def load_agerast(country, fromage, toage, gender, year):
agestring = format(fromage, "02") + format(toage, "02")
name = next((f['ISO1AL3'] for f in country))
region = {
'AFG': 'Asia',
'COL': 'LAC',
'COD': 'AFR',
'NGA': 'AFR',
'YEM': 'Asia'
}[name]
version = {'AFR': 5, 'Asia': 2, 'LAC': 1}[region]
filename = "{region}_PPP_A{agestring}_{gender}_{year}_adj_v{version}.tif".format(
agestring=agestring,
gender=gender,
year=year,
region=region,
version=version)
print 'loading'
rast = pg.RasterData('data/' + filename)
print rast.filepath
print 'clipping'
clip = rast.manage.clip(country, bbox=country.bbox)
print 'cleaning'
del rast
gc.collect()
return clip
def make_childrast(country, year):
xmin, ymin, xmax, ymax = country.bbox
calcrast = pg.RasterData(
mode='float32',
bbox=[xmin, ymax, xmax,
ymin], #xoffset=country.bbox[0], yoffset=country.bbox[3],
xscale=0.00833333329999305,
yscale=-0.00833333329999305)
calcband = calcrast.add_band()
for gend in "FM":
print gend
for toage in [4, 9, 14, 19]:
fromage = toage - 4
print fromage, toage
rast = load_agerast(country, fromage, toage, gend, year)
print rast.bands[0].summarystats()
rast.view(cutoff=(0, 2))
print 'summing'
if toage == 19:
calcband += rast.bands[0] * (
3 / 5.0
) # in agegroup 15-19, we only want 15-17, which is only 3 of the 5 years
else:
calcband += rast.bands[0]
calcrast.bands[0] = calcband
return calcrast
def load(self):
# TODO: should prob be threaded
filepath = self.filepath.get()
data = None
for typ in pg.vector.loader.file_extensions:
if filepath.endswith(typ):
data = pg.VectorData(filepath, encoding=self.encoding.get())
break
for typ in pg.raster.loader.file_extensions:
if filepath.endswith(typ):
data = pg.RasterData(filepath)
break
self.onsuccess(data)
def viewresult(res):
from PIL import Image
vz = pg.renderer.Map()
for r in res:
props = [] #r[:-1] if len(r) > 1 else []
if r[-1]:
rast = r[
-1] # assumes last value of row is returned as geojson string
aff = list(rast.affine)[:6]
#aff[4] *= -1 # invert for normal images
ims = [Image.fromarray(b.data()) for b in rast.bands]
im = Image.merge('RGB', ims)
d = pg.RasterData(
image=im,
#mode=rast.band(0).dtype, width=rast.width, height=rast.height,
affine=aff)
d.bands[0].nodataval = 0
vz.add_layer(d)
vz.render_all()
vz.view()
import pythongis as pg
rw = 6
rh = 3
w = 360
h = 180
xscale = w / float(rw)
yscale = h / float(rh)
affine = [xscale, 0, -180, 0, -yscale, 90]
r = pg.RasterData(width=rw, height=rh, mode='float32', affine=affine)
rb = r.add_band()
for y in range(rh):
for x in range(rw):
rb.set(x, y, (x + 1) * (y + 1))
v = pg.VectorData()
bounds = [(-180, -90), (180, -90), (180, 90), (-180, 90)]
bounds.append(bounds[0])
v.add_feature([], {'type': 'Polygon', 'coordinates': [bounds]})
m = pg.renderer.Map(2000, 1000, 'white')
m.add_layer(r)
m.add_layer(v, fillcolor=None, outlinecolor='red')
m.zoom_auto()
m.view()
import pythongis as pg
import pycrs
pg.vector.data.DEFAULT_SPATIAL_INDEX = 'quadtree'
data = pg.VectorData(r"P:\(Temp Backup)\priocountries\priocountries.shp")#"C:\Users\kimok\Desktop\BIGDATA\priocountries\priocountries.shp")
rast = pg.RasterData(r"C:\Users\kimok\Documents\GitHub\AutoMap\tests\testmaps\burkina_pol96_georeferenced.tif")
#testcrs = '+proj=robin +datum=WGS84 +ellps=WGS84 +a=6378137.0 +rf=298.257223563 +pm=0 +lon_0=0 +x_0=0 +y_0=0 +units=m +axis=enu +no_defs'
#testcrs = pycrs.parse.from_sr_code(6980).to_proj4() # space
#testcrs = pycrs.parse.from_sr_code(7619).to_proj4() # goode?
