def locs_metrics(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
outfile = ctx.obj["outfile"]
lm = LocsMetrics(db)
lm.generate(outfile)
def usermetrics(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
um = UserMetrics(db)
um.generate()
db.close()
def locs_metrics(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
outfile = ctx.obj['outfile']
lm = LocsMetrics(db)
lm.generate(outfile)
def photodensity(ctx):
config = ctx.obj["config"]
db = DB(ctx.obj["dbname"], config)
db.open()
pd = PhotoDensity(db)
pd.generate()
db.close()
def usersamples(ctx):
dbname = ctx.obj["dbname"]
infile = ctx.obj["infile"]
db = DB(dbname, ctx.obj["config"])
db.open()
us = UserSamples(db, dbname, infile)
us.generate()
db.close()
def fix_locations(ctx):
click.echo("Fixing locations")
config = ctx.obj["config"]
db = DB(ctx.obj["dbname"], config)
db.open()
fixer = FixLocations(db)
fixer.run()
db.close()
def areas(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
infile = ctx.obj["infile"]
smooth = ctx.obj["smooth"]
ar = Areas(db, infile, smooth)
ar.compute()
def clean_locations(ctx):
click.echo("Cleaning location data")
db = DB(ctx.obj["dbname"], ctx.obj["config"])
db.open()
locs = Locations(db)
locs.clean()
db.close()
click.echo("done.")
def retrieve(ctx):
click.echo("Retrieving Instagram data")
config = ctx.obj["config"]
db = DB(ctx.obj["dbname"], config)
db.open()
retriever = Retriever(config, db)
retriever.run()
db.close()
def areas(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
infile = ctx.obj['infile']
smooth = ctx.obj['smooth']
ar = Areas(db, infile, smooth)
ar.compute()
def add_locations(ctx):
country_code = ctx.obj["country_code"]
click.echo("Adding locations for %s" % country_code)
db = DB(ctx.obj["dbname"], ctx.obj["config"])
db.open()
locs = Locations(db)
(points, inserted) = locs.add_locations(ctx.obj["locs_file"], country_code)
db.close()
click.echo("%d points found, %d points added." % (points, inserted))
def crop_rectangle(ctx):
min_lat = float(ctx.obj["min_lat"])
min_lng = float(ctx.obj["min_lng"])
max_lat = float(ctx.obj["max_lat"])
max_lng = float(ctx.obj["max_lng"])
db = DB(ctx.obj["dbname"], ctx.obj["config"])
db.open()
ghostb.cropdata.crop_rectangle(db, min_lat, min_lng, max_lat, max_lng)
db.close()
def distances(ctx):
dbname = ctx.obj["dbname"]
infile = ctx.obj["infile"]
outfile = ctx.obj["outfile"]
db = DB(dbname, ctx.obj["config"])
db.open()
dist = Distances(db)
dist.compute(infile, outfile)
db.close()
def gen_graph(ctx):
dbname = ctx.obj["dbname"]
outfile = ctx.obj["outfile"]
table = ctx.obj["table"]
db = DB(dbname, ctx.obj["config"])
db.open()
gg = GenGraph(db, outfile, table)
gg.generate()
db.close()
def dists(ctx):
dbname = ctx.obj["dbname"]
infile = ctx.obj["infile"]
outfile = ctx.obj["outfile"]
db = DB(dbname, ctx.obj["config"])
db.open()
g = ghostb.graph.read_graph(infile)
ghostb.graph.write_dists(g, db, outfile)
db.close()
def borders(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
indir = ctx.obj['indir']
infile = ctx.obj['infile']
outfile = ctx.obj['outfile']
smooth = ctx.obj['smooth']
bs = Borders(db, smooth)
bs.process(indir, infile, outfile)
def scales_usermetrics(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
outdir = ctx.obj["outdir"]
intervals = int(ctx.obj["intervals"])
scale_membership = ctx.obj["scale_membership"]
s = Scales(outdir, intervals)
s.usermetrics(db, scale_membership)
def dist_sequence(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
outdir = ctx.obj["outdir"]
intervals = int(ctx.obj["intervals"])
smooth = ctx.obj["smooth"]
scales = Scales(outdir, intervals)
scales.dist_sequence(db, smooth)
def borders(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
indir = ctx.obj["indir"]
