Merge pull request #1594 from danforthcenter/add_metadata_to_outputs

Add metadata to outputs

plantcv/plantcv/analyze/size.py

@@ -124,6 +124,8 @@ def _analyze_size(img, mask, label):
  (255, 0, 255), params.line_thickness)
 
  # Store outputs
+ outputs.add_metadata(term="image_height", datatype=int, value=np.shape(img)[0])
+ outputs.add_metadata(term="image_width", datatype=int, value=np.shape(img)[1])
  outputs.add_observation(sample=label, variable='area', trait='area',
  method='plantcv.plantcv.analyze.size', scale='pixels', datatype=int,
  value=area, label='pixels')

plantcv/plantcv/classes.py

@@ -3,6 +3,8 @@
 import cv2
 import json
 import numpy as np
+import datetime
+from plantcv.plantcv import __version__ as ver
 from plantcv.plantcv import fatal_error
 from plantcv.plantcv.annotate.points import _find_closest_pt
 import matplotlib.pyplot as plt
@@ -150,7 +152,7 @@ def add_metadata(self, term, datatype, value):
  # Save the observation for the sample and variable
  self.metadata[term] = {
  "datatype": str(datatype),
- "value": value
+ "value": [value]
  }
 
  # Method to save observations to a file
@@ -164,6 +166,11 @@ def save_results(self, filename, outformat="json"):
  :param filename: str
  :param outformat: str
  """
+ # Add current date & time to metadata in UTC format
+ run_datetime = datetime.datetime.now().strftime("%Y-%m-%dT%H:%M:%S.%fZ")
+ self.add_metadata(term="run_date", datatype=str, value=run_datetime)
+ self.add_metadata(term="plantcv_version", datatype=str, value=ver)
+
  if outformat.upper() == "JSON":
  if os.path.isfile(filename):
  with open(filename, 'r') as f:

tests/plantcv/test_outputs.py

@@ -81,7 +81,7 @@ def test_save_results_csv(test_data, tmpdir):
  results = fp.read()
  with open(test_data.outputs_results_csv, "r") as fp:
  test_results = fp.read()
- assert results == test_results
+ assert results[-18:] == test_results[-18:]
 
 
 def test_save_results_csv_add_metadata(tmpdir):
@@ -96,8 +96,8 @@ def test_save_results_csv_add_metadata(tmpdir):
  outputs.save_results(filename=outfile, outformat="csv")
  with open(outfile, "r") as fp:
  results = fp.read()
- x = slice(0, 33)
- assert results[x] == "add_date,sample,trait,value,label"
+ x = slice(0, 58)
+ assert results[x] == "add_date,run_date,plantcv_version,sample,trait,value,label"
 
 
 def test_add_metadata_invalid_type():