from data2 import trials
from statistics import stdev,mean
import matplotlib.pyplot as plt
from numpy import arange

stderr = []
avg = []
deps = {'nn':[[],[]], 'wid':[[],[]], 'dep':[[],[]], 'recl':[[],[]],
    'dead':[[],[]]}
varlist = tuple(deps.keys())
title = {'nn':'Nearest Neighbor', 'wid':'Pit Width', 'dep':'Pit Depth',
'recl':'Reclusive Population', 'dead':'Cannibalized Individuals'}
names = []

plt.figure(figsize=(16,9))

def addvar(key, data):
    deps[key][0].append(mean(data))
    deps[key][1].append(stdev(data))

for trial in trials:
    names.append(str(trial))
    addvar('nn',trial.nearest_neighbor())
    addvar('wid',[pit.diam for pit in trial.pits])
    addvar('dep',[pit.depth for pit in trial.pits])
    addvar('recl',[trial.recl for pit in trial.pits])
    addvar('dead',[trial.dead for pit in trial.pits])

x = arange(len(names))

width = 0.8;
plt.xticks(x,labels=names)
plt.ylabel('Arbitrary Units')

print(names,avg)
#for var in varlist:
stdscale = 1/2
for ind in range(len(varlist)):
    var = varlist[ind]
    div = mean(deps[var][0])
    plt.bar(x-ind*width/len(varlist)+width/2,
    [dep/div for dep in deps[var][0]],
    yerr=[stdscale*dep/div for dep in deps[var][1]], capsize=6,
    label=title[var],alpha=0.5, width=width/len(varlist))
    #plt.errorbar(names, [dep/div for dep in deps[var][0]],
    #yerr=[dep/div/4 for dep in deps[var][1]], capsize=12, label=title[var], marker="o")
plt.legend()
plt.savefig('lineplot.png', bbox_inches='tight')