Make this into more of a CLI thing. Also write some code

graphs.py

@@ -0,0 +1,156 @@
+import sys
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.colors as colors
+from utils import *
+
+order=16
+grid_size=128
+def line_chart(x,y ):
+    plt.plot(x, y)
+    plt.show()
+
+
+def graph_density(ip_list: str):
+    xarr = []
+    yarr = []
+    for ip in ip_list:
+        try:
+            if ":" in ip:
+                ip = ip_to_int(ip.split(":")[0])
+            else:
+                ip = ip_to_int(ip)
+        except ValueError as e:
+            print(e)
+            continue
+        x, y = d2xy(2**order, ip)
+        xarr.append(x)
+        yarr.append(y)
+
+
+    fig, ax = plt.subplots(figsize=(64, 64))
+
+    # Create density grid
+    H, xedges, yedges = np.histogram2d(xarr, yarr, bins=grid_size, range=[[0, 2**order], [0, 2**order]])
+
+    # Plot heatmap
+    im = ax.imshow(H.T, cmap='YlOrRd', extent=[0, 2**order, 0, 2**order], origin='lower',
+                   norm=colors.LogNorm(vmin=1, vmax=H.max()))
+    # Plot points
+    ax.scatter(xarr, yarr, color='blue', s=1, alpha=0.5)
+
+    ax.set_xlim(0, 2 ** order)
+    ax.set_ylim(0, 2 ** order)
+
+    # plt.colorbar(im, label='Number of IPs')
+    plt.axis('on')
+    plt.show()
+
+def graph_ports(ip_list: str):
+    count = np.zeros(65536)
+
+    for ip in ip_list:
+        if not ":" in ip:
+            continue
+        port = int(ip.split(":")[1])
+        count[port] += 1
+
+    line_chart(np.arange(0, 65536), count)
+
+
+def graph_nonstandard_ports(ip_list: str):
+    xarr = []
+    yarr = []
+    colorarr = []
+    for ip in ip_list:
+        try:
+            if ":" in ip:
+                split = ip.split(":")
+                ip = ip_to_int(split[0])
+                if split[1] == "25565":
+                    colorarr.append('red')
+                else:
+                    colorarr.append('blue')
+
+            else:
+                ip = ip_to_int(ip)
+                colorarr.append('green')
+        except ValueError as e:
+            print(e)
+            continue
+        x, y = d2xy(2**order, ip)
+        xarr.append(x)
+        yarr.append(y)
+
+
+    fig, ax = plt.subplots(figsize=(12, 12))
+
+    # Create density grid
+    H, xedges, yedges = np.histogram2d(xarr, yarr, bins=grid_size, range=[[0, 2**order], [0, 2**order]])
+
+    # Plot heatmap
+    im = ax.imshow(H.T, cmap='YlOrRd', extent=[0, 2**order, 0, 2**order], origin='lower',
+                   norm=colors.LogNorm(vmin=1, vmax=H.max()))
+    # Plot points
+    ax.scatter(xarr, yarr, color=colorarr, s=1, alpha=0.5)
+
+    ax.set_xlim(0, 2 ** order)
+    ax.set_ylim(0, 2 ** order)
+
+    # plt.colorbar(im, label='Number of IPs')
+    plt.axis('on')
+    plt.show()
+
+def random_choord(H):
+    weights = H.flatten()
+
+    weights = weights / np.sum(weights)
+    index = np.random.choice(grid_size*grid_size, p=weights)
+    x, y = divmod(index, grid_size)
+
+    x += np.random.random()
+    y += np.random.random()
+
+    x /= grid_size
+    y /= grid_size
+
+    x *= 2 ** order
+    y *= 2 ** order
+
+    return x, y
+
+
+def generate_random_ips(ip_list: str, count: int):
+    xarr = []
+    yarr = []
+    for ip in ip_list:
+        try:
+            if ":" in ip:
+                split = ip.split(":")
+                ip = ip_to_int(split[0])
+            else:
+                ip = ip_to_int(ip)
+        except ValueError as e:
+            print(e)
+            continue
+        x, y = d2xy(2**order, ip)
+        xarr.append(x)
+        yarr.append(y)
+
+    fig, ax = plt.subplots(figsize=(12, 12))
+
+    H, xedges, yedges = np.histogram2d(xarr, yarr, bins=grid_size, range=[[0, 2**order], [0, 2**order]])
+
+
+    # x /= grid_size
+    # y /= grid_size
+
+    # ips = []
+
+    print(count)
+
+    for i in range(count):
+        x, y = random_choord(H)
+        d = xy2d(2**order, x, y)
+        ip = ip_int_to_ip(d)
+        print(ip)