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Comb_FIS.py
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Comb_FIS.py
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# -------------------------------------------------------------------------------
# Name: Comb_FIS
# Purpose: Runs the combined FIS for the BRAT input table
#
# Author: Jordan Gilbert
#
# Created: 09/2016
# Copyright: (c) Jordan 2016
# Licence: <your licence>
# -------------------------------------------------------------------------------
import arcpy
import skfuzzy as fuzz
from skfuzzy import control as ctrl
import numpy as np
import os
import sys
from SupportingFunctions import make_layer, make_folder, find_available_num_prefix, \
find_relative_path, write_xml_element_with_path
import XMLBuilder
reload(XMLBuilder)
XMLBuilder = XMLBuilder.XMLBuilder
def main(proj_path, in_network, max_da_thresh, out_name):
"""
The main function, runs the combined FIS for the BRAT input table
:param proj_path: The path to the project folder for this BRAT run
:param in_network: The input BRAT network
:param max_da_thresh: The drainage area value above which the stream is assumed to not support dam building
:param out_name: The output name for the Combined Capacity Network
:return:
"""
scratch = 'in_memory'
output_folder = os.path.dirname(os.path.dirname(in_network))
analyses_folder = make_folder(output_folder, "02_Analyses")
if out_name.endswith('.shp'):
out_network = os.path.join(analyses_folder, out_name)
else:
out_network = os.path.join(analyses_folder, out_name + ".shp")
if os.path.exists(out_network):
arcpy.Delete_management(out_network)
arcpy.CopyFeatures_management(in_network, out_network)
# run the combined fis function for both potential and existing
comb_cap_fis(out_network, 'hpe', scratch, max_da_thresh)
comb_cap_fis(out_network, 'ex', scratch, max_da_thresh)
make_layers(out_network)
add_xml_output(in_network, out_network)
def comb_cap_fis(in_network, model_run, scratch, max_da_thresh):
"""
The combined capacity FIS function
:param in_network: The input BRAT network
:param model_run: The model being run, either 'Hpe' or 'ex" (Potential or Existing)
:param scratch: The current workspace
:param max_da_thresh: The drainage area value above which the stream is assumed to not support dam building
:return:
"""
arcpy.env.overwriteOutput = True
# get list of all fields in the flowline network
fields = [f.name for f in arcpy.ListFields(in_network)]
# set the carrying capacity and vegetation field depending on whether potential or existing run
if model_run == 'hpe':
out_field = "oCC_HPE"
veg_field = "oVC_HPE"
mcc_field = "mCC_HPE_CT"
else:
out_field = "oCC_EX"
veg_field = "oVC_EX"
mcc_field = "mCC_EX_CT"
# check for oCC_* field in the network attribute table and delete if exists
if out_field in fields:
arcpy.DeleteField_management(in_network, out_field)
# get arrays for fields of interest
segid_np = arcpy.da.FeatureClassToNumPyArray(in_network, "ReachID")
ovc_np = arcpy.da.FeatureClassToNumPyArray(in_network, veg_field)
ihydsp2_np = arcpy.da.FeatureClassToNumPyArray(in_network, "iHyd_SP2")
ihydsplow_np = arcpy.da.FeatureClassToNumPyArray(in_network, "iHyd_SPLow")
igeoslope_np = arcpy.da.FeatureClassToNumPyArray(in_network, "iGeo_Slope")
segid_array = np.asarray(segid_np, np.int64)
ovc_array = np.asarray(ovc_np, np.float64)
ihydsp2_array = np.asarray(ihydsp2_np, np.float64)
