Adopt unitest for main_visulize_postprocess.py

test/run_pytest.sh

@@ -2,7 +2,7 @@
 
 # Name of virtual environment 
 #VIRT_ENV_NAME="vp_new_structure"
-VIRT_ENV_NAME="juwels_env"
+VIRT_ENV_NAME="env_hdfml"
 
 if [ -z ${VIRTUAL_ENV} ]; then
    if [[ -f ../video_prediction_tools/${VIRT_ENV_NAME}/bin/activate ]]; then
@@ -24,7 +24,7 @@ fi
 source ../video_prediction_tools/env_setup/modules_train.sh
 ##Test for preprocess moving mnist
 #python -m pytest test_prepare_moving_mnist_data.py
-python -m pytest test_train_moving_mnist_data.py 
+#python -m pytest test_train_moving_mnist_data.py 
 #Test for process step2
 #python -m pytest test_data_preprocess_step2.py
 #python -m pytest test_era5_data.py
@@ -33,5 +33,5 @@ python -m pytest test_train_moving_mnist_data.py
 #rm /p/project/deepacf/deeprain/video_prediction_shared_folder/models/test/* 
 #python -m pytest test_train_model_era5.py
 #python -m pytest test_vanilla_vae_model.py
-#python -m pytest test_visualize_postprocess.py
+python -m pytest test_visualize_postprocess.py
 #python -m pytest test_meta_postprocess.py

test/test_visualize_postprocess.py

@@ -7,14 +7,13 @@ from main_scripts.main_visualize_postprocess import *
 import pytest
 import numpy as np
 import datetime
-
+from netCDF4 import Dataset, date2num
 
 ########Test case 1################
 results_dir = "/p/project/deepacf/deeprain/video_prediction_shared_folder/results/era5-Y2007-2019M01to12-92x56-3840N0000E-2t_tcc_t_850/savp/20210324T120926_ji4_savp_cv12" 
 checkpoint = "/p/project/deepacf/deeprain/video_prediction_shared_folder/models/era5-Y2007-2019M01to12-92x56-3840N0000E-2t_tcc_t_850/savp/20210324T120926_ji4_savp_cv12" 
 mode = "test"
 batch_size = 2
-num_samples = 16
 num_stochastic_samples = 2
 gpu_mem_frac = 0.5
 seed = 12345
@@ -32,15 +31,7 @@ args = MyClass(results_dir)
 @pytest.fixture(scope="module")
 def vis_case1():
     return Postprocess(results_dir=results_dir,checkpoint=checkpoint,
-                       mode=mode,batch_size=batch_size, num_samples=num_samples,
-                       num_stochastic_samples=num_stochastic_samples,
-                       seed=seed,args=args,eval_metrics=eval_metrics)
-######instance2
-num_samples2 = 200000
-@pytest.fixture(scope="module")
-def vis_case2():
-    return Postprocess(results_dir=results_dir, checkpoint=checkpoint,
-                       mode=mode, batch_size=batch_size, num_samples=num_samples2,
+                       mode=mode,batch_size=batch_size, 
                        num_stochastic_samples=num_stochastic_samples,
                        seed=seed,args=args,eval_metrics=eval_metrics)
 
@@ -60,28 +51,21 @@ def test_get_metadata(vis_case1):
 def test_setup_test_dataset(vis_case1):
     vis_case1.test_dataset.mode == mode
 
-def test_setup_num_samples_per_epoch(vis_case1):
-    vis_case1.setup_test_dataset()
-    vis_case1.setup_num_samples_per_epoch()
-    assert vis_case1.num_samples_per_epoch == num_samples
-    
 def test_get_data_params(vis_case1):
-    vis_case1.get_data_params()
     assert vis_case1.context_frames == 12
     assert vis_case1.future_length == 12
 
 def test_run_deterministic(vis_case1):
-    vis_case1()
     vis_case1.init_session()
     vis_case1.restore(vis_case1.sess,vis_case1.checkpoint)
     vis_case1.sample_ind = 0
-    vis_case1.input_results,vis_case1.input_images_denorm_all, vis_case1.t_starts = vis_case1.run_and_plot_inputs_per_batch() 
-    assert len(vis_case1.t_starts_results) == batch_size
+    vis_case1.input_results,vis_case1.input_images_denorm_all, vis_case1.t_starts = vis_case1.get_input_data_per_batch(vis_case1.inputs) 
+    assert len(vis_case1.t_starts) == batch_size
     ts_1 = vis_case1.t_starts[0][0]
     year = str(ts_1)[:4]
     month = str(ts_1)[4:6]
     filename = "ecmwf_era5_" +  str(ts_1)[2:] + ".nc"
-    fl = os.path.join("/p/project/deepacf/deeprain/video_prediction_shared_folder/extractedData",year, month, filename)
+    fl = os.path.join("/p/scratch/deepacf/deeprain/ambs_era5/extractedData",year, month, filename)
     print("netCDF file name:",fl)
     with Dataset(fl,"r")  as data_file:
        t2_var = data_file.variables["2t"][0,:,:]