def grow_landuse(land1, num_growth_pix):
nrows = IGrid.nrows
ncols = IGrid.ncols
ticktock = Processing.get_current_year()
landuse0_year = IGrid.igrid.get_landuse_year(0)
landuse1_year = IGrid.igrid.get_landuse_year(1)
urban_code = LandClass.get_urban_code()
new_indices = LandClass.get_new_indices()
landuse_classes = LandClass.get_landclasses()
class_indices = LandClass.get_reduced_classes()
background = IGrid.igrid.get_background()
slope = IGrid.igrid.get_slope()
deltatron = PGrid.get_deltatron()
z = PGrid.get_z()
land2 = PGrid.get_land2()
class_slope = Transition.get_class_slope()
ftransition = Transition.get_ftransition()
if ticktock >= landuse0_year:
# Place the New Urban Simulation into the Land Use Image
Utilities.condition_gt_gif(z.gridData, 0, land1.gridData,
urban_code)
Deltatron.deltatron(new_indices, landuse_classes, class_indices,
deltatron, land1, land2, slope, num_growth_pix,
class_slope, ftransition)
# Switch the old to the new
for i in range(len(land2.gridData)):
land1.gridData[i] = land2.gridData[i]
if Processing.get_processing_type() == Globals.mode_enum['predict'] or \
(Processing.get_processing_type() == Globals.mode_enum['test'] and
Processing.get_current_monte() == Processing.get_last_monte()):
#Write land1 to file
if IGrid.using_gif:
filename = f"{Scenario.get_scen_value('output_dir')}{IGrid.igrid.location}_land_n_urban" \
f".{Processing.get_current_year()}.gif"
else:
filename = f"{Scenario.get_scen_value('output_dir')}{IGrid.igrid.location}_land_n_urban" \
f".{Processing.get_current_year()}.tif"
IGrid.echo_meta(
f"{Scenario.get_scen_value('output_dir')}{IGrid.igrid.location}_land_n_urban."
f"{Processing.get_current_year()}.tfw", "landuse")
date = f"{Processing.get_current_year()}"
ImageIO.write_gif(land1, Color.get_landuse_table(), filename, date,
nrows, ncols)
# Compute final match statistics for landuse
Utilities.condition_gt_gif(z.gridData, 0, land1.gridData, urban_code)