infile = ctx.obj["infile"]
outfile = ctx.obj["outfile"]
smooth = ctx.obj["smooth"]
bs = Borders(db, smooth)
bs.process(indir, infile, outfile)
def filter_dists(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
infile = ctx.obj["infile"]
outfile = ctx.obj["outfile"]
max_dist = float(ctx.obj["max_dist"])
fd = FilterDists(db)
fd.filter(infile, outfile, max_dist)
db.close()
def dist_sequence(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
outdir = ctx.obj['outdir']
intervals = int(ctx.obj['intervals'])
smooth = ctx.obj['smooth']
scales = Scales(outdir, intervals)
scales.dist_sequence(db, smooth)
def replace_low_degree(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
infile = ctx.obj["infile"]
outfile = ctx.obj["outfile"]
min_degree = float(ctx.obj["min_degree"])
rld = ReplaceLowDegree(db, infile, min_degree)
rld.run(outfile)
db.close()
def scales_usermetrics(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
outdir = ctx.obj['outdir']
intervals = int(ctx.obj['intervals'])
scale_membership = ctx.obj['scale_membership']
s = Scales(outdir, intervals)
s.usermetrics(db, scale_membership)
def add_region_grid(ctx):
region = ctx.obj["region"]
rows = int(ctx.obj["rows"])
cols = int(ctx.obj["cols"])
click.echo("Adding grid of locations for region: %s" % region)
db = DB(ctx.obj["dbname"], ctx.obj["config"])
db.open()
locs = Locations(db)
locs.add_region_grid(region, rows, cols)
db.close()
def similarity_matrix(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
outdir = ctx.obj['outdir']
intervals = int(ctx.obj['intervals'])
smooth = ctx.obj['smooth']
optimize = ctx.obj['optimize']
scales = Scales(outdir, intervals)
scales.similarity_matrix(db, smooth, optimize)
def scales_borders(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
outdir = ctx.obj['outdir']
best = ctx.obj['best']
smooth = ctx.obj['smooth']
intervals = int(ctx.obj['intervals'])
scales = Scales(outdir, intervals)
scales.generate_borders(db, best, smooth)
def similarity_matrix(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
outdir = ctx.obj["outdir"]
intervals = int(ctx.obj["intervals"])
smooth = ctx.obj["smooth"]
optimize = ctx.obj["optimize"]
scales = Scales(outdir, intervals)
scales.similarity_matrix(db, smooth, optimize)
def scales_graphs(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
outdir = ctx.obj['outdir']
intervals = int(ctx.obj['intervals'])
scale = ctx.obj['scale']
table = ctx.obj['table']
scales = Scales(outdir, intervals)
scales.generate_graphs(db, scale, table)
def userscales(ctx):
dbname = ctx.obj["dbname"]
infile = ctx.obj["infile"]
outfile = ctx.obj["outfile"]
scales = ctx.obj["scales"]
table = ctx.obj["table"]
db = DB(dbname, ctx.obj["config"])
db.open()
us = UserScales(db, outfile, infile, scales, table)
us.generate()
db.close()
def scales_borders(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
outdir = ctx.obj["outdir"]
best = ctx.obj["best"]
smooth = ctx.obj["smooth"]
intervals = int(ctx.obj["intervals"])
scales = Scales(outdir, intervals)
scales.generate_borders(db, best, smooth)
def scales_graphs(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
outdir = ctx.obj["outdir"]
intervals = int(ctx.obj["intervals"])
scale = ctx.obj["scale"]
table = ctx.obj["table"]
scales = Scales(outdir, intervals)
scales.generate_graphs(db, scale, table)
def add_area(ctx):
min_lat = float(ctx.obj["min_lat"])
min_lng = float(ctx.obj["min_lng"])
max_lat = float(ctx.obj["max_lat"])
max_lng = float(ctx.obj["max_lng"])
click.echo("Adding locations in area: [%s, %s, %s, %s]" % (min_lat, min_lng, max_lat, max_lng))
db = DB(ctx.obj["dbname"], ctx.obj["config"])
db.open()
locs = Locations(db)
(points, inserted) = locs.add_area(ctx.obj["locs_file"], min_lat, min_lng, max_lat, max_lng)
