# -*- coding: utf-8 -*-
"""
Created on Sat Jul  3 19:52:04 2021

@author: nils
"""
import pandas as pd
import numpy as np
import string
import textwrap
import json
import matplotlib
import matplotlib.lines as mlines
from matplotlib import ticker
from matplotlib.ticker import NullFormatter
from plotstyle import boxplot_style

def cm2inch(*tupl):
    inch = 2.54
    if isinstance(tupl[0], tuple):
        return tuple(i/inch for i in tupl[0])
    else:
        return tuple(i/inch for i in tupl)
#%% ##################### From https://stackoverflow.com/questions/52878845/swarmplot-with-hue-affecting-marker-beyond-color ##
# to change marker types in seaborn swarmplot

import seaborn as sns
import matplotlib.pyplot as plt

############## Begin hack ##############
from matplotlib.axes._axes import Axes
from matplotlib.markers import MarkerStyle
from numpy import ndarray

def GetColor2Marker(markers):
    colorslist = ['#40A787',  # cyan'#
                  '#F0D730',  # yellow
                  '#C02717',  # red
                  '#007030',  # dark green
                  '#AAB71B',  # lightgreen
                  '#008797',  # light blue
                  '#F78017',  # orange
                  '#478010',  # green
                  '#53379B',  # purple
                  '#2060A7',  # blue
                  '#873770',  # magenta
                  '#D03050'  # pink
                  ]
    import matplotlib.colors
    palette = [matplotlib.colors.to_rgb(c) for c in colorslist]
    mkcolors = [(palette[i]) for i in range(len(markers))]
    return dict(zip(mkcolors,markers))

def fixlegend(ax,markers,markersize=3,**kwargs):
    # Fix Legend
    legtitle =  ax.get_legend().get_title().get_text()
    _,l = ax.get_legend_handles_labels()
    colorslist = ['#40A787',  # cyan'#
                  '#F0D730',  # yellow
                  '#C02717',  # red
                  '#007030',  # dark green
                  '#AAB71B',  # lightgreen
                  '#008797',  # light blue
                  '#F78017',  # orange
                  '#478010',  # green
                  '#53379B',  # purple
                  '#2060A7',  # blue
                  '#873770',  # magenta
                  '#D03050'  # pink
                  ]
    import matplotlib.colors
    palette = [matplotlib.colors.to_rgb(c) for c in colorslist]
    mkcolors = [(palette[i]) for i in range(len(markers))]
    newHandles = [plt.Line2D([0],[0], ls="none", marker=m, color=c, mec="none", markersize=markersize,**kwargs) \
                for m,c in zip(markers, mkcolors)]
    ax.legend(newHandles,l)
    leg = ax.get_legend()
    leg.set_title(legtitle)

old_scatter = Axes.scatter
def new_scatter(self, *args, **kwargs):
    colors = kwargs.get("c", None)
    co2mk = kwargs.pop("co2mk",None)
    FinalCollection = old_scatter(self, *args, **kwargs)
    if co2mk is not None and isinstance(colors, ndarray):
        Color2Marker = GetColor2Marker(co2mk)
        paths=[]
        for col in colors:
            mk=Color2Marker[tuple(col)]
            marker_obj = MarkerStyle(mk)
            paths.append(marker_obj.get_path().transformed(marker_obj.get_transform()))
        FinalCollection.set_paths(paths)
    return FinalCollection
Axes.scatter = new_scatter
############## End hack. ##############

########################################################################################################################

#%%
def boxplot_with_markers(ax,max_width, alteration='shift', msize=3):
    # size =4
    # ax.tick_params(axis='x', rotation=90)
    model_names = ['RS pyramidal','RS inhibitory','FS',
                                  'RS pyramidal +$K_V1.1$','RS inhibitory +$K_V1.1$',
                'FS +$K_V1.1$','Cb stellate','Cb stellate +$K_V1.1$',
          'Cb stellate $\Delta$$K_V1.1$','STN','STN +$K_V1.1$',
          'STN $\Delta$$K_V1.1$']

    colorslist = ['#007030',  # dark green
                  '#F0D730',  # yellow
                  '#C02717',  # red
                    '#478010',  # green
                  '#AAB71B',  # lightgreen
                '#F78017',  # orange
                  '#40A787',  # cyan'#
                  '#008797',  # light blue
                '#2060A7',  # blue
                  '#D03050',  # pink
                  '#53379B',  # purple
                  '#873770',  # magenta
                  ]

