************************************************ #
# IMPORT SOME glass MODULES FOR GRASS GIS #
# ************************************************************************ #
from glass.g.it.rst import rst_to_grs, grs_to_rst
from glass.g.rst.mos import rsts_to_mosaic
from glass.g.wenv.grs import rst_to_region
# ************************************************************************ #
# SET GRASS GIS LOCATION EXTENT #
# ************************************************************************ #
extRst = rst_to_grs(refRaster, 'extent_raster')
rst_to_region(extRst)
time_f = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# MapResults #
mergeOut = {}
# ************************************************************************ #
# ************************************************************************ #
# 1 - Selection Rule #
# ************************************************************************ #
"""
selOut = {
cls_code : rst_name, ...
}
"""
selOut, timeCheck1 = grs_rst(osm_db, osmTableData['polygons'], api=roadsAPI)
for cls in selOut:
mergeOut[cls] = [selOut[cls]]
time_g = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# 2 - Get Information About Roads Location #
# ************************************************************************ #
"""
roads = {
cls_code : rst_name, ...
}
"""
if roadsAPI != 'POSTGIS':
roads, timeCheck2 = grs_rst_roads(
osm_db, osmTableData['lines'], osmTableData['polygons'],
workspace, 1221 if nomenclature != "GLOBE_LAND_30" else 801
)
else:
roadCls = 1221 if nomenclature != "GLOBE_LAND_30" else 801
roads, timeCheck2 = roads_sqdb(
osm_db, osmTableData['lines'], osmTableData['polygons'],
apidb='POSTGIS', asRst=roadCls
)
roads = {roadCls : roads}
for cls in roads:
if cls not in mergeOut:
mergeOut[cls] = [roads[cls]]
else:
mergeOut[cls].append(roads[cls])
time_h = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# 3 - Area Upper than #
# ************************************************************************ #
"""
auOut = {
cls_code : rst_name, ...
}
"""
if nomenclature != 'GLOBE_LAND_30':
auOut, timeCheck3 = rst_area(
osm_db, osmTableData['polygons'], UPPER=True, api=roadsAPI
)
for cls in auOut:
if cls not in mergeOut:
mergeOut[cls] = [auOut[cls]]
else:
mergeOut[cls].append(auOut[cls])
time_l = datetime.datetime.now().replace(microsecond=0)
else:
timeCheck3 = None
time_l = None
# ************************************************************************ #
# 4 - Area Lower than #
# ************************************************************************ #
"""
alOut = {
cls_code : rst_name, ...
}
"""
if nomenclature != 'GLOBE_LAND_30':
alOut, timeCheck4 = rst_area(
osm_db, osmTableData['polygons'], UPPER=None, api=roadsAPI
)
for cls in alOut:
if cls not in mergeOut:
mergeOut[cls] = [alOut[cls]]
else:
mergeOut[cls].append(alOut[cls])
time_j = datetime.datetime.now().replace(microsecond=0)
else:
timeCheck4 = None
time_j = None
# ************************************************************************ #
# 5 - Get data from lines table (railway | waterway) #
# ************************************************************************ #
"""
bfOut = {
cls_code : rst_name, ...
}
"""
bfOut, timeCheck5 = basic_buffer(
osm_db, osmTableData['lines'], workspace, apidb=roadsAPI
)
for cls in bfOut:
if cls not in mergeOut:
mergeOut[cls] = [bfOut[cls]]
else:
mergeOut[cls].append(bfOut[cls])
time_m = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# 7 - Assign untagged Buildings to tags #
# ************************************************************************ #
if nomenclature != "GLOBE_LAND_30":
buildsOut, timeCheck7 = rst_pnt_to_build(
osm_db, osmTableData['points'], osmTableData['polygons'],
api_db=roadsAPI
)
for cls in buildsOut:
if cls not in mergeOut:
mergeOut[cls] = buildsOut[cls]
else:
mergeOut[cls] += buildsOut[cls]
time_n = datetime.datetime.now().replace(microsecond=0)
else:
timeCheck7 = None
time_n = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# Produce LULC Map #
# ************************************************************************ #
"""
Merge all results for one cls into one raster
mergeOut = {
cls_code : [rst_name, rst_name, ...], ...
}
into
mergeOut = {
cls_code : patched_raster, ...