#testcrs = next(pycrs.utils.search('van der grinten'))['proj4']
testcrs = next(pycrs.utils.search('eckert iv'))['proj4']
#### original crs
#data.view()
#### test on-the-fly crs
#data.view(crs=testcrs)
#### raster crs
rast.save('C:/Users/kimok/Desktop/testmap.png')
#rast.view() #testcrs)
#rast.manage.reproject(testcrs, resample='nearest').view()
#rast.manage.reproject(testcrs, resample='bilinear').view()
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import unittest
import pythongis as pg
# data
pointdata = pg.VectorData('data/ne_10m_populated_places_simple.shp',
encoding='latin')
linedata = pg.VectorData('data/ne_10m_railroads.shp', encoding='latin')
polygondata = pg.VectorData('data/ne_10m_admin_0_countries.shp',
encoding='latin')
rasterdata = pg.RasterData('data/land_shallow_topo_2048.png')
rasterdata.set_geotransform(width=2048,
height=1024,
affine=[0.175781250, 0, -180, 0, -0.175781250, 90])
# base class
class BaseTestCases:
class DrawShapes(unittest.TestCase):
width = 600
height = 300
kwargs = {'fillcolor': 'yellow', 'outlinecolor': 'black'}
output_prefix = 'render_projections'
crs = None
def create_map(self):
self.map = pg.renderer.Map(self.width,
self.height,
background='gray',
import pythongis as pg
import gc
countries = pg.VectorData(r"C:\Users\kimok\Desktop\ch est\data\cshapes.shp")
countries = countries.select(
lambda f: f["GWCODE"] != -1 and f["GWEYEAR"] == 2016)
print countries
# mapit
#rast = pg.RasterData(r'C:\Users\kimok\Downloads\F182013.v4c_web.stable_lights.avg_vis.tif')
rast = pg.RasterData(
r'C:\Users\kimok\Downloads\SVDNB_npp_20170701-20170731_75N060W_vcmcfg_v10_c201708061230.avg_rade9.tif'
)
print rast
for iso in ['NGA', 'COD', 'YEM']:
print iso
c = countries.select(lambda f: f["ISO1AL3"] == iso)
clip = rast.manage.clip(c, bbox=c.bbox)
print clip
clip.view(cutoff=(0.1, 99.9))
print 'finished!'
import pythongis as pg
###
print("\n" + "raster test")
rast = pg.RasterData(
r"C:\Users\kimo\Dropbox\Work\Workplace\Geobook15\pygeo book 2\code\(raw sandbox,incl abondoned ideas)\test_files\geotiff\TrueMarble.16km.2700x1350.tif"
)
for b in rast.bands:
#b.img.show()
b.nodataval = 0 # note: if set nodataval first and then manually override mask, means previous nodatavals wont get affected
#b.mask.show()#view(1000,500)
#b.img.show()
#rast.bands.pop(-1)
#rast.bands = rast.bands[:1]
print rast.bands
#rast.mask.show()
#rast.mask = rast.bands[0].conditional("val == 0").img
#rast.mask.show()
#rast.view(1000,500, type="colorscale", gradcolors=[(0,0,255),(0,255,0),(255,0,0)])
#iyiy
###
print("\n" + "multimap test")
mapp = pg.renderer.Map()
vect = pg.vector.data.VectorData(
r"C:\Users\kimo\Dropbox\Work\Workplace\Geobook15\pygeo book 2\code\(raw sandbox,incl abondoned ideas)\test_files\shp\domestic.shp"
)
print vect.fields
mapp.add_layer(rast,
bandnum=1,
import pythongis as pg
import gc
countries = pg.VectorData("data/ne_10m_admin_0_countries.shp")
print countries
# mapit
rast = pg.RasterData(r'C:\Users\kimok\Downloads\F182013.v4c_web.stable_lights.avg_vis.tif')
for iso in ['TUR']:
print iso
c = countries.select(lambda f: f["ISO_A3"]==iso)
clip = rast.manage.clip(c, bbox=c.bbox)
print clip
mapp = pg.renderer.Map()
mapp.add_layer(clip)
mapp.add_layer(c, fillcolor=None)
