Note
Click here to download the full example code
Time-Series SimsΒΆ
Time-series simulations are found in hyppo.tools
. Here, we visualize
what these
simulations look like.
![Time-Series Simulations, Independent, Cross Correlation, Nonlinear](../_images/sphx_glr_time_series_sim_001.png)
import matplotlib.pyplot as plt
import seaborn as sns
from hyppo.tools import cross_corr_ar, indep_ar, nonlinear_process
# make plots look pretty
sns.set(color_codes=True, style="white", context="talk", font_scale=2)
PALETTE = sns.color_palette("Greys", n_colors=9)
sns.set_palette(PALETTE[2::2])
# constants
N = 100
# dictionary mapping of simulations
SIMULATIONS = [
(indep_ar, "Independent"),
(cross_corr_ar, "Cross Correlation"),
(nonlinear_process, "Nonlinear"),
]
# make a function to plot the guassian simulations
def plot_time_series_sims():
"""Plot simulations"""
fig, ax = plt.subplots(nrows=2, ncols=3, figsize=(17, 12))
plt.suptitle("Time-Series Simulations", y=0.95, va="baseline")
for i, row in enumerate(ax):
for j, col in enumerate(row):
sim, sim_title = SIMULATIONS[j]
# time-series simulation
x, y = sim(N)
n = x.shape[0]
t = range(1, n + 1)
if i == 0:
col.plot(t, x, label="X_t")
col.plot(t, y, label="Y_t")
else:
col.scatter(x, y)
# make the plot look pretty
col.set_yticks([])
if j == 0:
col.set_yticks([-5, 0, 5])
if i == 1:
col.set_xticks([-3, 0, 3])
col.set_xlim(-3, 3)
if i == 0:
col.set_title("{}".format(sim_title))
col.set_xticks([0, 100])
col.set_ylim(-5, 5)
plt.subplots_adjust(hspace=0.5)
fig.text(0.5, 0.02, r"$X_t$", ha="center")
fig.text(0.5, 0.5, r"$t$", ha="center")
fig.text(0.05, 0.25, r"$Y_t$", va="center", rotation="vertical")
# run the created function for the time-series simulations
plot_time_series_sims()
Total running time of the script: ( 0 minutes 0.259 seconds)