}
"""
for cls in mergeOut:
if len(mergeOut[cls]) == 1:
mergeOut[cls] = mergeOut[cls][0]
else:
mergeOut[cls] = rsts_to_mosaic(
mergeOut[cls], 'mosaic_{}'.format(str(cls)), api="grass"
)
time_o = datetime.datetime.now().replace(microsecond=0)
"""
Merge all Class Raster using a priority rule
"""
__priorities = PRIORITIES[nomenclature]
lst_rst = []
for cls in __priorities:
if cls not in mergeOut:
continue
else:
lst_rst.append(mergeOut[cls])
outGrs = rsts_to_mosaic(lst_rst, os.path.splitext(
os.path.basename(lulcRst))[0], api="grass"
)
time_p = datetime.datetime.now().replace(microsecond=0)
# Ceck if lulc Rst has an valid format
outIsRst = check_isRaster(lulcRst)
if not outIsRst:
from glass.pys.oss import fprop
lulcRst = os.path.join(
os.path.dirname(lulcRst),
fprop(lulcRst, 'fn') + '.tif'
)
grs_to_rst(outGrs, lulcRst, as_cmd=True)
osmlulc_rsttbl(nomenclature, os.path.join(
os.path.dirname(lulcRst), os.path.basename(lulcRst) + '.vat.dbf'
))
time_q = datetime.datetime.now().replace(microsecond=0)
# Dump Database if PostGIS was used
# Drop Database if PostGIS was used
if roadsAPI == 'POSTGIS':
dump_db(osm_db, os.path.join(
workspace, osm_db + '.sql'
), api='psql')
drop_db(osm_db)
return lulcRst, {
0 : ('set_settings', time_b - time_a),
1 : ('osm_to_sqdb', time_c - time_b),
2 : ('cls_in_sqdb', time_d - time_c),
3 : ('proj_data', time_e - time_d),
4 : ('set_grass', time_f - time_e),
5 : ('rule_1', time_g - time_f, timeCheck1),
6 : ('rule_2', time_h - time_g, timeCheck2),
7 : None if not timeCheck3 else ('rule_3', time_l - time_h, timeCheck3),
8 : None if not timeCheck4 else ('rule_4', time_j - time_l, timeCheck4),
9 : ('rule_5', time_m - time_j if timeCheck4 else time_m - time_h, timeCheck5),
10 : None if not timeCheck7 else ('rule_7', time_n - time_m, timeCheck7),
11 : ('merge_rst', time_o - time_n),
12 : ('priority_rule', time_p - time_o),
13 : ('export_rst', time_q - time_p)
}
def vector_based(osmdata, nomenclature, refRaster, lulcShp,
overwrite=None, dataStore=None, RoadsAPI='POSTGIS'):
"""
Convert OSM Data into Land Use/Land Cover Information
An vector based approach.
TODO: Add a detailed description.
RoadsAPI Options:
* GRASS
* SQLITE
* POSTGIS
"""
# ************************************************************************ #
# Python Modules from Reference Packages #
# ************************************************************************ #
import datetime; import os; import copy
# ************************************************************************ #
# glass dependencies #
# ************************************************************************ #
from glass.pys.oss import fprop, mkdir
from glass.g.wenv.grs import run_grass
if RoadsAPI == 'POSTGIS':
from glass.ng.sql.db import create_db
from glass.g.it.db import osm_to_psql
from glass.ng.sql.db import drop_db
from glass.ng.sql.bkup import dump_db
else:
from glass.g.it.osm import osm_to_sqdb
from glass.ete.osm2lulc.utils import osm_project, add_lulc_to_osmfeat, get_ref_raster
from glass.g.dp.mge import shps_to_shp
from glass.ete.osm2lulc.mod1 import grs_vector
if RoadsAPI == 'SQLITE' or RoadsAPI == 'POSTGIS':
from glass.ete.osm2lulc.mod2 import roads_sqdb
else:
from glass.ete.osm2lulc.mod2 import grs_vec_roads
from glass.ete.osm2lulc.m3_4 import grs_vect_selbyarea
from glass.ete.osm2lulc.mod5 import grs_vect_bbuffer
from glass.ete.osm2lulc.mod6 import vector_assign_pntags_to_build
from glass.g.dp.mge import same_attr_to_shp
from glass.g.prj import def_prj
# ************************************************************************ #
# Global Settings #
# ************************************************************************ #
# Check if input parameters exists!
if not os.path.exists(os.path.dirname(lulcShp)):
raise ValueError('{} does not exist!'.format(os.path.dirname(lulcShp)))
if not os.path.exists(osmdata):
raise ValueError('File with OSM DATA ({}) does not exist!'.format(osmdata))
if not os.path.exists(refRaster):
raise ValueError('File with reference area ({}) does not exist!'.format(refRaster))
# Check if Nomenclature is valid
nomenclature = "URBAN_ATLAS" if nomenclature != "URBAN_ATLAS" and \
nomenclature != "CORINE_LAND_COVER" and \
nomenclature == "GLOBE_LAND_30" else nomenclature
time_a = datetime.datetime.now().replace(microsecond=0)
# Create workspace for temporary files
workspace = os.path.join(os.path.dirname(
lulcShp), 'osmtolulc') if not dataStore else dataStore
# Check if workspace exists
if os.path.exists(workspace):
if overwrite:
mkdir(workspace)
else:
raise ValueError('Path {} already exists'.format(workspace))
