import h5py
import numpy as np
import os
import pandas as pd


spiking = pd.DataFrame(columns=['t', 'RS Pyramidal','RS Inhibitory','FS','IB',
                                'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
                                'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
                                'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
                                'IB +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
                                'Cb stellate','Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
          'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$','STN','STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
          'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'])
values = pd.DataFrame(index = ['spike_ind', 'ramp_up','ramp_down'], columns=['RS Pyramidal','RS Inhibitory','FS','IB',
                                'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
                                'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
                                'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
                                'IB +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$','Cb stellate','Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
          'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$','STN','STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
          'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'])
F = pd.DataFrame(columns=['I','I_inhib', 'RS Pyramidal','RS Inhibitory','FS','IB',
                                'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
                                'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
                                'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
                                'IB +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$','Cb stellate','Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
          'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$','STN','STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
          'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'])


# RS Pyramidal #########################################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/RS_pyramidal.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 60
spiking['RS Pyramidal'] = f['data']['V_m'][ind][start:]
spiking['t'] = time
F['I'] = I_mag
F['RS Pyramidal'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'RS Pyramidal'] = I_mag[ind]
values.loc['ramp_up', 'RS Pyramidal']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'RS Pyramidal']  = f['analysis']['ramp_I_down'][()]

# RS Inhibitory #########################################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/RS_inhib.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 25
spiking['RS Inhibitory'] = f['data']['V_m'][ind][start:]
F['I_inhib'] = I_mag
F['RS Inhibitory'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'RS Inhibitory'] = I_mag[ind]
values.loc['ramp_up', 'RS Inhibitory']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'RS Inhibitory']  = f['analysis']['ramp_I_down'][()]


# FS#####################################################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/FS.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 50
spiking['FS'] = f['data']['V_m'][ind][start:]
F['FS'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'FS'] = I_mag[ind]
values.loc['ramp_up', 'FS']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'FS']  = f['analysis']['ramp_I_down'][()]

# RS Pyramidal Kv #########################################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/RS_pyramidal_Kv.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 60
spiking['RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['data']['V_m'][ind][start:]
spiking['t'] = time
F['I'] = I_mag
F['RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = I_mag[ind]
values.loc['ramp_up', 'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_down'][()]

# RS Inhibitory #########################################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/RS_inhib_Kv.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 50
spiking['RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['data']['V_m'][ind][start:]
F['I_inhib'] = I_mag
F['RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = I_mag[ind]
values.loc['ramp_up', 'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_down'][()]


# FS#####################################################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/FS_Kv.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 50
spiking['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['data']['V_m'][ind][start:]
F['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = I_mag[ind]
values.loc['ramp_up', 'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_down'][()]

# Cb Stellate cell ######################################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/Cb_stellate.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 60
spiking['Cb stellate'] = f['data']['V_m'][ind][start:]
F['Cb stellate'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'Cb stellate'] = I_mag[ind]
values.loc['ramp_up', 'Cb stellate']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'Cb stellate']  = f['analysis']['ramp_I_down'][()]


# 'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'
# Cb stellate Kv #############################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/Cb_stellate_Kv.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 130
spiking['Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['data']['V_m'][ind][start:]
F['Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = I_mag[ind]
values.loc['ramp_up', 'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_down'][()]

# 'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'
# Cb stellate Kv only ####################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/Cb_stellate_Delta_Kv.hdf5.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 75
spiking['Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['data']['V_m'][ind][start:]
F['Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = I_mag[ind]
values.loc['ramp_up', 'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_down'][()]

# STN ###################################################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/STN.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 25
spiking['STN'] = f['data']['V_m'][ind][start:]
F['STN'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'STN'] = I_mag[ind]
values.loc['ramp_up', 'STN']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'STN']  = f['analysis']['ramp_I_down'][()]

# 'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
# STN Kv ##################################################################################################
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/STN_Kv.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 95
spiking['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['data']['V_m'][ind][start:]
F['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = I_mag[ind]
values.loc['ramp_up', 'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_down'][()]

# 'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'
# STN Kv only #############################################################################################3
script_dir = os.path.dirname(os.path.realpath("__file__"))
fname = os.path.join(script_dir, '../Neuron_models/STN_Delta_Kv.hdf5')
f = h5py.File(fname, "r")
I_mag = np.arange(f['data'].attrs['I_low'], f['data'].attrs['I_high'], (f['data'].attrs['I_high'] - f['data'].attrs['I_low']) / f['data'].attrs['stim_num'])*1000
start = np.int(f['data'].attrs['initial_period']*1/f['data'].attrs['dt'])
stim_len = np.int((f['data'].attrs['stim_time'] - start) *f['data'].attrs['dt'])
time = np.arange(0, stim_len,f['data'].attrs['dt'])
ind = 80
spiking['STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['data']['V_m'][ind][start:]
F['STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = f['analysis']['F_inf'][:]
values.loc['spike_ind', 'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'] = I_mag[ind]
values.loc['ramp_up', 'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_up'][()]
values.loc['ramp_down', 'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']  = f['analysis']['ramp_I_down'][()]

#%%
spiking.to_csv('model_spiking.csv')
values.to_csv('firing_values.csv')
F.to_csv('model_F_inf.csv')