Student's code snippets for Tangible Landscape

TL_class.py

# Ruixue Wang
def run_contour(scanned_elev,env,**kwargs):
    gscript.run_command('r.contour',input=scanned_elev,output='Ruixue_contour',step=2,env=env)
    
# Rohith
def run_mvwatershed(scanned_elev, env, **kwargs):
    gscript.run_command('r.watershed', elevation=scanned_elev, accumulation='flow_accum',
                        basin='watersheds', threshold=800, env=env)
    gscript.run_command('r.slope.aspect', elevation=scanned_elev, slope='slope', env=env)
    gscript.run_command('r.stats.zonal', base='watersheds', cover='slope', method='average',
                        output='watersheds_slope', env=env)
    gscript.run_command('r.colors', map='watersheds_slope', color='bgyr', env=env)
    
 # Kimia
 def run_slopeK(scanned_elev,env,**kwargs):
    gscript.run_command('r.watershed',elevation=scanned_elev, accumulation='flow_accum',basin='watersheds',threshold=1000,env=env)
    gscript.run_command('r.slope.aspect', elevation=scanned_elev, slope='slope', env=env)
    gscript.run_command('r.stats.zonal', base='watersheds', cover='slope', method='average',output='watersheds_slope',env=env)
    gscript.run_command('r.colors', map='watersheds_slope', color='bgyr', env=env)
    
#shannon
def run_pond_shan(scanned_elev, env, **kwargs):
    repeat = 2
    input_dem = scanned_elev
    output = "tmp_filldir"
    for i in range(repeat):
        gscript.run_command('r.fill.dir', input=input_dem, output=output, direction="tmp_dir", env=env)
        input_dem = output
    # filter depression deeper than 0.1 m to
    gscript.mapcalc('{new} = if({out} - {scan} > 0.1, {out} - {scan}, null())'.format(new='ponds', out=output,
                                                                                      scan=scanned_elev), env=env)
    gscript.write_command('r.colors', map='ponds', rules='-', stdin='0% aqua\n100% blue', env=env)
    
# Kellyn local relief (may need to install add on)
def run_local_relief(scanned_elev, env, **kwargs):
    # compute the analysis
    gscript.run_command('r.local.relief', input=scanned_elev, 
        color_table="differences", shaded_output="kellyn_shadedlocal", 
        output="kellyn_localrelief", env=env)

# Kellyn's geomorphons
def run_geomorph(scanned_elev, env, **kwargs):
    # compute the analysis
    gscript.run_command('r.geomorphon', elevation=scanned_elev, 
        search=3, skip=0, dist=0, forms="kellyn_geomorph", env=env)

## Zekun
def run_solar(scanned_elev, env, **kwargs):
    gscript.run_command('r.sun', elevation=scanned_elev, day=31, beam_rad=zekun_beam,env=env)
    
## Megan
def run_flow(scanned_elev, env, **kwargs):
    gscript.run_command('r.flow', elevation = scanned_elev, flowline = 'flowline', env=env)
    
# Corey v.surf.rst
def run_surf_rst_corey(scanned_elev, env, **kwargs):
    # compute the analysis
    gscript.run_command('r.random', input=scanned_elev, vector="tmp_elev_points", npoints=500, env=env)
    gscript.run_command('v.surf.rst', input="tmp_elev_points", elevation="corey_elev", zcolumn="value", env=env)
    gscript.mapcalc('{difference} = {original} - {calc}'.format(original=scanned_elev, calc="corey_elev", difference='diff_corey'), env=env)
    gscript.run_command('r.colors', map='diff_corey', color='differences', env=env)
    
# Vishnu
def run_slope(scanned_elev, env, **kwargs):
    # compute the analysis
    gscript.run_command('r.slope.aspect',  elevation=scanned_elev , slope='vv_slope_elev_lid792_1m',  aspect='vv_aspect_elev_lid792_1m', env=env) 
    
#Mandy's r.sim.water
def MandySimWater(scanned_elev, env, **kwargs): 
	gscript.run_command('r.slope.aspect', elevation=scanned_elev, slope='slope', aspect='aspect', dx='dxscanelev', dy='dyscanelev', env=env)
	gscript.run_command('r.sim.water', elevation=scanned_elev, dx='dxscanelev', dy='dyscanelev', depth='depth50mm', env=env)
 
# Nikki 
def run_nikki(scanned_elev, env, **kwargs):
    data = gscript.read_command('v.out.ascii', input='change', type='point', format='point', env=env).strip()
    c1, c2 = data.splitlines()
    c1 = c1.split('|')
    c2 = c2.split('|')
    start = (float(c1[0]), float(c1[1]))
    end = (float(c2[0]), float(c2[1]))

    gscript.run_command('r.slope.aspect', elevation=scanned_elev, slope='slope', env=env)
    gscript.run_command('r.cost', input='slope', output='cost', start_coordinates=start,
                        outdir='outdir', flags='k', env=env)
    gscript.run_command('r.colors', map='cost', color='gyr', env=env)
    gscript.run_command('r.drain', input='cost', output='drain', direction='outdir',
                        drain='drain', flags='d', start_coordinates=end, env=env)
    gscript.run_command('v.to.points', input='drain', output='points', dmax='20', flags='pr', env=env)
    gscript.run_command('r.viewshed.cva', input=scanned_elev, vector='points', output='cva', env=env)


# Garrett
def run_LCP(scanned_elev, env, **kwargs):
    data = gscript.read_command('v.out.ascii', input='change', type='point', format='point', env=env).strip()
    c1, c2 = data.splitlines()
    c1 = c1.split('|')
    c2 = c2.split('|')
    start = (float(c1[0]), float(c1[1]))
    end = (float(c2[0]), float(c2[1]))

    gscript.run_command('r.slope.aspect', elevation=scanned_elev, slope='slope', env=env)
    gscript.run_command('r.cost', input='slope', output='cost', start_coordinates=start,
                        outdir='outdir', flags='k', env=env)
    gscript.run_command('r.colors', map='cost', color='gyr', env=env)
    gscript.run_command('r.drain', input='cost', output='drain', direction='outdir',
                        drain='drain', flags='d', start_coordinates=end, env=env)




from tangible_utils import get_environment

def run_points(scanned_elev, real_elev, env, **kwargs):
    env_crop = get_environment(raster=real_elev, n='n-100', s='s+100', e='e-100', w='w+100')
    analyses.change_detection('scan_saved', scanned_elev, 'change', height_threshold=[15, 100], cells_threshold=[5, 100], add=True,
    max_detected=2, debug=True, env=env_crop)