else:
mkdir(workspace)
# Get Reference Raster
refRaster, epsg = get_ref_raster(refRaster, workspace, cellsize=10)
from glass.ete.osm2lulc import osmTableData, PRIORITIES, LEGEND
__priorities = PRIORITIES[nomenclature]
__legend = LEGEND[nomenclature]
time_b = datetime.datetime.now().replace(microsecond=0)
if RoadsAPI != 'POSTGIS':
# ******************************************************************** #
# Convert OSM file to SQLITE DB #
# ******************************************************************** #
osm_db = osm_to_sqdb(osmdata, os.path.join(workspace, 'osm.sqlite'))
else:
# Convert OSM file to POSTGRESQL DB #
osm_db = create_db(fprop(
osmdata, 'fn', forceLower=True), overwrite=True)
osm_db = osm_to_psql(osmdata, osm_db)
time_c = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# Add Lulc Classes to OSM_FEATURES by rule #
# ************************************************************************ #
add_lulc_to_osmfeat(
osm_db, osmTableData, nomenclature,
api='SQLITE' if RoadsAPI != 'POSTGIS' else RoadsAPI
)
time_d = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# Transform SRS of OSM Data #
# ************************************************************************ #
osmTableData = osm_project(
osm_db, epsg,
api='SQLITE' if RoadsAPI != 'POSTGIS' else RoadsAPI,
isGlobeLand=None if nomenclature != 'GLOBE_LAND_30' else True
)
time_e = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# Start a GRASS GIS Session #
# ************************************************************************ #
grass_base = run_grass(workspace, grassBIN='grass78', location='grloc', srs=epsg)
#import grass.script as grass
import grass.script.setup as gsetup
gsetup.init(grass_base, workspace, 'grloc', 'PERMANENT')
# ************************************************************************ #
# IMPORT SOME glass MODULES FOR GRASS GIS #
# ************************************************************************ #
from glass.g.gp.ovl import erase
from glass.g.wenv.grs import rst_to_region
from glass.g.gp.gen import dissolve
from glass.g.tbl.grs import add_and_update, reset_table, update_table
from glass.g.tbl.col import add_fields
from glass.g.it.shp import shp_to_grs, grs_to_shp
from glass.g.it.rst import rst_to_grs
# ************************************************************************ #
# SET GRASS GIS LOCATION EXTENT #
# ************************************************************************ #
extRst = rst_to_grs(refRaster, 'extent_raster')
rst_to_region(extRst)
time_f = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# MapResults #
# ************************************************************************ #
osmShps = []
# ************************************************************************ #
# 1 - Selection Rule #
# ************************************************************************ #
ruleOneShp, timeCheck1 = grs_vector(
osm_db, osmTableData['polygons'], apidb=RoadsAPI
)
osmShps.append(ruleOneShp)
time_g = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# 2 - Get Information About Roads Location #
# ************************************************************************ #
ruleRowShp, timeCheck2 = roads_sqdb(
osm_db, osmTableData['lines'], osmTableData['polygons'], apidb=RoadsAPI
) if RoadsAPI == 'SQLITE' or RoadsAPI == 'POSTGIS' else grs_vec_roads(
osm_db, osmTableData['lines'], osmTableData['polygons'])
osmShps.append(ruleRowShp)
time_h = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# 3 - Area Upper than #
# ************************************************************************ #
if nomenclature != "GLOBE_LAND_30":
ruleThreeShp, timeCheck3 = grs_vect_selbyarea(
osm_db, osmTableData['polygons'], UPPER=True, apidb=RoadsAPI
)
osmShps.append(ruleThreeShp)
time_l = datetime.datetime.now().replace(microsecond=0)
else:
timeCheck3 = None
time_l = None
# ************************************************************************ #
# 4 - Area Lower than #
# ************************************************************************ #
if nomenclature != "GLOBE_LAND_30":
ruleFourShp, timeCheck4 = grs_vect_selbyarea(
osm_db, osmTableData['polygons'], UPPER=False, apidb=RoadsAPI
)
osmShps.append(ruleFourShp)
time_j = datetime.datetime.now().replace(microsecond=0)
else:
timeCheck4 = None
time_j = None
# ************************************************************************ #
# 5 - Get data from lines table (railway | waterway) #
# ************************************************************************ #
ruleFiveShp, timeCheck5 = grs_vect_bbuffer(
osm_db, osmTableData["lines"], api_db=RoadsAPI
)
osmShps.append(ruleFiveShp)
time_m = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# 7 - Assign untagged Buildings to tags #
# ************************************************************************ #
if nomenclature != "GLOBE_LAND_30":
ruleSeven11, ruleSeven12, timeCheck7 = vector_assign_pntags_to_build(
osm_db, osmTableData['points'], osmTableData['polygons'],
apidb=RoadsAPI
)
if ruleSeven11:
osmShps.append(ruleSeven11)
if ruleSeven12:
osmShps.append(ruleSeven12)
time_n = datetime.datetime.now().replace(microsecond=0)
else:
timeCheck7 = None
time_n = datetime.datetime.now().replace(microsecond=0)
# ************************************************************************ #
# Produce LULC Map #
# ************************************************************************ #
"""
Get Shps with all geometries related with one class - One Shape for Classe
"""
_osmShps = []
for i in range(len(osmShps)):
if not osmShps[i]: continue
_osmShps.append(grs_to_shp(
osmShps[i], os.path.join(workspace, osmShps[i] + '.shp'),
'auto', lyrN=1, asCMD=True, asMultiPart=None
))
for shp in _osmShps:
def_prj(os.path.splitext(shp)[0] + '.prj', epsg=epsg, api='epsgio')
_osmShps = same_attr_to_shp(
_osmShps, "cat", workspace, "osm_", resultDict=True
)
del osmShps
time_o = datetime.datetime.now().replace(microsecond=0)
"""
Merge all Classes into one feature class using a priority rule
"""
osmShps = {}
for cls in _osmShps:
if cls == '1':
osmShps[1221] = shp_to_grs(_osmShps[cls], "osm_1221", asCMD=True)
else:
osmShps[int(cls)] = shp_to_grs(_osmShps[cls], "osm_" + cls,
asCMD=True)
# Erase overlapping areas by priority
osmNameRef = copy.deepcopy(osmShps)
for e in range(len(__priorities)):
if e + 1 == len(__priorities): break
if __priorities[e] not in osmShps:
continue
else:
for i in range(e+1, len(__priorities)):
if __priorities[i] not in osmShps:
continue
else:
osmShps[__priorities[i]] = erase(
osmShps[__priorities[i]], osmShps[__priorities[e]],
"{}_{}".format(osmNameRef[__priorities[i]], e),
notTbl=True, api='pygrass'
)
time_p = datetime.datetime.now().replace(microsecond=0)
# Export all classes
lst_merge = []
a = None
for i in range(len(__priorities)):
if __priorities[i] not in osmShps:
continue
if not a:
reset_table(
osmShps[__priorities[i]],
{'cls' : 'varchar(5)', 'leg' : 'varchar(75)'},
{'cls' : str(__priorities[i]), 'leg' : str(__legend[__priorities[i]])}
)
a = 1
else:
add_and_update(
osmShps[__priorities[i]],
{'cls' : 'varchar(5)'},
{'cls' : str(__priorities[i])}
)
ds = dissolve(
osmShps[__priorities[i]],
'dl_{}'.format(str(__priorities[i])), 'cls', api="grass"
)
add_fields(ds, {'leg': 'varchar(75)'}, api="grass")
update_table(ds, 'leg', str(__legend[__priorities[i]]), 'leg is null')
lst_merge.append(grs_to_shp(
ds, os.path.join(
workspace, "lulc_{}.shp".format(str(__priorities[i]))
), 'auto', lyrN=1, asCMD=True, asMultiPart=None
))
time_q = datetime.datetime.now().replace(microsecond=0)
if fprop(lulcShp, 'ff') != '.shp':
lulcShp = os.path.join(
os.path.dirname(lulcShp), fprop(lulcShp, 'fn') + '.shp')
shps_to_shp(lst_merge, lulcShp, api='pandas')
# Check if prj of lulcShp exists and create it if necessary
prj_ff = os.path.splitext(lulcShp)[0] + '.prj'
if not os.path.exists(prj_ff):
def_prj(prj_ff, epsg=epsg, api='epsgio')
time_r = datetime.datetime.now().replace(microsecond=0)
# Dump Database if PostGIS was used
# Drop Database if PostGIS was used
if RoadsAPI == 'POSTGIS':
dump_db(osm_db, os.path.join(
workspace, osm_db + '.sql'
), api='psql')
drop_db(osm_db)
return lulcShp, {
0 : ('set_settings', time_b - time_a),
1 : ('osm_to_sqdb', time_c - time_b),
2 : ('cls_in_sqdb', time_d - time_c),
3 : ('proj_data', time_e - time_d),
4 : ('set_grass', time_f - time_e),
5 : ('rule_1', time_g - time_f, timeCheck1),
6 : ('rule_2', time_h - time_g, timeCheck2),
7 : None if not timeCheck3 else ('rule_3', time_l - time_h, timeCheck3),
8 : None if not timeCheck4 else ('rule_4', time_j - time_l, timeCheck4),
9 : ('rule_5',
time_m - time_j if timeCheck4 else time_m - time_h, timeCheck5),
10 : None if not timeCheck7 else ('rule_7', time_n - time_m, timeCheck7),
11 : ('disj_cls', time_o - time_n),
12 : ('priority_rule', time_p - time_o),
13 : ('export_cls', time_q - time_p),
14 : ('merge_cls', time_r - time_q)
}
def match_cellsize_and_clip(rstBands, refRaster, outFolder,
clipShp=None):
"""
Resample images to make them with the same resolution and clip
Good to resample Sentinel bands with more than 10 meters.
Dependencies:
