graph.py

"""
Module for graphing
"""

import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns

def hist_distributivity_graph(N,RESOLUTION,seed,data):
    """
    graphs histograms
    see values function in main module
    """
    plt.clf()
    for name in data:
        print("building "+str(name)+" histogram...")
        xlabel= "Value"
        ylabel="Count"
        title_name= name +"\n N = "+str(N)+"\n seed = "+str(seed) 
        graph=sns.displot(data[name], kde=True)
        graph.set(title=title_name)
        graph.set_axis_labels(xlabel,ylabel)
        graph.savefig(name+'_hist.png', bbox_inches='tight')
    return

def ecdf_graph(N,RESOLUTION,seed,data):
    """
    graphs histograms
    see values function in main module
    """
    plt.clf()
    for name in data:
        print("building "+str(name)+" ecdf...")
        xlabel= "Value"
        ylabel="Cumulative Probability"
        title_name= name +"\n N = "+str(N)+"\n seed = "+str(seed) 
        if N==0:
            title_name= name +"\n seed = "+str(seed) 
        graph=sns.displot(data[name], kind="ecdf")
        graph.set(title=title_name)
        graph.set_axis_labels(xlabel,ylabel)
        graph.savefig(name+'_ecdf.png', bbox_inches='tight')
    return

def compare_ecdf(N, RESOLUTION, seed, data):
    """
    Create graphs superposing  ecdf   
    """
    plt.clf()
    BW = 0.337
    name = "compare_ecdf_"
    for e in data:
        name += e+"_"
    
    #subdata = {k : data[k] for k in names}  
    print("graphing "+str(name)+"...")
    
    xlabel = "Value"
    ylabel = "Density"
    title_name="N = "+str(N)+"\n seed = "+str(seed)
    if N == 0:
        title_name = "seed = "+str(seed)
    graph=sns.displot(data,legend=True
                        , kind="ecdf")
    graph.set(title=title_name)
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    #plt.legend()
    plt.savefig(name+'.png', bbox_inches='tight')    
    return

def compare(N, RESOLUTION, seed, data):
    """
    Create graphs superposing two, already generated,
    distributivity
    """
    plt.clf()
    BW = 0.337
    name = "compare_"
    for e in data:
        name += e+"_"
    
    #subdata = {k : data[k] for k in names}  
    print("graphing "+str(name)+"...")
    
    xlabel = "Value"
    ylabel = "Density"
    title_name="N = "+str(N)+"\n seed = "+str(seed)
    if N == 0:
        title_name = "seed = "+str(seed)
    for e in data:
        graph=sns.kdeplot(data[e],legend=True,bw_adjust=BW,common_norm=False
                          ,label=str(e))
    graph.set(title=title_name)
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    graph.axes.set
    plt.legend()
    plt.savefig(name+'.png', bbox_inches='tight')
    return

def lineplot_wrap(data, xlabel, ylabel, title, iterN):
    plt.clf()
    print("graphing "+str(title)+"...")
    for e in data:
        plt.plot(iterN, data[e], marker="o", label="seed="+str(e))
    #graph = sns.lineplot(data, legend=True, x=iterN)
    plt.title(title)
    plt.legend()
    plt.xscale('log')
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    plt.savefig(title.replace(" ", "_")+".png", bbox_inches="tight")

def lineplot_mean_alot(data, xlabel, ylabel, title, iterN):
    plt.clf()
    print("graphing "+str(title)+"...")
    for e in data:
        plt.plot(iterN, data[e], marker="o", alpha=0.05
                 , color="red")
    plt.plot(iterN, [0.5]*len(iterN), color="blue",linestyle='dotted')
    plt.title(title)
    plt.xscale('log')
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    plt.savefig(title+".png", bbox_inches="tight")