import os
import sys
import time
import pandas as pd
import json
import numpy as np
import math
import matplotlib.pyplot as plt
#import sklearn.datasets as data
#import hdbscan ##NOTE: hdbscan needs Cython. please install Cython before use.
import seaborn as sns
import pandas as pd




def draw_plot_cam_1(dataframe, path):
    df = dataframe
    imgpath = path
    sns.set_context('poster')
    sns.set_style('white')
    sns.set_color_codes()
    plot_kwds = {'alpha': 0.5, 'linewidths':0 }
    plt.rcParams['figure.figsize'] = 9, 7

    fig = plt.figure()
    ax = fig.add_subplot(projection = '3d')
    ax.scatter(df['x'],df['y'],df['z'], color='g', s=0.3, **plot_kwds)
    plt.savefig(path, dpi=660)
    plt.clf()

def draw_plot_cam_2(dataframe, path):
    df = dataframe
    sns.set_context('poster')
    sns.set_style('white')
    sns.set_color_codes()
    plot_kwds = {'alpha': 0.5, 'linewidths':0 }
    plt.rcParams['figure.figsize'] = 9, 7

    fig = plt.figure()
    ax = fig.add_subplot(projection = '3d')
    ax.scatter(df['x'],df['y'],df['z'], color='r', s=0.3, **plot_kwds)
    plt.savefig(path, dpi=660)
    plt.clf()

def draw_xy(dataframe,path):
    df = dataframe
    path_list=path.split('/')    
    plt.rcParams['figure.figsize'] = 9, 7
    fig=plt.figure()
    plt.scatter(df['x'], df['y'], s=0.2)
    plt.title(path_list[-1])
    plt.savefig(path, dpi=600)
    plt.clf()
    

def draw_yz(dataframe, path):
    df = dataframe
    path_list=path.split('/')    
    plt.rcParams['figure.figsize'] = 9, 7
    fig=plt.figure()
    plt.scatter(df['y'], df['z'], s=0.2)
    plt.title(path_list[-1])
    plt.savefig(path, dpi=600)
    plt.clf()

def draw_xz(dataframe, path):
    df = dataframe
    path_list=path.split('/')    
    plt.rcParams['figure.figsize'] = 9, 7
    fig=plt.figure()
    plt.scatter(df['z'], df['x'], s=0.2)
    plt.title(path_list[-1])
    plt.savefig(path, dpi=600)
    plt.clf()

def draw_plot_total(dataframe, path):
    df = dataframe
    sns.set_context('poster')
    sns.set_style('white')
    sns.set_color_codes()
    plot_kwds = {'alpha': 0.5, 'linewidths':0 }
    plt.rcParams['figure.figsize'] = 9, 7

    fig = plt.figure()
    ax = fig.add_subplot(projection = '3d')
    ax.axes.set_xlim3d(left=-1.8, right=1.8)
    ax.axes.set_ylim3d(bottom=-1.8, top=1.8)
    ax.axes.set_zlim3d(bottom=0, top=1.8)
    ax.set_xlabel('x (left_right)')
    ax.set_ylabel('y (head_tail)')
    ax.set_zlabel('z (floor_ceiling)')

    cam_1 = df[df['cam'] == 1]
    cam_2 = df[df['cam'] == 2]
    ax.scatter(cam_1['x'],cam_1['y'],cam_1['z'], color='g', s=0.3, **plot_kwds)
    ax.scatter(cam_2['x'],cam_2['y'],cam_2['z'], color='r', s=0.3, **plot_kwds)
    
    plt.savefig(path, dpi=660)
    plt.clf()

def draw_diff_diff(dataframe, path):
    data = dataframe
    plt.rcParams['figure.figsize'] =30, 7
    #plt.axes().set_aspect('equal')
    plt.xlim(data['frame'].min()-10, data['frame'].max()+10)
    #l = range(0, len(data['diff_diff']))
    #plt.xticks(l*10, data['diff_diff'])
    plt.ylim(data['diff_diff'].min(), data['diff_diff'].max())
    fig = plt.figure()
    plt.plot(data['frame'], data['diff_diff'], color='g')
    #plt.gca().set_aspect('auto')
    plt.savefig('./diff.png', dpi=600)
    plt.clf()