graph_test.py

import sys
import numpy as np 
import matplotlib.pyplot as plt
from orderenv import OrderMethods

sys.path.append("/home/kmm11/orderml/Active Learning Fit Check")
import model_setup

logstore = '/wrk/kmm11/orderout/thirdpapertest/'
imgstore = '/wrk/kmm11/orderout/thirdpapertestgraphs/'

data = np.loadtxt(logstore +  "successdata.npy")

plt.scatter(data[0], data[5]+1, s=3) # fix +1 if needed
plt.xlabel("Tn Value")
plt.ylabel("steps to succeed")
plt.savefig(imgstore + "steptns.png")
plt.close()

temps = np.loadtxt(logstore + "temps.npy")
T = np.arange(3,340,2)
I = OrderMethods.orderparameter(T, data[0], data[1], data[2], data[3])
# I = OrderMethods.orderparameter(T, Bk = 0.193547, Jt = 0.403109, Nf = 148.449, Tn = 128.817)
plt.plot(T, I)
Itemps = OrderMethods.orderparameter(temps, data[0], data[1], data[2], data[3])
print(temps)
temps[-1]=temps[-2]+35 # 35 hardcoded from output of test.py run because of a weird bug
# plt.scatter(temps, Itemps)
for temp in temps:
    plt.axvline(temp, color='red', linestyle="--")

dirname="/wrk/kmm11/orderdata/nexus-selected"
dirname_reduced="/wrk/kmm11/orderdata/autoreduce-selected"
start_num=531827
end_num=531845
tth_arr, I_arr, Ierr_arr, T_arr = model_setup.read_data(dirname, dirname_reduced, start_num, end_num)

# print(I_arr)
# print(T_arr)

# realIs = []
# for i in range(len(temps)):
#     realIs.append(np.sum(I_arr[int(temps[i])]))

# plt.scatter(temps, realIs, 'ro')
plt.title("Measured Temperatures for ORNL Data")
plt.xlabel("Temperature")
plt.ylabel("Intensity")

plt.savefig(imgstore + "actions.png")