* GRASS GIS;
* GDAL/OGR.
"""
import os
from glass.g.prop.prj import get_rst_epsg
from glass.g.wenv.grs import run_grass
from glass.pys.oss import fprop, mkdir
# Check if outfolder exists
if not os.path.exists(outFolder):
mkdir(outFolder, overwrite=None)
# Get EPSG from refRaster
epsg = get_rst_epsg(refRaster, returnIsProj=None)
"""
Start GRASS GIS Session
"""
GRS_WORKSPACE = mkdir(os.path.join(outFolder, 'grswork'))
grsb = run_grass(
GRS_WORKSPACE, grassBIN='grass78', location='resample',
srs=epsg
)
import grass.script.setup as gsetup
gsetup.init(grsb, GRS_WORKSPACE, 'resample', 'PERMANENT')
"""
Import packages related with GRASS GIS
"""
from glass.g.it.rst import rst_to_grs, grs_to_rst
from glass.g.wenv.grs import rst_to_region
from glass.g.it.shp import shp_to_grs
from glass.g.dp.torst import grsshp_to_grsrst as shp_to_rst
from glass.g.it.rst import grs_to_mask
# Send Ref Raster to GRASS GIS and set region
extRst = rst_to_grs(refRaster, 'ext_rst')
rst_to_region(extRst)
# Import all bands in rstBands
grs_bands = [rst_to_grs(i, fprop(i, 'fn')) for i in rstBands]
if clipShp:
# Add clipShp to GRASS
grs_clip = shp_to_grs(clipShp, fprop(clipShp, 'fn'), asCMD=True)
# SHP to Raster
rstClip = shp_to_rst(
grs_clip, 1, f'rst_{grs_clip}',
cmd=True
)
# Set region using
rst_to_region(rstClip)
# Set mask
grs_to_mask(rstClip)
# Export bands
return [grs_to_rst(
i, os.path.join(outFolder, i + '.tif')
) for i in grs_bands]
def shp_diff_fm_ref(refshp, refcol, shps, out_folder, refrst, db=None):
"""
Check differences between each shp in shps and one reference shape
Dependencies:
- GRASS;
- PostgreSQL with Postgis or GeoPandas;
"""
import os
from glass.g.prop import check_isRaster
from glass.g.wenv.grs import run_grass
from glass.pys.oss import fprop
from glass.g.tbl.tomtx import tbl_to_areamtx
# Check if folder exists, if not create it
if not os.path.exists(out_folder):
from glass.pys.oss import mkdir
mkdir(out_folder)
# Start GRASS GIS Session
gbase = run_grass(out_folder,
grassBIN='grass78',
location='shpdif',
srs=refrst)
import grass.script.setup as gsetup
gsetup.init(gbase, out_folder, 'shpdif', 'PERMANENT')
from glass.g.it.shp import shp_to_grs, grs_to_shp
from glass.g.it.rst import rst_to_grs
from glass.g.tbl.col import rn_cols
from glass.g.dp.rst.toshp import rst_to_polyg
# Convert to SHAPE if file is Raster
# Rename interest columns
i = 0
lstff = [refshp] + list(shps.keys())
__shps = {}
for s in lstff:
is_rst = check_isRaster(s)
if is_rst:
# To GRASS
rname = fprop(s, 'fn')
inrst = rst_to_grs(s, "rst_" + rname, as_cmd=True)
# To vector
d = rst_to_polyg(inrst,
rname,
rstColumn="lulc_{}".format(str(i)),
gisApi="grass")
else:
# To GRASS
d = shp_to_grs(s, fprop(s, 'fn'), asCMD=True)
# Change name of interest colum
rn_cols(d, {shps[s] if i else refcol: "lulc_{}".format(str(i))},
api="grass")
# Export To Shapefile
if not i:
refshp = grs_to_shp(d, os.path.join(out_folder, d + '.shp'),
'area')
refcol = "lulc_{}".format(str(i))
else:
shp = grs_to_shp(d, os.path.join(out_folder, d + '.shp'), 'area')
__shps[shp] = "lulc_{}".format(str(i))
i += 1
# Union Shapefiles
union_shape = {}
for shp in __shps:
# Optimized Union
sname = fprop(shp, 'fn')
union_shape[shp] = optimized_union_anls(
shp,
refshp,
os.path.join(out_folder, sname + '_un.shp'),
refrst,
os.path.join(out_folder, "wk_" + sname),
multiProcess=True)
# Produce confusion matrices
mtxf = tbl_to_areamtx(union_shape[shp],
"a_" + __shps[shp],
'b_' + refcol,
os.path.join(out_folder, sname + '.xlsx'),
db=db,
with_metrics=True)
return out_folder
def check_shape_diff(SHAPES_TO_COMPARE, OUT_FOLDER, REPORT, DB,
GRASS_REGION_TEMPLATE):
"""
Script to check differences between pairs of Feature Classes
Suponha que temos diversas Feature Classes (FC) e que cada uma delas
possui um determinado atributo; imagine tambem que,
considerando todos os pares possiveis entre estas FC,
se pretende comparar as diferencas na distribuicao dos valores
desse atributo para cada par.
* Dependencias:
- GRASS;
- PostgreSQL;
- PostGIS.
"""
import datetime
import os
import pandas
from glass.ng.sql.q import q_to_obj
from glass.ng.it import db_to_tbl
from glass.g.wt.sql import df_to_db
from glass.g.dp.rst.toshp import rst_to_polyg
from glass.g.it.db import shp_to_psql
from glass.g.dp.tomtx import tbl_to_area_mtx
from glass.g.prop import check_isRaster
from glass.pys.oss import fprop
from glass.ng.sql.db import create_db
from glass.ng.sql.tbl import tbls_to_tbl
from glass.ng.sql.q import q_to_ntbl
# Check if folder exists, if not create it
if not os.path.exists(OUT_FOLDER):
