enable additional information in reports

README.md

@@ -1,4 +1,4 @@
-# proMAD <img src='proMAD/data/templates/logo.png?raw=true' align="right"/>
+# proMAD <img src='https://github.com/theia-dev/proMAD/raw/master/proMAD/data/templates/logo.png' align="right"/>
 Semiquantitative densitometric measurement of protein microarrays
 
 

proMAD/config.py

@@ -1,7 +1,7 @@
 from pathlib import Path
 
 app_name = 'proMAD'
-version_number = (0, 2, 4)
+version_number = (0, 2, 5)
 version = f'{version_number[0]}.{version_number[1]}.{version_number[2]}'
 app_author = 'Anna Jaeschke; Hagen Eckert'
 url = 'https://proMAD.dev'

proMAD/core.py

@@ -1240,7 +1240,7 @@ def figure_contact_sheet_spot(self, position, kind='raw', file=None, max_size=No
                 im = Image.fromarray(image)
                 im.save(file, format='JPEG')
 
-    def report(self, file=None, norm='hist_raw', report_type=None):
+    def report(self, file=None, norm='hist_raw', report_type=None, additional_info=None):
         """
         Summarize the results for a specific evaluation strategy in a report.
 
@@ -1291,5 +1291,5 @@ def report(self, file=None, norm='hist_raw', report_type=None):
             warnings.warn(f'No file was given.', RuntimeWarning)
             return
 
-        report_types[report_type]['func'](aa=self, file=file, norm=norm)
+        report_types[report_type]['func'](aa=self, file=file, norm=norm, additional_info=additional_info)
 

proMAD/data/templates/short_report.tex

@@ -54,9 +54,14 @@
         \BLOCK{ endif }
         \item [\VAR{dn['array_id']}:] \VAR{dv['array_id']}
         \item [\VAR{dn['array_name']}:] \VAR{dv['array_name']} (\VAR{dv['array_type']})
-        \item [\VAR{dn['norm']}:] \VAR{dv['norm']}
+        \item [\VAR{dn['norm_name']}:] \VAR{dv['norm_name']} (libkey: \VAR{ dv.norm })
         \item [\VAR{dn['norm_description']}:] \VAR{dv['norm_description']}
-        \item[\VAR{dn['unit']}:] \VAR{dv['unit']}
+        \item [\VAR{dn['unit']}:] \VAR{dv['unit']}
+        \BLOCK{ if additional_info }
+        \BLOCK{ for entry in additional_info }
+        \item [\VAR{entry.name}:] \VAR{entry.value}
+        \BLOCK{ endfor }
+        \BLOCK{ endif }
     \end{description}
 \end{center}
 
@@ -65,7 +70,7 @@
 \begin{axis}[
     width  = \textwidth,
     bar width=0.04*\textwidth,
-    height = 11cm,
+    height = 9cm,
     ybar,
     compat=newest,
     ymajorgrids = true,
@@ -101,9 +106,6 @@
 \caption{Overview and alignment check}\label{fig:alignment}
 \end{figure}
 
-
-
-
 \begin{longtable}{l|rcS[table-number-alignment = center]}
     \caption{List of average values of analyte spots.}\label{tab:all}\\
     \toprule

proMAD/report.py

@@ -10,6 +10,8 @@
 from pylatexenc.latexencode import unicode_to_latex
 import shutil
 
+from typing import List, Dict
+
 from openpyxl import Workbook
 from openpyxl.chart import BarChart, Reference
 from openpyxl.drawing.image import Image as opImage
@@ -30,6 +32,15 @@ class Report:
         reac="estimate of the catalytic enzyme concentration"
     )
 
+    norm_names = dict(
+        raw='Spot average',
+        raw_bg='Background corrected spot average',
+        local_bg='Ratio to local background',
+        hist_fg='Foreground to global background ratio',
+        hist_raw='Ratio to global background',
+        reac='Catalytic enzyme concentration'
+    )
+
     norm_return = dict(
         raw=('values',),
         raw_bg=('values',),
@@ -76,6 +87,7 @@ def get_details(cls, aa, norm, tex=False):
             array_name=aa.array_data['name'],
             array_type=aa.array_data['array_type'],
             array_id=aa.array_data['id'],
+            norm_name=cls.norm_names[norm],
             norm=norm,
             norm_description=cls.norm_descriptions[norm],
             unit=cls.norm_unit[norm]
@@ -93,15 +105,16 @@ def get_details(cls, aa, norm, tex=False):
             array_name='Array Name',
             array_type='Array Type',
             array_id='Array ID',
-            norm='Norm key',
-            norm_description='Norm description',
+            norm_name='Method',
+            norm='Method key',
+            norm_description='Method description',
             unit='Unit'
         )
 
