# In[14]:
try:
get_ipython().run_line_magic('matplotlib', 'inline')
except:
pass
# In[15]:
x = np.array(df.theta)
s = np.array(df.sin)
c = np.array(df.cos)
# In[16]:
to_plot = [[x, s, "sin(x)"], [x, c, "cos(x)"]]
# In[17]:
myplot(bl="time",
sl="out\nVolts",
topl="two plots",
width=1,
sets=to_plot,
doxkcd=True)
def mytan(s, c):
return s / c
df['tan'] = df.apply(lambda row: mytan(row['sin'], row['cos']), axis=1)
print(df)
import os
try:
get_ipython().run_line_magic('matplotlib', 'inline')
except:
pass
os.getcwd()
#sys.path.append("/Users/tkaiser2/bin")
sys.path.append(os.getcwd())
from plsub import myplot
# In[ ]:
if doplot:
myplot(bl="Time (seconds) ",
sl="reward_mean",
topl="Eagle breakout-dqn",
sets=[[d0_time, d0_reward, "CPU"], [d1_time, d1_reward, "1 GPU"],
[d2_time, d2_reward, "2 GPUs"]])
# In[ ]:
if doplot:
myplot(bl="Time (seconds) ",
sl="Interation",
topl="Eagle breakout-dqn",
sets=[[d0_time, d0_it, "CPU"], [d1_time, d1_it, "1 GPU"],
[d2_time, d2_it, "2 GPUs"]])
# In[ ]:
out0 = pd.DataFrame(
def doomp(hdir, base, bind):
nplots = 0
global results
global cases
global thedirs
thedirs.append(hdir)
for ver in ["stf_ii", "stf_ig"]:
import os
import numpy as np
from plsub import myplot
import matplotlib.pyplot as plt
command = "grep -l " + ver + " " + hdir + "/2*"
#print("COMMAND",command)
c = os.popen(command, "r")
files = c.read()
cores = np.array(range(0, 64))
sums = np.zeros(64)
mins = np.zeros(64) + 1e6
maxs = np.zeros(64) - 1e6
icnt = np.zeros(64)
nf = 0
files = files.split()
#print(files)
nt = len(files)
heat = np.zeros([nt, 64])
for f in files:
#print(f)
nf = nf + 1
infile = open(f, "r")
dat = infile.readlines()
isums = np.zeros(64)
imins = np.zeros(64) + 1e6
imaxs = np.zeros(64) - 1e6
for d in dat:
d = d.split()
l = float(d[4])
c = int(d[6]) % 64
#print(c,l)
isums[c] = isums[c] + l
heat[nf - 1, c] = heat[nf - 1, c] + l
icnt[c] = 1
for c in range(0, 64):
if isums[c] < imins[c]: imins[c] = isums[c]
if isums[c] > imaxs[c]: imaxs[c] = isums[c]
sums = sums + isums
for c in range(0, 64):
if imins[c] < 1e5:
if imins[c] < mins[c]: mins[c] = imins[c]
if imaxs[c] > 0.0:
if imaxs[c] > maxs[c]: maxs[c] = imaxs[c]
sums = sums / nf
#print(sums)
cores = []
fmins = []
faves = []
fmaxs = []
for c in range(0, 64):
if sums[c] > 0.0:
cores.append(c)
fmins.append(mins[c])
faves.append(sums[c])
fmaxs.append(maxs[c])
#print(c,mins[c],sums[c],maxs[c])
# print(len(cores),fmins,faves,fmaxs)
asets = [[cores, fmins, "min"], [cores, faves, "ave"],
[cores, fmaxs, "max"]]
#myplot(sets=asets,doxkcd=False,width=0,do_sym="y",bl="Physical Core",sl="Load",topl=title,outname=ver+"-"+edir,yr="90,105",xr="0,64")
command = "grep cpus-per-task " + hdir + "/script* | tail -1"
print(command)
c = os.popen(command, "r")
lines = c.read()
#print(lines)
settings = "NONE"
settings = lines.replace("#SBATCH --", "")
settings = settings.strip()
#print(settings)
if lines.find("rank") > -1: settings = "cpu-bind=rank"
if lines.find("socket") > -1: settings = "cpu-bind=sockets"
if lines.find("core") > -1: settings = "cpu-bind=cores"
#command="grep 'run time' "+hdir+"/slurm-*.out | awk {'print $NF }'"
#print(settings+"01")
count = 0
try:
lines = lines.split("-n")
lines = lines[1]
lines = lines.split()
ccount = lines[0]
except:
#print("count failed")
ccount = "0"
#print(settings+"02")
#print("count=",ccount)
command = "grep 'run time' " + hdir + "/slurm-*.out"
#print(command)
c = os.popen(command, "r")
times = c.readlines()