from glass.pys.oss import mkdir
mkdir(OUT_FOLDER, overwrite=None)
else:
raise ValueError('{} already exists!'.format(OUT_FOLDER))
from glass.g.wenv.grs import run_grass
gbase = run_grass(OUT_FOLDER,
grassBIN='grass78',
location='shpdif',
srs=GRASS_REGION_TEMPLATE)
import grass.script as grass
import grass.script.setup as gsetup
gsetup.init(gbase, OUT_FOLDER, 'shpdif', 'PERMANENT')
from glass.g.it.shp import shp_to_grs, grs_to_shp
from glass.g.it.rst import rst_to_grs
from glass.g.tbl.col import rn_cols
# Convert to SHAPE if file is Raster
i = 0
_SHP_TO_COMPARE = {}
for s in SHAPES_TO_COMPARE:
isRaster = check_isRaster(s)
if isRaster:
# To GRASS
rstName = fprop(s, 'fn')
inRst = rst_to_grs(s, "rst_" + rstName, as_cmd=True)
# To Vector
d = rst_to_polyg(inRst,
rstName,
rstColumn="lulc_{}".format(i),
gisApi="grass")
# Export Shapefile
shp = grs_to_shp(d, os.path.join(OUT_FOLDER, d + '.shp'), "area")
_SHP_TO_COMPARE[shp] = "lulc_{}".format(i)
else:
# To GRASS
grsV = shp_to_grs(s, fprop(s, 'fn'), asCMD=True)
# Change name of column with comparing value
ncol = "lulc_{}".format(str(i))
rn_cols(grsV, {SHAPES_TO_COMPARE[s]: "lulc_{}".format(str(i))},
api="grass")
# Export
shp = grs_to_shp(grsV, os.path.join(OUT_FOLDER, grsV + '_rn.shp'),
"area")
_SHP_TO_COMPARE[shp] = "lulc_{}".format(str(i))
i += 1
SHAPES_TO_COMPARE = _SHP_TO_COMPARE
__SHAPES_TO_COMPARE = SHAPES_TO_COMPARE
# Create database
create_db(DB, api='psql')
""" Union SHAPEs """
UNION_SHAPE = {}
FIX_GEOM = {}
SHPS = list(__SHAPES_TO_COMPARE.keys())
for i in range(len(SHPS)):
for e in range(i + 1, len(SHPS)):
# Optimized Union
print("Union between {} and {}".format(SHPS[i], SHPS[e]))
time_a = datetime.datetime.now().replace(microsecond=0)
__unShp = optimized_union_anls(
SHPS[i],
SHPS[e],
os.path.join(OUT_FOLDER, "un_{}_{}.shp".format(i, e)),
GRASS_REGION_TEMPLATE,
os.path.join(OUT_FOLDER, "work_{}_{}".format(i, e)),
multiProcess=True)
time_b = datetime.datetime.now().replace(microsecond=0)
print(time_b - time_a)
# Rename cols
unShp = rn_cols(
__unShp, {
"a_" + __SHAPES_TO_COMPARE[SHPS[i]]:
__SHAPES_TO_COMPARE[SHPS[i]],
"b_" + __SHAPES_TO_COMPARE[SHPS[e]]:
__SHAPES_TO_COMPARE[SHPS[e]]
})
UNION_SHAPE[(SHPS[i], SHPS[e])] = unShp
# Send data to postgresql
SYNTH_TBL = {}
for uShp in UNION_SHAPE:
# Send data to PostgreSQL
union_tbl = shp_to_psql(DB, UNION_SHAPE[uShp], api='shp2pgsql')
# Produce table with % of area equal in both maps
areaMapTbl = q_to_ntbl(
DB,
"{}_syn".format(union_tbl),
("SELECT CAST('{lulc_1}' AS text) AS lulc_1, "
"CAST('{lulc_2}' AS text) AS lulc_2, "
"round("
"CAST(SUM(g_area) / 1000000 AS numeric), 4"
") AS agree_area, round("
"CAST((SUM(g_area) / MIN(total_area)) * 100 AS numeric), 4"
") AS agree_percentage, "
"round("
"CAST(MIN(total_area) / 1000000 AS numeric), 4"
") AS total_area FROM ("
"SELECT {map1_cls}, {map2_cls}, ST_Area(geom) AS g_area, "
"CASE "
"WHEN {map1_cls} = {map2_cls} "
"THEN 1 ELSE 0 "
"END AS isthesame, total_area FROM {tbl}, ("
"SELECT SUM(ST_Area(geom)) AS total_area FROM {tbl}"
") AS foo2"
") AS foo WHERE isthesame = 1 "
"GROUP BY isthesame").format(
lulc_1=fprop(uShp[0], 'fn'),
lulc_2=fprop(uShp[1], 'fn'),
map1_cls=__SHAPES_TO_COMPARE[uShp[0]],
map2_cls=__SHAPES_TO_COMPARE[uShp[1]],
tbl=union_tbl),
api='psql')
# Produce confusion matrix for the pair in comparison
matrixTbl = tbl_to_area_mtx(DB, union_tbl,
__SHAPES_TO_COMPARE[uShp[0]],
__SHAPES_TO_COMPARE[uShp[1]],
union_tbl + '_mtx')
SYNTH_TBL[uShp] = {"TOTAL": areaMapTbl, "MATRIX": matrixTbl}
# UNION ALL TOTAL TABLES
total_table = tbls_to_tbl(DB, [SYNTH_TBL[k]["TOTAL"] for k in SYNTH_TBL],
'total_table')
# Create table with % of agreement between each pair of maps
mapsNames = q_to_obj(
DB,
("SELECT lulc FROM ("
"SELECT lulc_1 AS lulc FROM {tbl} GROUP BY lulc_1 "
"UNION ALL "
"SELECT lulc_2 AS lulc FROM {tbl} GROUP BY lulc_2"
") AS lu GROUP BY lulc ORDER BY lulc").format(tbl=total_table),
db_api='psql').lulc.tolist()
FLDS_TO_PIVOT = ["agree_percentage", "total_area"]
Q = ("SELECT * FROM crosstab('"
"SELECT CASE "
"WHEN foo.lulc_1 IS NOT NULL THEN foo.lulc_1 ELSE jtbl.tmp1 "
"END AS lulc_1, CASE "
"WHEN foo.lulc_2 IS NOT NULL THEN foo.lulc_2 ELSE jtbl.tmp2 "
"END AS lulc_2, CASE "
"WHEN foo.{valCol} IS NOT NULL THEN foo.{valCol} ELSE 0 "
"END AS agree_percentage FROM ("
"SELECT lulc_1, lulc_2, {valCol} FROM {tbl} UNION ALL "
"SELECT lulc_1, lulc_2, {valCol} FROM ("
"SELECT lulc_1 AS lulc_2, lulc_2 AS lulc_1, {valCol} "
"FROM {tbl}"
") AS tst"
") AS foo FULL JOIN ("
"SELECT lulc_1 AS tmp1, lulc_2 AS tmp2 FROM ("
