diff --git a/a.png b/a.png
index e8c3462..68429aa 100644
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diff --git a/b.png b/b.png
index dea5eb6..1f8e4d5 100644
Binary files a/b.png and b/b.png differ
diff --git a/xls2ternary.py b/xls2ternary.py
index 983f2e3..3846277 100755
--- a/xls2ternary.py
+++ b/xls2ternary.py
@@ -30,9 +30,9 @@ par.add_argument('-si', '--sheet_index', default=0, type=int,
 par.add_argument('-hl', '--header', default=0, type=int,
                  help="header line number in excel file[0]")
 par.add_argument('-m', '--mol_col', nargs=3, default=[0, 1, 2], type=int,
-                 help="row number for mol percent [0 1 2]")
+                 help="col number for mol percent [0 1 2]")
 par.add_argument('-p', '--GC_col', default=3, type=int,
-                 help="row number for G/C ratio [3]")
+                 help="col number for G/C ratio [3]")
 par.add_argument('-xmin', '--xmin', default=0, type=float,
                  help="x minimum [0]")
 par.add_argument('-o', '--outfile', default=None,
@@ -168,7 +168,7 @@ def ScatterPlot(header, data, xlabel, val, psum=100, order=[1, 2, 0]):
         zi = griddata((x, y), val, (xi[None, :], yi[:, None]),
                       method=args.interp)
         zi[zi == 0] = 1e-8
-        alpha = 0.8
+        alpha = 0.7
         level = np.linspace(0, 1, 20)
         plt.contourf(xi, yi, zi, level, cmap=cmap, alpha=alpha)
         # 内挿して得られる最大ポイントの表示
@@ -200,7 +200,7 @@ def ScatterPlot(header, data, xlabel, val, psum=100, order=[1, 2, 0]):
     if args.nocolorbar is False:
         cbar = fig.colorbar(cs, fraction=0.035, alpha=1.0)
         cbar.ax.set_ylabel('glass vol%', fontsize=14)
-        cbar.ax.set_yticklabels(['%.0f' % (200 * x)
+        cbar.ax.set_yticklabels(['%.0f' % (100 * x)
                                  for x in bounds], fontsize=12)
     if args.nolegend is False:
         ax.legend(loc="best")
@@ -210,9 +210,10 @@ def ScatterPlot(header, data, xlabel, val, psum=100, order=[1, 2, 0]):
 # xlsデータの読み込み
 df = pd.read_excel(args.xlsfile, skiprows=args.header)
 df = df.dropna()
-# mol_data = mol_data/18.67*100
 mol_header = df.columns
 mol_data = df.iloc[:, args.mol_col].to_numpy()
+# mol_data = mol_data/18.67*100
+
 val = df.iloc[:, args.GC_col].to_numpy()
 print("Number of data : ", df.shape)
 print("Plot header [col]: ", mol_header[args.mol_col].to_list(), args.mol_col)