#print(times)
j = 0
for t in times:
t = t.split("=")
#print("t=",t)
t = t[1]
ttt = t.split()
t = float(ttt[0])
t = "%5.2f" % (t)
times[j] = t
j = j + 1
#print(times)
#print(settings+"03")
cset = "CSET"
#print("ver",ver)
if ver.find("ii") > -1:
cset = "ifort t=" + times[0] + " "
if ver.find("ig") > -1:
cset = "gfortran t=" + times[1] + " "
if ver.find("og") > -1:
cset = "OpenMPI/GNU t=" + times[2] + " "
if ver.find("oi") > -1:
cset = "OpenMPI/Intel t=" + times[3] + " "
#print(cset,settings,ccount)
title = cset + settings
#print(title)
#settings=settings.replace("cpu-bind=","")
#print(settings+"04")
#get OMP_
command = "grep 'OMP_' " + hdir + "/env*"
c = os.popen(command, "r")
omp = c.read()
#print("bonk",omp)
if len(omp) > 0:
omp = omp.replace("\n", " ")
#print("OMP=",omp)
title = title + "\n" + omp
#print(title)
ofn = base + "/" + ver + "_" + settings + "_" + ccount + "_" + bind
ofn = nfname(ofn, ".pdf")
#print(ofn)
myplot(sets=asets,
doxkcd=False,
width=0,
do_sym="y",
bl="Physical Core",
sl="Load",
topl=title,
outname=ofn,
xr="0,64")
t2 = title.replace("\n", " ")
cases.append(t2)
results = pdappend(results, topd(title, ofn))
nplots = nplots + 1
fig, ax = plt.subplots(figsize=(12, 6),
subplot_kw={
'xticks': [],
'yticks': []
})
fig.subplots_adjust(hspace=100.0, wspace=50)
zmax = np.max(heat)
zmin = np.min(heat)
x = np.array(range(0, nt))
x = x / (nt - 1)
cores = np.array(range(0, 64))
#print(x)
#print(cores)
from scipy import interpolate
#nh= interpolate.interp2d(cores, x, heat)
#nh= interpolate.RectBivariateSpline(cores, x, heat,kx=1,ky=1)
#nh= interpolate.RectBivariateSpline(x, cores, heat,kx=1,ky=1,s=0)
nh = interpolate.RegularGridInterpolator((x, cores),
heat,
method="nearest")
#print(nh)
newx = np.array(range(0, 64)) / 64.0
nheat = np.zeros([64, 64])
for i in range(0, 64):
for j in range(0, 64):
yi = cores[i]
xi = newx[j]
#print(xi,yi)
#pts=np.array([xi,yi])
#print(nh([[4,4]]))
pts = np.array([[xi, yi]])
nheat[j][i] = nh(pts)
#c = ax.pcolormesh(x, cores, heat, cmap='RdBu', vmin=zmin, vmax=zmax)
#heat[3]=0
c = ax.pcolormesh(cores,
x,
heat,
cmap='rainbow',
vmin=zmin,
vmax=zmax,
shading='nearest')
#c = ax.pcolormesh(cores, newx, nheat, cmap='rainbow', vmin=zmin, vmax=zmax,shading='nearest')
#c=plt.imshow(heat,cmap='rainbow',interpolation="none")
c = plt.imshow(nheat, cmap='rainbow', interpolation="none")
ax.set_title(title)
ax.set_ylabel('Relative Time')
ax.set_xlabel('Physical Core')
ax.set_xticks(range(0, 65, 4))
yticks = range(0, 65, 4)
yticks = np.array(yticks) / 65
ax.set_yticks(range(0, 65, 4))
#ax.set_size=(20,2)
#ax.axis([x.max(), x.min(), cores.min(), cores.max()])
fig.colorbar(c, ax=ax)
#plt.show()
outname = nfname(outname, ".pdf")
outname = base + "/" + "h_" + ver + "_" + settings + "_" + ccount + "_" + bind
plt.savefig(outname + ".pdf")
nplots = nplots + 1
# for h in heat[:] :
# print(h)
return (nplots)
sets = []
for j in range(0, len(xs1[0, :])):
#print(xs1[0,j])
x = np.empty(len(cs1))
y = np.empty(len(cs1))
for i in range(0, len(cs1)):
#print(cs1[i],ys1[i,j])
x[i] = cs1[i]
y[i] = ys1[i, j]
#print(x)
#print(y)
sub = [x, y, str(xs1[0, j])]
sets.append(sub)
myplot(sets=sets,
do_log="y",
topl="Biband, TPN=" + TPN,
bl="Nodes",
sl='Msg/sec')
# cs1
# In[ ]:
TPN = "36"
ys1 = np.array(Biband.loc[Biband.tpn == TPN]['Msg/sec'])
xs1 = np.array(Biband.loc[Biband.tpn == TPN]['size'])
cs1 = np.array(Biband.loc[Biband.tpn == TPN]['cores'])
#print(ys1)
#print(xs1)
#print(cs1)