t, p = stats.ttest_rel(exp2_econ_part, exp3_econ_part)
print('Economic decision making:\nt=%s, p=%s ' % (t, p))
# -----------------
# 3. Prepare figure
# -----------------
# Figure properties
fig_ratio = 0.65
fig_witdh = 15
linewidth = 1
markersize = 2
fontsize = 6
# Create figure
f = plt.figure(figsize=cm2inch(fig_witdh, fig_ratio * fig_witdh))
# Create plot grid
gs0 = gridspec.GridSpec(18, 16, left=0.075, right=0.99, top=0.95, bottom=0.08, hspace=100, wspace=10)
# ----------------------------
# 4. Plot task trial schematic
# ----------------------------
# Create subplot grid and axis
gs00 = gridspec.GridSpecFromSubplotSpec(1, 8, subplot_spec=gs0[0:7, 0:8], wspace=0)
ax_0 = plt.Subplot(f, gs00[:])
f.add_subplot(ax_0)
# Picture paths
path = ['gb_figures/patches.png', 'gb_figures/fix_cross.png', 'gb_figures/fractals.png',
# Figure properties
low_alpha = 0.3
medium_alpha = 0.6
high_alpha = 1
blue_1 = '#46b3e6'
blue_2 = '#4d80e4'
blue_3 = '#2e279d'
green_1 = '#94ed88'
green_2 = '#52d681'
green_3 = '#00ad7c'
fig_ratio = 0.65
fig_witdh = 15
fig_heigth = 10
# Create figure
f = plt.figure(figsize=cm2inch(fig_witdh, fig_heigth))
# Create plot grid
gs = gridspec.GridSpec(nrows=4,
ncols=6,
left=0.1,
right=0.99,
wspace=1.5,
top=0.95,
bottom=0.1,
hspace=0.5)
# -----------------------------
# 3. Plot posterior predictions
# -----------------------------
for i in range(0, len(p_hat.o)):
# Set current agent variables
agent.c_t = np.asarray(C_t[t]) # coefficient
agent.o_t = p_hat.o[
i] # observation todo: adjust for sampling-based validation
# p_{t-1}(\mu|r_t = 0, o_t) analytical result
agent.learn(p_hat.r_e[r])
pdf_mu_giv_r_t_o_t[:, i, r] = np.polyval(agent.c_t, p_hat.mu)
# Initialize figure
# -----------------
fig_width = 15
fig_height = 20
f = plt.figure(figsize=cm2inch(fig_width, fig_height))
ax_0 = plt.subplot2grid((4, 4), (0, 0), colspan=2)
ax_1 = plt.subplot2grid((4, 4), (0, 2))
ax_2 = plt.subplot2grid((4, 4), (0, 3))
ax_3 = plt.subplot2grid((4, 4), (1, 0), colspan=2)
ax_4 = plt.subplot2grid((4, 4), (1, 2), colspan=2)
ax_5 = plt.subplot2grid((4, 4), (2, 0), colspan=2)
ax_6 = plt.subplot2grid((4, 4), (2, 2), colspan=2)
ax_7 = plt.subplot2grid((4, 4), (3, 0))
ax_8 = plt.subplot2grid((4, 4), (3, 1))
ax_9 = plt.subplot2grid((4, 4), (3, 2))
ax_10 = plt.subplot2grid((4, 4), (3, 3))
barcolor = "slategray"
# p_t(\mu)