    # colorslist = ['#40A787', # cyan'#
    # '#F0D730',  # yellow
    # 'C02717', # red
    # '#007030', # dark green
    # '#AAB71B', # lightgreen
    # '#008797', # light blue
    # '#F78017', # orange
    # '#478010', # green
    # '#53379B',  # purple
    # '#2060A7', # blue
    # '#873770', # magenta
    # '#D03050' # pink
    # ]
    hlinewidth =0.5

    import matplotlib.colors
    colors = [matplotlib.colors.to_rgb(c) for c in colorslist] # sns.color_palette("hls", 14, desat=0.75)#[cm.tab20(i) for i in range(20)]
    clr_dict = {}
    for m in range(len(model_names)):
        clr_dict[model_names[m]] = colors[m]
    Markers = ["o", "o", "o", "^", "^", "^", "D", "D", "D", "s", "s", "s"]
    if alteration=='shift':
        i = 2  # Kd act
        ax.axvspan(i - 0.4, i + 0.4, fill=False, edgecolor = 'k')
        df = pd.read_csv('./Figures/Data/AUC_shift_corr.csv')
        sns.swarmplot(y="corr", x="$\Delta V_{1/2}$", hue="model", data=df,
                      palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
                      order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation',
                             '$K_V1.1$ inactivation', 'A activation', 'A inactivation'],
                      hue_order=model_names, co2mk=Markers)
        lim = ax.get_xlim()
        ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
        ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
        ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
        # ax.get_legend().remove()
        # sns.despine(trim=True, bottom=True, ax=ax)
        # ax.set(xlabel=None, ylabel=r'Kendall $\it{\tau}$')
        ax.set_title("Shift ($\Delta V_{1/2}$)", y=1.05)
    elif alteration=='slope':
        i = 3  # Kv1.1 act
        ax.axvspan(i - 0.4, i + 0.4, fill=False, edgecolor='k')
        df = pd.read_csv('./Figures/Data/AUC_scale_corr.csv')

        # Add in points to show each observation
        sns.swarmplot(y="corr", x="Slope (k)", hue="model", data=df, #dodge=True,
                      palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
                      order=['Na activation', 'Na inactivation', 'K activation', '$K_V1.1$ activation',
                             '$K_V1.1$ inactivation', 'A activation', 'A inactivation'],
                      hue_order=model_names, co2mk=Markers)
        lim = ax.get_xlim()
        # ax.plot([lim[0], lim[1]], [0,0], ':k')
        ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
        ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
        ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
        # Markers = ["o","s","v","^","<",">","p","h","P","X","D","*","8","o"]
        # ax=fixlegend(ax, Markers)
        # Tweak the visual presentation
        # ax.get_legend().remove()
        # ax.xaxis.grid(False)
        # ax.set_xticklabels(textwrap.fill(x.get_text(), max_width) for x in ax.get_xticklabels())
        # ax.set(xlabel=None, ylabel=r'Kendall $\it{\tau}$')
        ax.set_title("Slope (k)", y=1.05)
        # sns.despine(trim=True, bottom=True, ax=ax)
    elif alteration=='g':
        i = 1  # Kd
        ax.axvspan(i - 0.4, i + 0.4, fill=False, edgecolor='k')
        df = pd.read_csv('./Figures/Data/AUC_g_corr.csv')

        # Add in points to show each observation
        sns.swarmplot(y="corr", x="g", hue="model", data=df, #dodge=True,
                      palette=clr_dict, linewidth=0, orient='v', ax=ax, size=msize,
                      order=['Na', 'K', '$K_V1.1$', 'A', 'Leak'],
                      hue_order=model_names, co2mk=Markers)
        lim = ax.get_xlim()
        # ax.plot([lim[0], lim[1]], [0,0], ':k')
        ax.plot([lim[0], lim[1]], [0, 0], ':r',linewidth=hlinewidth)
        ax.plot([lim[0], lim[1]], [1, 1], ':k',linewidth=hlinewidth)
        ax.plot([lim[0], lim[1]], [-1, -1], ':k',linewidth=hlinewidth)
        # Tweak the visual presentation
        # ax.xaxis.grid(False)
        # sns.despine(trim=True, bottom=True, ax=ax)
        # ax.set(xlabel=None, ylabel=r'Kendall $\it{\tau}$')
        ax.set_title("Conductance (g)", y=1.05)
        # ax.set_xticklabels(textwrap.fill(x.get_text(), max_width) for x in ax.get_xticklabels())
    else:
        print('Please chose "shift", "slope" or "g"')
    ax.get_legend().remove()
    ax.xaxis.grid(False)
    sns.despine(trim=True, bottom=True, ax=ax)
    ax.set(xlabel=None, ylabel=r'Kendall $\it{\tau}$')
    ax.set_xticklabels(textwrap.fill(x.get_text(), max_width) for x in ax.get_xticklabels())
    # fixlegend(ax, Markers)