ihydsplow_array = np.asarray(ihydsplow_np, np.float64)
igeoslope_array = np.asarray(igeoslope_np, np.float64)
# check that inputs are within range of fis
# if not, re-assign the value to just within range
ovc_array[ovc_array < 0] = 0
ovc_array[ovc_array > 45] = 45
ihydsp2_array[ihydsp2_array < 0] = 0.0001
ihydsp2_array[ihydsp2_array > 10000] = 10000
ihydsplow_array[ihydsplow_array < 0] = 0.0001
ihydsplow_array[ihydsplow_array > 10000] = 10000
igeoslope_array[igeoslope_array > 1] = 1
# delete temp arrays
items = [segid_np, ovc_np, ihydsp2_np, ihydsplow_np, igeoslope_np]
for item in items:
del item
# create antecedent (input) and consequent (output) objects to hold universe variables and membership functions
ovc = ctrl.Antecedent(np.arange(0, 45, 0.01), 'input1')
sp2 = ctrl.Antecedent(np.arange(0, 10000, 1), 'input2')
splow = ctrl.Antecedent(np.arange(0, 10000, 1), 'input3')
slope = ctrl.Antecedent(np.arange(0, 1, 0.0001), 'input4')
density = ctrl.Consequent(np.arange(0, 45, 0.01), 'result')
# build membership functions for each antecedent and consequent object
ovc['none'] = fuzz.trimf(ovc.universe, [0, 0, 0.1])
ovc['rare'] = fuzz.trapmf(ovc.universe, [0, 0.1, 0.5, 1.5])
ovc['occasional'] = fuzz.trapmf(ovc.universe, [0.5, 1.5, 4, 8])
ovc['frequent'] = fuzz.trapmf(ovc.universe, [4, 8, 12, 25])
ovc['pervasive'] = fuzz.trapmf(ovc.universe, [12, 25, 45, 45])
sp2['persists'] = fuzz.trapmf(sp2.universe, [0, 0, 1000, 1200])
sp2['breach'] = fuzz.trimf(sp2.universe, [1000, 1200, 1600])
sp2['oblowout'] = fuzz.trimf(sp2.universe, [1200, 1600, 2400])
sp2['blowout'] = fuzz.trapmf(sp2.universe, [1600, 2400, 10000, 10000])
splow['can'] = fuzz.trapmf(splow.universe, [0, 0, 150, 175])
splow['probably'] = fuzz.trapmf(splow.universe, [150, 175, 180, 190])
splow['cannot'] = fuzz.trapmf(splow.universe, [180, 190, 10000, 10000])
slope['flat'] = fuzz.trapmf(slope.universe, [0, 0, 0.0002, 0.005])
slope['can'] = fuzz.trapmf(slope.universe, [0.0002, 0.005, 0.12, 0.15])
slope['probably'] = fuzz.trapmf(slope.universe, [0.12, 0.15, 0.17, 0.23])
slope['cannot'] = fuzz.trapmf(slope.universe, [0.17, 0.23, 1, 1])
density['none'] = fuzz.trimf(density.universe, [0, 0, 0.1])
density['rare'] = fuzz.trapmf(density.universe, [0, 0.1, 0.5, 1.5])
density['occasional'] = fuzz.trapmf(density.universe, [0.5, 1.5, 4, 8])
density['frequent'] = fuzz.trapmf(density.universe, [4, 8, 12, 25])
density['pervasive'] = fuzz.trapmf(density.universe, [12, 25, 45, 45])
# build fis rule table
rule1 = ctrl.Rule(ovc['none'], density['none'])
rule2 = ctrl.Rule(splow['cannot'], density['none'])
rule3 = ctrl.Rule(slope['cannot'], density['none'])
rule4 = ctrl.Rule(ovc['rare'] & sp2['persists'] & splow['can'] & ~slope['cannot'], density['rare'])
rule5 = ctrl.Rule(ovc['rare'] & sp2['persists'] & splow['probably'] & ~slope['cannot'], density['rare'])
rule6 = ctrl.Rule(ovc['rare'] & sp2['breach'] & splow['can'] & ~slope['cannot'], density['rare'])
rule7 = ctrl.Rule(ovc['rare'] & sp2['breach'] & splow['probably'] & ~slope['cannot'], density['rare'])
rule8 = ctrl.Rule(ovc['rare'] & sp2['oblowout'] & splow['can'] & ~slope['cannot'], density['rare'])
rule9 = ctrl.Rule(ovc['rare'] & sp2['oblowout'] & splow['probably'] & ~slope['cannot'], density['rare'])
rule10 = ctrl.Rule(ovc['rare'] & sp2['blowout'] & splow['can'] & ~slope['cannot'], density['none'])
rule11 = ctrl.Rule(ovc['rare'] & sp2['blowout'] & splow['probably'] & ~slope['cannot'], density['none'])