         return detail_values, detail_names
 
     @classmethod
-    def exp_excel(cls, aa, file, norm='hist_raw', name=None, additional_info=None):
+    def exp_excel(cls, aa, file, norm='hist_raw', additional_info=None):
         """
         Export results in an Excel file.
 
@@ -113,10 +126,8 @@ def exp_excel(cls, aa, file, norm='hist_raw', name=None, additional_info=None):
                 evaluation strategy selection (see ArrayAnalyse.evaluate)
         file:
             file can be a path to a file (a string), a path-like object, or a file-like object
-        name: str
-            membrane name
-        additional_info: list((str, str))
-            a list with pairs of additional information ('name', 'value')
+        additional_info: List[Dict]
+            list with dictionaries containing 'name' and 'value' key
         """
 
         if not aa.is_finalized:
@@ -193,10 +204,7 @@ def exp_excel(cls, aa, file, norm='hist_raw', name=None, additional_info=None):
             else:
                 new_rows.append([entry['info'][0], pos, entry['value']])
 
-        if name is None:
-            ws['A1'] = 'Membrane Results'
-        else:
-            ws['A1'] = f'{name} Results'
+        ws['A1'] = 'Membrane Results'
         ws['A1'].style = highlight
         ws.append([])
         ws.append(('Name', 'Position', 'Value'))
@@ -235,10 +243,7 @@ def exp_excel(cls, aa, file, norm='hist_raw', name=None, additional_info=None):
         data = aa.evaluate(norm=norm)
         for entry in data:
             new_rows.append([entry['info'][0], aa.get_position_string(entry['position'])] + [v for v in entry['value']])
-        if name is None:
-            ws['A1'] = 'Membrane Result Details'
-        else:
-            ws['A1'] = f'{name} Result Details'
+        ws['A1'] = 'Membrane Result Details'
         ws['A1'].style = highlight
         ws.append([])
         ws.append(['Name', 'Position'] + [head.title() for head in cls.norm_return[norm]])
@@ -262,7 +267,7 @@ def exp_excel(cls, aa, file, norm='hist_raw', name=None, additional_info=None):
         detail_values, detail_names = cls.get_details(aa, norm)
         info_list = ['date', 'time', 'skip',
                      'program', 'version', 'url', 'skip',
-                     'array_name', 'array_type', 'array_id', 'norm', 'norm_description', 'unit'
+                     'array_name', 'array_type', 'array_id', 'norm_name', 'norm', 'norm_description', 'unit'
                      ]
         tech_data_list = []
         for key in info_list:
@@ -272,7 +277,7 @@ def exp_excel(cls, aa, file, norm='hist_raw', name=None, additional_info=None):
                 tech_data_list.append((detail_names[key], detail_values[key]))
 
         if additional_info:
-            tech_data_list += [('', '')] + additional_info
+            tech_data_list += [('', '')] + [(entry['name'], entry['value']) for entry in additional_info]
 
         ws.column_dimensions['A'].width = 15
         ws.column_dimensions['B'].width = 15
@@ -289,7 +294,7 @@ def exp_excel(cls, aa, file, norm='hist_raw', name=None, additional_info=None):
                 file.write(tmp.read())
 
     @classmethod
-    def exp_csv(cls, aa, file, norm='hist_raw'):
+    def exp_csv(cls, aa, file, norm='hist_raw', additional_info=None):
         """
         Export results in a comma separated file.
 