def model_legend(ax, marker_s_leg, pos, ncol):
    colorslist = [  '#40A787', # cyan'#
        '#F0D730',  # yellow
        '#C02717',  # red
        '#007030',  # dark green
        '#AAB71B',  # lightgreen
        '#008797',  # light blue
        '#F78017',  # orange
        '#478010',  # green
        '#53379B',  # purple
        '#2060A7',  # blue
        '#873770',  # magenta
        '#D03050'  # pink
    ]
    import matplotlib.colors
    colors = [matplotlib.colors.to_rgb(c) for c in colorslist] #sns.color_palette("hls", 14, desat=0.75) #[cm.tab20(i) for i in range(20)]

    model_pos = {'Cb stellate':0, 'RS Inhibitory':1, 'FS':2, 'RS Pyramidal':3,
              'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':4,
              'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':5, 'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':6,
              'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':7, 'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':8,
              'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':9,
              'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':10, 'STN':11}

    Markers = ["o", "o", "o", "^", "^", "^", "D", "D", "D", "s", "s", "s"]
    RS_p = mlines.Line2D([], [], color=colors[model_pos['RS Pyramidal']], marker=Markers[model_pos['RS Pyramidal']], markersize=marker_s_leg, linestyle='None',
                         label='RS pyramidal')
    RS_i = mlines.Line2D([], [], color=colors[model_pos['RS Inhibitory']], marker=Markers[model_pos['RS Inhibitory']], markersize=marker_s_leg, linestyle='None',
                         label='RS inhibitory')
    FS = mlines.Line2D([], [], color=colors[model_pos['FS']], marker=Markers[model_pos['FS']], markersize=marker_s_leg, linestyle='None', label='FS')
    RS_p_Kv = mlines.Line2D([], [], color=colors[model_pos['RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
                         label='RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
    RS_i_Kv = mlines.Line2D([], [], color=colors[model_pos['RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
                         label='RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
    FS_Kv = mlines.Line2D([], [], color=colors[model_pos['Cb stellate']], marker=Markers[model_pos['Cb stellate']], markersize=marker_s_leg, linestyle='None', label='FS +$K_V1.1$')
    Cb = mlines.Line2D([], [], color=colors[8], marker=Markers[8], markersize=marker_s_leg, linestyle='None',
                       label='Cb stellate')
    Cb_pl = mlines.Line2D([], [], color=colors[model_pos['Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
                          label='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
    Cb_sw = mlines.Line2D([], [], color=colors[model_pos['Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
                          label='Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
    STN = mlines.Line2D([], [], color=colors[model_pos['STN']], marker=Markers[model_pos['STN']], markersize=marker_s_leg, linestyle='None', label='STN')
    STN_pl = mlines.Line2D([], [], color=colors[model_pos['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
                           label='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
    STN_sw = mlines.Line2D([], [], color=colors[model_pos['STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], marker=Markers[model_pos['STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$']], markersize=marker_s_leg, linestyle='None',
                           label='STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$')
    ax.legend(handles=[RS_p, RS_i, FS, RS_p_Kv, RS_i_Kv, FS_Kv, Cb, Cb_pl, Cb_sw, STN, STN_pl, STN_sw], loc='center',
                  bbox_to_anchor=pos, ncol=ncol, frameon=False)

def plot_AUC_alt(ax, model='FS', color1='red', color2='dodgerblue', alteration='shift'):
    ax.spines["right"].set_visible(False)
    ax.spines["top"].set_visible(False)
    model_names = ['RS Pyramidal','RS Inhibitory','FS',
                                  'RS Pyramidal +$K_V1.1$','RS Inhibitory +$K_V1.1$',
                'FS +$K_V1.1$','Cb stellate','Cb stellate +$K_V1.1$',
          'Cb stellate $\Delta$$K_V1.1$','STN','STN +$K_V1.1$',
          'STN $\Delta$$K_V1.1$']

