[FIX] Report figures: consistent fonts via figsize↔slot, smaller files, paginated multipanels, clock ±30 / stage1

oceanarray/config/parameters.py

@@ -33,6 +33,23 @@
 FIGURE_SIZE_WIDE = (14, 6)  # multi-instrument overview (scatter / line)
 FIGURE_SIZE_TALL = (12, 8)  # stacked single-instrument panels
 
+# ---------------------------------------------------------------------------
+# Report figure slot widths (inches).  The HTML report body is ~1150-1200px
+# wide; figures display at full/two-thirds/half/third of that slot via the
+# `.fig` CSS max-width caps.  Rendering a figure at the matching slot WIDTH
+# makes displayed font size depend only on figsize (font_px = pt/72 x
+# display_px/fig_in) — independent of dpi — so mplstyle fonts appear at a
+# consistent, readable size instead of the double-shrink that oversized (12-16
+# in) figsizes caused at half/third slots.  Set figure *width* to one of these;
+# height is content-driven.  (dpi is a separate size knob, set once in the
+# mplstyle's savefig.dpi; report figure bytes are cut mainly by palette
+# quantization in _fig_to_base64, not by dpi.)
+# ---------------------------------------------------------------------------
+W_FULL = 9.0  # full-slot figure (CSS max-width 100%)
+W_TWOTHIRDS = 6.0  # two-thirds slot (~66%)
+W_HALF = 4.5  # half slot (~50%)
+W_THIRD = 3.0  # one-third slot (~33%)
+
 # ---------------------------------------------------------------------------
 # Resampling
 # ---------------------------------------------------------------------------

oceanarray/oceanarray.mplstyle

@@ -1,18 +1,24 @@
-axes.titlesize : 15
-axes.labelsize : 12
+axes.titlesize : 12
+axes.labelsize : 10
 date.autoformatter.day: %Y-%m-%d
 date.converter: auto
 figure.figsize: 8, 4
 figure.dpi: 100
 savefig.dpi: 150
 font.family:  sans-serif
 font.style:   normal
-font.size: 12
-legend.fontsize: 12
+font.size: 10
+legend.fontsize: 9
 lines.linewidth : 1
 lines.linestyle: -
 lines.markersize : 10
-xtick.labelsize : 12
+xtick.labelsize : 10
 xtick.alignment: center
-ytick.labelsize : 12
+ytick.labelsize : 10
 axes.grid : False
+axes.linewidth : 0.6
+grid.alpha : 0.5
+grid.color : 0.5
+grid.linestyle : :
+grid.linewidth : 0.6
+contour.linewidth : 0.8

oceanarray/plotters/__init__.py

@@ -43,7 +43,7 @@
     draw_ts_diagram, draw_stack_ts_diagram, draw_grid_ts_diagram
 
   Hydrography (hydrography.py):
-    draw_isopycnal_fig, draw_isopycnal_ts_fig, draw_isopycnal_coverage,
+    draw_isopycnal_ts_fig, draw_isopycnal_coverage,
     draw_overflow_temperature_fig
 
 Legacy functions (from plotter.py — available via backward-compat shim):
@@ -131,7 +131,6 @@
 # draw_* functions — isopycnal
 # ---------------------------------------------------------------------------
 from oceanarray.plotters.hydrography import (  # noqa: F401
-    draw_isopycnal_fig,
     draw_isopycnal_ts_fig,
     draw_isopycnal_coverage,
     draw_overflow_temperature_fig,
@@ -190,7 +189,6 @@
     "draw_stack_ts_diagram",
     "draw_grid_ts_diagram",
     # draw_* — isopycnal
-    "draw_isopycnal_fig",
     "draw_isopycnal_ts_fig",
     "draw_isopycnal_coverage",
     "draw_overflow_temperature_fig",

oceanarray/plotters/current.py

@@ -144,7 +144,7 @@ def plot_speed_boxplot(
         val = np.percentile(speed_clean, p)
         print(f"  {p:2d}th percentile: {val:.4f} {units}")
 
-    fig, ax = plt.subplots(figsize=(4, 6))
+    fig, ax = plt.subplots(figsize=(params.W_THIRD, 6))
     bp = ax.boxplot(
         speed_clean,
         vert=True,
@@ -249,7 +249,7 @@ def plot_multi_aquadopp_trajectories(
         _bounds = _nice_colorbar_bounds(0.0, 1.0, n=20)
     norm: mcolors.BoundaryNorm = mcolors.BoundaryNorm(_bounds, ncolors=256)
 
-    fig, ax = plt.subplots(figsize=(6, 5))
+    fig, ax = plt.subplots(figsize=(params.W_FULL, 5), constrained_layout=True)
 
     for instr_i, x, y, temp in trajs:
         serial = str(serials[instr_i])
@@ -322,7 +322,6 @@ def plot_multi_aquadopp_trajectories(
         title = ds.attrs.get("id", "")
     if title:
         ax.set_title(title)
-    fig.tight_layout()
     return fig
 
