import torch

import numpy as np

import matplotlib.pyplot as plt

import seaborn as sns

import anndata

import pandas as pd

from gpsa import VariationalGPSA

from gpsa import matern12_kernel, rbf_kernel

from gpsa.plotting import callback_twod

import sys

sys.path.append("../../data")

from simulated.generate_twod_data import generate_twod_data

import matplotlib

font = {"size": 30}

matplotlib.rc("font", **font)

matplotlib.rcParams["text.usetex"] = True

device = "cuda" if torch.cuda.is_available() else "cpu"

results_df = pd.read_csv("out/error_experiment_large_numspots.csv", index_col=0)

# results_df = results_df[results_df.value < 0.8]

# import ipdb; ipdb.set_trace()

plt.figure(figsize=(7, 6))

sns.boxplot(data=results_df, x="method", y="value")

plt.xlabel("")

plt.ylabel("Error")

plt.tight_layout()

plt.savefig("./out/error_experiment_large_numspots.png")

plt.show()

plt.close()

import ipdb

ipdb.set_trace()