    model_name_dict = {'RS Pyramidal': 'RS Pyramidal',
                       'RS Inhibitory': 'RS Inhibitory',
                       'FS': 'FS',
                       'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'RS Pyramidal +$K_V1.1$',
                       'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'RS Inhibitory +$K_V1.1$',
                       'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'FS +$K_V1.1$',
                       'Cb stellate': 'Cb stellate',
                       'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'Cb stellate +$K_V1.1$',
                       'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'Cb stellate $\Delta$$K_V1.1$',
                       'STN': 'STN',
                       'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'STN +$K_V1.1$',
                       'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'STN $\Delta$$K_V1.1$'}
    colorslist = ['#007030',  # dark green
                  '#F0D730',  # yellow
                  '#C02717',  # red
                  '#478010',  # green
                  '#AAB71B',  # lightgreen
                  '#F78017',  # orange
                  '#40A787',  # cyan'#
                  '#008797',  # light blue
                  '#2060A7',  # blue
                  '#D03050',  # pink
                  '#53379B',  # purple
                  '#873770',  # magenta
                  ]

    import matplotlib.colors
    colors = [matplotlib.colors.to_rgb(c) for c in
              colorslist]  #sns.color_palette("hls", 14, desat=0.75)#[cm.tab20(i) for i in range(20)]
    clr_dict = {}
    for m in range(len(model_names)):
        clr_dict[model_names[m]] = colors[m]
    if alteration=='shift':
        df = pd.read_csv('./Figures/Data/AUC_shift_ex.csv')
        df = df.sort_values('alteration')
        ax.set_xlabel('$\Delta$$V_{1/2}$')
    elif alteration=='slope':
        df = pd.read_csv('./Figures/Data/AUC_slope_ex.csv')
        ax.set_xscale("log")
        ax.set_xticks([0.5, 1, 2])
        ax.xaxis.set_major_formatter(ticker.ScalarFormatter())
        ax.xaxis.set_minor_formatter(NullFormatter())
        ax.set_xlabel('Slope factor k')
    elif alteration=='g':
        df = pd.read_csv('./Figures/Data/AUC_g_ex.csv')
        ax.set_xscale("log")
        ax.set_xticks([0.5, 1, 2])
        ax.xaxis.set_major_formatter(ticker.ScalarFormatter())
        ax.xaxis.set_minor_formatter(NullFormatter())
        ax.set_xlabel('g')
    for mod in model_names:
        if mod == model_name_dict[model]:
            ax.plot(df['alteration'], df[mod], color=clr_dict[mod], alpha=1, zorder=10, linewidth=2)
        else:
            ax.plot(df['alteration'], df[mod], color=clr_dict[mod],alpha=1, zorder=1, linewidth=1)
    ax.set_ylabel('Normalized AUC')
    x = df['alteration']
    y = df[model_name_dict[model]]
    ax.set_xlim(x.min(), x.max())
    ax.set_ylim(df[model_names].min().min(), df[model_names].max().max())
    return ax

def plot_fI(ax, model='RS Pyramidal', type='shift', alt='m', color1='red', color2='dodgerblue'):
    model_save_name = {'RS Pyramidal': 'RS_pyr_posp',
                       'RS Inhibitory': 'RS_inhib_posp',
                       'FS': 'FS_posp',
                       'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'RS_pyr_Kv',
                       'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'RS_inhib_Kv',
                       'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'FS_Kv',
                       'Cb stellate': 'Cb_stellate',
                       'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'Cb_stellate_Kv',
                       'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'Cb_stellate_Kv_only',
                       'STN': 'STN',
                       'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'STN_Kv',
                       'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': 'STN_Kv_only'}
    cvals = [-2., 2]
    colors = [color1, color2]
    norm = plt.Normalize(min(cvals), max(cvals))
    tuples = list(zip(map(norm, cvals), colors))
    cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", tuples)
    colors = cmap(np.linspace(0, 1, 22))
    df = pd.read_csv('./Figures/Data/Model_fI/{}_fI.csv'.format(model_save_name[model]))
    df.drop(['Unnamed: 0'], axis=1)
    newdf = df.loc[df.index[(df['alt'] == alt) & (df['type'] == type)], :]
    newdf['mag'] = newdf['mag'].astype('float')
    newdf = newdf.sort_values('mag').reset_index()
    c = 0
    for i in newdf.index:
        ax.plot(json.loads(newdf.loc[i, 'I']), json.loads(newdf.loc[i, 'F']), color=colors[c])
        c += 1
    ax.set_ylabel('Frequency [Hz]')
    ax.set_xlabel('Current [nA]')
    ax.set_title(model)
    ax.spines["right"].set_visible(False)
    ax.spines["top"].set_visible(False)
    L = ax.get_ylim()
    ax.set_ylim([0, L[1]])
    return ax


