Update app.py

app.py

@@ -26,11 +26,14 @@ MODEL_FALLBACKS = [MODELS_DIR / "model.joblib", MODELS_DIR / "model.pkl"]
 COLORS = {"pred": "#1f77b4", "actual": "#f2b702", "ref": "#5a5a5a"}
 
 # ---- Plot sizing controls ----
-CROSS_W = 350; CROSS_H = 350      # square cross-plot
-TRACK_W = 400; TRACK_H = 950      # log-strip style
+CROSS_W = None          # let the chart fill the column
+CROSS_H = 420
+TRACK_W = None          # let the chart fill the column
+TRACK_H = 820
 FONT_SZ  = 15
-PLOT_COLS = [30, 1, 20]           # left • spacer • right
-CROSS_NUDGE = 0.02
+PLOT_COLS = [42, 2, 30]  # wider left & right, a thicker spacer in the middle
+CROSS_NUDGE = 0.0
+
 
 # =========================
 # Page / CSS
@@ -167,131 +170,59 @@ def _nice_tick0(xmin: float, step: int = 100) -> float:
 # =========================
 # Cross-plot (Matplotlib, static)
 # =========================
+# =========================
+# Cross plot (Matplotlib, fixed limits & ticks)
+# =========================
 def cross_plot_static(actual, pred):
-    a = pd.Series(actual).astype(float)
-    p = pd.Series(pred).astype(float)
+    a = pd.Series(actual, dtype=float)
+    p = pd.Series(pred,   dtype=float)
 
     fixed_min, fixed_max = 6000, 10000
-    ticks = np.arange(6000, 10001, 1000)
+    ticks = np.arange(fixed_min, fixed_max + 1, 1000)
 
-    fig, ax = plt.subplots(figsize=(CROSS_W/100, CROSS_H/100), dpi=100)
+    # use constrained_layout + generous margins so big labels never overlap
+    fig, ax = plt.subplots(
+        figsize=((CROSS_W or 500)/100, (CROSS_H or 500)/100),
+        dpi=100,
+        constrained_layout=True
+    )
 
-    ax.scatter(a, p, s=14, c=COLORS["pred"], alpha=0.9, edgecolors="none")
+    # points
+    ax.scatter(a, p, s=18, c=COLORS["pred"], alpha=0.9, linewidths=0)
 
     # 1:1 diagonal
     ax.plot([fixed_min, fixed_max], [fixed_min, fixed_max],
             linestyle="--", linewidth=1.2, color=COLORS["ref"])
 
-    # Limits and ticks
+    # identical axes limits + ticks
     ax.set_xlim(fixed_min, fixed_max)
     ax.set_ylim(fixed_min, fixed_max)
     ax.set_xticks(ticks)
     ax.set_yticks(ticks)
 
-    # Equal aspect for true 45°
-    ax.set_aspect('equal', adjustable='box')
+    # equal aspect → true 45° reference
+    ax.set_aspect("equal", adjustable="box")
 
-    # Thousands formatter
+    # thousands formatting
     fmt = FuncFormatter(lambda x, _: f"{int(x):,}")
     ax.xaxis.set_major_formatter(fmt)
     ax.yaxis.set_major_formatter(fmt)
 
-    # Labels (bold, larger)
+    # labels (bold, larger)
     ax.set_xlabel("Actual UCS (psi)", fontweight="bold", fontsize=16)
     ax.set_ylabel("Predicted UCS (psi)", fontweight="bold", fontsize=16)
 
-    # Grid & frame
+    # grid & frame
     ax.grid(True, linestyle=":", alpha=0.35)
     for spine in ax.spines.values():
-        spine.set_visible(True)
         spine.set_linewidth(1.2)
         spine.set_color("#444")
 
-    fig.tight_layout()
-    return fig
+    # extra room for the large labels
+    fig.subplots_adjust(left=0.23, bottom=0.20, right=0.98, top=0.98)
 
