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succession.py
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succession.py
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import os
import logging
import arcpy
import numpy as np
import pandas as pd
import scipy.stats as ss
import settings as s
import utils
import tree_allometry as ta
class Succession(object):
def __init__(self, year):
self.year = year
self._ecocommunities_filename = 'ecocommunities_%s.tif'
utils.set_arc_env(s.ecocommunities)
self.canopy = None
self.forest_age = None
self.dbh = None
self.ecocommunities = None
self.climax_communities = arcpy.RasterToNumPyArray(s.ecocommunities)
self.climax_canopy = None
self.pond_time_since_disturbance = None
self.garden_time_since_disturbance = None
self.community_table = pd.read_csv(s.COMMUNITY_TABLE, index_col=0)
self.dbh_lookup = pd.read_csv(s.DBH_LOOKUP, index_col=0)
self.header, self.header_text, self.shape = utils.get_ascii_header(s.reference_ascii)
self.set_ecocommunities()
self.set_canopy()
self.set_forest_age()
self.set_dbh()
def set_ecocommunities(self):
this_year_ecocomms = os.path.join(s.OUTPUT_DIR, self._ecocommunities_filename % self.year)
last_year_ecocomms = os.path.join(s.OUTPUT_DIR, self._ecocommunities_filename % (self.year - 1))
if os.path.isfile(this_year_ecocomms):
logging.info(this_year_ecocomms)
ecocomm = arcpy.Raster(this_year_ecocomms)
ecocomm.save(os.path.join(s.TEMP_DIR, 'ecosystems_before_RasterToNumPyArray_{}.tif'.format(self.year)))
self.ecocommunities = arcpy.RasterToNumPyArray(this_year_ecocomms)
elif os.path.isfile(last_year_ecocomms):
logging.info(last_year_ecocomms)
ecocomm = arcpy.Raster(last_year_ecocomms)
ecocomm.save(os.path.join(s.TEMP_DIR, 'ecosystems_before_RasterToNumPyArray_{}.tif'.format(self.year)))
self.ecocommunities = arcpy.RasterToNumPyArray(last_year_ecocomms)
else:
logging.info('initial run')
logging.info(s.ecocommunities)
self.ecocommunities = arcpy.RasterToNumPyArray(s.ecocommunities)
# ecocomm = arcpy.NumPyArrayToRaster(self.ecocommunities,
# arcpy.Point(arcpy.env.extent.XMin, arcpy.env.extent.YMin),
# x_cell_size=s.CELL_SIZE,
# y_cell_size=s.CELL_SIZE)
# ecocomm.save(os.path.join(s.TEMP_DIR, 'ecosystems_after_set_ecocommunities_{}.tif'.format(self.year)))
self.shape = self.ecocommunities.shape
def set_canopy(self):
"""
set canopy for given year if no canopy raster exists, use previous year,
else: initialize canopy raster
:return:
"""
if os.path.isfile(s.CANOPY):
logging.info('Setting canopy')
self.canopy = arcpy.RasterToNumPyArray(s.CANOPY)
else:
logging.info('Assigning initial values to canopy array')
# if self.ecocommunities_array is None:
# self.ecocommunities_array = arcpy.RasterToNumPyArray(self.ecocommunities)
self.canopy = np.empty(self.shape, dtype=np.int8)
for index, row in self.community_table.iterrows():
self.canopy[self.ecocommunities == index] = row.max_canopy
canopy = arcpy.NumPyArrayToRaster(self.canopy,
arcpy.Point(arcpy.env.extent.XMin, arcpy.env.extent.YMin),
x_cell_size=s.CELL_SIZE,
y_cell_size=s.CELL_SIZE)
canopy.save(s.CANOPY)
def set_forest_age(self):
"""
set forest age for given year, if no forest age raster exists, use previous year,
else: initialize froest age raster
:return:
"""
if os.path.isfile(s.FOREST_AGE):