db.close()
click.echo("%d points found, %d points added." % (points, inserted))
def scales_multi_borders(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
outdir = ctx.obj["outdir"]
outfile = ctx.obj["outfile"]
smooth = ctx.obj["smooth"]
intervals = int(ctx.obj["intervals"])
scales = ctx.obj["scales"]
s = Scales(outdir, intervals)
s.generate_multi_borders(db, outfile, smooth, scales)
def scales_multi_borders(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
outdir = ctx.obj['outdir']
outfile = ctx.obj['outfile']
smooth = ctx.obj['smooth']
intervals = int(ctx.obj['intervals'])
scales = ctx.obj['scales']
s = Scales(outdir, intervals)
s.generate_multi_borders(db, outfile, smooth, scales)
def add_grid(ctx):
min_lat = float(ctx.obj["min_lat"])
min_lng = float(ctx.obj["min_lng"])
max_lat = float(ctx.obj["max_lat"])
max_lng = float(ctx.obj["max_lng"])
rows = int(ctx.obj["rows"])
cols = int(ctx.obj["cols"])
click.echo("Adding grid of locations for area: [%s, %s, %s, %s]" % (min_lat, min_lng, max_lat, max_lng))
db = DB(ctx.obj["dbname"], ctx.obj["config"])
db.open()
locs = Locations(db)
locs.add_grid(min_lat, min_lng, max_lat, max_lng, rows, cols)
db.close()
def scales_metric(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
outdir = ctx.obj['outdir']
best = ctx.obj['best']
intervals = int(ctx.obj['intervals'])
smooth = ctx.obj['smooth']
scale = ctx.obj['scale']
metric = ctx.obj['metric']
scales = Scales(outdir, intervals)
scales.metric(metric, db, best, smooth, scale)
def scales_metric(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
outdir = ctx.obj["outdir"]
best = ctx.obj["best"]
intervals = int(ctx.obj["intervals"])
smooth = ctx.obj["smooth"]
scale = ctx.obj["scale"]
metric = ctx.obj["metric"]
scales = Scales(outdir, intervals)
scales.metric(metric, db, best, smooth, scale)
def usermetrics(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
um = UserMetrics(db)
um.generate()
db.close()
def photodensity(ctx):
config = ctx.obj['config']
db = DB(ctx.obj['dbname'], config)
db.open()
pd = PhotoDensity(db)
pd.generate()
db.close()
def json_export(ctx):
dbname = ctx.obj['dbname']
outfile = ctx.obj['outfile']
db = DB(dbname, ctx.obj['config'])
db.open()
je = JsonExport(db, outfile)
je.export()
db.close()
def clean_locations(ctx):
click.echo('Cleaning location data')
db = DB(ctx.obj['dbname'], ctx.obj['config'])
db.open()
locs = Locations(db)
locs.clean()
db.close()
click.echo('done.')
def retrieve(ctx):
click.echo('Retrieving Instagram data')
config = ctx.obj['config']
db = DB(ctx.obj['dbname'], config)
db.open()
retriever = Retriever(config, db)
retriever.run()
db.close()
def fix_locations(ctx):
click.echo('Fixing locations')
config = ctx.obj['config']
db = DB(ctx.obj['dbname'], config)
db.open()
fixer = FixLocations(db)
fixer.run()
db.close()
def usersamples(ctx):
dbname = ctx.obj['dbname']
infile = ctx.obj['infile']
db = DB(dbname, ctx.obj['config'])
db.open()
us = UserSamples(db, dbname, infile)
us.generate()
db.close()
def import_locations(ctx):
infile = ctx.obj['infile']
click.echo('Importing locations from %s' % infile)
db = DB(ctx.obj['dbname'], ctx.obj['config'])
db.open()
locs = Locations(db)
(points, inserted) = locs.import_locations(infile)
db.close()
click.echo('%d points found, %d points added.' % (points, inserted))
def crop_rectangle(ctx):
min_lat = float(ctx.obj['min_lat'])
min_lng = float(ctx.obj['min_lng'])
max_lat = float(ctx.obj['max_lat'])
max_lng = float(ctx.obj['max_lng'])
db = DB(ctx.obj['dbname'], ctx.obj['config'])
db.open()
ghostb.cropdata.crop_rectangle(db, min_lat, min_lng, max_lat, max_lng)
db.close()
def dists(ctx):
dbname = ctx.obj['dbname']
infile = ctx.obj['infile']
outfile = ctx.obj['outfile']
