# -*- coding: utf-8 -*-
"""
Created on Tue Oct 14 18:11:07 2014

@author: Geoffrey
"""

# -*- coding: utf-8 -*-
"""
Created on Wed Oct 08 15:35:11 2014

@author: c1248317
"""

import sys
pack_path = "D:/Google Drive/Work/Experiences/EyeTracking"
sys.path.insert(0, pack_path)
output_path = "D:/Google Drive/Work/Experiences/experiment-deviation-initial/img"
seq_path = "D:/Experience-EyeTrackerData/experiment-deviation-initial/output-seq.h5"
traj_path = "D:/Experience-EyeTrackerData/experiment-deviation-initial/output.h5"
import os
os.chdir(pack_path)
from eyetools import util_old as util
os.chdir(output_path)
import numpy as np
import pandas as pd
import matplotlib
from matplotlib import cm
from scipy.interpolate import interp1d
import matplotlib.patches as patches
import matplotlib.pyplot as plt
matplotlib.rcParams.update({'font.size': 18})
plt.ioff()
import pickle
#m = pickle.load( open( "save_traj.p", "rb" ) )
m = pickle.load( open(output_path+"/traj_and_RT_second_only.p", "rb" ) )
offset_control_second = m["offset_control"]
back_color = "#3C3C3C"
xmin, xmax = -800, 800
ymin, ymax = -800, 800
directions_toplot = np.array([15.0, 30.0])
cv = matplotlib.colors.ColorConverter()
rc = np.array(m["rectangle_tol"])

def distLinePoint(p1, p2, p3): ## p3 is the point, p1 to p2 is the line
    """Give the distance between a point p3 and a line defined by p1 and p2.
    The distance is negative if the point above or on the left of the line"""
    v_ortho = np.array((-(p1[1]-p2[1]),p1[0]-p2[0]))[np.newaxis,:] ## v = (x0 - x1, y1 - y0)
    v_hypotenus = np.array(p3) - np.array(p1)[np.newaxis,:] ## we could have done p3 - p2 or p1 - p3, does not matter
    distance = np.dot(v_ortho, v_hypotenus.T) / np.sqrt(v_ortho.dot(v_ortho.T))
    #print distance
    return -distance

cmap1 = cm.get_cmap('autumn')
cmap2 = cm.get_cmap('cool')
def plotDeviation(data, xlabel, ylabel, ax, lcolor, aligned=(False, False), time_normed=False):
    nb = data["trial ID"].iloc[0]
    lcolor = cmap1(float(nb)/(800)) if lcolor=="r" else cmap2(float(nb)/(800))
    if data["trial ID"].iloc[0] % 5 != 0:
        return pd.DataFrame(columns = ["time", "deviation"])

    else:
        print data["trial ID"].iloc[0]
    if time_normed==True:
        f = interp1d(data[xlabel].values, data[ylabel].values, kind= "linear")
        norm_time = np.linspace(data[xlabel].min(),data[xlabel].max(), 100)
        #print f(norm_time).shape, np.arange(100)[:,np.newaxis].shape
        new_data = np.hstack((np.arange(100)[:,np.newaxis],f(norm_time)[:,np.newaxis]))
        ax.plot(new_data[:,0], new_data[:,1], color = lcolor, lw=3.0, alpha=0.9)
        return pd.DataFrame(new_data, columns = ["time", "deviation"])
    else:
        x = data[xlabel] - aligned[0]*data[xlabel].iloc[0]
        y = data[ylabel] - aligned[1]*data[ylabel].iloc[0]
        #ax.scatter(x, y, color = lcolor, lw=1.0, alpha=0.9)
        ax.plot(x, y, color = lcolor, lw=2.5, alpha=0.7)
        return pd.DataFrame([x,y], columns = ["time", "deviation"])

def plotAllTraj(ax, traj, direction, xlabel, ylabel, aligned=(False, False)):
    select = util.selectByHalfDistance(traj, direction, "right")
    new = traj.ix[select,:]
    new.groupby("trial ID").apply(plotDeviation, xlabel, ylabel, ax, "r", aligned=aligned)
    
    select = util.selectByHalfDistance(traj, direction, "left")
    new = traj.ix[select,:]
    new.groupby("trial ID").apply(plotDeviation, xlabel, ylabel, ax, "l", aligned=aligned)
    
def compDeviation(traj):
    """ Calculate the deviation of a saccade from the straight line 
    formed by its start and end points
        Params:
            -- traj: should be numpy array of shape (n, 2)
    """
    if isinstance(traj, pd.DataFrame):
        #print "got a dataframe, try to put it in an array..."
        traj = traj.values
    #print traj
    p0 = traj[0,:]; p1 = traj[-1,:] ## pray for no NaN!
    #print p0[0], p0[1], p1[0], p1[1]
    distances = distLinePoint(p0, p1, traj)
    return pd.DataFrame(distances.T, columns = ["deviation"]) 

ALIGNED = True # aligned on the start position
BOOTSTRAP = False
for i in xrange(len(m["subjects"] )): 
    participant = m["subjects"][i]
    onetraj = m["test2"][i]
    controltraj = m["control2"][i]
    for d1 in directions_toplot:
        print "Working on file:", participant, str(d1)
        fig = plt.figure(figsize = (7, 11))

        ax = fig.add_subplot(211, axisbg="#666666", aspect='equal')#, projection = "3d")
        ax.set_title(participant+" dir:"+str(d1)+"\n\nSaccade Trajectories")
        ax.set_ylabel("Y-axis(degrees)")
        ax.set_xlabel("X-axis(degrees)")
        onetraj["xp_degree"] = onetraj["xp"] * 0.035935614921
        onetraj["yp_degree"] = onetraj["yp"] * 0.035935614921
        plotAllTraj(ax, onetraj, d1, "xp_degree", "yp_degree", aligned=(False, False))
        ax.set_xlim((-14.5,14.5))
        ax.set_ylim((14.5, -14.5))
        ax.vlines(0, -14.5, 14.5, color="black", lw=1.5, linestyles="dashed", zorder=10)
        ax.hlines(0, -14.5, 14.5, color="black", lw=1.5, linestyles="dashed", zorder=10)

        ## only true for the condition 30 degrees:
        ax.scatter([-11.69, 11.69], [0, 0], marker="x", color="red", s=45.0, zorder=11)
        #ax.scatter([0, 0], [-6.75, 6.75], marker="o", color="red", s=45.0, zorder=11)

        ax = fig.add_subplot(212, axisbg="#666666")
        ax.set_title("Saccade Deviation over Time")
        ax.set_ylim((-2.9,2.9))
        onetraj["deviation"] = onetraj[["xp_degree", "yp_degree"]].groupby(onetraj["trial ID"]).apply(compDeviation).values
        onetraj.reset_index(inplace=True, drop = True)
        plotAllTraj(ax, onetraj, d1, "time", "deviation", aligned=(True, False))
        ax.set_ylabel("deviation from \nstraight line (degrees)")
        ax.set_xlabel("time from saccade start (ms)")
        ax.vlines(20.0, -3, 3, color="black", lw=1.5, linestyles="dashed", zorder=10)
        ax.hlines(0, 0, 150, color="gray", lw=1.0, linestyles="dashed")
        ax.set_xlim((0,150))
        plt.tight_layout()
        plt.savefig("curves/condition-both-aligned"+m["subjects"][i]+"-"+str(d1)+".png", dpi = 300)
        plt.close()