rule12 = ctrl.Rule(ovc['occasional'] & sp2['persists'] & splow['can'] & ~slope['cannot'], density['occasional'])
rule13 = \
ctrl.Rule(ovc['occasional'] & sp2['persists'] & splow['probably'] & ~slope['cannot'], density['occasional'])
rule14 = ctrl.Rule(ovc['occasional'] & sp2['breach'] & splow['can'] & ~slope['cannot'], density['occasional'])
rule15 = ctrl.Rule(ovc['occasional'] & sp2['breach'] & splow['probably'] & ~slope['cannot'], density['occasional'])
rule16 = ctrl.Rule(ovc['occasional'] & sp2['oblowout'] & splow['can'] & ~slope['cannot'], density['occasional'])
rule17 = \
ctrl.Rule(ovc['occasional'] & sp2['oblowout'] & splow['probably'] & ~slope['cannot'], density['occasional'])
rule18 = ctrl.Rule(ovc['occasional'] & sp2['blowout'] & splow['can'] & ~slope['cannot'], density['rare'])
rule19 = ctrl.Rule(ovc['occasional'] & sp2['blowout'] & splow['probably'] & ~slope['cannot'], density['rare'])
rule20 = ctrl.Rule(ovc['frequent'] & sp2['persists'] & splow['can'] & slope['flat'], density['occasional'])
rule21 = ctrl.Rule(ovc['frequent'] & sp2['persists'] & splow['can'] & slope['can'], density['frequent'])
rule22 = ctrl.Rule(ovc['frequent'] & sp2['persists'] & splow['can'] & slope['probably'], density['occasional'])
rule23 = ctrl.Rule(ovc['frequent'] & sp2['persists'] & splow['probably'] & slope['flat'], density['occasional'])
rule24 = ctrl.Rule(ovc['frequent'] & sp2['persists'] & splow['probably'] & slope['can'], density['frequent'])
rule25 = ctrl.Rule(ovc['frequent'] & sp2['persists'] & splow['probably'] & slope['probably'], density['occasional'])
rule26 = ctrl.Rule(ovc['frequent'] & sp2['breach'] & splow['can'] & slope['flat'], density['occasional'])
rule27 = ctrl.Rule(ovc['frequent'] & sp2['breach'] & splow['can'] & slope['can'], density['frequent'])
rule28 = ctrl.Rule(ovc['frequent'] & sp2['breach'] & splow['can'] & slope['probably'], density['occasional'])
rule29 = ctrl.Rule(ovc['frequent'] & sp2['breach'] & splow['probably'] & slope['flat'], density['occasional'])
rule30 = ctrl.Rule(ovc['frequent'] & sp2['breach'] & splow['probably'] & slope['can'], density['frequent'])
rule31 = ctrl.Rule(ovc['frequent'] & sp2['breach'] & splow['probably'] & slope['probably'], density['occasional'])
rule32 = ctrl.Rule(ovc['frequent'] & sp2['oblowout'] & splow['can'] & slope['flat'], density['occasional'])
rule33 = ctrl.Rule(ovc['frequent'] & sp2['oblowout'] & splow['can'] & slope['can'], density['frequent'])
rule34 = ctrl.Rule(ovc['frequent'] & sp2['oblowout'] & splow['can'] & slope['probably'], density['occasional'])
rule35 = ctrl.Rule(ovc['frequent'] & sp2['oblowout'] & splow['probably'] & slope['flat'], density['rare'])
rule36 = ctrl.Rule(ovc['frequent'] & sp2['oblowout'] & splow['probably'] & slope['can'], density['occasional'])
rule37 = ctrl.Rule(ovc['frequent'] & sp2['oblowout'] & splow['probably'] & slope['probably'], density['rare'])
rule38 = ctrl.Rule(ovc['frequent'] & sp2['blowout'] & splow['can'] & slope['flat'], density['rare'])
rule39 = ctrl.Rule(ovc['frequent'] & sp2['blowout'] & splow['can'] & slope['can'], density['rare'])
rule40 = ctrl.Rule(ovc['frequent'] & sp2['blowout'] & splow['can'] & slope['probably'], density['rare'])
rule41 = ctrl.Rule(ovc['frequent'] & sp2['blowout'] & splow['probably'] & slope['flat'], density['rare'])
rule42 = ctrl.Rule(ovc['frequent'] & sp2['blowout'] & splow['probably'] & slope['can'], density['rare'])
rule43 = ctrl.Rule(ovc['frequent'] & sp2['blowout'] & splow['probably'] & slope['probably'], density['rare'])
rule44 = ctrl.Rule(ovc['pervasive'] & sp2['persists'] & splow['can'] & slope['flat'], density['frequent'])
rule45 = ctrl.Rule(ovc['pervasive'] & sp2['persists'] & splow['can'] & slope['can'], density['pervasive'])
rule46 = ctrl.Rule(ovc['pervasive'] & sp2['persists'] & splow['can'] & slope['probably'], density['frequent'])
rule47 = ctrl.Rule(ovc['pervasive'] & sp2['persists'] & splow['probably'] & slope['flat'], density['frequent'])
rule48 = ctrl.Rule(ovc['pervasive'] & sp2['persists'] & splow['probably'] & slope['can'], density['pervasive'])
rule49 = ctrl.Rule(ovc['pervasive'] & sp2['persists'] & splow['probably'] & slope['probably'], density['frequent'])
rule50 = ctrl.Rule(ovc['pervasive'] & sp2['breach'] & splow['can'] & slope['flat'], density['frequent'])
rule51 = ctrl.Rule(ovc['pervasive'] & sp2['breach'] & splow['can'] & slope['can'], density['pervasive'])
rule52 = ctrl.Rule(ovc['pervasive'] & sp2['breach'] & splow['can'] & slope['probably'], density['frequent'])
rule53 = ctrl.Rule(ovc['pervasive'] & sp2['breach'] & splow['probably'] & slope['flat'], density['frequent'])
rule54 = ctrl.Rule(ovc['pervasive'] & sp2['breach'] & splow['probably'] & slope['can'], density['pervasive'])
rule55 = ctrl.Rule(ovc['pervasive'] & sp2['breach'] & splow['probably'] & slope['probably'], density['frequent'])
rule56 = ctrl.Rule(ovc['pervasive'] & sp2['oblowout'] & splow['can'] & slope['flat'], density['frequent'])
rule57 = ctrl.Rule(ovc['pervasive'] & sp2['oblowout'] & splow['can'] & slope['can'], density['pervasive'])
rule58 = ctrl.Rule(ovc['pervasive'] & sp2['oblowout'] & splow['can'] & slope['probably'], density['frequent'])
rule59 = ctrl.Rule(ovc['pervasive'] & sp2['oblowout'] & splow['probably'] & slope['flat'], density['occasional'])
rule60 = ctrl.Rule(ovc['pervasive'] & sp2['oblowout'] & splow['probably'] & slope['can'], density['frequent'])
rule61 = \
ctrl.Rule(ovc['pervasive'] & sp2['oblowout'] & splow['probably'] & slope['probably'], density['occasional'])
rule62 = ctrl.Rule(ovc['pervasive'] & sp2['blowout'] & splow['can'] & slope['flat'], density['occasional'])
rule63 = ctrl.Rule(ovc['pervasive'] & sp2['blowout'] & splow['can'] & slope['can'], density['occasional'])
rule64 = ctrl.Rule(ovc['pervasive'] & sp2['blowout'] & splow['can'] & slope['probably'], density['rare'])
rule65 = ctrl.Rule(ovc['pervasive'] & sp2['blowout'] & splow['probably'] & slope['flat'], density['occasional'])
rule66 = ctrl.Rule(ovc['pervasive'] & sp2['blowout'] & splow['probably'] & slope['can'], density['occasional'])
rule67 = ctrl.Rule(ovc['pervasive'] & sp2['blowout'] & splow['probably'] & slope['probably'], density['rare'])
comb_ctrl = ctrl.ControlSystem([rule1, rule2, rule3, rule4, rule5, rule6, rule7, rule8, rule9, rule10,
rule11, rule12, rule13, rule14, rule15, rule16, rule17, rule18, rule19, rule20,
rule21, rule22, rule23, rule24, rule25, rule26, rule27, rule28, rule29, rule30,
rule31, rule32, rule33, rule34, rule35, rule36, rule37, rule38, rule39, rule40,
rule41, rule42, rule43, rule44, rule45, rule46, rule47, rule48, rule49, rule50,
rule51, rule52, rule53, rule54, rule55, rule56, rule57, rule58, rule59, rule60,
rule61, rule62, rule63, rule64, rule65, rule66, rule67])
comb_fis = ctrl.ControlSystemSimulation(comb_ctrl)
