def gnuplot(f, *between):
''' Plot the function f within the optional limits *between '''
# Create an instance of the gnuplot class
graph = Gnuplot()
# Get the full file name and root_file_name (excluding extension)
file_name, root_file_name = graph.file_name, graph.root_file_name
# Plot the function
graph.plot_function(f, *between)
# Return a string / html representation of the graph
return StrWithHtml('Image saved to ' + file_name,
'''<img src="{}.svg" style="width: 100%" />'''.format(root_file_name))
def main():
""" Main interface """
parser = _create_parser()
args = parser.parse_args()
if len(sys.argv) == 1:
parser.print_usage()
parser.exit(status=1)
elif args.countries:
print("\n".join(map(str, data.countries())))
sys.exit()
elif args.states:
print("\n".join(map(str, data.states())))
sys.exit()
region = data.read(args.region)
if not region:
print(f"Region '{args.region}' not found.")
sys.exit(1)
title = f"COVID-19 Infections ({region})"
with tempfile.NamedTemporaryFile(mode="w") as datfile:
for stats in region.daily_stats():
datfile.write(f"{stats.date}\t{stats.cases}\t{stats.avg}\n")
datfile.flush()
gnuplot = Gnuplot("./covid.gp", args.terminal, args.output)
gnuplot.set_var("datfile", datfile.name)
gnuplot.set_var("title", title)
gnuplot.run()
def gnuplot(self, reg):
#####################################################################
"plot with gnuplot"
#####################################################################
if not self.__dict__.has_key('gp'):
self.gp = Gnuplot()
CQLRIO.DumpSamples('samples.dat', self.reg)
if self.p.GetDimensions() == 1:
CQLRIO.Distrib(reg)
self.plot_to_file('distrib.dat', 100)
self.gp.send('load "clop.gpi"')
elif self.p.GetDimensions() == 2:
CQLRIO.Distrib(reg)
self.plot_to_file_2d('distrib.dat', 40)
self.gp.send('load "samples2d.gpi"')
def _plot_non_consecutive_graph(self, graph_type):
"""TODO: Docstring for _plot_non_consecutive_graph.
:returns: TODO
"""
cuts = Cut.all_cuts(self.cube)
with open('output/detailed_output.csv', 'a', newline='') as csvfile:
writer = csv.writer(csvfile)
writer.writerow([graph_type])
writer.writerow(['filename', 'dependant', 'parameters'])
for i, cut in enumerate(cuts):
self.cube.populate_cut(cut)
with Gnuplot() as plot:
plot.output = "%s_cut_%d" % (graph_type, i)
plot.xlabel = cut.dep
plot.benchdata = self._format_data_for_gnuplot(
cut, graph_type)
plot.run()
writer.writerow(
[plot.output, cut.dep,
cut.parameters.items()])
def plot( self, font_fname=None ) : plt = Gnuplot() plt.open() plt.xlabel( "Time (s)" ) plt.ylabel( "$$$ spent (estimate)" ) plt.set_style( "linespoints" ) plots = [] labels = [] for i in range( self.nplayers ) : player = self.kwr.players[i] if not player.is_player() : continue pair = self.split( self.spents[ i ] ) if not pair : continue ts, costs = pair plt.plot( ts, costs ) labels.append( sanitize_name( player, xor=True ) ) plt.legend( labels ) plt.show() plt.close()
def plot_unit_distribution( self ) :
color = 1
for i in range( self.nplayers ) :
player = self.kwr.players[i]
if not player.is_player() :
continue
plt = Gnuplot()
plt.open()
histo = self.units[ i ]
plt.write( 'set style fill solid\n' )
plt.write( 'set key off\n' )
plt.write( 'set boxwidth 0.5\n' )
plt.write( 'set title "%s"\n' % sanitize_name( player ) )
n_kinds = len( histo )
plt.write( 'set xrange[-1:%d]\n' % n_kinds )
# set X tics, 45 degress rotated.
cmd = "set xtics ("
i = 0
items = []
for unit, cnt in histo.items() :
items.append( '"%s" %d' % ( unit, i ) )
i += 1
cmd += ", ".join( items )
cmd += ") rotate by 45 right\n"
plt.write( cmd )
# write values on the graph (labels)
#i = 0
#for unit, cnt in histo.items() :
# cmd = 'set label "%d" at %d,%d\n' % ( cnt, i, cnt+5 )
# plt.write( cmd )
# i += 1
# y range, manually.
max_cnt = 0
for unit, cnt in histo.items() :
max_cnt = max( max_cnt, cnt )
print( max_cnt )
plt.write( "set yrange [0:%f]\n" % ( 1.2*max_cnt ) )
# feed data
cmd = 'plot "-" using 0:1 with boxes linecolor %s, ' % color
cmd += "'-' using 0:1:1 with labels offset 0, 1\n"
plt.write( cmd )
for unit, cnt in histo.items() :
plt.write( str(cnt) + "\n" )
plt.write( 'e\n' )
for unit, cnt in histo.items() :
plt.write( str(cnt) + "\n" )
plt.write( 'e\n' )
color += 1
plt.close()
def plot( self, interval, font_fname=None ) : plt = Gnuplot() plt.open() cmds_at_second = self.group_commands_by_time() counts_at_second = self.count_player_actions( interval, cmds_at_second ) # actions counted for that second... ts = [ t for t in range( len( counts_at_second ) ) ] apmss = self.make_apmss( interval, counts_at_second ) #apmss[pid][t] = apm at time t, of player pid. plt.xlabel( "Time (s)" ) plt.ylabel( "APM" ) labels = [] for i in range( self.nplayers ) : player = self.kwr.players[i] if not player.is_player() : continue plt.plot( ts, apmss[ i ] ) name = sanitize_name( player, xor=True ) labels.append( name ) # touch up label of the curve # draw legend plt.legend( labels ) avg_apms = self.calc_avg_apm( cmds_at_second ) avg_apm_texts = self.avg_apm2txts( avg_apms ) # draw peak arrow. self.draw_peak_labels( plt, apmss ) # now the plot begins. plt.write( 'plot \\\n' ) # begin the plot command. color = 1 for pid in range( self.nplayers ) : player = self.kwr.players[pid] if not player.is_player() : continue #name = sanitize_name( player, xor=True ) #print( name, avg_apms[ pid ] ) plt.write( "%f title \"%s\" linecolor %d linetype 0 linewidth 2, \\\n" % ( avg_apms[ pid ], avg_apm_texts[pid], color ) ) color += 1 plt.data_plot_command() # plot apm(player, t) data. plt.close()
class Experiment:
#########################################################################
"contains all data for an experiment: results, sampling policy, etc."
