diff --git a/code/NR_Interpolate-0001_t_10M.py b/code/NR_Interpolate-0001_t_10M.py
index 048855d6e13f9dda952fac7b9f839a179f3a710c..489e245ebd3b8abef8a6cd3532de279b827d8f82 100755
--- a/code/NR_Interpolate-0001_t_10M.py
+++ b/code/NR_Interpolate-0001_t_10M.py
@@ -10,6 +10,8 @@
 import numpy as np
 from scipy import interpolate
 import corner
+import os
+os.environ['MPLCONFIGDIR'] = '/home/rayne.liu/.config/matplotlib'
 import matplotlib.pyplot as plt
 from matplotlib.ticker import MaxNLocator
 from matplotlib import rc
@@ -130,7 +132,7 @@ plt.plot(timespan_new, gwdatanew_re, "b", alpha=0.3, lw=2, label='After_re')
 plt.plot(timespan, gwdata_im, alpha=0.3, lw=2, label='Before_im')
 plt.plot(timespan_new, gwdatanew_im, alpha=0.3, lw=2, label='After_im')
 plt.legend()
-figtest.savefig(rootpath + '/plotsmc/001_interpolated_datatest.png', format='png', bbox_inches='tight', dpi=300)
+figtest.savefig(rootpath + '/plotsmc/0001_interpolated_datatest.png', format='png', bbox_inches='tight', dpi=300)
 
 
 # ### Now the interpolation seems nice according to what we have above...let's start sampling!
@@ -207,7 +209,7 @@ def log_probability(theta):
 pool = choose_pool(1)
 pool.size = 1
 np.random.seed(42)
-pos = np.array([random.uniform(-0.02,0.02), random.uniform(-0.1,0.15), random.uniform(-0.2.,0.08),                 random.uniform(0.,1.), random.uniform(0.4,0.8), random.uniform(0.5, 1.), random.uniform(0.5, 0.6),                 random.uniform(0.5, 0.6)])
+pos = np.array([random.uniform(-0.02,0.02), random.uniform(-0.1,0.15), random.uniform(-0.2,0.08),                 random.uniform(0.,1.), random.uniform(0.4,0.8), random.uniform(0.5, 1.), random.uniform(0.5, 0.6),                 random.uniform(0.5, 0.6)])
 pos = list(pos)
 pos += 1e-5 * np.random.randn(ntemps, nwalkers, ndim)
 sampler = ptemcee.Sampler(nwalkers, ndim, log_likelihood, log_prior, ntemps=ntemps, pool=pool)
@@ -276,4 +278,4 @@ for yi in range(naxes):
         ax.axvline(median[xi], color=mediancolor)
         ax.axhline(median[yi], color=mediancolor)
         ax.plot(median[xi], median[yi], color = mediancolor, marker = 's')
-figcorn.savefig(rootpath + '/plotsmc/0001_10M_interpolated_cornerplot.png', format='png', bbox_inches='tight', dpi=300)
\ No newline at end of file
+figcorn.savefig(rootpath + '/plotsmc/0001_10M_interpolated_cornerplot.png', format='png', bbox_inches='tight', dpi=300)
diff --git a/code/condor_submit_Interpolate0001_t_10M.sub b/code/condor_submit_Interpolate0001_t_10M.sub
index 7b4ae34569d45fead1371cb90da7e933757abc69..271cdaf85982d1aa21f90fc6f97a67cf3dc12a76 100755
--- a/code/condor_submit_Interpolate0001_t_10M.sub
+++ b/code/condor_submit_Interpolate0001_t_10M.sub
@@ -12,7 +12,7 @@ initialdir = .
 notify_user = rl746@cornell.edu
 notification = Complete
 arguments  = "-processid $(Process)" 
-request_memory = 128GB
+request_memory = 64GB
 request_cpus = 1
 on_exit_remove = (ExitBySignal == False) || ((ExitBySignal == True) && (ExitSignal != 11))
 accounting_group = aei.dev.test_dynesty