R Äquivalent Python-Code gibt verschiedene Ausgabe

Question

Ich versuche, R entsprechenden Code in Python zu schreiben, aber nicht das gleiche Ergebnis zu bekommen. Der R-Code ist wie folgt:

# 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) 

I entsprechenden Code in Python geschrieben habe, wie folgt:

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') 

Ein paar erstes gespeicherte Grundstück von R aussehen this aber Python Ausgabe sieht wie folgt this Ich mag wissen, ob dies an einem Rundungsfehler liegt.

Answer 1

Der Code ist in Ordnung, aber Sie löschen nicht Ihre Achsen, so wird es jeden Lauf hinzufügen, ohne die letzte zu löschen.

Durch Hinzufügen von plt.cla() nach plt.savefig(...) wird es ähnlich aussehen wie der R-Ausgang