from neuron import h
import numpy as np

VERBOSE = 0
from new_geomnseg import *

def range_func(sect,typ,bounds):
	for seg in sect:
		exec("seg." + typ +"= np.interp(seg.x,[0,1],bounds)")

def init(neuron_obj, p):
	test = neuron_obj
	distalance = p['dst']
	cattog = p['gcat']
	hcntog = p['ghcn']
	taukv4 = p['taukv4']
	shift = -p['na_shift']
	hshift = p['na_hshift']
	SCALE = p['scale']
	h.distance(0,test.soma(0.5)) # set 0 of distance to soma # may be redundant
	tcap = 0 
	tnseg =0 
	for s in test.all:
		tnseg+=s.nseg
		#s.nseg = s.nseg*4+1
		s.Ra = 100.0*p['ra']
		s.cm = 1.0*p['cm']
		s.insert('hhb') # for Kv4, Kdr
		#s.insert('pump')
		s.insert('leak')
		#s.insert('nabalan')
		#s.insert('Na12')
		s.insert('NaMark')
		#s.insert('Na16')
		s.insert('cabalstore')
		#s.insert('cicr') # requires cabalstore
		s.insert('hcn')
		#s.insert('katp')
		#s.insert('skpool')
		s.insert('kca')
		#s.insert('catchan')
		s.insert('canchan')
		s.insert('calhh')
		s.insert('erg')
		if p['kmark'] >0:
			s.insert('KdrMark')
	
		s.insert('typem') # a module that creates a range variable that specifies compartment type by color
		s.gnabar_NaMark = 1000e-6*p['gnahh']
		if p['ratio'] < 1:
			s.insert('FastNaMark')
			s.gnabar_FastNaMark = 1000e-6*(1-p['ratio'])*p['gnahh']
			s.shift_FastNaMark = shift
			s.hshift_FastNaMark = hshift
		s.gnabar_NaMark = 1000e-6*p['ratio']*p['gnahh']
		
		#s.DCa_cabalthin = 0.0
		#s.shellfrac_cabalthin = min(0.1/s.diam,1.0) 

		s.ashift_hhb = p['kasv']
		s.asshift_hhb = p['kass']
		s.gkabar_hhb = 300e-6*p['gka']*1.5 # 1.5 to match data from Roeper lab while keeping sum of fast/slow to 1
		#s.scale_Na12 = 0.2
		s.nspeed_hhb = p['nspeed']
		
		if p['kmark'] >0:
			s.gkhhbar_hhb = 0
			s.gkbar_KdrMark = 500e-6*p['gkhh']
		else:
			s.gkhhbar_hhb = 500e-6*p['gkhh']
		
		
		#s.c1c2half_NaMark=p['na_base']
		
		s.scale_NaMark = SCALE
		#s.shift_Na12 = -15.0
		s.shift_NaMark = shift
		s.hshift_NaMark = hshift
		s.gergbar_erg = 0e-6
		
		for seg in s:
			tcap+=s.cm*h.area(seg.x,sec=s)
		#s.ipumpmax_pump*=0.0
		
		s.gkhhbar_hhb = 500e-6*p['gkhh']
		#s.gnabar_hhb = 0
		#s.gnabar_Na12 = 1000e-6*p[5]
		
		#s.scale_Na16 =0.2
		#s.gnabar_Na16 = 1000e-6*p[5]
		s.gkbar_leak=1.0e-6*p['glk']
		s.gnabar_leak=1.0e-6*p['glna']
		#s.vhblock_hhb = 0
		#s.gnabar_Na16 *= 1.0
		#s.gnabar_Na12 *= 0.5
		
		#s.prad_bkpool = 0.001
		#s.prad_skpool = 0.1
		
		#s.prad_cabalthin = s.prad_skpool
		s.TotalBuffer_cabalstore = 0.03
		
		#s.gkbar_bk = 0e-3
		s.gkbar_kca = 100e-6*p['gkca']
		s.tausk_kca = 15.0
		s.icapumpmax_cabalstore *= p['capump']
		
		s.gcanbar_canchan = 50e-6
		s.gcalbar_calhh =10.0e-6*p['gcal'] # 
		s.skcoup_calhh = 1.0 # coupling of L-type to SK pool
		s.mhalf_calhh = -30 # half activation
		
		#s.gnabar_hhb *= 1.0
		s.gkbar_leak *=1.0
		s.gkhhbar_hhb *=1.0
		s.ghcnbar_hcn = 50.0e-6*hcntog
		s.taukv4_hhb = taukv4
  
	for s in test.somatic:
		s.marker_typem = 0

		#s.deptog_hhb = 1
		#s.gcatbar_catchan*=0
		if test.basal!=None:
			s.gkabar_hhb *=0.1
		else:
			s.gkabar_hhb *=1
		#s.gkbar_katp = 0
		#s.n_katp = 1.3
		
		#s.ghcnbar_hcn = hcntog*50e-6
		#s.tau1_hcn *=0.5
		#s.tau2_hcn *=0.5
	try:
		for s in test.basal:
			s.marker_typem = 1
	except:
		if VERBOSE:
			print( 'no dendrites')
	try:
		for s in test.excitozone:
			print( s)
			s.marker_typem = 0.5
			s.gnabar_NaMark *= p['ais_na']
			if p['kmark'] > 0:
				s.gkbar_KdrMark *= p['ais_na']
			else:
				s.gkhhbar_hhb *= p['ais_na']
			s.gkbar_kca *= 0.25
			s.icapumpmax_cabalstore *= 2
			s.gka_hhb *= 2
			#s.dist_NaMark=0
			#s.c1c2half_NaMark -= p['ais_shift']
	except:
		if VERBOSE:
			print( 'no AIS or axon')


def to_shreds_you_say(neuron_obj,chop_dist):  # removes sections whose midpoints are greater than chop distance, name is futurama reference.
	blest = neuron_obj
	h.distance(0,blest.soma(0.5))
	for s in blest.all:
		sref = h.SectionRef(sec = s)
		dist = h.distance(0.5, sec=s)
		if dist > chop_dist:
			h.disconnect(sref)
			h.delete_section(sref)