import unicodedata
import numpy as np
from ProfileDataType import Profile
from scipy.interpolate import interp1d
from scipy.signal import butter, filtfilt
from DataBase import DataBase

'''
************************************************************
该模块用读取实测的声速剖面
************************************************************
'''

def is_number(s):
    '''
    判断是否为数字
    '''
    try:
        float(s)
        return True
    except ValueError:
        pass
 
    try:
        unicodedata.numeric(s)
        return True
    except (TypeError, ValueError):
        pass
 
    return False

def readRawProfile(fname):
    # 读取经纬度, 海深等信息
    f = open(fname)
    line = f.readline()
    line = line.split(',')
    if is_number(line[1]):
        lat = float(line[1])
    else:
        lat = None
    if is_number(line[3]):
        lon = float(line[3])
    else:
        lon = None
    if is_number(line[5]):
        botDep = float(line[5])
    else:
        botDep = None
    f.close()
    # 读取数据
    data = np.loadtxt(fname, skiprows=2,delimiter=',')
    # 剖面赋值
    velPf = Profile()
    velPf.set_data(data[:, 0], data[:, 1])
    velPf.set_coord(lat, lon)
    velPf.set_bottomDepth(botDep)
    return velPf


def removeHead(velPf):
    '''
    去掉剖面头部异常数据, 刚入水的
    '''
    lat = velPf.lat
    lon = velPf.lon
    botDep = velPf.botDep
    dep = velPf.x
    vel = velPf.y
    # 梯度阈值
    gradc = 1.0
    # 去掉前面一段（刚入水）变化计较剧烈的区域
    for i in range(dep.size-1):
        grad = np.abs((vel[i+1]-vel[i])/(dep[i+1]-dep[i]))
        if grad < gradc:
            break
    dep = dep[i+1:]
    vel = vel[i+1:]
    # 剖面赋值
    velPf = Profile()
    velPf.set_data(dep, vel)
    velPf.set_coord(lat, lon)
    velPf.set_bottomDepth(botDep)
    return velPf


def removeTail(velPf, ETOPO1Path, STPath):
    '''
    去掉剖面尾部异常数据, 触底后的
    '''
    lat = velPf.lat
    lon = velPf.lon
    botDep = velPf.botDep
    dep = velPf.x
    vel = velPf.y
    # 如果没有给定深度，则直接从数据库中提取
    if botDep == None:
        data = DataBase(ETOPO1Path, STPath)
        data.set_coord(lat, lon)
        botDep = data.get_bottomDepth()
    # 过滤掉触底后的曲线
    temp = dep < botDep
    dep = dep[temp]
    vel = vel[temp]
    # 剖面赋值
    velPf = Profile()
    velPf.set_data(dep, vel)
    velPf.set_coord(lat, lon)
    velPf.set_bottomDepth(botDep)
    return velPf


def resampleProfile(velPf):
    '''
    重采样剖面, 间隔1m采样
    '''
    lat = velPf.lat
    lon = velPf.lon
    botDep = velPf.botDep
    dep = velPf.x
    vel = velPf.y
    # 得到等间距的采样曲线
    depInterp = np.arange(0, dep[-1])
    f = interp1d(dep, vel, fill_value='extrapolate')
    velInterp = f(depInterp)
    # 剖面赋值
    velPf = Profile()
    velPf.set_data(depInterp, velInterp)
    velPf.set_coord(lat, lon)
    velPf.set_bottomDepth(botDep)
    return velPf


def lowPassFilter(velPf):
    '''
    低通滤波器, 使曲线平滑
    '''
    lat = velPf.lat
    lon = velPf.lon
    botDep = velPf.botDep
    dep = velPf.x
    vel = velPf.y
    # 设计数字滤波器
    freqc = 0.05
    order = 2
    b, a = butter(order, freqc)
    # 对曲线进行滤波
    vel = filtfilt(b, a, vel)
    # 剖面赋值
    velPf = Profile()
    velPf.set_data(dep, vel)
    velPf.set_coord(lat, lon)
    velPf.set_bottomDepth(botDep)
    return velPf


def processProfile(velRawPf, ETOPO1Path, STPath):
    '''
    对原始剖面数据进行处理, 得到处理后的剖面
    '''
    # 去掉刚入水，剧烈变化部分
    velPf = removeHead(velRawPf)
    # 去掉触底后，无效部分
    velPf = removeTail(velPf, ETOPO1Path, STPath)
    # 等间距重采样
    velPf = resampleProfile(velPf)
    # 低通滤波
    velPf = lowPassFilter(velPf)
    return velPf