update python scripts

tools/plot_cluster.py

@@ -1,25 +1,25 @@
 import numpy as np
-from mpl_toolkits.mplot3d import Axes3D 
+from mpl_toolkits.mplot3d import Axes3D
 import matplotlib.pyplot as plt
 import matplotlib.colors as colors
 import pandas as pd
 import argparse
 
 parser = argparse.ArgumentParser()
-parser.add_argument("--inputfile",type=str)
-parser.add_argument("--show",type=int,choices=[0,1],default=1)
-parser.add_argument("--depth",type=int,default=1)
-parser.add_argument("--save",type=str,default="")
+parser.add_argument("--inputfile", type=str)
+parser.add_argument("--show", type=int, choices=[0, 1], default=1)
+parser.add_argument("--depth", type=int, default=1)
+parser.add_argument("--save", type=str, default="")
 
 args = parser.parse_args()
 inputfile = args.inputfile
 depth = args.depth
 
 # First Data
-data = (pd.read_csv(inputfile,header=None)).T
+data = (pd.read_csv(inputfile, header=None)).T
 header = data.iloc[0]
 print(header)
-data =data[1:]
+data = data[1:]
 data.columns = header
 
 
@@ -31,14 +31,18 @@
 fig = plt.figure()
 ax = fig.add_subplot(111, projection='3d')
 
-ax.scatter(data["x_0"].tolist(), data["x_1"].tolist(), data["x_2"].tolist(),c=colormap(norm(data[str(depth)].tolist())), marker='o')
-
+if "x_2" in data.columns:
+    ax.scatter(data["x_0"].tolist(), data["x_1"].tolist(), data["x_2"].tolist(
+    ), c=colormap(norm(data[str(depth)].tolist())), marker='o')
+else:
+    ax.scatter(data["x_0"].tolist(), data["x_1"].tolist(),
+               c=colormap(norm(data[str(depth)].tolist())), marker='o')
 
 # Output
 if args.show:
     plt.show()
 
 
-if args.save!="":
-    fig.savefig(args.save,bbox_inches = 'tight',
-    pad_inches = 0)
+if args.save != "":
+    fig.savefig(args.save, bbox_inches='tight',
+                pad_inches=0)

tools/plot_hmatrix.py

@@ -6,69 +6,78 @@
 import argparse
 
 parser = argparse.ArgumentParser()
-parser.add_argument("--inputfile",type=str)
-parser.add_argument("--sizeWorld",type=int,default=1)
-parser.add_argument("--show",type=int,choices=[0,1],default=1)
-parser.add_argument("--save",type=str,default="")
+parser.add_argument("--inputfile", type=str)
+parser.add_argument("--show", type=int, choices=[0, 1], default=1)
+parser.add_argument("--save", type=str, default="")
 
 args = parser.parse_args()
 inputfile = args.inputfile
-sizeWorld = args.sizeWorld
 
 # First Data
-size = pd.read_csv(inputfile+"_0.csv",nrows=1,header=None) 
+size = pd.read_csv(inputfile, nrows=1, header=None)
 nr = size.iloc[0][0]
 nc = size.iloc[0][1]
-matrix = np.zeros((nr,nc))
+matrix = np.zeros((nr, nc))
 
 # Figure
-fig, axes = plt.subplots(1,1)
+fig, axes = plt.subplots(1, 1)
 axes.xaxis.tick_top()
 plt.imshow(matrix)
 
 # Issue: there a shift of one pixel along the y-axis...
-shift = axes.transData.transform([(0,0), (1,1)])
-shift = shift[1,1] - shift[0,1]  # 1 unit in display coords
+shift = axes.transData.transform([(0, 0), (1, 1)])
+shift = shift[1, 1] - shift[0, 1]  # 1 unit in display coords
 shift = 0
 # 1/shift  # 1 pixel in display coords
 
 # Loop
-for i in range(0,sizeWorld):
-    print(i)
-    data = pd.read_csv(inputfile+"_"+str(i)+".csv",skiprows=1,header=None) 
-
-    for index, row in data.iterrows():
-        matrix[np.ix_(range(row[0],row[0]+row[1]),range(row[2],row[2]+row[3]))]=row[4]
-        rect = patches.Rectangle((row[2]-0.5,row[0]-0.5+shift),row[3],row[1],linewidth=0.75,edgecolor='k',facecolor='none')
-        axes.add_patch(rect)
-        if row[4]>=0 and row[3]/float(nc)>0.05 and row[1]/float(nc)>0.05:
-            axes.annotate(row[4],(row[2]+row[3]/2.,row[0]+row[1]/2.),color="white",size=10, va='center', ha='center')
-
-
-
+data = pd.read_csv(inputfile, skiprows=1, header=None)
+for index, row in data.iterrows():
+    matrix[
+        np.ix_(range(row[0], row[0] + row[1]), range(row[2], row[2] + row[3]))
+    ] = row[4]
+    rect = patches.Rectangle(
+        (row[2] - 0.5, row[0] - 0.5 + shift),
+        row[3],
+        row[1],
+        linewidth=0.75,
+        edgecolor="k",
+        facecolor="none",
+    )
+    axes.add_patch(rect)
+    if row[4] >= 0 and row[3] / float(nc) > 0.05 and row[1] / float(nc) > 0.05:
+        axes.annotate(
+            row[4],
+            (row[2] + row[3] / 2.0, row[0] + row[1] / 2.0),
+            color="white",
+            size=10,
+            va="center",
+            ha="center",
+        )
 
 
 # Colormap
 def truncate_colormap(cmap, minval=0.0, maxval=1.0, n=100):
     new_cmap = colors.LinearSegmentedColormap.from_list(
-        'trunc({n},{a:.2f},{b:.2f})'.format(n=cmap.name, a=minval, b=maxval),
-        cmap(np.linspace(minval, maxval, n)))
+        "trunc({n},{a:.2f},{b:.2f})".format(n=cmap.name, a=minval, b=maxval),
+        cmap(np.linspace(minval, maxval, n)),
+    )
     return new_cmap
 
-cmap = plt.get_cmap('YlGn')
+
+cmap = plt.get_cmap("YlGn")
 new_cmap = truncate_colormap(cmap, 0.4, 1)
 
 
 # Plot
-matrix =np.ma.masked_where(0>matrix,matrix)
+matrix = np.ma.masked_where(0 > matrix, matrix)
 new_cmap.set_bad(color="red")
-plt.imshow(matrix,cmap=new_cmap,vmin=0, vmax=10)
+plt.imshow(matrix, cmap=new_cmap, vmin=0, vmax=10)
 
 # Output
 if args.show:
     plt.show()
 
 
-if args.save!="":
-    fig.savefig(args.save,bbox_inches = 'tight',
-    pad_inches = 0)
+if args.save != "":
+    fig.savefig(args.save, bbox_inches="tight", pad_inches=0)