Question

我正在尝试在python中编写R等效代码，但没有得到相同的结果。 R代码如下：

# Set parameters
max.people = 50
max.trials = 500
plot.step  = 1

# load libraries
library(tidyverse)

#Set up an initial data frame
df<-data.frame("trial"=NA,"people"=NA, "val"=NA)

# Set up a common theme for plots
ztheme<-function(){
  theme_classic()+
    theme(panel.background=element_rect(fill="#F0F0F0", color="#F0F0F0"))+
    theme(plot.background=element_rect(fill="#F0F0F0", color="#F0F0F0"))}

#Run main loop
for(trial in 1:max.trials){
  # set up a buffer. Makes the program run a lot faster.
  buff<-data.frame("trial"=NA,"people"=NA, "val"=NA)
  for(people in 1:max.people){
    buff<-rbind(buff,data.frame("trial"=trial,"people"=people, "val"=NA))
    samp<-sample(1:365, people, replace=T)
    if(length(unique(samp))==length(samp)){
      buff$val[nrow(buff)]<-0
    }else{
      buff$val[nrow(buff)]<-1
    }; rm(samp)}
  df<-rbind(df, buff); rm(buff)
  print(paste(round(trial/(max.trials)*100, 2), "% Complete", sep=""))
}
df<-subset(df, !is.na(df$trial))
rm(max.people); rm(people); rm(trial)

# Generate multiple plots of result
for(n in seq(plot.step,max.trials,plot.step)){
  print(
    ggplot(summarise(group_by(subset(df, trial<=n), people), prob=mean(val)), aes(people, prob))+
      geom_bar(stat="identity", fill="steelblue1")+
      geom_smooth(se=F, color="black", method="loess")+
      scale_y_continuous(labels=scales::percent, limits=c(0,1))+
      labs(title="Birthday Paradox",
           subtitle=paste("Based on",n,"simulations."),
           x="Number of People in Room",
           y="One or More Matching Birthdays (True/False Ratio)",
           caption="created by /u/zonination")+
      ztheme())
  ggsave(paste("bday_", formatC(n,width=5,flag = "0"), ".png", sep=""), height=4.5, width=7, dpi=120, type="cairo-png")
}; rm(n)

我在python中编写了等效代码，如下所示：

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import random
plt.style.use('ggplot')

maxTrials = 500
maxPeople = 50
plotStep = 1

df = pd.DataFrame(columns=['trial','people','val'])

for trial in range(plotStep, maxTrials+1):
    buff = pd.DataFrame()
    for people in range(plotStep,maxPeople+1):
        buff = buff.append(pd.DataFrame({'trial':[trial],'people':[people],'val':[np.nan]}), ignore_index=True)
        samp = [random.randint(1,366) for x in range(people)]
        if len(set(samp)) == len(samp):
            buff.at[len(buff.index)-1,'val'] = 0
        else:
            buff.at[len(buff.index)-1,'val'] = 1
        del(samp)
    df = df.append(buff, ignore_index=True)
    del(buff)
    print(str(round(trial/(maxTrials)*100, 2)) + "% Complete")
df = df.dropna(axis=0, how='any')
del(maxPeople)
del(people)
del(trial)

for n in range(plotStep,5):
    dfCopy = df.loc[df.trial<=n]
    dfCopy = dfCopy.groupby(['people'])['val'].mean().to_frame(name='prob').reset_index()
    print(dfCopy)
    plt.bar(dfCopy['people'],
            dfCopy['prob'],
            color='blue',
            edgecolor='none',
            width=0.5,
            align='center')
    plt.suptitle("Birthday Paradox\n")
    plt.title("Based on "+str(n)+" simulations.")
    plt.yticks([0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0])
    plt.xlabel("Number of people in room")
    plt.ylabel("Probability of one or more matching birthdays")
    plt.savefig("bday_"+str(n)+".png", dpi=110, bbox_inches='tight')

R中一些初始保存的图看起来像this但是python输出看起来像this我想知道这是否是因为某种舍入错误。

Answer 1

代码很好，但你没有清除你的轴，所以它会在不清除最后一次的情况下添加每次运行。

在plt.cla()之后添加plt.savefig(...)会使其看起来更像R输出

R等效python代码给出不同的输出

1 个答案: