// get a and b from previous script
print(len(a))
print(len(b))


import requests
import pprint
import json
from collections import defaultdict
from statistics import mean
from statistics import median



validator_category = defaultdict(int)
validator_category_index = defaultdict(list)

for i in a.keys():
    if a[i] >= 20000:
        validator_category["Stakewise"] += 1
        validator_category_index["Stakewise"].extend(b[i])
    elif a[i] >= 10000:
        validator_category["Kleros"] += 1
        validator_category_index["Kleros"].extend(b[i])
    elif a[i] >= 4096:
        validator_category["xDAI"] += 1
        validator_category_index["xDAI"].extend(b[i])
    elif a[i] >= 4000:
        validator_category["Gnosis"] += 1
        validator_category_index["Gnosis"].extend(b[i])
    elif a[i] >= 1000:
        validator_category["Large"] += 1
        validator_category_index["Large"].extend(b[i])
    elif a[i] >= 100:
        validator_category["Medium"] += 1
        validator_category_index["Medium"].extend(b[i])
    elif a[i] >= 5:
        validator_category["Small"] += 1
        validator_category_index["Small"].extend(b[i])
    else:
        validator_category["Subsidy"] += 1
        validator_category_index["Subsidy"].extend(b[i])
print(validator_category)
print("")
print("Stakewise: " + str(len(validator_category_index["Stakewise"])))
print("Kleros: " + str(len(validator_category_index["Kleros"])))
print("xDAI: " + str(len(validator_category_index["xDAI"])))
print("Gnosis: " + str(len(validator_category_index["Gnosis"])))
print("Large: " + str(len(validator_category_index["Large"])))
print("Medium: " + str(len(validator_category_index["Medium"])))
print("Small: " + str(len(validator_category_index["Small"])))
print("Subsidy: " + str(len(validator_category_index["Subsidy"])))
print("")

import numpy as np
import random

for j in ["Stakewise","Kleros","xDAI","Gnosis","Large","Medium","Small", "Subsidy"]:


    validator_index_string = ""
    random.shuffle(validator_category_index[j])
    for i in validator_category_index[j][:100]:
        validator_index_string += str(i)+","
    #print(validator_index_string)
    response = requests.get("https://beacon.gnosischain.com/api/v1/validator/" + validator_index_string[:-1] + "/performance")

    #pprint.pprint(response.content)
    parsed = json.loads(response.content)
    perf1day = []
    perf7day = []
    #print(parsed)
    for i in parsed["data"]:
        #print(i)
        perf1day.append(i["performance1d"])
        perf7day.append(i["performance7d"])

    print(j + " Mean:" + str(mean(perf1day) *365/32000000000))
    print(j + " Median:" + str(median(perf1day) *365/32000000000))
    a = np.array(perf1day)
    print(j + " bottom 5%: " + str(np.percentile(a, 5) *365/32000000000))
    print(j + " bottom 10%: " + str(np.percentile(a, 10) *365/32000000000))
    print(j + " bottom 15%: " + str(np.percentile(a, 15) *365/32000000000))
    print(j + " top 10%: " + str(np.percentile(a, 90) *365/32000000000))

    print()
    print(j + " Mean7:" + str(mean(perf7day)/7 *365/32000000000))
    print(j + " Median7:" + str(median(perf7day)/7 *365/32000000000))
    a = np.array(perf7day)
    print(j + " bottom 5%7: " + str(np.percentile(a, 5)/7 *365/32000000000))
    print(j + " bottom 10%7: " + str(np.percentile(a, 10)/7 *365/32000000000))
    print(j + " bottom 15%7: " + str(np.percentile(a, 15)/7 *365/32000000000))
    print(j + " top 10%7: " + str(np.percentile(a, 90)/7 *365/32000000000))
    print()

#print(json.dumps(parsed, indent=4, sort_keys=True))
#print(parsed["data"])