code: def mesh(self, offset=0, height=2.5, wf_data=None):
      if wf_data is not None:
          wf_data = struct.unpack(str(2 * self.CHUNK) + "B", wf_data)
          wf_data = np.array(wf_data, dtype="b")[::2] + 128
          wf_data = np.array(wf_data, dtype="int32") - 128
          wf_data = wf_data * 0.04
          wf_data = wf_data.reshape(
              (len(self.xpoints), len(self.ypoints))
          )
      else:
          wf_data = np.array([1] * 1024)
          wf_data = wf_data.reshape(
              (len(self.xpoints), len(self.ypoints))
          )
  
      faces = []
      colors = []
      verts = np.array(
          [
              [
                  x,
                  y,
                  wf_data[xid][yid]
                  * self.noise.noise2d(
                      x=xid / 5 + offset, y=yid / 5 + offset
                  ),
              ]
              for xid, x in enumerate(self.xpoints)
              for yid, y in enumerate(self.ypoints)
          ],
          dtype=np.float32,
      )
  
      for yid in range(self.nfaces - 1):
          yoff = yid * self.nfaces
          for xid in range(self.nfaces - 1):
              faces.append(
                  [
                      xid + yoff,
                      xid + yoff + self.nfaces,
                      xid + yoff + self.nfaces + 1,
                  ]
              )
              faces.append(
                  [
                      xid + yoff,
                      xid + yoff + 1,
                      xid + yoff + self.nfaces + 1,
                  ]
              )
              colors.append(
                  [
                      xid / self.nfaces,
                      1 - xid / self.nfaces,
                      yid / self.nfaces,
                      0.7,
                  ]
              )
              colors.append(
                  [
                      xid / self.nfaces,
                      1 - xid / self.nfaces,
                      yid / self.nfaces,
                      0.8,
                  ]
              )
  
      faces = np.array(faces, dtype=np.uint32)
      colors = np.array(colors, dtype=np.float32)
  
      return verts, faces, colors
  
file_path: audio-spectrum-analyzer/terrain_audio.py
imports: import numpy
  from opensimplex import OpenSimplex
  import pyqtgraph.opengl
  from pyqtgraph.Qt import QtCore, QtGui
  import struct
  import pyaudio
  import sys
label_desc: Use image node_id 2 for calling the Terrain obj's underlying member method code with example usage: obj.mesh(offset, height, wf_data) and returns: verts,  faces,  colors