 
@@ -368,10 +367,14 @@ def plot_hodograph(
     import pandas as pd
 
     instr_id = ds.attrs.get("id", "")
-    fig, axes = plt.subplots(1, 2, figsize=(12, 5))
-    fig.subplots_adjust(top=0.90)
+    # constrained_layout places the shared colorbar correctly against the
+    # equal-aspect ("box"-adjustable) panels; without it the colorbar overlaps
+    # the panel whitespace and appears to sit inside the axes.
+    fig, axes = plt.subplots(
+        1, 2, figsize=(params.W_FULL, 4.5), constrained_layout=True
+    )
     if instr_id:
-        fig.suptitle(instr_id, fontsize=10, y=0.995)
+        fig.suptitle(instr_id)
 
     if u_var not in ds.data_vars or v_var not in ds.data_vars:
         for ax in axes:
@@ -466,13 +469,13 @@ def _panel(ax: plt.Axes, e: np.ndarray, n: np.ndarray, title: str) -> None:
                 linewidths=0.5,
                 label="End",
             )
-            ax.legend(fontsize=7, loc="upper right", framealpha=0.7)
+            ax.legend(loc="upper right", framealpha=0.7)
         ax.axhline(0, color="#bbb", lw=0.7, zorder=0)
         ax.axvline(0, color="#bbb", lw=0.7, zorder=0)
         ax.set_aspect("equal", adjustable="box")
         ax.set_xlabel(f"East ({units})")
         ax.set_ylabel(f"North ({units})")
-        ax.set_title(title, fontsize=10)
+        ax.set_title(title)
         ax.grid(True, linestyle="--", linewidth=0.4, alpha=0.4)
 
     _panel(axes[0], east, north, f"Raw ({smooth_hours:.0f}-h smoothed)")
@@ -564,7 +567,7 @@ def plot_aquadopp_speed_profile(
     hab_range = max(hab_vals) - min(hab_vals) if len(hab_vals) > 1 else 10.0
     box_width = max(2.0, hab_range * 0.06)
 
-    fig, ax = plt.subplots(figsize=(5, max(3, len(records) * 0.7 + 1)))
+    fig, ax = plt.subplots(figsize=(params.W_HALF, max(3, len(records) * 0.7 + 1)))
 
     for hab, serial, spd_clean in records:
         bp = ax.boxplot(
@@ -701,7 +704,7 @@ def plot_adcp_trajectories(
         _bounds = _nice_colorbar_bounds(hab_min, hab_max, n=_n_hab)
     norm: mcolors.BoundaryNorm = mcolors.BoundaryNorm(_bounds, ncolors=256)
 
-    fig, ax = plt.subplots(figsize=(6, 5))
+    fig, ax = plt.subplots(figsize=(params.W_FULL, 5))
 
     for hab, x, y in trajs:
         points = np.array([x, y]).T.reshape(-1, 1, 2)
@@ -803,7 +806,7 @@ def _masked(flag_mask: "np.ndarray") -> "tuple[np.ndarray, np.ndarray]":
     fig, axs = plt.subplots(
         1,
         ncols,
-        figsize=(ncols * 3.0, 3.2),
+        figsize=(params.W_TWOTHIRDS, 3.2),
         subplot_kw={"projection": "polar"},
         squeeze=False,
     )
@@ -911,7 +914,7 @@ def draw_rose_grid(
     fig, axs = plt.subplots(
         nrows,
         ncols,
-        figsize=(ncols * 3.0, nrows * 3.2),
+        figsize=(params.W_FULL, nrows * 3.2),
         subplot_kw={"projection": "polar"},
         squeeze=False,
     )
@@ -988,7 +991,7 @@ def draw_grid_rose(ds: "xr.Dataset", max_roses: int = 4) -> "Optional[plt.Figure
     fig, axs = plt.subplots(
         nrows,
         ncols,
-        figsize=(ncols * 3.0, nrows * 3.2),
+        figsize=(params.W_FULL, nrows * 3.2),
         subplot_kw={"projection": "polar"},
         squeeze=False,
     )
@@ -1055,7 +1058,7 @@ def draw_grid_trajectory(ds: "xr.Dataset") -> "Optional[plt.Figure]":
     _bounds, norm = colorbar_norm(vmin=min(p_vals), vmax=max(p_vals))
     cmap = plt.get_cmap("viridis_r")  # shallow (low p) → light; deep → dark
 