#%%
boxplot_style()
color_dict = {'Cb stellate': '#40A787', # cyan'#
              'RS Inhibitory': '#F0D730',  # yellow
              'FS': '#C02717',  # red
              'RS Pyramidal': '#007030',  # dark green
              'RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#AAB71B',  # lightgreen
              'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$':  '#008797',  # light blue
              'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#F78017',  # orange
              'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#478010',  # green
              'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#53379B',  # purple
              'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#2060A7',  # blue
              'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$': '#873770',  # magenta
              'STN':  '#D03050'  # pink
              }

# plot setup
marker_s_leg = 2
max_width = 20
pad_x = 0.65
pad_y= 0.4
pad_w = 0.85
pad_h = 0.7

fig = plt.figure()
# fig = plt.figure()
# fig.set_size_inches(cm2inch(17.6,10))
gs = fig.add_gridspec(3, 6, wspace=1., hspace=0.8)
# plt.subplots_adjust(hspace=0.8) #, wspace=0.6
ax0 = fig.add_subplot(gs[0,2:6])
ax0_ex = fig.add_subplot(gs[0,1])
ax0_fI = fig.add_subplot(gs[0,0])
ax1 = fig.add_subplot(gs[1,2:6])
ax1_ex = fig.add_subplot(gs[1,1])
ax1_fI = fig.add_subplot(gs[1,0])
ax2 = fig.add_subplot(gs[2,2:6])
ax2_ex = fig.add_subplot(gs[2,1])
ax2_fI = fig.add_subplot(gs[2,0])

line_width = 1
# plot fI examples
ax0_fI = plot_fI(ax0_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='shift', alt='s',  color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1  + pad_h, fill=False, lw=line_width,transform=ax0_fI.transAxes,  color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax0_fI.add_patch(rec)
rec.set_clip_on(False)

ax1_fI = plot_fI(ax1_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='slope', alt='u',  color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1  + pad_h, fill=False, lw=line_width,transform=ax1_fI.transAxes,  color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax1_fI.add_patch(rec)
rec.set_clip_on(False)

ax2_fI = plot_fI(ax2_fI, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='g', alt='Leak',  color1='lightgrey', color2='k')
rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1  + pad_h, fill=False, lw=line_width,transform=ax2_fI.transAxes,  color=color_dict['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
rec = ax2_fI.add_patch(rec)
rec.set_clip_on(False)

# label subplots with letters
ax0_fI.text(-0.95, 1.12, string.ascii_uppercase[0], transform=ax0_fI.transAxes, size=10, weight='bold') #-0.09
ax1_fI.text(-0.95, 1.12, string.ascii_uppercase[1], transform=ax1_fI.transAxes,size=10, weight='bold')
ax2_fI.text(-0.95, 1.12, string.ascii_uppercase[2], transform=ax2_fI.transAxes,size=10, weight='bold')

# plot boxplots
boxplot_with_markers(ax0,max_width, alteration='shift')
boxplot_with_markers(ax1,max_width, alteration='slope')
boxplot_with_markers(ax2,max_width, alteration='g')

# plot legend
pos = (0.25, -0.6)
ncol = 6
model_legend(ax2,  marker_s_leg, pos, ncol)

# plot examples
plot_AUC_alt(ax0_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='shift')
plot_AUC_alt(ax1_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k',alteration='slope')
plot_AUC_alt(ax2_ex, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='g')

#save
# plt.tight_layout(pad=0)
print(fig.dpi)
fig.set_size_inches(cm2inch(21,10))
fig.savefig('./Figures/AUC_correlation.pdf', dpi=fig.dpi) #bbox_inches='tight', dpi=fig.dpi
plt.show()

