Added show_values

Author: PredictiveManish

pypfopt/plotting.py

@@ -66,7 +66,9 @@ def _plot_io(**kwargs):
         plt.show()
 
 
-def plot_covariance(cov_matrix, plot_correlation=False, show_tickers=True, **kwargs):
+def plot_covariance(
+    cov_matrix, plot_correlation=False, show_tickers=True, show_values=False, **kwargs
+):
     """
     Generate a basic plot of the covariance (or correlation) matrix, given a
     covariance matrix.
@@ -80,6 +82,9 @@ def plot_covariance(cov_matrix, plot_correlation=False, show_tickers=True, **kwa
     show_tickers : bool, optional
         whether to use tickers as labels (not recommended for large portfolios),
         defaults to True
+    show_values : bool, optional
+        if True, annotate each cell with the numeric value formatted to
+        two decimal places. Defaults to False.
 
     Returns
     -------
@@ -92,6 +97,7 @@ def plot_covariance(cov_matrix, plot_correlation=False, show_tickers=True, **kwa
         matrix = risk_models.cov_to_corr(cov_matrix)
     else:
         matrix = cov_matrix
+
     fig, ax = plt.subplots()
 
     cax = ax.imshow(matrix)
@@ -104,6 +110,30 @@ def plot_covariance(cov_matrix, plot_correlation=False, show_tickers=True, **kwa
         ax.set_yticklabels(matrix.index)
         plt.xticks(rotation=90)
 
+    # Optional: overlay numeric values on each cell
+    if show_values:
+        is_dataframe = hasattr(matrix, "iloc")
+        n_rows, n_cols = matrix.shape
+
+        for i in range(n_rows):
+            for j in range(n_cols):
+                if is_dataframe:
+                    val = matrix.iloc[i, j]
+                else:
+                    val = matrix[i, j]
+
+                text_str = f"{val:.2f}"
+
+                ax.text(
+                    j,
+                    i,
+                    text_str,
+                    ha="center",
+                    va="center",
+                    color="w",
+                    fontsize=plt.rcParams.get("font.size", 10) * 0.9,
+                )
+
     _plot_io(**kwargs)
 
     return ax

tests/test_efficient_frontier.py

@@ -608,7 +608,7 @@ def test_min_vol_pair_constraint():
     ef.min_volatility()
     old_sum = ef.weights[:2].sum()
     ef = setup_efficient_frontier()
-    ef.add_constraint(lambda w: (w[1] + w[0] <= old_sum / 2))
+    ef.add_constraint(lambda w: w[1] + w[0] <= old_sum / 2)
     ef.min_volatility()
     new_sum = ef.weights[:2].sum()
     assert new_sum <= old_sum / 2 + 1e-4
@@ -620,7 +620,7 @@ def test_max_sharpe_pair_constraint():
     old_sum = ef.weights[:2].sum()
 
     ef = setup_efficient_frontier()
-    ef.add_constraint(lambda w: (w[1] + w[0] <= old_sum / 2))
+    ef.add_constraint(lambda w: w[1] + w[0] <= old_sum / 2)
     ef.max_sharpe(risk_free_rate=0.02)
     new_sum = ef.weights[:2].sum()
     assert new_sum <= old_sum / 2 + 1e-4