"SELECT lulc_1 AS lulc_1 FROM {tbl} GROUP BY lulc_1 "
"UNION ALL "
"SELECT lulc_2 AS lulc_1 FROM {tbl} GROUP BY lulc_2"
") AS tst_1, ("
"SELECT lulc_1 AS lulc_2 FROM {tbl} GROUP BY lulc_1 "
"UNION ALL "
"SELECT lulc_2 AS lulc_2 FROM {tbl} GROUP BY lulc_2"
") AS tst_2 WHERE lulc_1 = lulc_2 GROUP BY lulc_1, lulc_2"
") AS jtbl ON foo.lulc_1 = jtbl.tmp1 AND foo.lulc_2 = jtbl.tmp2 "
"ORDER BY lulc_1, lulc_2"
"') AS ct("
"lulc_map text, {crossCols}"
")")
TOTAL_AGREE_TABLE = None
TOTAL_AREA_TABLE = None
for f in FLDS_TO_PIVOT:
if not TOTAL_AGREE_TABLE:
TOTAL_AGREE_TABLE = q_to_ntbl(
DB,
"agreement_table",
Q.format(tbl=total_table,
valCol=f,
crossCols=", ".join([
"{} numeric".format(map_) for map_ in mapsNames
])),
api='psql')
else:
TOTAL_AREA_TABLE = q_to_ntbl(DB,
"area_table",
Q.format(tbl=total_table,
valCol=f,
crossCols=", ".join([
"{} numeric".format(map_)
for map_ in mapsNames
])),
api='psql')
# Union Mapping
UNION_MAPPING = pandas.DataFrame(
[[k[0], k[1], fprop(UNION_SHAPE[k], 'fn')] for k in UNION_SHAPE],
columns=['shp_a', 'shp_b', 'union_shp'])
UNION_MAPPING = df_to_db(DB, UNION_MAPPING, 'union_map', api='psql')
# Export Results
TABLES = [UNION_MAPPING, TOTAL_AGREE_TABLE, TOTAL_AREA_TABLE
] + [SYNTH_TBL[x]["MATRIX"] for x in SYNTH_TBL]
SHEETS = ["union_map", "agreement_percentage", "area_with_data_km"] + [
"{}_{}".format(fprop(x[0], 'fn')[:15],
fprop(x[1], 'fn')[:15]) for x in SYNTH_TBL
]
db_to_tbl(DB, ["SELECT * FROM {}".format(x) for x in TABLES],
REPORT,
sheetsNames=SHEETS,
dbAPI='psql')
return REPORT
def make_dem(grass_workspace, data, field, output, extent_template,
method="IDW", cell_size=None, mask=None):
"""
Create Digital Elevation Model
Methods Available:
* IDW;
* BSPLINE;
* SPLINE;
* CONTOUR;
"""
from glass.pys.oss import fprop
from glass.g.wenv.grs import run_grass
from glass.g.prop.prj import get_epsg
LOC_NAME = fprop(data, 'fn', forceLower=True)[:5] + "_loc"
# Get EPSG From Raster
EPSG = get_epsg(extent_template)
if not EPSG:
raise ValueError(
'Cannot get EPSG code of Extent Template File ({})'.format(
extent_template
)
)
# Know if data geometry are points
if method == 'BSPLINE' or method == 'SPLINE':
from glass.g.prop.feat import get_gtype
data_gtype = get_gtype(data, gisApi='ogr')
# Create GRASS GIS Location
grass_base = run_grass(grass_workspace, location=LOC_NAME, srs=EPSG)
# Start GRASS GIS Session
import grass.script.setup as gsetup
gsetup.init(grass_base, grass_workspace, LOC_NAME, 'PERMANENT')
# Get Extent Raster
ref_template = ob_ref_rst(extent_template, os.path.join(
grass_workspace, LOC_NAME
), cellsize=cell_size)
# IMPORT GRASS GIS MODULES #
from glass.g.it.rst import rst_to_grs, grs_to_rst
from glass.g.it.shp import shp_to_grs
from glass.g.wenv.grs import rst_to_region
# Configure region
rst_to_grs(ref_template, 'extent')
rst_to_region('extent')
# Convert elevation "data" to GRASS Vector
elv = shp_to_grs(data, 'elevation')
OUTPUT_NAME = fprop(output, 'fn', forceLower=True)
if method == "BSPLINE":
from glass.g.rst.itp import bspline
# Convert to points if necessary
if data_gtype != 'POINT' and data_gtype != 'MULTIPOINT':
from glass.g.dp.cg import feat_vertex_to_pnt
elev_pnt = feat_vertex_to_pnt(elv, "elev_pnt", nodes=None)
else:
elev_pnt = elv
outRst = bspline(elev_pnt, field, OUTPUT_NAME, mway='bicubic', lyrN=1, asCMD=True)
elif method == "SPLINE":
from glass.g.rst.itp import surfrst
# Convert to points if necessary
if data_gtype != 'POINT' and data_gtype != 'MULTIPOINT':
from glass.g.dp.cg import feat_vertex_to_pnt
elev_pnt = feat_vertex_to_pnt(elv, "elev_pnt", nodes=None)
else:
elev_pnt = elv
outRst = surfrst(elev_pnt, field, OUTPUT_NAME, lyrN=1, ascmd=True)
elif method == "CONTOUR":
from glass.g.dp.torst import grsshp_to_grsrst as shp_to_rst
from glass.g.rst.itp import surfcontour
# Apply mask if mask
if mask:
from glass.g.it.rst import grs_to_mask, rst_to_grs
rst_mask = rst_to_grs(mask, 'rst_mask', as_cmd=True)
grs_to_mask(rst_mask)
# Elevation (GRASS Vector) to Raster
elevRst = shp_to_rst(elv, field, 'rst_elevation')
# Run Interpolator
outRst = surfcontour(elevRst, OUTPUT_NAME, ascmd=True)
elif method == "IDW":
from glass.g.rst.itp import ridw
from glass.g.rst.alg import rstcalc
from glass.g.dp.torst import grsshp_to_grsrst as shp_to_rst
# Elevation (GRASS Vector) to Raster
elevRst = shp_to_rst(elv, field, 'rst_elevation')
# Multiply cells values by 100 000.0
rstcalc('int(rst_elevation * 100000)', 'rst_elev_int', api='pygrass')
# Run IDW to generate the new DEM
ridw('rst_elev_int', 'dem_int', numberPoints=15)
