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💄 Fixes minor mistakes

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This commit is contained in:
Daniel Svitan 2024-12-27 16:13:25 +01:00
parent 6ddd476834
commit 96a6599cf9
2 changed files with 71 additions and 22 deletions
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26
analyze.py
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@ -119,10 +119,14 @@ def plot_violin(data, labels, Fs, ps, title):
axs[j, k].set_ylabel(grade_name_labels[index], fontweight="bold")
# q1-q3 lines
for vec in data[index]:
inds = np.arange(1, len(data[index]) + 1)
for ind, vec in enumerate(data[index]):
quartile1, median, quartile3 = np.percentile(vec, [25, 50, 75])
axs[j, k].vlines(inds, quartile1, quartile3, color="gray", linewidths=3)
if quartile1 == quartile3:
if quartile1 >= 0.1:
quartile1 -= 0.1
if quartile3 <= max(vec) - 0.1:
quartile3 += 0.1
axs[j, k].vlines(ind + 1, quartile1, quartile3, color="gray", linewidths=3)
axs[j, k].set_xticks(np.arange(1, len(labels) + 1), labels=labels)
axs[j, k].set_yticks(np.arange(1, 5.01, step))
@ -134,9 +138,9 @@ def plot_violin(data, labels, Fs, ps, title):
part.set_facecolor(colors[i % len(colors)])
part.set_edgecolor(edge_colors[i % len(edge_colors)])
F = round(Fs[index], 2)
p = round(ps[index], 4)
axs[j, k].text(0.01, 0.99, f"F-stat: {F:.2f}\np-val: {p:.4f}", ha="left", va="top",
F = Fs[index]
p = ps[index]
axs[j, k].text(0.01, 0.99, f"F-stat: {F:.4f}\np-val: {p:.4f}", ha="left", va="top",
transform=axs[j, k].transAxes,
fontweight="bold")
axs[j, k].text(0.99, 0.99,
@ -147,12 +151,12 @@ def plot_violin(data, labels, Fs, ps, title):
medians = list([np.median(a) for a in data[index]])
means = list([a.mean() for a in data[index]])
for l in range(len(medians)):
median = round(medians[l], 2)
mean = round(means[l], 2)
for l in range(len(data[index])):
median = medians[l]
mean = means[l]
# left - mean, right - median
axs[j, k].text(l + 1.13, median - 0.05, f"{median}", color="green")
axs[j, k].text(l + 0.90 - len(labels) * 0.065, mean - 0.05, f"{mean}", color="red")
axs[j, k].text(l + 1.13, median - 0.05, f"{median:.2f}", color="green")
axs[j, k].text(l + 0.90 - len(labels) * 0.065, mean - 0.05, f"{mean:.2f}", color="red")
fig.tight_layout()
if save != "":

67
analyze_absence.py
View File

@ -11,6 +11,9 @@ args = parser.parse_args()
graph = args.graph
save = args.save
colors = ["lightblue", "lightgreen", "lightcoral"]
edge_colors = ["blue", "green", "red"]
dataset = np.load("clean.npy")
print(f"dataset shape: {dataset.shape}; analyzing column 11 (absence)")
print("\tinteger value")
@ -55,29 +58,71 @@ for j in range(2):
step = 1 if index > 0 else 0.5
if index == 0:
axs[j, k].scatter(dataset[:, 11], dataset[:, 2])
x = dataset[:, 11] # absence
y = dataset[:, 2] # gpa
axs[j, k].scatter(x, y)
axs[j, k].set_xlabel("Počet vymeškaných hodín")
axs[j, k].set_ylabel(grade_name_labels[index])
# trendline
z = np.polyfit(x, y, 1)
p = np.poly1d(z)
axs[j, k].plot(x, p(x), color="gray")
else:
current = list([data[index][0][data[index][1] == i + 1] for i in range(5)]) # i wanna kms
axs[j, k].violinplot(list(filter(lambda x: len(x), current)), showmeans=True)
axs[j, k].set_xticks(np.arange(1, 6, 1), labels=["1", "2", "3", "4", "5"])
# data[index][0] = absence
# data[index][1] = grade
# data[index][0][where this specific grade] -> absences for that sepcific grade
# iterate 1 through 5 and plug into ^^
parts = axs[j, k].violinplot(list([x if len(x) else [0] for x in current]), showmeans=True,
showmedians=True)
axs[j, k].set_xticks(np.arange(1, 6), labels=["1", "2", "3", "4", "5"])
axs[j, k].set_xlabel(grade_name_labels[index])
axs[j, k].set_ylabel("Počet vymeškaných hodín")
# q1-q3 lines
for ind, vec in enumerate(current):
if len(vec) == 0:
continue
quartile1, median, quartile3 = np.percentile(vec, [25, 50, 75])
print(quartile1, median, quartile3)
axs[j, k].vlines(ind + 1, quartile1, quartile3, color="gray", linewidths=3)
parts["cmeans"].set_color("red")
parts["cmedians"].set_color("green")
for i, part in enumerate(parts["bodies"]):
part.set_facecolor(colors[i % len(colors)])
part.set_edgecolor(edge_colors[i % len(edge_colors)])
axs[j, k].set_title(grade_names[index])
tau = round(taus[index], 2)
p = round(ps[index], 4)
axs[j, k].text(0.01, 0.99, f"Tau τ: {tau:.2f}\np-val: {p:.4f}", ha="left", va="top", transform=axs[j, k].transAxes,
tau = taus[index]
p = ps[index]
axs[j, k].text(0.01, 0.99, f"Tau τ: {tau:.4f}\np-val: {p:.4f}", ha="left", va="top",
transform=axs[j, k].transAxes,
fontweight="bold")
if index:
by_grade = [data[index][0][data[index][1] == i + 1] for i in range(5)]
means = list([a.mean() for a in filter(lambda b: len(b), by_grade)])
for l in range(len(means)):
mean = round(means[l], 2)
axs[j, k].text(l + 1.02, mean + 5, f"{mean}")
axs[j, k].text(0.99, 0.99,
f"Na ľavo - priemer (červená)\nNa pravo - medián (zelená)\nSivá - medzi kvartilom 1 a 3",
ha="right",
va="top",
transform=axs[j, k].transAxes)
current = list([data[index][0][data[index][1] == i + 1] for i in range(5)]) # i wanna kms
medians = list([np.median(a) if len(a) else -1 for a in current])
means = list([a.mean() if len(a) else -1 for a in current])
for l in range(len(current)):
median = medians[l]
mean = means[l]
# left - mean, right - median
if median >= 0:
axs[j, k].text(l + 1.14, median - 5, f"{median:.2f}", color="green", ha="left")
if mean >= 0:
axs[j, k].text(l + 0.85, mean - 5, f"{mean:.2f}", color="red", ha="right")
fig.tight_layout()
if save != "":