@@ -298,9 +303,11 @@ def exp_csv(cls, aa, file, norm='hist_raw'):
         aa:
             ArrayAnalyse instant
         norm: str
-                evaluation strategy selection (see ArrayAnalyse.evaluate)
+            evaluation strategy selection (see ArrayAnalyse.evaluate)
         file:
             file can be a path to a file (a string), a path-like object, or a file-like object (string based)
+        additional_info:
+            is ignored for CSV
         """
 
         data = aa.evaluate(norm=norm)
@@ -330,8 +337,8 @@ def exp_latex(cls, aa, file, norm='hist_raw', additional_info=None):
                 evaluation strategy selection (see ArrayAnalyse.evaluate)
         file:
             can be a path to a file (a string), a path-like object, or a file-like object (string based)
-        additional_info: dict
-            dictionary with pairs of additional information
+        additional_info: List[Dict]
+            list with dictionaries containing name and value key
         """
 
         overview = []
@@ -367,6 +374,11 @@ def exp_latex(cls, aa, file, norm='hist_raw', additional_info=None):
         col_num = sum(aa.array_data['net_layout_x'])
         row_num = sum(aa.array_data['net_layout_y'])
 
+        if additional_info:
+            for entry in additional_info:
+                entry['name'] = unicode_to_latex(entry['name'])
+                entry['value'] = unicode_to_latex(entry['value'])
+        info_dict['additional_info'] = additional_info
         info_dict['ai'] = dict(
             row=[(get_column_letter(row_num-n), f'{n/row_num + 0.5/row_num:.3f}') for n in range(row_num)],
             col=[(str(n+1), f'{n/col_num + 0.5/col_num:.3f}') for n in range(col_num)]
@@ -399,8 +411,8 @@ def exp_json(cls, aa, file, norm='hist_raw', additional_info=None):
                 evaluation strategy selection (see ArrayAnalyse.evaluate)
         file:
             can be a path to a file (a string), a path-like object, or a file-like object (string based)
-        additional_info: dict
-            dictionary with pairs of additional information
+        additional_info: List[Dict]
+            list with dictionaries containing 'key' and 'value' key
         """
 
         data = aa.evaluate(norm=norm)
@@ -423,7 +435,12 @@ def exp_json(cls, aa, file, norm='hist_raw', additional_info=None):
         )
 
         if additional_info:
-            export_dict['info'].update(additional_info)
+            info_update = {entry['key']: entry['value'] for entry in additional_info}
+        else:
+            info_update = {}
+
+        if additional_info:
+            export_dict['info'].update(info_update)
 
         if isinstance(file, os.PathLike) or isinstance(file, str):
             Path(file).write_text(json.dumps(export_dict, indent=4))

tests/test_core.py

@@ -303,8 +303,9 @@ def test_figure_alignment(self):
             '87027ff24e5dc57ee7ba21c10969a4b5873fb980c92a09fb657b690a790b5532'])
 
         self.aa.figure_alignment(file=self.out_folder / 'alignment.jpg', max_size=500)
-        self.assertEqual(hash_file(self.out_folder / 'alignment.jpg'),
-                         'abc22b8192d0e2d5d10e5631ff50e827da29577c6567a3ee309701e90480cdf2')
+        self.assertIn(hash_file(self.out_folder / 'alignment.jpg'), [
+            'abc22b8192d0e2d5d10e5631ff50e827da29577c6567a3ee309701e90480cdf2',
+            '315efb4e3b7ce92dcfa0999b36014c2d63d87700b3d40caa54bb0c3a02799aeb'])
 
     def test_figure_contact_sheet_spot(self):
         save_mem = io.BytesIO()
@@ -314,8 +315,9 @@ def test_figure_contact_sheet_spot(self):
             '953544ba7e4e0c70eaa70de6dc513b52849da5fe0e5b5adfedfcacf835232781'])
 
         self.aa.figure_contact_sheet_spot(file=self.out_folder / 'contact_sheet_spot.jpg', max_size=150, position='A1')
-        self.assertEqual(hash_file(self.out_folder / 'contact_sheet_spot.jpg', skip=0),
-                         '10ddfc8494dda2a3a0e29ed0f1fd996347a10d2b806d212358e390ecc26ef450')
+        self.assertIn(hash_file(self.out_folder / 'contact_sheet_spot.jpg', skip=0), [
+            '10ddfc8494dda2a3a0e29ed0f1fd996347a10d2b806d212358e390ecc26ef450',
+            '60f694b096a3ff2e0820bc896b1351dfa270cef59db8343e218a6acf997285a3'])
 
     def test_figure_reaction_fit(self):
         self.aa.figure_reaction_fit(file=self.out_folder / 'reaction_fit.png')

tests/test_report.py

@@ -18,6 +18,10 @@ def setUpClass(cls):
         cls.aa = ArrayAnalyse.load(cls.cases / 'save' / 'dump.tar')
         cls.out_folder = cls.cases / 'testing_reports'
         cls.out_folder.mkdir(exist_ok=True, parents=True)
+        cls.additional_info = [
+            dict(key='system_name', name='System name', value='UnitTest'),
+            dict(key='membrane_name', name='Membrane name', value='Membrane A')
+        ]
 
