Merge pull request #11 from zachessesjohnson/copilot/fix-toml-syntax-error

Fix CI failures: TOML syntax error, asm_spread typo, missing plotting module

Author: zachessesjohnson

.github/workflows/pytest.yml

@@ -25,6 +25,7 @@ jobs:
           python -m pip install -U pip
           pip install -r requirements.txt
           pip install -e .
+          pip install -e sovereign_debt_py/
 
       - name: Run tests
         run: |

pyproject.toml

@@ -22,4 +22,3 @@ dev = ["pytest"]
 [tool.setuptools.packages.find]
 where = ["."]
 include = ["sovereign_debt_xl*"]
-include = ["sovereign_debt_xl*", "sovereign_debt_py*"]

sovereign_debt_py/sovereign_debt_py/plotting/__init__.py

@@ -0,0 +1,349 @@
+"""Pure-Python plotting helpers for sovereign debt analysis.
+
+All functions return ``(fig, ax)`` tuples so callers can further customise
+the chart before saving or displaying it.  Use :func:`fig_to_png_bytes` to
+serialise a figure to PNG bytes.
+"""
+from __future__ import annotations
+
+import datetime
+import io
+from typing import Any
+
+import matplotlib
+
+matplotlib.use("Agg")  # headless – must come before pyplot import
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+import numpy as np
+
+from .core import coerce_dates, to_1d_array, validate_same_length
+
+__all__ = [
+    "plot_yield_curve",
+    "plot_timeseries",
+    "plot_rolling_average",
+    "plot_spread",
+    "plot_fan_chart",
+    "fig_to_png_bytes",
+]
+
+_VALID_STYLES = ("line", "markers", "line+markers")
+
+
+# ---------------------------------------------------------------------------
+# plot_yield_curve
+# ---------------------------------------------------------------------------
+
+def plot_yield_curve(
+    tenors: Any,
+    yields: Any,
+    title: str | None = None,
+    style: str = "line",
+    fig: Any = None,
+    ax: Any = None,
+) -> tuple[Any, Any]:
+    """Plot a yield curve (tenors vs yields) and return ``(fig, ax)``.
+
+    Parameters
+    ----------
+    tenors:
+        Sequence of numeric tenor values (years).
+    yields:
+        Sequence of yield values matching *tenors* in length.
+    title:
+        Optional chart title.
+    style:
+        One of ``"line"``, ``"markers"``, or ``"line+markers"``.
+    fig, ax:
+        Optional existing Matplotlib figure and axes to plot into.
+
+    Raises
+    ------
+    ValueError
+        If *tenors* and *yields* have different lengths, or *style* is invalid.
+    """
+    t_arr = to_1d_array(tenors)
+    y_arr = to_1d_array(yields)
+    validate_same_length(t_arr, y_arr)
+    if style not in _VALID_STYLES:
+        raise ValueError(
+            f"Invalid style {style!r}; must be one of {_VALID_STYLES}"
+        )
+
+    if fig is None or ax is None:
+        fig, ax = plt.subplots()
+
+    use_marker = style in ("markers", "line+markers")
+    use_line = style in ("line", "line+markers")
+    ax.plot(
+        t_arr,
+        y_arr,
+        marker="o" if use_marker else None,
+        linestyle="-" if use_line else "none",
+        linewidth=2,
+    )
+    if title:
+        ax.set_title(title)
+    ax.set_xlabel("Tenor")
+    ax.set_ylabel("Yield")
+    ax.grid(True, linestyle="--", alpha=0.5)
+    return fig, ax
+
+
+# ---------------------------------------------------------------------------
+# plot_timeseries
+# ---------------------------------------------------------------------------
+
+def plot_timeseries(
+    dates: Any,
+    values: Any,
+    title: str | None = None,
+) -> tuple[Any, Any]:
+    """Plot a time-series (dates vs values) and return ``(fig, ax)``.
+
+    Parameters
+    ----------
+    dates:
+        Sequence of date-like values (:class:`datetime.date`,
+        :class:`datetime.datetime`, or ISO-format strings).
+    values:
