def main():
args = get_args(__file__)
labels = [
'N/A', 'Id. Física', 'Id. Historiográfica', 'Desconocido', 'Perdido'
]
colornames = ['light grey', 'medium green', 'denim blue', 'pale red']
df = pd.DataFrame(read_table(args.table))
df['ident'] = df.apply(categorize, axis=1)
data = df\
.drop_duplicates(['bid', 'lid'], keep='first')\
.pivot(index='bid', columns='lid', values='ident')\
.fillna(0)
#colors = sns.color_palette('hls', len(data))
#colors = sns.color_palette('husl', len(data))
#colors = sns.light_palette('red', len(data))
colors = sns.xkcd_palette(colornames)
f, ax = plt.subplots()
sns.heatmap(data,
ax=ax,
square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(set(df.year.values)), 'Libros')
legend(f, ax, labels, colors)
plotting(plt, args)
def plot(args):
df = pd.DataFrame(read_table(args.table))
configurer = configs[args.color_by]
data, labels, colors = configurer(df, args.color_by)
f, ax = plt.subplots()
fig = sns.heatmap(
data,
ax=ax,
#square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(set(df.year.values)), ylabel='Posición')
legend(f, ax, labels, colors)
if args.annotated and args.color_by in ['bid', 'year']:
df_by_bid = df.drop_duplicates('bid').set_index('bid')
texts = [
fig.text(
15,
bid,
df.loc[bid, 'short'],
fontsize=8,
) for bid, row in data.iterrows()
]
plotting(plt, args)
def run_experiment(board, next, win, gmme, gabe):
b = [0 for x in range(9)]
common.set_board(b, board)
common.print_board(b)
common.variables.explored = 0
wmm = student_code.minmax_tictactoe(b, next)
mme = common.variables.explored
common.variables.explored = 0
wabp = student_code.abprun_tictactoe(b, next)
abpe = common.variables.explored
print(common.legend(next) + " moves Result :")
res1 = "- MIN-MAX: " + common.legend(wmm) + " wins "
if (wmm != win):
res1 += "(" + bcolors.RED + "Fail" + bcolors.NORMAL + ")"
else:
res1 += "(" + bcolors.GREEN + "Pass" + bcolors.NORMAL + ")"
res1 += " boards explored " + str(mme)
if (mme != gmme):
res1 += "(" + bcolors.RED + "Fail" + bcolors.NORMAL + ")"
else:
res1 += "(" + bcolors.GREEN + "Pass" + bcolors.NORMAL + ")"
print(res1)
res1 = "- ALPHA-BETA: " + common.legend(wabp) + " wins "
if (wabp != win):
res1 += "(" + bcolors.RED + "Fail" + bcolors.NORMAL + ")"
else:
res1 += "(" + bcolors.GREEN + "Pass" + bcolors.NORMAL + ")"
res1 += " boards explored " + str(abpe)
if (abpe != gabe):
res1 += "(" + bcolors.RED + "Fail" + bcolors.NORMAL + ")"
else:
res1 += "(" + bcolors.GREEN + "Pass" + bcolors.NORMAL + ")"
print(res1)
print("")
print("")
return wmm == win and mme <= gmme and wabp == win and abpe <= gabe
def simFilters():
df = loadCSV('VS-filtering-34.csv', (
'AbsAlt', 'TerAlt', 'Alt', 'AltAhead', 'Err', 'VSP', 'VSF', 'MinVSF', 'aV', 'rV', 'dV', 'mdTWR', 'mTWR', 'hV'))
df = df[df.Alt > 3].reset_index()
addL(df)
L = df.L
a = df.TerAlt
aa = df.AltAhead
# t1 = 20
T = np.arange(0, df.shape[0] * dt, dt)
# er = np.sin(T*0.5)+np.random.normal(size=len(L))/10.0
ewa = vFilter(aa, EWA, ratio=0.1)
ewa2 = vFilter(aa, EWA2, ratio=0.9)
ax = plt.subplot()
ax1 = ax.twinx()
ax.plot(T, a, label='Alt')
ax1.plot(T, -aa, label='Rad')
ax1.plot(T, -ewa, label='EWA')
ax1.plot(T, -ewa2, label='EWA2')
# ax1.plot(L, g2, label='Gauss2')
legend()
plt.show()
def sim_Rotation():
def _plot(r, c, n, X, Y, aa, ylab):
plt.subplot(r, c, n)
plt.plot(X, Y, label=("V: AA=%.1f" % aa))
plt.xlabel("time (s)")
plt.ylabel(ylab)
MaxAngularA = np.arange(0.5, 30, 5);
start_error = 0.8 * np.pi
end_time = 10.0
def test(c, n, pid):
p = pid.kp;
d = pid.kd
for aa in MaxAngularA:
A = [start_error]
V = [0.0]
S = [0.0]
T = [0.0]
def plot(c, n, Y, ylab):
_plot(3, c, n, T, Y, aa, ylab)
pid.kp = p / aa
pid.kd = d / aa
while T[-1] < end_time:
S.append(pid.update(A[-1]))
V.append(V[-1] - S[-1] * aa * dt)
A.append(A[-1] + V[-1] * dt)
T.append(T[-1] + dt)
plot(c, n, np.fromiter(A, float) / np.pi * 180.0, 'Angle')
plot(c, c + n, V, 'Angular velocity')
plot(c, c * 2 + n, S, 'Steering')
test(2, 1, PID(6.0, 0, 10.0, -1, 1))
test(2, 2, PID(4.0, 0, 6.0, -1, 1))
legend()
plt.show()
def main():
args = get_args(__file__)
names = ['NA', 'LAT', 'ROM', 'FRAN']
labels = ['N/A', 'Latín', 'Romance', 'Francés']
colornames = ['light grey', 'pale red', 'medium green', 'denim blue']
df = pd.DataFrame(read_table(args.table))
data = categorical_by(df, 'lang', names)
colors = sns.xkcd_palette(colornames)
f, ax = plt.subplots()
sns.heatmap(data,
ax=ax,
square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(set(df.year.values)), 'Libros')
legend(f, ax, labels, colors)
plotting(plt, args)
def main():
args = get_args(__file__)
names = ['NA', 'REL', 'CRONIC', 'ANTI']
labels = ['N/A', 'Religioso', 'Crónicas y Leyes', 'Historia Antigua']
colornames = ['light grey', 'pale red', 'medium green', 'denim blue']
df = pd.DataFrame(read_table(args.table))
#df = pd.read_csv(args.table)
data = categorical_by(df, 'topic', names)
colors = sns.xkcd_palette(colornames)
f, ax = plt.subplots()
sns.heatmap(data,
ax=ax,
square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(df.year.values), ylabel='Posición')
legend(f, ax, labels, colors)
plotting(plt, args)