mapp.add_legend()
mapp.view()
c = c.manage.reproject('+proj=robin')
clip = clip.manage.reproject('+proj=robin')
mapp = pg.renderer.Map()
mapp.add_layer(clip)
mapp.add_layer(c, fillcolor=None)
mapp.add_legend()
mapp.view()
import pythongis as pg
import gc
# create the test data
##focus = pg.VectorData("data/ne_10m_admin_0_countries.shp", select=lambda f: f['ISO_A3']=='IRN')
##print focus
##for yr in [1990,2000,2015]:
## rast = pg.RasterData(r"C:\Users\kimok\Desktop\redd barna\Input\pop%s.tif"%yr)
## clip = rast.manage.clip(focus, bbox=focus.bbox)
## print clip
## clip.save('data/pop%s.tif'%yr)
for yr, rast in pg.raster.manager.sequence(
range(1990, 2015 + 1),
rasts={
1990: lambda: pg.RasterData(r'data/pop1990.tif'),
2000: lambda: pg.RasterData(r'data/pop2000.tif'),
2015: lambda: pg.RasterData(r'data/pop2015.tif')
}):
print yr
#print rast.bands[0].summarystats()
#rast.view()
def view_image(self, mapID):
import pythongis as pg
import urllib
import io
# get map info
link, width, height, mapregion = self.get(
'select link,width,height,mapregion from maps where oid=?',
(mapID, ))
# init renderer
render = pg.renderer.Map(width, height)
render._create_drawer()
render.drawer.pixel_space()
# load image
print 'loading', link
if link.startswith('http'):
fobj = io.BytesIO(urllib.urlopen(link).read())
img = PIL.Image.open(fobj)
else:
img = PIL.Image.open(link)
rast = pg.RasterData(image=img)
render.add_layer(rast)
# add image regions
bounds = pg.VectorData()
bounds.add_feature([], json.loads(mapregion))
render.add_layer(bounds,
fillcolor=None,
outlinecolor='red',
outlinewidth=0.2)
# add text
texts = pg.VectorData(fields=['text', 'conf'])
textquery = self.query(
'select text,conf,left,top,width,height from maptext where maptext.map = ?',
(mapID, ))
for text in textquery:
x1, y1 = text['left'], text['top']
x2, y2 = x1 + text['width'], y1 + text['height']
box = [x1, y1, x2, y2]
row = [text['text'], text['conf']]
geoj = {
'type': 'Polygon',
'coordinates': [[(x1, y1), (x2, y1), (x2, y2), (x1, y2)]]
}
texts.add_feature(row, geoj)
render.add_layer(texts,
fillcolor=None,
outlinecolor='green',
outlinewidth=0.5)
# add tiepoints
tiepoints = pg.VectorData()
tiepointquery = self.query(
'select col,row from maptiepoints where maptiepoints.map = ?',
(mapID, ))
for col, row in tiepointquery:
geoj = {'type': 'Point', 'coordinates': (col, row)}
tiepoints.add_feature([], geoj)
if len(tiepoints):
render.add_layer(tiepoints,
fillcolor=None,
outlinecolor='red',
outlinewidth=0.3)
# view
render.zoom_auto()
render.view()
#print lat,lon
d.add_feature(row=[col, row, i],
geometry={
'type': 'Point',
'coordinates': (lon, lat)
})
d.view(fillcolor=dict(breaks='proportional', key='i'))
dvec = d
# raw grid
data = [v for r in vals[time] for v in r]
import PIL, PIL.Image
img = PIL.Image.new('L', (88, 88))
img.putdata(data)
d = pg.RasterData(image=img, width=88, height=88, bbox=[0, 0, 1, 1])
d.view()
# projected stereo
import pyproj
stereo = pyproj.Proj(init='EPSG:3411')
d = pg.VectorData(fields=['col', 'row', 'i', 'val'])
for col in range(88):
#print col
for row in range(88):
i = col * row + row
lat, lon = lats[row, col], lons[row, col]
val = vals[time, row, col]
if val == 0: continue
#print lat,lon
x, y = stereo(lon, lat)