+        Sequence of numeric values matching *dates* in length.
+    title:
+        Optional chart title.
+
+    Raises
+    ------
+    ValueError
+        If *dates* and *values* have different lengths.
+    """
+    d_list = coerce_dates(dates)
+    v_arr = to_1d_array(values)
+    validate_same_length(np.array(d_list), v_arr)
+
+    fig, ax = plt.subplots()
+    x_dt = [datetime.datetime(d.year, d.month, d.day) for d in d_list]
+    ax.plot(x_dt, v_arr, linewidth=1.5)
+    if title:
+        ax.set_title(title)
+    ax.xaxis.set_major_locator(mdates.AutoDateLocator())
+    ax.xaxis.set_major_formatter(
+        mdates.AutoDateFormatter(mdates.AutoDateLocator())
+    )
+    fig.autofmt_xdate(rotation=30)
+    ax.grid(True, linestyle="--", alpha=0.5)
+    return fig, ax
+
+
+# ---------------------------------------------------------------------------
+# plot_rolling_average
+# ---------------------------------------------------------------------------
+
+def plot_rolling_average(
+    dates: Any,
+    values: Any,
+    window: int,
+    base_label: str = "Original",
+    roll_label: str | None = None,
+) -> tuple[Any, Any]:
+    """Plot data with a rolling-average overlay and return ``(fig, ax)``.
+
+    Parameters
+    ----------
+    dates:
+        Sequence of date-like values.
+    values:
+        Sequence of numeric values matching *dates* in length.
+    window:
+        Rolling window size (number of periods).  Must be ≥ 1 and ≤
+        ``len(values)``.
+    base_label:
+        Legend label for the raw series (default ``"Original"``).
+    roll_label:
+        Legend label for the rolling-average series.  Defaults to
+        ``f"Rolling {window}"``.
+
+    Raises
+    ------
+    ValueError
+        If *dates* and *values* have different lengths, or *window* is larger
+        than the data length.
+    """
+    d_list = coerce_dates(dates)
+    v_arr = to_1d_array(values)
+    validate_same_length(np.array(d_list), v_arr)
+    window = int(window)
+    if window < 1:
+        raise ValueError(f"window must be >= 1 (got {window})")
+    if window > len(v_arr):
+        raise ValueError(
+            f"window ({window}) is larger than the data length ({len(v_arr)})"
+        )
+    if roll_label is None:
+        roll_label = f"Rolling {window}"
+
+    rolling = np.full_like(v_arr, np.nan, dtype=float)
+    for i in range(window - 1, len(v_arr)):
+        rolling[i] = float(np.mean(v_arr[i - window + 1: i + 1]))
+
+    fig, ax = plt.subplots()
+    x_dt = [datetime.datetime(d.year, d.month, d.day) for d in d_list]
+    ax.plot(x_dt, v_arr, color="lightsteelblue", linewidth=1.0, alpha=0.7, label=base_label)
+    ax.plot(x_dt, rolling, color="steelblue", linewidth=2.0, label=roll_label)
+    ax.xaxis.set_major_locator(mdates.AutoDateLocator())
+    ax.xaxis.set_major_formatter(
+        mdates.AutoDateFormatter(mdates.AutoDateLocator())
+    )
+    fig.autofmt_xdate(rotation=30)
+    ax.legend(loc="best")
+    ax.grid(True, linestyle="--", alpha=0.5)
+    return fig, ax
+
+
+# ---------------------------------------------------------------------------
+# plot_spread
+# ---------------------------------------------------------------------------
+
+def plot_spread(
+    x: Any,
+    series_a: Any,
+    series_b: Any,
+    label_a: str = "Series A",
+    label_b: str = "Series B",
+    title: str | None = None,
+) -> tuple[Any, Any]:
+    """Plot two series and their spread and return ``(fig, ax)``.
+
+    Parameters
+    ----------
+    x:
+        Sequence of x-axis values (dates or numerics).
+    series_a, series_b:
+        Sequences of numeric values, each matching *x* in length.
+    label_a, label_b:
+        Legend labels.
+    title:
+        Optional chart title.
+
+    Raises
