tutorial 4

README.md

@@ -9,3 +9,5 @@ I am planning to share how to make publication-quality figures in python, I will
     * Link: https://frankligy.medium.com/making-publication-quality-figures-in-python-part-ii-line-plot-legends-colors-4430a5891706
 3. Tutorial III (boxplot, scatter plot, heatmap, colormap, barplot, histogram)
     * Link: https://frankligy.medium.com/making-publication-quality-figures-in-python-part-iii-box-plot-bar-plot-scatter-plot-407fa457449
+4. Tutorial IV (Violin plot, dendrogram)
+    * Link: https://towardsdatascience.com/making-publication-quality-figures-in-python-part-iv-violin-plot-and-dendrogram-ed0bb8b23ddd

tutorial_4_violin_dendrogram.py

@@ -0,0 +1,78 @@
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+from matplotlib.colors import ListedColormap
+
+mpl.rcParams['pdf.fonttype'] = 42
+mpl.rcParams['ps.fonttype'] = 42
+mpl.rcParams['font.family'] = 'Arial'
+
+import numpy as np
+
+np.random.seed(42)
+data1 = np.random.randn(100)
+data2 = np.random.randn(100)
+data3 = np.random.randn(100)
+
+dataset = [data1,data2,data3]
+positions = [1,5,7]
+fig,ax = plt.subplots()
+vp = ax.violinplot(dataset=dataset,positions=[1,5,7])
+
+for body in vp['bodies']:
+    body.set_facecolor('red')
+    body.set_edgecolor('black')
+    body.set_alpha(1)
+vp['cmaxes'].set_color('black')
+vp['cmins'].set_color('black')
+vp['cbars'].set_color('black')
+
+tmp = [np.percentile(data,[25,50,75]) for data in dataset]
+
+def get_whisker(tmp,dataset):
+    whisker = []
+    for quantile,data in zip(tmp,dataset):
+        data = np.array(data)
+        q1 = quantile[0]
+        median = quantile[1]
+        q3 = quantile[2]
+        iqr = q3 - q1
+        upper = q3 + 1.5 * iqr
+        upper = np.clip(upper,q3,data.max())
+        lower = q1 - 1.5 * iqr
+        lower = np.clip(lower,data.min(),q1)
+        whisker.append((upper,lower))
+    return whisker
+
+whisker = get_whisker(tmp,dataset)
+ax.scatter(positions,[quantile[1] for quantile in tmp],marker='o',color='white',s=30,zorder=3)
+ax.vlines(positions,[quantile[0] for quantile in tmp],[quantile[2] for quantile in tmp],color='black',linestyle='-',lw=5)
+ax.vlines(positions,[bound[0] for bound in whisker],[bound[1] for bound in whisker],color='black',linestyle='-',lw=4)
+
+
+sample1 = np.random.randn(100)
+sample2 = np.random.randn(100)
+sample3 = np.random.randn(100)
+sample4 = np.random.randn(100)
+sample5 = np.random.randn(100)
+sample6 = np.random.randn(100)
+
+mat = np.row_stack([sample1,sample2,sample3,sample4,sample5,sample6])
+
+from scipy.spatial.distance import pdist,squareform
+dense_distance = pdist(mat,'euclidean')
+square_distance = squareform(dense_distance)
+
+from scipy.cluster.hierarchy import linkage,dendrogram
+linkage_matrix = linkage(dense_distance,method='ward',metric='euclidean')
+fig,ax = plt.subplots()
+dendrogram(linkage_matrix,ax=ax)
+
+
+
+
+
+
+
+
+
+