logging.info('Setting forest age')
self.forest_age = arcpy.RasterToNumPyArray(s.FOREST_AGE)
else:
logging.info('Assigning initial values to forest age array')
# if self.ecocommunities_array is None:
# self.ecocommunities_array = arcpy.RasterToNumPyArray(self.ecocommunities)
# create truncated normal distrbution for age
lower = s.MINIMUM_FOREST_AGE
upper = s.MAXIMUM_FOREST_AGE
mu = s.MEAN_INITIAL_FOREST_AGE
sigma = s.AGE_VAR
n = ss.truncnorm((lower - mu) / sigma, (upper - mu) / sigma, loc=mu, scale=sigma)
# populate an array with ages from distribution
tn = n.rvs(self.shape).astype(int)
self.forest_age = np.empty(shape=self.shape, dtype=np.int32)
for index, row in self.community_table.iterrows():
if row.forest == 1:
self.forest_age = np.where(self.ecocommunities == index, tn, self.forest_age)
forestage = arcpy.NumPyArrayToRaster(self.forest_age,
arcpy.Point(arcpy.env.extent.XMin, arcpy.env.extent.YMin),
x_cell_size=s.CELL_SIZE,
y_cell_size=s.CELL_SIZE)
forestage.save(s.FOREST_AGE)
def set_dbh(self):
if os.path.isfile(s.DBH):
logging.info('Setting dbh')
self.dbh = arcpy.RasterToNumPyArray(s.DBH)
else:
logging.info('Assigning initial values to dbh array')
self.dbh = np.zeros(shape=self.shape, dtype=np.float32)
# self.dbh = np.empty(shape=self.shape, dtype=np.float16)
for index, row in self.community_table.iterrows():
if row.forest == 1:
age = np.ma.masked_where(self.ecocommunities != index, self.forest_age)
if s.DEBUG_MODE:
logging.info(index)
for a in np.ma.compressed(np.unique(age)):
if s.DEBUG_MODE:
logging.info(a)
d = self.dbh_lookup.ix[int(a)][str(index)]
self.dbh[(self.ecocommunities == index) & (self.forest_age == a)] = d
dbh = arcpy.NumPyArrayToRaster(self.dbh,
arcpy.Point(arcpy.env.extent.XMin, arcpy.env.extent.YMin),
x_cell_size=s.CELL_SIZE,
y_cell_size=s.CELL_SIZE)
dbh.save(s.DBH)
def grow(self):
"""
for each upland community increment canopy, forest age and DBH
:return:
"""
for index, row in self.community_table.iterrows():
canopy_growth = int(row['canopy_growth'])
max_canopy = int(row['max_canopy'])
# increment age of all communities that have trees all upland communities
if row['forest'] == 1:
# increment canopy
self.canopy[(self.ecocommunities == index) & (self.canopy < max_canopy)] += canopy_growth
elif max_canopy > 0 and row.forest == 0:
# increment non forest canopy
self.canopy[(self.ecocommunities == index)] += canopy_growth
if max_canopy > 0:
# increment forest age
self.forest_age[self.ecocommunities == index] += 1
# increment dbh
if s.DEBUG_MODE:
logging.info("%s %s | max canopy: %s" % (index, row['Name'], max_canopy))
self.dbh[(self.ecocommunities == index) &
(self.forest_age == 1)
& (self.dbh == 0)] = 0.5
dbh_model = int(row['dbh_model'])
site_index = int(row['site_index'])
d_grow = ta.get_dgrow(species=dbh_model, site_index=site_index, dbh=self.dbh)
self.dbh = np.where(self.ecocommunities == index, self.dbh + d_grow, self.dbh)
def transition(self):
"""
for each community type, transition the community to new state if conditions are met
:return:
"""
for index, row in self.community_table.iterrows():
# CANOPY BASED SUCCESSION
if row.succession_code == 1:
self.ecocommunities[(self.ecocommunities == index) &
(self.canopy > row['max_canopy'])] = row.to_ID