# #%% alternative layout
# # boxplot_style()
# marker_s_leg = 8
# max_width = 10
# pad_x = 0.2
# pad_y= 0.4
# pad_w = 0.22
# pad_h = 0.6
#
# fig = plt.figure(figsize=(12,20))
# gs = fig.add_gridspec(3, 1, hspace=0.4, wspace=0.4)
# gs0 = gs[0].subgridspec(2, 4, wspace=0.6, hspace=1.)
# gs1 = gs[1].subgridspec(2, 4, wspace=0.6, hspace=1.)
# gs2 = gs[2].subgridspec(2, 4, wspace=0.6, hspace=1.)
# ax0 = fig.add_subplot(gs0[1,:])
# ax0_ex = fig.add_subplot(gs0[0,2:])
# ax0_fI = fig.add_subplot(gs0[0,:2])
# ax1 = fig.add_subplot(gs1[1,:])
# ax1_ex = fig.add_subplot(gs1[0,2:])
# ax1_fI = fig.add_subplot(gs1[0,:2])
# ax2 = fig.add_subplot(gs2[1,:])
# ax2_ex = fig.add_subplot(gs2[0,2:])
# ax2_fI = fig.add_subplot(gs2[0,:2])
#
#
# ax0_fI = plot_fI(ax0_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='shift', alt='s',  color1='lightgrey', color2='k')
# rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1  + pad_h, fill=False, lw=2,transform=ax0_fI.transAxes,  color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
# rec = ax0_fI.add_patch(rec)
# rec.set_clip_on(False)
#
# ax1_fI = plot_fI(ax1_fI, model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='slope', alt='u',  color1='lightgrey', color2='k')
# rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1  + pad_h, fill=False, lw=2,transform=ax1_fI.transAxes,  color=color_dict['FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
# rec = ax1_fI.add_patch(rec)
# rec.set_clip_on(False)
#
# ax2_fI = plot_fI(ax2_fI, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', type='g', alt='Leak',  color1='lightgrey', color2='k')
# rec = plt.Rectangle((-pad_x, -pad_y), 1 + pad_w, 1  + pad_h, fill=False, lw=2,transform=ax2_fI.transAxes,  color=color_dict['STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$'], alpha=1, zorder=-1)
# rec = ax2_fI.add_patch(rec)
# rec.set_clip_on(False)
#
# # label subplots with letters
# ax0_fI.text(-0.2, 1.38, string.ascii_uppercase[0], transform=ax0_fI.transAxes, size=16, weight='bold') #-0.09
# ax1_fI.text(-0.2, 1.38, string.ascii_uppercase[1], transform=ax1_fI.transAxes,size=16, weight='bold')
# ax2_fI.text(-0.2, 1.38, string.ascii_uppercase[2], transform=ax2_fI.transAxes,size=16, weight='bold')
#
# # plot boxplots
# boxplot_with_markers(ax0,max_width, alteration='shift')
# boxplot_with_markers(ax1,max_width, alteration='slope')
# boxplot_with_markers(ax2,max_width, alteration='g')
# # plot legend
# pos = (0.5, -1.)
# ncol = 6
# model_legend(ax2,  marker_s_leg, pos, ncol)
#
# # # plot rheo across model for example alteration
# # plot_rheo_alt(ax0_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='red', color2='maroon', alteration='shift')
# # plot_rheo_alt(ax1_ex,model='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='orchid', color2='purple',alteration='slope')
# # plot_rheo_alt(ax2_ex, model='Cb stellate', color1='darkviolet', color2='indigo', alteration='g')
# # plot_rheo_alt(ax0_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='shift')
# # plot_rheo_alt(ax1_ex,model='Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k',alteration='slope')
# # plot_rheo_alt(ax2_ex, model='Cb stellate', color1='lightgrey', color2='k', alteration='g')
#
# # plot examples
# plot_AUC_alt(ax0_ex,model='FS', color1='lightgrey', color2='k', alteration='shift')
# plot_AUC_alt(ax1_ex,model='FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k',alteration='slope')
# plot_AUC_alt(ax2_ex, model='STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', color1='lightgrey', color2='k', alteration='g')
# fig.savefig('AUC_correlation_2.pdf', bbox_inches='tight') #
# # plt.saveas(fig, 'AUC_correlation_2.png')
# plt.show()