# DEM to Float
rstcalc('dem_int / 100000.0', OUTPUT_NAME, api='pygrass')
# Export DEM to a file outside GRASS Workspace
grs_to_rst(OUTPUT_NAME, output)
return output
def run_viewshed_by_cpu(tid, db, obs, dem, srs,
vis_basename='vis', maxdst=None, obselevation=None):
# Create Database
new_db = create_db("{}_{}".format(db, str(tid)), api='psql')
# Points to Database
pnt_tbl = df_to_db(
new_db, obs, 'pnt_tbl', api='psql',
epsg=srs, geomType='Point', colGeom='geometry')
# Create GRASS GIS Session
workspace = mkdir(os.path.join(
os.path.dirname(dem), 'work_{}'.format(str(tid))
))
loc_name = 'vis_loc'
gbase = run_grass(workspace, location=loc_name, srs=dem)
# Start GRASS GIS Session
import grass.script as grass
import grass.script.setup as gsetup
gsetup.init(gbase, workspace, loc_name, 'PERMANENT')
from glass.g.it.rst import rst_to_grs, grs_to_rst
from glass.g.rst.surf import grs_viewshed
from glass.g.deldt import del_rst
# Send DEM to GRASS GIS
grs_dem = rst_to_grs(dem, 'grs_dem', as_cmd=True)
# Produce Viewshed for each point in obs
for idx, row in obs.iterrows():
# Get Viewshed raster
vrst = grs_viewshed(
grs_dem, (row.geometry.x, row.geometry.y),
'{}_{}'.format(vis_basename, str(row[obs_id])),
max_dist=maxdst, obs_elv=obselevation
)
# Export Raster to File
frst = grs_to_rst(vrst, os.path.join(workspace, vrst + '.tif'))
# Raster to Array
img = gdal.Open(frst)
num = img.ReadAsArray()
# Two Dimension to One Dimension
# Reshape Array
numone = num.reshape(num.shape[0] * num.shape[1])
# Get Indexes with visibility
visnum = np.arange(numone.shape[0]).astype(np.uint32)
visnum = visnum[numone == 1]
# Get Indexes intervals
visint = get_minmax_fm_seq_values(visnum)
# Get rows indexes
_visint = visint.reshape(visint.shape[0] * visint.shape[1])
visrow = _visint / num.shape[1]
visrow = visrow.astype(np.uint32)
# Get cols indexes
viscol = _visint - (visrow * num.shape[1])
# Reshape
visrow = visrow.reshape(visint.shape)
viscol = viscol.reshape(visint.shape)
# Split array
irow, erow = np.vsplit(visrow.T, 1)[0]
icol, ecol = np.vsplit(viscol.T, 1)[0]
# Visibility indexes to Pandas DataFrame
idxnum = np.full(irow.shape, row[obs_id])
visdf = pd.DataFrame({
'pntid' : idxnum, 'rowi' : irow, 'rowe' : erow,
'coli': icol, 'cole' : ecol
})
# Pandas DF to database
# Create Visibility table
df_to_db(
new_db, visdf, vis_basename,
api='psql', colGeom=None,
append=None if not idx else True
)
# Delete all variables
numone = None
visnum = None
visint = None
_visint = None
visrow = None
viscol = None
irow = None
erow = None
icol = None
ecol = None
idxnum = None
visdf = None
del img
# Delete GRASS GIS File
del_rst(vrst)
# Delete TIFF File
del_file(frst)
frst = None
def bnds_to_mosaic(bands, outdata, ref_raster, loc=None):
"""
Satellite image To mosaic
bands = {
'bnd_2' : [path_to_file, path_to_file],
'bnd_3' : [path_to_file, path_to_file],
'bnd_4' : [path_to_file, path_to_file],
}
"""
"""
Start GRASS GIS Session
"""
import os
from glass.pys.oss import fprop
from glass.g.prop.prj import get_rst_epsg
from glass.g.wenv.grs import run_grass
# Get EPSG from refRaster
epsg = get_rst_epsg(ref_raster, returnIsProj=None)
LOC = loc if loc else 'gr_loc'
grass_base = run_grass(outdata, grassBIN='grass78', location=LOC, srs=epsg)
import grass.script as grass
import grass.script.setup as gsetup
gsetup.init(grass_base, outdata, LOC, 'PERMANENT')
# ************************************************************************ #
# GRASS MODULES #
# ************************************************************************ #
from glass.g.it.rst import rst_to_grs, grs_to_rst
from glass.g.wenv.grs import rst_to_region
# ************************************************************************ #
# SET GRASS GIS LOCATION EXTENT #
# ************************************************************************ #
extRst = rst_to_grs(ref_raster, 'extent_raster')
rst_to_region(extRst)
# ************************************************************************ #
# SEND DATA TO GRASS GIS #
# ************************************************************************ #
grs_bnds = {}
for bnd in bands:
l = []
for b in bands[bnd]:
bb = rst_to_grs(b, fprop(b, 'fn'))
l.append(bb)
grs_bnds[bnd] = l
# ************************************************************************ #
# PATCH bands and export #
# ************************************************************************ #
for bnd in grs_bnds:
mosaic_band = rseries(grs_bnds[bnd], bnd, 'maximum')
grs_bnds[bnd] = grs_to_rst(mosaic_band,
os.path.join(outdata, mosaic_band + '.tif'),
as_cmd=True)
return grs_bnds
