--- title: utils.dedimensions keywords: fastai sidebar: home_sidebar nb_path: "00_utils_rd.ipynb" ---
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn import datasets
iris = datasets.load_iris()
X = iris.data
y = iris.target
def scatter_plots_for_reduce_dimensional(df,x,y,output=None,hue=None,size=None,style=None,xlabel=None,ylabel=None,title=None):
fig, ax = plt.subplots()
ax = sns.scatterplot(x=x, y=y, data=df,hue=hue,size=size,style=style)
if xlabel is not None:
ax.set_xlabel(xlabel)
if ylabel is not None:
ax.set_ylabel(ylabel)
if title is not None:
ax.set_title(title)
if output is not None:
fig.savefig(output,dpi=300)
for i in [PCA,MDS,TSNE,UMAP,PHATE]:
rd_data,reducer = reduce_dimensional(X,i,3)
rd_data['target'] = y
scatter_plots_for_reduce_dimensional(rd_data,getattr(i,'__name__')+'1',
getattr(i,'__name__')+'2',hue='target')
pd.DataFrame(X,columns=['f1','f2','f3','f4']).to_csv('tests/test.csv')
pd.DataFrame(y,columns=['targets']).to_csv('tests/test_anno.csv')
!bash build.bash