# run fuzzy inference system on inputs and defuzzify output
# TODO Test this using nas instead of zeros
out = np.zeros(len(ovc_array))
for i in range(len(out)):
comb_fis.input['input1'] = ovc_array[i]
comb_fis.input['input2'] = ihydsp2_array[i]
comb_fis.input['input3'] = ihydsplow_array[i]
comb_fis.input['input4'] = igeoslope_array[i]
comb_fis.compute()
out[i] = comb_fis.output['result']
# save fuzzy inference system output as table
columns = np.column_stack((segid_array, out))
out_table = os.path.dirname(in_network) + "/" + out_field + "_Table.txt"
# TODO See if possible to skip this step
np.savetxt(out_table, columns, delimiter=",", header="ReachID, " + out_field, comments="")
occ_table = scratch + "/" + out_field + "Tbl"
arcpy.CopyRows_management(out_table, occ_table)
# join the fuzzy inference system output to the flowline network
# create empty dictionary to hold input table field values
tbl_dict = {}
# add values to dictionary
with arcpy.da.SearchCursor(occ_table, ['ReachID', out_field]) as cursor:
for row in cursor:
tbl_dict[row[0]] = row[1]
# populate flowline network out field
arcpy.AddField_management(in_network, out_field, 'DOUBLE')
with arcpy.da.UpdateCursor(in_network, ['ReachID', out_field]) as cursor:
for row in cursor:
try:
a_key = row[0]
row[1] = tbl_dict[a_key]
cursor.updateRow(row)
# TODO There should be no bare excepts. What kind of error is this trying to catch?
except:
pass
tbl_dict.clear()
# calculate defuzzified centroid value for density 'none' MF group
# this will be used to re-classify output values that fall in this group
# important: will need to update the array (x) and MF values (mfx) if the
# density 'none' values are changed in the model
x = np.arange(0, 45, 0.01)
mfx_none = fuzz.trimf(x, [0, 0, 0.1])
defuzz_none = round(fuzz.defuzz(x, mfx_none, 'centroid'), 6)
mfx_pervasive = fuzz.trapmf(x, [12, 25, 45, 45])
defuzz_pervasive = round(fuzz.defuzz(x, mfx_pervasive, 'centroid'))
# update combined capacity (occ_*) values in stream network
# correct for occ_* greater than ovc_* as vegetation is most limiting factor in model
# (i.e., combined fis value should not be greater than the vegetation capacity)
# set occ_* to 0 if the drainage area is greater than the user defined threshold
# this enforces a stream size threshold above which beaver dams won't persist and/or won't be built
# set occ_* to 0 if output falls fully in 'none' category and to 40 if falls fully in 'pervasive' category
with arcpy.da.UpdateCursor(in_network, [out_field, veg_field, 'iGeo_DA', 'iGeo_Slope']) as cursor:
for row in cursor:
if round(row[0], 6) == defuzz_none:
row[0] = 0.0
if round(row[0]) >= defuzz_pervasive:
row[0] = 40.0
if row[0] > row[1]:
row[0] = row[1]
if row[2] >= float(max_da_thresh):
row[0] = 0.0
cursor.updateRow(row)
# delete temporary tables and arrays
arcpy.Delete_management(out_table)
arcpy.Delete_management(occ_table)
items = [columns, out, x, mfx_none, defuzz_none]
for item in items:
del item
# calculate dam count (mCC_**_CT) for each reach as number of dams * reach length (in km)
arcpy.AddField_management(in_network, mcc_field, 'SHORT')
with arcpy.da.UpdateCursor(in_network, [mcc_field, out_field, 'iGeo_Len']) as cursor:
for row in cursor:
len_km = row[2] / 1000
raw_ct = row[1] * len_km
if 1 > raw_ct > 0:
row[0] = 1
else:
row[0] = round(raw_ct)
cursor.updateRow(row)
# calculate dam count historic departure as difference between potential count and existing count
if model_run == 'ex':
