zhaozhengcoder
diff --git a/‎序列预测/PCA去趋势化/__pycache__/pca.cpython-35.pyc
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diff --git a/‎序列预测/PCA去趋势化/dev2/__pycache__/pca.cpython-36.pyc
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diff --git a/‎序列预测/PCA去趋势化/show.py
Lines changed: 48 additions & 3 deletions b/‎序列预测/PCA去趋势化/show.py
Lines changed: 48 additions & 3 deletions
diff --git a/‎序列预测/PCA去趋势化/加上刻度—重新画的图-主要成分.png
53.6 KB b/‎序列预测/PCA去趋势化/加上刻度—重新画的图-主要成分.png
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diff --git a/‎序列预测/PCA去趋势化/加上刻度—重新画的图-偏差数据.png
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diff --git a/‎序列预测/PCA去趋势化/加上刻度—重新画的图-原始数据.png
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diff --git a/‎序列预测/PCA去趋势化/加上刻度—重新画的图-原始数据2.png
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@@ -33,6 +33,47 @@ def show_index(arr,index):
     plt.show()
     plt.close()
 
+#给横坐标由原来的0~480，变成现在的0~24，改变横坐标的比例
+def show_index_ticks(arr,index,pic_color,pic_label):
+    plt.xlabel("Index of time")
+    plt.ylabel("Traffic volume")
+    #图例
+    plt.plot(arr[index],color=pic_color,label=pic_label)
+    plt.legend(loc='upper right')
+    #改变x轴的刻度
+    x_kedu=[0,4,8,12,16,20,24]
+    orig_ticks = [i*20 for i in x_kedu]
+    new_ticks = x_kedu
+    plt.xticks(orig_ticks,new_ticks)
+    #改变y轴的刻度
+    y_kedu=[0,5,10,15,20]
+    y_orig_ticks = y_kedu
+    y_new_ticks =y_kedu
+    plt.yticks(y_orig_ticks,y_new_ticks)
+    plt.grid()
+    plt.show()
+
+
+def show_index_ticks_residual(arr,index,pic_color,pic_label):
+    plt.xlabel("Time (hour)")
+    plt.ylabel("Traffic volume")
+    #图例
+    plt.plot(arr[index],color=pic_color,label=pic_label)
+    plt.legend(loc='upper right')
+    #改变x轴的刻度
+    x_kedu=[0,4,8,12,16,20,24]
+    orig_ticks = [i*20 for i in x_kedu]
+    new_ticks = x_kedu
+    plt.xticks(orig_ticks,new_ticks)
+    #residual 的 y轴的刻度
+    y_kedu=[-2,-1,0,1,2]
+    y_orig_ticks = y_kedu
+    y_new_ticks =y_kedu
+    plt.yticks(y_orig_ticks,y_new_ticks)
+    #加上网格
+    plt.grid()
+    plt.show()
+
 if __name__=="__main__":
     arr = myload("dump_arr_9-13.txt")
     main_x = myload("dump_main_x_9-13.txt")
@@ -41,6 +82,10 @@ def show_index(arr,index):
     #show1(main_x)
     #show1(rest_x)
     #show2(main_x,rest_x)
-    show_index(arr,0)
-    show_index(main_x,0)
-    show_index(rest_x,0)
+    #show_index(arr,0)
+    #show_index(main_x,0)
+    #show_index(rest_x,0)
+
+    show_index_ticks(arr,3,"black","traffic data flow")
+    show_index_ticks(main_x,3,"red","main trend data")
+    show_index_ticks_residual(rest_x,3,"blue","residual data")