-    fig, ax = plt.subplots(figsize=(6, 5))
+    fig, ax = plt.subplots(figsize=(params.W_HALF, 5))
 
     for p_val, x, y in trajs:
         points = np.array([x, y]).T.reshape(-1, 1, 2)
@@ -1223,7 +1226,7 @@ def draw_adcp_velocity(nc_path: str) -> "Optional[plt.Figure]":
 
         n = len(present)
         fig, axes = plt.subplots(
-            n, 1, figsize=(13, 3.5 * n), sharex=True, squeeze=False
+            n, 1, figsize=(params.W_FULL, 3.5 * n), sharex=True, squeeze=False
         )
 
         orientation = ds.attrs.get("orientation_yaml") or ds.attrs.get(
@@ -1374,7 +1377,7 @@ def draw_adcp_rose(nc_path: str) -> "Optional[plt.Figure]":
         fig, axs = plt.subplots(
             1,
             ncols,
-            figsize=(ncols * 3.2, 4.0),
+            figsize=(params.W_FULL, 4.0),
             subplot_kw={"projection": "polar"},
             squeeze=False,
         )
@@ -1505,7 +1508,7 @@ def draw_adcp_hodograph(
 
     from oceanarray.report._plots import _draw_hodograph_pair
 
-    fig, axes = plt.subplots(2, 2, figsize=(13, 9))
+    fig, axes = plt.subplots(2, 2, figsize=(params.W_FULL, 9))
     fig.subplots_adjust(hspace=0.55, wspace=0.45)
 
     _draw_hodograph_pair(
@@ -1612,8 +1615,9 @@ def draw_grid_hodograph(
 
     smooth_n = max(3, int(round(smooth_hours * 3600.0 / dt_s)))
 
-    fig, (ax_shallow, ax_deep) = plt.subplots(1, 2, figsize=(13, 6))
-    fig.subplots_adjust(wspace=0.45)
+    fig, (ax_shallow, ax_deep) = plt.subplots(
+        1, 2, figsize=(params.W_FULL, 4.5), constrained_layout=True
+    )
 
     for ax, i_lev, label in [
         (ax_shallow, i_shallow, f"Shallow ({label_shallow})"),
@@ -1626,7 +1630,7 @@ def draw_grid_hodograph(
             ax.text(
                 0.5, 0.5, "No data", transform=ax.transAxes, ha="center", va="center"
             )
-            ax.set_title(label, fontsize=9)
+            ax.set_title(label)
             continue
         t_frac = np.linspace(0.0, 1.0, len(east_2d[:, i_lev]))[mask]
         hodograph_panel(

oceanarray/plotters/diagnostic.py

@@ -677,24 +677,30 @@ def plot_clock_offset_check(
     nc_paths: "Dict[str, Path]",
     deploy_dt: "Optional[datetime]",
     recover_dt: "Optional[datetime]",
-    window_minutes: int = 10,
+    window_minutes: int = 30,
 ) -> "Optional[matplotlib.figure.Figure]":
-    """Overlaid temperature time series zoomed to deployment start and end.
+    """Overlaid, per-instrument normalised temperature around deploy and recover.
 
-    Plots the first and last *window_minutes* of the deployment for every
-    instrument that has a temperature variable, so that clock alignment
-    between instruments can be assessed visually.  If an instrument's clock
-    is offset the temperature signal will appear shifted in time relative to
-    the other instruments.
+    Plots a ``±window_minutes`` window centred on deployment and on recovery for
+    every instrument with a temperature variable, so clock alignment between
+    instruments can be assessed visually.  If an instrument's clock is offset the
+    temperature signal appears shifted in time relative to the others.
+
+    Each instrument's trace is **standardised over the plotted window**
+    (subtract the window mean, divide by the window standard deviation) so
+    instruments with different absolute temperatures and amplitudes overlay on a
+    common ``std`` y-axis and their *timing* can be compared directly.
 
     Two sub-panels are produced side by side:
 
-    - **Left**: first ``window_minutes`` minutes after ``deploy_dt``
-    - **Right**: last ``window_minutes`` minutes before ``recover_dt``
+    - **Left**: ``deploy_dt ± window_minutes``
+    - **Right**: ``recover_dt ± window_minutes``
 
     When ``deploy_dt`` or ``recover_dt`` is ``None``, only the available
     window is produced.  A shared legend below both panels lists all
-    instruments.
+    instruments.  An instrument with zero variance in a window (flat/constant)
+    is skipped for that window (no timing information, and normalisation is
+    undefined).
 
