Html repr with JupyterLab TOC

lmfit/minimizer.py

@@ -339,8 +339,9 @@
 
     def _repr_html_(self, show_correl=True, min_correl=0.1):
         """Return a HTML representation of parameters data."""
-        return fitreport_html_table(self, show_correl=show_correl,
-                                    min_correl=min_correl)
+        report = fitreport_html_table(self, show_correl=show_correl,
+                                      min_correl=min_correl)
+        return f"<h2>Fit Result</h2> {report}"
 
 
 class Minimizer:

lmfit/model.py

@@ -1725,7 +1725,7 @@ def _repr_html_(self, show_correl=True, min_correl=0.1):
         report = fitreport_html_table(self, show_correl=show_correl,
                                       min_correl=min_correl)
         modname = self.model._reprstring(long=True)
-        return f"<h2> Model</h2> {modname} {report}"
+        return f"<h2>Fit Result</h2> <p>Model: {modname}</p> {report}"
 
     def summary(self):
         """Return a dictionary with statistics and attributes of a ModelResult.

lmfit/printfuncs.py

@@ -224,6 +224,26 @@ def fit_report(inpars, modelpars=None, show_correl=True, min_correl=0.1,
     return '\n'.join(buff)
 
 
+def lcol(s, cat='td'):
+    "html left column"
+    return f"<{cat} style='text-align:left'>{s}</{cat}>"
+
+
+def rcol(s, cat='td'):
+    "html right column"
+    return f"<{cat} style='text-align:right'>{s}</{cat}>"
+
+
+def trow(columns, cat='td'):
+    "html row"
+    nlast = len(columns)-1
+    rows = []
+    for i, col in enumerate(columns):
+        cform = rcol if i == nlast else lcol
+        rows.append(cform(col, cat=cat))
+    return rows
+
+
 def fitreport_html_table(result, show_correl=True, min_correl=0.1):
     """Generate a report of the fitting result as an HTML table.
 
@@ -246,11 +266,15 @@ def fitreport_html_table(result, show_correl=True, min_correl=0.1):
     html = []
     add = html.append
 
-    def stat_row(label, val, val2=''):
-        add(f'<tr><td>{label}</td><td>{val}</td><td>{val2}</td></tr>')
+    def stat_row(label, val, val2=None, cat='td'):
+        if val2 is None:
+            rows = trow([label, val], cat=cat)
+        else:
+            rows = trow([label, val, val2], cat=cat)
+        add(f"<tr>{''.join(rows)}</tr>")
 
-    add('<h2>Fit Statistics</h2>')
-    add('<table>')
+    add('<table class="jp-toc-ignore">')
+    add('<caption class="jp-toc-ignore">Fit Statistics</caption>')
     stat_row('fitting method', result.method)
     stat_row('# function evals', result.nfev)
     stat_row('# data points', result.ndata)
@@ -262,7 +286,6 @@ def stat_row(label, val, val2=''):
     if hasattr(result, 'rsquared'):
         stat_row('R-squared', gformat(result.rsquared))
     add('</table>')
-    add('<h2>Variables</h2>')
     add(params_html_table(result.params))
     if show_correl:
         correls = []
@@ -279,9 +302,10 @@ def stat_row(label, val, val2=''):
         if len(correls) > 0:
             sort_correls = sorted(correls, key=lambda val: abs(val[2]))
             sort_correls.reverse()
-            extra = f'(unreported correlations are < {min_correl:.3f})'
-            add(f'<h2>Correlations {extra}</h2>')
-            add('<table>')
+            extra = f'(unreported values are < {min_correl:.3f})'
+            add('<table class="jp-toc-ignore">')
+            add(f'<caption>Correlations {extra}</caption>')
+            stat_row('Parameter1', 'Parameter 2', 'Correlation', cat='th')
             for name1, name2, val in sort_correls:
                 stat_row(name1, name2, f"{val:+.4f}")
             add('</table>')
@@ -345,10 +369,7 @@ def params_html_table(params):
     html = []
     add = html.append
 
-    def cell(x, cat='td'):
-        return add(f'<{cat}> {x} </{cat}>')
-
-    add('<table><tr>')
+    add('<table class="jp-toc-ignore"><caption>Parameters</caption>')
     headers = ['name', 'value']
     if has_err:
         headers.extend(['standard error', 'relative error'])
@@ -357,9 +378,9 @@ def cell(x, cat='td'):
         headers.append('expression')
     if has_brute:
         headers.append('brute step')
-    for h in headers:
-        cell(h, cat='th')
-    add('</tr>')
+
+    hrow = trow(headers, cat='th')
+    add(f"<tr>{''.join(hrow)}</tr>")
 
     for par in params.values():
         rows = [par.name, gformat(par.value)]
@@ -386,10 +407,8 @@ def cell(x, cat='td'):
                 brute_step = gformat(par.brute_step)
             rows.append(brute_step)
 
-        add('<tr>')
-        for r in rows:
-            cell(r)
-        add('</tr>')
+        hrow = trow(rows, cat='td')
+        add(f"<tr>{''.join(hrow)}</tr>")
     add('</table>')
     return ''.join(html)
 

tests/test_parameters.py

@@ -383,7 +383,7 @@ def test_parameters__repr_html_(parameters):
     repr_html = pars._repr_html_()
 
     assert isinstance(repr_html, str)
-    assert '<table><tr><th> name </th><th> value </th>' in repr_html
+    assert '<table class="jp-toc-ignore"><caption>Parameters</caption>' in repr_html
 
 
 def test_parameters_add():

tests/test_printfuncs.py

@@ -142,9 +142,8 @@ def test_reports_created(fitresult):
 
     html_report = fitresult._repr_html_()
     assert len(html_report) > 1000
-    for header in report_headers:
-        header_title = header.replace('[', '').replace(']', '').strip()
-        assert header_title in html_report
+    for header in ('Model', 'Fit Statistics', 'Parameters', 'Correlations'):
+        assert header in html_report
 
 
 def test_fitreports_init_values(fitresult):