def main():
if not os.path.isdir("figures"):
os.mkdir("figures")
set_sns()
#resample_wake(x=1.0)
plotwake(plotlist=["meancontquiv"], save=True)
#make_momentum_trans_bargraph()
if not os.path.isfile("processed/mom_transport.csv"):
run_funky_batch()
#plot_mom_transport()
plot_streamwise(save=True)
plt.show()
def main():
if not os.path.isdir("figures"):
os.mkdir("figures")
set_sns()
#resample_wake(x=1.0)
plotwake(plotlist=["meancontquiv"], save=True)
#make_momentum_trans_bargraph()
if not os.path.isfile("processed/mom_transport.csv"):
run_funky_batch()
#plot_mom_transport()
plot_streamwise(save=True)
plt.show()
def setpltparams(seaborn=True, fontsize=18, latex=True):
if seaborn:
set_sns()
else:
if latex:
font = {"family" : "serif", "serif" : "cmr10", "size" : fontsize}
else:
font = {"size" : fontsize}
lines = {"markersize" : 9, "markeredgewidth" : 1,
"linewidth" : 1.2}
legend = {"numpoints" : 1, "fontsize" : "small"}
matplotlib.rc("text", usetex=latex)
matplotlib.rc("font", **font)
matplotlib.rc("lines", **lines)
matplotlib.rc("legend", **legend)
matplotlib.rc("xtick", **{"major.pad":6})
parser.add_argument("--single-tare-torque",
help="Process a tare torque run")
parser.add_argument("--section", help="Process a test matrix section")
parser.add_argument("--tare-drag", help="Process tare drag runs",
action="store_true")
parser.add_argument("--tare-torque", help="Process tare torque runs",
action="store_true")
parser.add_argument("--all", "-a", action="store_true",
help="Process all data")
parser.add_argument("--plot", action="store_true", default=False,
help="Create plots (if applicable)")
args = parser.parse_args()
if args.plot:
from pxl.styleplot import set_sns
set_sns()
if args.single_run:
# Dealing with individual runs
section = args.single_run[0]
nrun = int(args.single_run[1])
print("Processing {} run {}".format(section, nrun))
r = Run(section, nrun)
if args.plot:
r.plot_perf("cp")
r.plot_wake()
print(r.summary)
if args.single_tare_drag:
process_tare_drag(args.single_tare_drag, plot=args.plot)
#!/usr/bin/env python
"""
This script generates the relevant figures and/or tables from the experiment. To
reprocess the data, run `process.py`.
"""
import py_2015_09_24_turbine_test_bed_demo.plotting as pl
from pxl.styleplot import set_sns
import matplotlib.pyplot as plt
save = True
savetype = ".pdf"
show = True
if __name__ == "__main__":
# Set plot style using PXL's Seaborn wrapper
set_sns(rc={"axes.grid": True, "lines.linewidth": 2})
# Call plotting functions here
pl.plot_torque(marker="o", save=save, savetype=savetype)
if show:
plt.show()
#!/usr/bin/env python
"""Plot results from the turbinesFoam RM2 simulation."""
import pandas as pd
import matplotlib.pyplot as plt
import os
import sys
from pyrm2tf.plotting import *
from pxl.styleplot import set_sns
import argparse
if __name__ == "__main__":
set_sns()
plt.rcParams["axes.grid"] = True
parser = argparse.ArgumentParser(description="Generate plots.")
parser.add_argument("plot",
nargs="*",
help="What to plot",
default="perf",
choices=[
"perf", "wake", "blade-perf", "strut-perf",
"perf-curves", "perf-curves-exp", "recovery",
"verification", "wake-profiles",
"wake-profiles-exp"
])
parser.add_argument("--all",
"-A",
help="Generate all figures",
default=False,
action="store_true")