+    ------
+    ValueError
+        If any of the three sequences have different lengths.
+    """
+    a_arr = to_1d_array(series_a)
+    b_arr = to_1d_array(series_b)
+
+    # x may be dates or numerics
+    try:
+        x_vals: Any = coerce_dates(x)
+        x_plot = [datetime.datetime(d.year, d.month, d.day) for d in x_vals]
+        use_dates = True
+    except (ValueError, TypeError):
+        x_plot = list(x)
+        use_dates = False
+
+    validate_same_length(np.array(x_plot), a_arr)
+    validate_same_length(a_arr, b_arr)
+
+    fig, ax = plt.subplots()
+    ax.plot(x_plot, a_arr, label=label_a, linewidth=1.5)
+    ax.plot(x_plot, b_arr, label=label_b, linewidth=1.5)
+    if use_dates:
+        ax.xaxis.set_major_locator(mdates.AutoDateLocator())
+        ax.xaxis.set_major_formatter(
+            mdates.AutoDateFormatter(mdates.AutoDateLocator())
+        )
+        fig.autofmt_xdate(rotation=30)
+    if title:
+        ax.set_title(title)
+    ax.legend(loc="best")
+    ax.grid(True, linestyle="--", alpha=0.5)
+    return fig, ax
+
+
+# ---------------------------------------------------------------------------
+# plot_fan_chart
+# ---------------------------------------------------------------------------
+
+def plot_fan_chart(
+    x: Any,
+    p50: Any,
+    bands: dict[tuple[float, float], tuple[Any, Any]],
+    title: str | None = None,
+) -> tuple[Any, Any]:
+    """Plot a fan chart with confidence bands and return ``(fig, ax)``.
+
+    Parameters
+    ----------
+    x:
+        Sequence of x-axis values (e.g. years).
+    p50:
+        Sequence of median values matching *x* in length.
+    bands:
+        Mapping of ``(low_prob, high_prob)`` → ``(lower_series, upper_series)``
+        where each series matches *x* in length.
+    title:
+        Optional chart title.
+
+    Raises
+    ------
+    ValueError
+        If *x* and *p50* (or any band series) have different lengths.
+    """
+    x_arr = to_1d_array(x)
+    p50_arr = to_1d_array(p50)
+    validate_same_length(x_arr, p50_arr)
+
+    fig, ax = plt.subplots()
+    for (lo_prob, hi_prob), (lower, upper) in bands.items():
+        lo_arr = to_1d_array(lower)
+        hi_arr = to_1d_array(upper)
+        validate_same_length(x_arr, lo_arr)
+        validate_same_length(x_arr, hi_arr)
+        label = f"{int(lo_prob * 100)}–{int(hi_prob * 100)}%"
+        ax.fill_between(x_arr, lo_arr, hi_arr, alpha=0.3, label=label)
+    ax.plot(x_arr, p50_arr, linewidth=2, label="Median", color="steelblue")
+    if title:
+        ax.set_title(title)
+    ax.legend(loc="best")
+    ax.grid(True, linestyle="--", alpha=0.5)
+    return fig, ax
+
+
+# ---------------------------------------------------------------------------
+# fig_to_png_bytes
+# ---------------------------------------------------------------------------
+
+def fig_to_png_bytes(
+    fig: Any,
+    width_px: int | None = None,
+    height_px: int | None = None,
+    dpi: int = 100,
+    close: bool = False,
+) -> bytes:
+    """Render *fig* to PNG bytes.
+
+    Parameters
+    ----------
+    fig:
+        Matplotlib figure to render.
+    width_px, height_px:
+        Optional output dimensions in pixels.  When provided the figure size
+        is adjusted before rendering.
+    dpi:
+        Dots per inch for the output PNG (default 100).
+    close:
+        If ``True``, close *fig* after rendering to free memory.
+
+    Returns
+    -------
+    bytes
+        PNG-encoded image bytes.
+    """
+    if width_px is not None and height_px is not None:
+        fig.set_size_inches(width_px / dpi, height_px / dpi)
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png", dpi=dpi, bbox_inches="tight")
+    if close:
+        plt.close(fig)
+    return buf.getvalue()