常用代码

一、常用引入库

from collections import Counter
import matplotlib.pyplot as plt
from math import atan,radians,tan,cos,sin,acos
import numpy as np
import seaborn as sns
plt.rcParams['figure.dpi'] = 300
plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] # Microsoft YaHei
plt.rcParams['axes.unicode_minus'] = False  # 负数

二、分布图绘制

def draw_distrubution(date, drawdata, xlabel, drawtype):
    if drawtype == 'hist':
        plt.figure(figsize=(10, 6))
        # data = [np.log10(a) for a in drawdata]  # 对数直方图，以10为底，np.log(a)默认以e为底
        data = drawdata
        min_val, max_val = np.min(data), np.max(data)
        bins1 = np.linspace(min_val, max_val, num=20)
        sns.histplot(data, bins=bins1, color="red", alpha=0.7, stat="density")  # stat='count'默认是频数 , stat="density"画概率密度
        plt.xlabel(xlabel, fontsize=14)
        plt.ylabel(drawtype, fontsize=14)
        plt.title(date, fontsize=16)
        plt.show()
    else:
        draw_y = []
        if drawtype == 'PDF':
            count = Counter(drawdata)  # 计算出现频次
            x = sorted(count.keys())
            y = [count[key] for key in x]
            draw_y = y
            
        else: 
            count = Counter(drawdata)  # 计算出现频次
            x = sorted(count.keys())
            y = [count[key] for key in x]
            y_cu = []  # 累积
            y_ccu = []  # 互补累积
            cu_pro = 0
            ccu_pro = 1
            total = sum(y) 
            for i in range(len(y)):
                cu_pro += y[i]/total
                y_cu.append(cu_pro) 
                
                y_ccu.append(ccu_pro)
                ccu_pro -= y[i]/total     
            if drawtype == 'CCDF':  
                draw_y = y_ccu
            elif drawtype == 'CDF':
                draw_y = y_cu
            
        plt.figure(figsize=(10, 6))
        plt.scatter(x, draw_y, c='red')
        plt.title(date, fontsize=16)
        plt.xscale('log', base=10)  # 默认底数为10,也可以设置base=np.e以e为底数
        plt.yscale('log', base=10)
        plt.xlabel(xlabel, fontsize=14)
        plt.ylabel(drawtype, fontsize=14)
        # plt.ylim(bottom=1e-6)  # 设置y轴下限
        plt.show()
    
    

三、计算

1、计算距离

def calcDistance(Lat_A, Lng_A, Lat_B, Lng_B):
    """
    input Lat_A 纬度A
    input Lng_A 经度A
    input Lat_B 纬度B
    input Lng_B 经度B
    output distance m
    """
    Lat_A=round(Lat_A,6)
    Lat_B=round(Lat_B,6)
    Lng_A=round(Lng_A,6)
    Lng_B=round(Lng_B,6)

    if Lat_A==Lat_B and Lng_A==Lng_B:
        return 0
    #
    ra = 6378.140  # 赤道半径 (km)
    rb = 6356.755  # 极半径 (km)
    flatten = (ra - rb) / ra  # 地球扁率
    rad_lat_A = radians(Lat_A)
    rad_lng_A = radians(Lng_A)
    rad_lat_B = radians(Lat_B)
    rad_lng_B = radians(Lng_B)
    pA = atan(rb / ra * tan(rad_lat_A))
    pB = atan(rb / ra * tan(rad_lat_B))
    try:
        xx = acos(sin(pA) * sin(pB) + cos(pA) * cos(pB) * cos(rad_lng_A - rad_lng_B))
        c1 = (sin(xx) - xx) * (sin(pA) + sin(pB)) ** 2 / cos(xx / 2) ** 2
        c2 = (sin(xx) + xx) * (sin(pA) - sin(pB)) ** 2 / sin(xx / 2) ** 2
        dr = flatten / 8 * (c1 - c2)
        distance = ra * (xx + dr)
    except:
        distance = 0
    return distance * 1000