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# -*- coding: utf-8 -*-
from __future__ import print_function
from __future__ import unicode_literals
from __future__ import with_statement
import matplotlib.pyplot as plt
#from matplotlib import rcParams
#rcParams['figure.figsize'] = (10, 6)
#rcParams['legend.fontsize'] = 16
#rcParams['axes.labelsize'] = 16
#rcParams['pdf.fonttype'] = 42
#rcParams['ps.fonttype'] = 42 # default type 3 is not supported by ACM
#rcParams['text.usetex']=True
#rcParams['font.family']='serif' #) # ACM font requirement
 
from matplotlib import cm
from matplotlib.lines import Line2D import matplotlib 
 
import os
import sys
import logging
import time
import pickle
import numpy as np
import pandas as pd
 
class Obj(object):
    def __init__(self, *args, **kwargs):
        self.data = []
 
    def do(self):
        self.vis()
        self.exit()
 
    def exit(self):
        log.info("end")
 
    def _extract_line(self, line):
        dt = line.split()
        ts = float(dt[0])
        x = float(dt[1])
        y = float(dt[2])
        z = float(dt[3])
        return [ts, x, y, z]
 
    def extract(self):
        datas = list()
        with open(c.postion_log) as fin:
            li = list()
 
            def add_data():
                if len(li) > 0:
                    data = np.vstack(li)
                    datas.append(data)
 
            for line in fin:
                if line.startswith(c.start_flag):
                    print("start: ", line)
                    add_data()
                    li = list()
                else:
                    infos = self._extract_line(line)
                    li.append(infos)
            add_data()
        return datas
 
    def load_or_extract(self):
        fn = c.postion_data
        if os.path.isfile(fn):
            self.data = self._load(fn)
        else:
            self.data = self.extract()
            self._cache(self.data, fn)
 
    def vis(self):
        self.load_or_extract()
        if 1:
            data = self.data[-1]
            X = data[:,0]
            Y = data[:,2] + np.pi / 2.0
 
            formatter = matplotlib.ticker.ScalarFormatter()
            formatter.set_scientific(True)
            formatter.set_powerlimits((0,0))
 
            ax = plt.subplot(1, 1, 1)
            #ax.yaxis.set_major_formatter(formatter)
            #plt.ylabel("recevied bytes")
            #plt.xlabel("timeline")
            #plt.ylim(ymin=0, ymax=1.05 * np.max(Y))
            #plt.xlim(xmax=np.max(X))
            cosxs = X * np.cos(Y)
            sinxs = X * np.sin(Y)
            c = np.arange(X.shape[0])
            c = np.random.randn(X.shape[0], 1)
            plt.scatter(cosxs, sinxs, marker='o', cmap='Blues', c=c, alpha=1, edgecolors='none')
            #plt.scatter(cosxs, sinxs, marker='o', cmap='viridis', c=c, alpha=1, edgecolors='none')
            plt.plot([0], [0], 'o', color='r')
            plt.colorbar()
            #plt.plot(X, Y, '-', color="g")
 
            def add_line(x, y):
                x = 1.05 * np.array(x)
                y = 1.05 * np.array(y)
                l = Line2D(x, y, marker='.', linewidth=1, color='black')
                ax.add_line(l)
            add_line([np.min(cosxs), np.max(cosxs)], [0.0, 0.0])
            add_line([0.0, 0.0], [np.min(sinxs), np.max(sinxs)])
 
            #ax = plt.subplot(2, 1, 2)
            #ax.yaxis.set_major_formatter(formatter)
            #plt.xlim(xmax=np.max(X))
            #plt.ylim(ymin=0, ymax=1.05 * np.max(cY))
            #plt.xlabel("timeline")
            #plt.ylabel("cumulative recevied bytes")
            #plt.plot(X, cY, "-", color="g")
 
            #plt.scatter(x=index, y=size, c="g", label="decoding timestamp")
            #plt.scatter(x=ts2, y=size, c="r", label="feed to decoding")
            #plt.plot(index, size, color='g', marker='o', label='docoding timestamp')
            #plt.plot(ts2, size, '-', color='g', label='time of feeding to decoder')
            #plt.legend()
            plt.show()
            plt.savefig(c.postion_fig)
 
    def _cache(self, data, fout):
        with open(fout, "wb") as f:
            pickle.dump(data, f)
            log.info("save data: %s" %fout)
 
    def _load(self, fout):
        if not os.path.isfile(fout):
            log.fatal("file not exist: %s" % fout)
            return None
        with open(fout, "rb") as f:
            data = pickle.load(f)
            log.info("load data: %s" % fout)
            return data
 
 
if __name__ == "__main__":
    obj = Obj()
    obj.do()