     @classmethod
     def tearDownClass(cls):
@@ -68,7 +72,7 @@ def test_json(self):
         compare_123 = {'position': [5, 11], 'info': ['IL-31', '386653', None], 'value': 0.9974935542164649,
                        'intercept': -0.0008484813336183776, 'r_squared': 0.9992305292185427}
 
-        self.aa.report(test_file_path, norm='raw')
+        self.aa.report(test_file_path, norm='raw', additional_info=self.additional_info)
         data = json.loads(test_file_path.read_text())
 
         self.assertAlmostEqual(data['result'][11]['values'][0], 0.023836107062511658, places=7)
@@ -79,6 +83,9 @@ def test_json(self):
         self.assertAlmostEqual(data['result'][123]['values'][2], 0.027834284233911134, places=7)
         self.assertAlmostEqual(data['result'][123]['values'][4], 0.03295996329826092, places=7)
 
+        for entry in self.additional_info:
+            self.assertEqual(data['info'][entry['key']], entry['value'])
+
         save_mem = io.StringIO()
         self.aa.report(save_mem, report_type='json')
         save_mem.seek(0)
@@ -93,7 +100,7 @@ def test_json(self):
 
     def test_latex(self):
         test_file_path = self.out_folder / 'rep.tex'
-        self.aa.report(test_file_path)
+        self.aa.report(test_file_path, additional_info=self.additional_info)
 
         self.assertTrue((self.out_folder / 'logo.png').is_file())
         self.assertTrue((self.out_folder / 'figure_alignment.jpg').is_file())
@@ -104,20 +111,22 @@ def test_latex(self):
             r'\node [anchor=east] (E) at (0, 0.550 ) {\small E};',
             r'\node [anchor=south] (15) at (0.604, 1) {\small 15};',
             r'BDNF &627~\href{https://www.ncbi.nlm.nih.gov/gene/?term=627}{\faExternalLink}& A15, A16 &0.9561\\',
-            r'Serpin E1 &5054~\href{https://www.ncbi.nlm.nih.gov/gene/?term=5054}{\faExternalLink}& I1, I2 &3.831\\'
+            r'Serpin E1 &5054~\href{https://www.ncbi.nlm.nih.gov/gene/?term=5054}{\faExternalLink}& I1, I2 &3.831\\',
+            r'\item [System name:] UnitTest'
         ]
+
         generated_tex = test_file_path.read_text()
         for part in compare:
             self.assertIn(part, generated_tex)
 
     def test_excel(self):
         test_file_path = self.out_folder / 'rep.xls'
-        self.aa.report(test_file_path)
+        self.aa.report(test_file_path, additional_info=self.additional_info)
         test_file_path = test_file_path.with_suffix('.xlsx')
         wb_file = load_workbook(filename=test_file_path, read_only=True)
 
         save_mem = io.BytesIO()
-        self.aa.report(save_mem, report_type='excel')
+        self.aa.report(save_mem, report_type='excel', additional_info=self.additional_info)
         wb_mem = load_workbook(filename=save_mem, read_only=True)
 
         for wb in [wb_mem, wb_file]:
@@ -143,14 +152,17 @@ def test_excel(self):
             self.assertAlmostEqual(ws['C7'].value, 0.965608450754212, places=7)
 
             ws = wb['Info']
-            self.assertEqual('A1:B15', ws.calculate_dimension())
+            self.assertEqual('A1:B19', ws.calculate_dimension())
             info_data = []
             for row in ws.rows:
                 for cell in row:
                     info_data.append(cell.value)
             self.assertIn('ARY022B', info_data)
             self.assertIn('hist_raw', info_data)
-            self.assertIn('Norm description', info_data)
+            self.assertIn('Method description', info_data)
+            for entry in self.additional_info:
+                self.assertIn(entry['name'], info_data)
+                self.assertIn(entry['value'], info_data)
 
 
 if __name__ == '__main__':