Update README.md

PCA for 2DIsing model/README.md

@@ -1,15 +1,11 @@
 Discovering phase transition in 2DIsing model with unsupervised learning method 
 
-Requirements: scikit-learn, numpy, numba 
+Requirements: scikit-learn, numpy, numba and Python 
 
 Quick start:
 
-1. python MC_sample.py to generate the datasets.
-
-   Datasets contain three parts： 20_L, 40_L and 80_L, in which "L" represent the size of 2D square Ising model.    
-
-   For each part, we generate the datas in the range of temperature from 1 to 3.0. 
-
-   For each temperature point, we generate 100 datas.
+1. python MC_sample.py to generate the datasets, which includes two parts:
+   (1). 20_L, 40_L and 80_L, in which "L" represent the size of 2D square Ising model;
+   (2). For each part, we generate the datas in the range of temperature from 1 to 3.0, with each temperature containing 100 data points.
 
-2. python sklearn_pca.py.
+3. python sklearn_pca.py.