# AGE BASED SUCCESSION
elif row.succession_code == 2:
self.ecocommunities = np.where((self.ecocommunities == index) &
(self.forest_age > row['age_out']),
self.climax_communities, self.ecocommunities)
def run_succession(self):
self.grow()
self.transition()
e = os.path.join(s.OUTPUT_DIR, self._ecocommunities_filename % self.year)
ecocomm = arcpy.NumPyArrayToRaster(self.ecocommunities,
arcpy.Point(arcpy.env.extent.XMin, arcpy.env.extent.YMin),
x_cell_size=s.CELL_SIZE,
y_cell_size=s.CELL_SIZE)
# ecocomm.save(os.path.join(s.TEMP_DIR, 'ecosystems_after_succession_{}.tif'.format(self.year)))
ecocomm.save(e)
canopy = arcpy.NumPyArrayToRaster(self.canopy,
arcpy.Point(arcpy.env.extent.XMin, arcpy.env.extent.YMin),
x_cell_size=s.CELL_SIZE,
y_cell_size=s.CELL_SIZE)
canopy.save(s.CANOPY)
forestage = arcpy.NumPyArrayToRaster(self.forest_age,
arcpy.Point(arcpy.env.extent.XMin, arcpy.env.extent.YMin),
x_cell_size=s.CELL_SIZE,
y_cell_size=s.CELL_SIZE)
forestage.save(s.FOREST_AGE)
dbh = arcpy.NumPyArrayToRaster(self.dbh,
arcpy.Point(arcpy.env.extent.XMin, arcpy.env.extent.YMin),
x_cell_size=s.CELL_SIZE,
y_cell_size=s.CELL_SIZE)
dbh.save(s.DBH)
# s1 = Succession(1508)
# logging.info(s1.succession_table.head())
# s1.run_succession()
#
# for index, row in s1.succession_table.iterrows():
# key = row['from_ID']
# logging.info(key, type(key))
# logging.info(row['max_canopy'])
# logging.info(row['to_ID'], type(row['to_ID']))
# if key == 635:
# self.communities[(self.communities == key) &
# (self.canopy > row['max_canopy'])] = row['to_ID']
# logging.info('communities \n')
# logging.info(s1.communities)
# logging.info('canopy \n')
# logging.info(s1.canopy)
# run = range(0, 25)
# for year in run:
# logging.info('year: %s' % year)
# s1.grow()
# s1.transition()
# logging.info('communities \n')
# logging.info(s1.communities)
# logging.info('canopy \n')
# logging.info(s1.canopy)
#
# if year == max(run):
# # communities
# ax = plt.subplot(311)
# ax.imshow(s1.communities, interpolation='none')
# min_val, max_val = 0, s1.shape[0]
# ind_array = np.arange(min_val, max_val, 1.0)
# x, y = np.meshgrid(ind_array, ind_array)
#
# for x_val, y_val, com in zip(x.flatten(), y.flatten(), s1.communities.flatten()):
# c = int(com)
# ax.text(x_val, y_val, c, va='center', ha='center', color='white')
#
# # logging.info(s1.communities)
# ax2 = plt.subplot(312)
# ax2.imshow(s1.communities, interpolation='none')
#
# # canopy
# min_val, max_val = 0, s1.shape[0]
# ind_array = np.arange(min_val, max_val, 1.0)
# x, y = np.meshgrid(ind_array, ind_array)
#
# for x_val, y_val, com in zip(x.flatten(), y.flatten(), s1.canopy.flatten()):
# c = int(com)
# ax2.text(x_val, y_val, c, va='center', ha='center', color='red')
#
# ax2.imshow(s1.canopy, interpolation='none', cmap='Greens')
#
# # forest age
# ax3 = plt.subplot(313)
# ax3.imshow(s1.forest_age, interpolation='none')
# min_val, max_val = 0, s1.shape[0]
# ind_array = np.arange(min_val, max_val, 1.0)
# x, y = np.meshgrid(ind_array, ind_array)
#
# for x_val, y_val, com in zip(x.flatten(), y.flatten(), s1.forest_age.flatten()):
# c = int(com)
# ax3.text(x_val, y_val, c, va='center', ha='center', color='red')
#
# ax3.imshow(s1.forest_age, interpolation='none', cmap='Blues')
# plt.show()
# # logging.info(s1.canopy)