arcpy.AddField_management(in_network, 'mCC_HisDep', 'SHORT')
with arcpy.da.UpdateCursor(in_network, ['mCC_HisDep', 'mCC_EX_CT', 'mCC_HPE_CT']) as cursor:
for row in cursor:
row[0] = row[2] - row[1]
cursor.updateRow(row)
def add_xml_output(in_network, out_network):
"""
Add the capacity output to the project xml file
:param in_network: The input BRAT network
:param out_network: The new Capacity Network being created
:return:
"""
proj_path = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(out_network))))
# xml file
xml_file_path = proj_path + "/project.rs.xml"
if not os.path.exists(xml_file_path):
arcpy.AddWarning("XML file not found. Could not update XML file")
return
xml_file = XMLBuilder(xml_file_path)
brat_element = get_brat_element(xml_file, in_network, proj_path)
analyses_element = xml_file.add_sub_element(brat_element, "Analyses")
analysis_element = xml_file.add_sub_element(analyses_element, "Analysis")
xml_file.add_sub_element(analysis_element, "Name", "BRAT Analysis")
write_xml_element_with_path(xml_file, analysis_element, "Vector", "BRAT Capacity Output", out_network, proj_path)
xml_file.write()
def get_brat_element(xml_file, in_network, proj_path):
"""
Gets the BRAT XML element for this particular in_network
:param xml_file: The project's XML file to add to
:param in_network: The input BRAT network
:param proj_path: The path to the project folder for this BRAT run
:return: The BRAT XML element
"""
relative_path = find_relative_path(in_network, proj_path)
path_element = xml_file.find_by_text(relative_path)
vec_element = xml_file.find_element_parent(path_element)
intermed_element = xml_file.find_element_parent(vec_element)
intermeds_element = xml_file.find_element_parent(intermed_element)
brat_element = xml_file.find_element_parent(intermeds_element)
return brat_element
def make_layers(out_network):
"""
Writes the layers
:param out_network: The output network, which we want to make into a layer
:return:
"""
arcpy.AddMessage("Making layers...")
analyses_folder = os.path.dirname(out_network)
output_folder = make_folder(analyses_folder, find_available_num_prefix(analyses_folder) + "_Capacity")
historic_folder = make_folder(output_folder, find_available_num_prefix(output_folder) + "_HistoricCapacity")
existing_folder = make_folder(output_folder, find_available_num_prefix(output_folder) + "_ExistingCapacity")
trib_code_folder = os.path.dirname(os.path.abspath(__file__))
symbology_folder = os.path.join(trib_code_folder, 'BRATSymbology')
existing_capacity_layer = os.path.join(symbology_folder, "ExistingDamBuildingCapacity.lyr")
historic_capacity_layer = os.path.join(symbology_folder, "HistoricDamBuildingCapacity.lyr")
existing_capacity_count_layer = os.path.join(symbology_folder, "ExistingDamComplexSize.lyr")
historic_capacity_count_layer = os.path.join(symbology_folder, "HistoricDamComplexSize.lyr")
make_layer(existing_folder, out_network, "Existing Dam Building Capacity",
existing_capacity_layer, is_raster=False)
make_layer(historic_folder, out_network, "Historic Dam Building Capacity",
historic_capacity_layer, is_raster=False)
make_layer(existing_folder, out_network, "Existing Dam Complex Size",
existing_capacity_count_layer, is_raster=False)
make_layer(historic_folder, out_network, "Historic Dam Complex Size",
historic_capacity_count_layer, is_raster=False)
if __name__ == '__main__':
main(
sys.argv[1],
sys.argv[2],
sys.argv[3],
sys.argv[4])