LoRA_are_lie_detectors/notebooks/100_dev_plotting.ipynb

In [1]:

import matplotlib.pyplot as plt
import numpy as np

from sklearn import datasets
from sklearn.gaussian_process import GaussianProcessClassifier
from sklearn.gaussian_process.kernels import RBF
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
from sklearn.svm import SVC

# plt.style.use("seaborn-v0_8")
# plt.style.use("fivethirtyeight")
import seaborn as sns
sns.set_theme('paper')

# plt.style.use("ggplot")
iris = datasets.load_iris(as_frame=True)

In [2]:

plt.style.available

Out [2]:

['Solarize_Light2',
 '_classic_test_patch',
 '_mpl-gallery',
 '_mpl-gallery-nogrid',
 'bmh',
 'classic',
 'dark_background',
 'fast',
 'fivethirtyeight',
 'ggplot',
 'grayscale',
 'seaborn-v0_8',
 'seaborn-v0_8-bright',
 'seaborn-v0_8-colorblind',
 'seaborn-v0_8-dark',
 'seaborn-v0_8-dark-palette',
 'seaborn-v0_8-darkgrid',
 'seaborn-v0_8-deep',
 'seaborn-v0_8-muted',
 'seaborn-v0_8-notebook',
 'seaborn-v0_8-paper',
 'seaborn-v0_8-pastel',
 'seaborn-v0_8-poster',
 'seaborn-v0_8-talk',
 'seaborn-v0_8-ticks',
 'seaborn-v0_8-white',
 'seaborn-v0_8-whitegrid',
 'tableau-colorblind10']

In [3]:

iris['data'].plot(title='iris')

Out [3]:

<Axes: title={'center': 'iris'}>

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