fmda/moisture_rnn_test.py

   1 import numpy as np
   2 from moisture_rnn import staircase_spatial
   3
   4
   5 # Test Function Notes:
   6 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
   7
   8 # Testing for a single Functions:
   9 # 1. Helper function to create data objects, eg X & y
  10 # 2. Function to print X & y in human readable way
  11 # 3. Call target function eg staircase_spatial to create XX, yy, n_seqs
  12 # 4. Print previous output in human readable way (as similar to images in Overleaf FMDA w Recurrent Notebooks - Example 4)
  13 # 5. Compare to expectations* (eg see Overleaf FMDA w Recurrent Notebooks - Example 4) human or code
  14
  15
  16
  17 def staircase_spatial_test(total_time_steps, features, batch_size, timesteps, n_locs = 10):
  18     """
  19     Parameters:
  20     -----------
  21
  22
  23
  24     Run staircase_spatial with:
  25     -----------
  26     X : list of numpy arrays of length n_locs
  27         A list where each element is a numpy array containing features for a specific location. The shape of each array is `(total_time_steps, features)`.
  28
  29     y : list of numpy arrays of length n_locs
  30         A list where each element is a numpy array containing the target values for a specific location. The shape of each array is `(total_time_steps,)`.
  31
  32
  33     Returns:
  34     -----------
  35
  36     """
  37
  38
  39     #
  40     print("staircase_spatial_test inputs")
  41     print(f"total_time_steps: {total_time_steps}")
  42     print(f"features: {features}")
  43     print(f"batch_size: {batch_size}")
  44     print(f"timesteps: {timesteps}")
  45     print(f"n_locs: {n_locs}")
  46
  47
  48     # Create test arrays
  49     X = []
  50     y = []
  51
  52     for i in range(0, n_locs):
  53         Xi = np.arange(i, i+total_time_steps)
  54         yi = np.arange(i, i+total_time_steps)
  55         X.append(Xi)
  56         y.append(yi)
  57
  58
  59     print(X)
  60     print(y)
  61
  62
  63
  64
  65