-# =========================
-# Track plot (Plotly)
-# =========================
-def track_plot(df, include_actual=True):
-    depth_col = next((c for c in df.columns if 'depth' in str(c).lower()), None)
-    if depth_col is not None:
-        y = pd.Series(df[depth_col]).astype(float)
-        ylab = depth_col
-        y_range = [float(y.max()), float(y.min())]  # reverse
-    else:
-        y = pd.Series(np.arange(1, len(df) + 1))
-        ylab = "Point Index"
-        y_range = [float(y.max()), float(y.min())]
-
-    # X (UCS) range & ticks
-    x_series = pd.Series(df.get("UCS_Pred", pd.Series(dtype=float))).astype(float)
-    if include_actual and TARGET in df.columns:
-        x_series = pd.concat([x_series, pd.Series(df[TARGET]).astype(float)], ignore_index=True)
-    x_lo, x_hi = float(x_series.min()), float(x_series.max())
-    x_pad = 0.03 * (x_hi - x_lo if x_hi > x_lo else 1.0)
-    xmin, xmax = x_lo - x_pad, x_hi + x_pad
-    tick0 = _nice_tick0(xmin, step=100)
-
-    fig = go.Figure()
-    fig.add_trace(go.Scatter(
-        x=df["UCS_Pred"], y=y, mode="lines",
-        line=dict(color=COLORS["pred"], width=1.8),
-        name="UCS_Pred",
-        hovertemplate="UCS_Pred: %{x:.0f}<br>"+ylab+": %{y}<extra></extra>"
-    ))
-    if include_actual and TARGET in df.columns:
-        fig.add_trace(go.Scatter(
-            x=df[TARGET], y=y, mode="lines",
-            line=dict(color=COLORS["actual"], width=2.0, dash="dot"),
-            name="UCS (actual)",
-            hovertemplate="UCS (actual): %{x:.0f}<br>"+ylab+": %{y}<extra></extra>"
-        ))
-
-    fig.update_layout(
-        width=TRACK_W, height=TRACK_H, paper_bgcolor="#fff", plot_bgcolor="#fff",
-        margin=dict(l=72, r=18, t=36, b=48), hovermode="closest",
-        font=dict(size=FONT_SZ),
-        legend=dict(
-            x=0.98, y=0.05, xanchor="right", yanchor="bottom",
-            bgcolor="rgba(255,255,255,0.75)", bordercolor="#ccc", borderwidth=1
-        ),
-        legend_title_text=""
-    )
-    fig.update_xaxes(
-        title_text="<b>UCS (psi)</b>", title_font=dict(size=18),
-        side="top", range=[xmin, xmax],
-        ticks="outside", tickformat=",.0f", tickmode="auto", tick0=tick0,
-        showline=True, linewidth=1.2, linecolor="#444", mirror=True,
-        showgrid=True, gridcolor="rgba(0,0,0,0.12)", automargin=True
-    )
-    fig.update_yaxes(
-        title_text=f"<b>{ylab}</b>", title_font=dict(size=18),
-        range=y_range, ticks="outside",
-        showline=True, linewidth=1.2, linecolor="#444", mirror=True,
-        showgrid=True, gridcolor="rgba(0,0,0,0.12)", automargin=True
-    )
     return fig
 
-# ---------- Preview modal (matplotlib) ----------
-def preview_tracks(df: pd.DataFrame, cols: list[str]):
-    cols = [c for c in cols if c in df.columns]
-    n = len(cols)
-    if n == 0:
-        fig, ax = plt.subplots(figsize=(4, 2))
-        ax.text(0.5,0.5,"No selected columns",ha="center",va="center")
-        ax.axis("off")
-        return fig
-    fig, axes = plt.subplots(1, n, figsize=(2.2*n, 7.0), sharey=True, dpi=100)
-    if n == 1: axes = [axes]
-    idx = np.arange(1, len(df) + 1)
-    for ax, col in zip(axes, cols):
-        ax.plot(df[col], idx, '-', lw=1.4, color="#333")
-        ax.set_xlabel(col); ax.xaxis.set_label_position('top'); ax.xaxis.tick_top(); ax.invert_yaxis()
-        ax.grid(True, linestyle=":", alpha=0.3)
-        for s in ax.spines.values(): s.set_visible(True)
-    axes[0].set_ylabel("Point Index")
-    return fig
 
 try:
     dialog = st.dialog