     Parameters
     ----------
@@ -756,16 +762,18 @@ def plot_clock_offset_check(
     windows: list = []
     if deploy_dt is not None:
         t0 = np.datetime64(deploy_dt.replace(tzinfo=None).isoformat())
-        windows.append((t0, t0 + _td, f"Start +{window_minutes} min"))
+        windows.append((t0 - _td, t0 + _td, f"Deployment ±{window_minutes} min"))
     if recover_dt is not None:
         t1 = np.datetime64(recover_dt.replace(tzinfo=None).isoformat())
-        windows.append((t1 - _td, t1, f"End −{window_minutes} min"))
+        windows.append((t1 - _td, t1 + _td, f"Recovery ±{window_minutes} min"))
     if not windows:
         return None
 
     n_panels = len(windows)
     with plt.style.context(str(params.MPLSTYLE)):
-        fig, axes = plt.subplots(1, n_panels, figsize=(5 * n_panels, 3.5), sharey=False)
+        fig, axes = plt.subplots(
+            1, n_panels, figsize=(params.W_FULL, 3.5), sharey=False
+        )
         if n_panels == 1:
             axes = [axes]
 
@@ -778,16 +786,21 @@ def plot_clock_offset_check(
                 mask = (t >= t_lo) & (t <= t_hi) & np.isfinite(temp)
                 if not np.any(mask):
                     continue
-                ax.plot(t[mask], temp[mask], color=colors[serial], lw=1.0)
+                tw = temp[mask]
+                sd = np.nanstd(tw)
+                if not np.isfinite(sd) or sd == 0:
+                    continue  # flat window: no timing info, normalisation undefined
+                tw_norm = (tw - np.nanmean(tw)) / sd
+                ax.plot(t[mask], tw_norm, color=colors[serial], lw=1.0)
                 plotted_serials.add(serial)
 
-            ax.set_title(title, fontsize=8)
+            ax.set_title(title)
             ax.set_xlabel("Time (UTC)")
-            ax.set_ylabel("Temperature (°C)")
+            ax.set_ylabel("Normalised temperature (std)")
+            ax.grid(True, linestyle="--", linewidth=0.4, alpha=0.3)
             locator = mdates.AutoDateLocator()
             ax.xaxis.set_major_locator(locator)
             ax.xaxis.set_major_formatter(mdates.ConciseDateFormatter(locator))
-            ax.tick_params(axis="x", labelsize=7)
 
         if plotted_serials:
             from matplotlib.lines import Line2D
@@ -802,7 +815,6 @@ def plot_clock_offset_check(
                 loc="lower center",
                 ncol=min(len(handles), 6),
                 bbox_to_anchor=(0.5, -0.05),
-                fontsize=7,
                 frameon=True,
             )
 
@@ -823,6 +835,7 @@ def draw_windows(
     show_qc: bool = True,
     vlines: Optional[list] = None,
     stage1_nc: Optional[Path] = None,
+    panels: Optional[list] = None,
 ) -> "Optional[plt.Figure]":
     """Combined start + end window figure: (nrows × 2) — left = first N h, right = last N h.
 
@@ -836,6 +849,10 @@ def draw_windows(
         Width of each window in hours (default 6).
     show_qc : bool
         Overlay QC flag markers on the data.
+    panels : list, optional
+        Subset of ``_instrument_panels`` tuples to draw.  When given, only these
+        rows are rendered (used to paginate a tall window figure across several
+        images); otherwise every panel for the instrument is drawn on one figure.
     vlines : list of (time_val, color, label), optional
         Vertical marker lines to draw on both panels.  *time_val* may be a
         ``numpy.datetime64``, an ISO-8601 string, or a ``pandas.Timestamp``.
@@ -890,16 +907,17 @@ def draw_windows(
         # One sample interval used to expand x-axis limits (stage2/3 fallback).
         _dt_one = (time[1] - time[0]) if len(time) > 1 else np.timedelta64(300, "s")  # noqa: F841
 
-        panels = _instrument_panels(ds, combine_pitch_roll=True)
+        if panels is None:
+            panels = _instrument_panels(ds, combine_pitch_roll=True)
         if not panels:
             return None
 
         height_ratios = [
-            _COMPACT_PANEL_HEIGHT if vname in _COMPACT_PANEL_VARS else 3.0
+            _COMPACT_PANEL_HEIGHT if vname in _COMPACT_PANEL_VARS else 2.0
             for vname, *_ in panels
         ]
         nrows = len(panels)
-        fig = plt.figure(figsize=(13, sum(height_ratios)))
+        fig = plt.figure(figsize=(params.W_FULL, sum(height_ratios)))
         gs = GridSpec(
             nrows,
             2,
@@ -1423,7 +1441,7 @@ def draw_velocity_iqr_profile(ds: "xr.Dataset") -> "Optional[plt.Figure]":
     fig, axs = plt.subplots(
         1,
         n_panels,
-        figsize=(n_panels * 3.5, 6),
+        figsize=(params.W_FULL, 4.5),
         sharey=True,
         gridspec_kw={"width_ratios": [2] * (n_panels - 1) + [1]},
     )