#########################################################################
def __init__(self, p):
#####################################################################
"constructor"
#####################################################################
self.p = p
self.res = CResults(p.GetDimensions())
def seed(self, n):
#####################################################################
"seed random elements of the experiment"
#####################################################################
self.sp.Seed(n)
self.p.Seed(n + 1)
def add_clop(self):
#####################################################################
"add reg (and me) to this experiment"
#####################################################################
self.reg = CRegression(self.res,
CPFQuadratic(self.p.GetDimensions()))
self.me = CMERegressionMAPMax(self.reg)
def reset(self):
#####################################################################
"reset"
#####################################################################
self.res.Reset()
def max(self):
#####################################################################
"convert vectord to a list"
#####################################################################
v = vectord(self.p.GetDimensions())
if self.me.MaxParameter(v):
result = []
for i in range(v.size()):
result.append(v[i])
return result
else:
return None
def run(self, n, trace = False):
#####################################################################
"collect n samples"
#####################################################################
for i in range(n):
v = self.sp.NextSample(self.res.GetSamples())
r = self.p.GetOutcome(v)
if r == COutcome.Unknown:
return
self.res.AddSample(v, r)
if trace:
print "%6d" % i, r, v, self.max()
self.res.Refresh();
def gnuplot(self, reg):
#####################################################################
"plot with gnuplot"
#####################################################################
if not self.__dict__.has_key('gp'):
self.gp = Gnuplot()
CQLRIO.DumpSamples('samples.dat', self.reg)
if self.p.GetDimensions() == 1:
CQLRIO.Distrib(reg)
self.plot_to_file('distrib.dat', 100)
self.gp.send('load "clop.gpi"')
elif self.p.GetDimensions() == 2:
CQLRIO.Distrib(reg)
self.plot_to_file_2d('distrib.dat', 40)
self.gp.send('load "samples2d.gpi"')
def new_gnuplot(self, reg):
#####################################################################
"create a new gnuplot window"
#####################################################################
self.gp = Gnuplot()
self.gnuplot(reg)
def plot_to_file(self, filename, resolution):
#####################################################################
"write 1D model data to a file"
#####################################################################
f = open(filename, 'w')
for i in range(resolution + 1):
x = doubleArray(1)
x[0] = -1.0 + (2.0 * i) / resolution
f.write("%f %f %f\n" % (x[0],
self.p.GetProba(x),
self.p.GetStrength(x)))
def plot_to_file_2d(self, filename, resolution):
#####################################################################
"write 2D model data to a file"
#####################################################################
f = open(filename, 'w')
for i in range(resolution + 1):
x = -1.0 + (2.0 * i) / resolution
for j in range(resolution + 1):
y = -1.0 + (2.0 * j) / resolution
v = doubleArray(2)
v[0] = x
v[1] = y
f.write("%f %f %f %f\n" % (x,
y,
self.p.GetProba(v),
self.p.GetStrength(v)))
f.write('\n')
def experiment_setup(self):
#####################################################################
"get a CArtificialExperiment for CRepeatThreads"
#####################################################################
return CArtificialExperiment(self.p, self.sp, self.me, self.res)
def new_gnuplot(self, reg):
#####################################################################
"create a new gnuplot window"
#####################################################################
self.gp = Gnuplot()
self.gnuplot(reg)
def plot_orbit(self, plotfile, nsamp=100):
coeffs = self.coeffs[0].T
coords = self.coords / 1e3
t = self.time
time = np.linspace(self.t_start, self.t_stop, nsamp)
if self.centered:
time_cent = time - self.t_mean
poly = np.asarray([
np.polyval(coeffs[ii, :], time_cent) + mean_coords[ii]
for ii in range(3)
]).T
else:
poly = np.asarray(
[np.polyval(coeffs[ii, :], time) for ii in range(3)]).T
poly /= 1e3
gpt = Gnuplot()
gpt.output(plotfile, term="pngcairo", fontsize=8)
gpt.axis_format("x", "")
gpt.margins(bmargin=3.5)
gpt("set tics font ',8'")
gpt.multiplot(3,
portrait=True,
title="Fit of orbital vectors - "
"degree of polynom: {}".format(self.deg))
ylabels = ("X [km]", "Y [km]", "Z [km]")
for ii in range(3):
gpt.ylabel(ylabels[ii])
points = gpt.data(t,
coords[:, ii],
title="Orbital coordinates",
vith=linedef(point_type="empty_circle"))
fit = gpt.data(time,
poly[:, ii],
title="Fitted polynom",
vith="lines")
if ii == 2:
gpt("set format x")
gpt.xlabel("Time [s]")
gpt.plot(points, fit)