db = DB(dbname, ctx.obj['config'])
db.open()
g = ghostb.graph.read_graph(infile)
ghostb.graph.write_dists(g, db, outfile)
db.close()
def distances(ctx):
dbname = ctx.obj['dbname']
infile = ctx.obj['infile']
outfile = ctx.obj['outfile']
db = DB(dbname, ctx.obj['config'])
db.open()
dist = Distances(db)
dist.compute(infile, outfile)
db.close()
def gen_graph(ctx):
dbname = ctx.obj['dbname']
outfile = ctx.obj['outfile']
table = ctx.obj['table']
db = DB(dbname, ctx.obj['config'])
db.open()
gg = GenGraph(db, outfile, table)
gg.generate()
db.close()
def add_locations(ctx):
country_code = ctx.obj['country_code']
click.echo('Adding locations for %s' % country_code)
db = DB(ctx.obj['dbname'], ctx.obj['config'])
db.open()
locs = Locations(db)
(points, inserted) = locs.add_locations(ctx.obj['locs_file'], country_code)
db.close()
click.echo('%d points found, %d points added.' % (points, inserted))
def filter_dists(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
infile = ctx.obj['infile']
outfile = ctx.obj['outfile']
max_dist = float(ctx.obj['max_dist'])
fd = FilterDists(db)
fd.filter(infile, outfile, max_dist)
db.close()
def add_region_grid(ctx):
region = ctx.obj['region']
rows = int(ctx.obj['rows'])
cols = int(ctx.obj['cols'])
click.echo('Adding grid of locations for region: %s' % region)
db = DB(ctx.obj['dbname'], ctx.obj['config'])
db.open()
locs = Locations(db)
locs.add_region_grid(region, rows, cols)
db.close()
def replace_low_degree(ctx):
dbname = ctx.obj['dbname']
db = DB(dbname, ctx.obj['config'])
db.open()
infile = ctx.obj['infile']
outfile = ctx.obj['outfile']
min_degree = float(ctx.obj['min_degree'])
rld = ReplaceLowDegree(db, infile, min_degree)
rld.run(outfile)
db.close()
def userscales(ctx):
dbname = ctx.obj['dbname']
infile = ctx.obj['infile']
outfile = ctx.obj['outfile']
scales = ctx.obj['scales']
table = ctx.obj['table']
db = DB(dbname, ctx.obj['config'])
db.open()
us = UserScales(db, outfile, infile, scales, table)
us.generate()
db.close()
def cropgraph(ctx):
infile = ctx.obj['infile']
outfile = ctx.obj['outfile']
min_lat = float(ctx.obj['min_lat'])
min_lng = float(ctx.obj['min_lng'])
max_lat = float(ctx.obj['max_lat'])
max_lng = float(ctx.obj['max_lng'])
db = DB(ctx.obj['dbname'], ctx.obj['config'])
db.open()
cg = CropGraph(db)
cg.crop(infile, outfile, min_lat, min_lng, max_lat, max_lng)
db.close()
def add_area(ctx):
min_lat = float(ctx.obj['min_lat'])
min_lng = float(ctx.obj['min_lng'])
max_lat = float(ctx.obj['max_lat'])
max_lng = float(ctx.obj['max_lng'])
click.echo('Adding locations in area: [%s, %s, %s, %s]' % (min_lat, min_lng, max_lat, max_lng))
db = DB(ctx.obj['dbname'], ctx.obj['config'])
db.open()
locs = Locations(db)
(points, inserted) = locs.add_area(ctx.obj['locs_file'],
min_lat, min_lng, max_lat, max_lng)
db.close()
click.echo('%d points found, %d points added.' % (points, inserted))
def add_grid(ctx):
min_lat = float(ctx.obj['min_lat'])
min_lng = float(ctx.obj['min_lng'])
max_lat = float(ctx.obj['max_lat'])
max_lng = float(ctx.obj['max_lng'])
rows = int(ctx.obj['rows'])
cols = int(ctx.obj['cols'])
click.echo('Adding grid of locations for area: [%s, %s, %s, %s]' % (min_lat, min_lng, max_lat, max_lng))
db = DB(ctx.obj['dbname'], ctx.obj['config'])
db.open()
locs = Locations(db)
locs.add_grid(min_lat, min_lng, max_lat, max_lng, rows, cols)
db.close()
def create_db(ctx):
click.echo("Creating database")
db = DB(ctx.obj["dbname"], ctx.obj["config"])
db.create_db()
db.close()
def crop_region(ctx):
region = ctx.obj["region"]
db = DB(ctx.obj["dbname"], ctx.obj["config"])
db.open()
ghostb.cropdata.crop_region(db, region)
db.close()
def locphotos(ctx):
dbname = ctx.obj["dbname"]
db = DB(dbname, ctx.obj["config"])
db.open()
lp = LocPhotos(db)
lp.update()
