Replace amplicon_pipeline.py

amplicon_pipeline.py

@@ -16,6 +16,7 @@ import time
 import scipy
 import pandas as pd
 import matplotlib.pyplot as plt
+import matplotlib
 import seaborn as sns
 import scipy.stats
 from ete3 import NCBITaxa
@@ -600,7 +601,6 @@ def beta_diversity_plot(normalized_df, argOptions):
             for s in samples:
                 if c.startswith(s):
                     meta_df.loc[c, ['Sample']] = s
-
         fig = pcoa_results.plot(df=meta_df, column='Sample', cmap='Set1', s=50)
         plt.savefig('{}beta_diversity_pcoa.pdf'.format(argOptions['outputDir']))
         plt.close()
@@ -620,7 +620,7 @@ def beta_diversity_plot(normalized_df, argOptions):
         for target, color in zip(targets, sns.color_palette("husl", len(targets))):
             indicesToKeep = finalDf['Sample'] == target
             ax.scatter(finalDf.loc[indicesToKeep, 'principal component 1'],
-                       finalDf.loc[indicesToKeep, 'principal component 2'], c=color, s=50)
+                       finalDf.loc[indicesToKeep, 'principal component 2'], c=np.array([color]), s=50)
             ax.legend(targets)
             ax.grid()
         plt.savefig('{}beta_div_pca.pdf'.format(argOptions['outputDir']))
@@ -636,7 +636,7 @@ def beta_diversity_plot(normalized_df, argOptions):
         for target, color in zip(targets, sns.color_palette("husl", len(targets))):
             indicesToKeep = finalDf[finalDf['Sample'] == target]
             for i in indicesToKeep.index:
-                ax.scatter(X_r[i, 0], X_r[i, 1], c=color, s=50)
+                ax.scatter(X_r[i, 0], X_r[i, 1], c=np.array([color]), s=50)
             ax.legend(targets)
             ax.grid()
         plt.savefig('{}beta_diversity_mds.pdf'.format(argOptions['outputDir']))