Update app.py

app.py

@@ -27,8 +27,8 @@ COLORS = {"pred": "#1f77b4", "actual": "#f2b702", "ref": "#5a5a5a"}
 CROSS_W = 500; CROSS_H = 500      # square cross-plot (Build + Validate)
 TRACK_W = 400; TRACK_H = 950      # log-strip style (all pages)
 FONT_SZ  = 15
-PLOT_COLS = [30, 1, 8]         # 3-column band: left • spacer • right (Build + Validate)
-CROSS_NUDGE = 0.5                # push cross-plot to the RIGHT inside its band:
+PLOT_COLS = [30, 1, 10]         # 3-column band: left • spacer • right (Build + Validate)
+CROSS_NUDGE = 0.1                # push cross-plot to the RIGHT inside its band:
                                   # inner columns [CROSS_NUDGE : 1] → bigger = more right
 
 # =========================
@@ -182,59 +182,55 @@ def cross_plot(actual, pred):
     a = pd.Series(actual).astype(float)
     p = pd.Series(pred).astype(float)
 
-    # Common min/max for BOTH axes (with a tiny pad)
-    lo = float(np.nanmin([a.min(), p.min()]))
-    hi = float(np.nanmax([a.max(), p.max()]))
-    pad = 0.03 * (hi - lo if hi > lo else 1.0)
-    lo -= pad
-    hi += pad
-
-    # Fixed tick spacing for BOTH axes
-    step  = _nice_step(lo, hi, target_ticks=6)
-    tick0 = step * math.floor(lo / step)
+    # Get global min/max across both actual and predicted
+    all_vals = pd.concat([a, p])
+    lo = float(np.floor(all_vals.min() / 100) * 100)
+    hi = float(np.ceil(all_vals.max() / 100) * 100)
 
     fig = go.Figure()
+
     fig.add_trace(go.Scatter(
         x=a, y=p, mode="markers",
         marker=dict(size=6, color=COLORS["pred"]),
         hovertemplate="Actual: %{x:.0f}<br>Pred: %{y:.0f}<extra></extra>",
         showlegend=False
     ))
-    # 45° reference
+
     fig.add_trace(go.Scatter(
-        x=[lo, hi], y=[lo, hi],
-        mode="lines", line=dict(color=COLORS["ref"], width=1.2, dash="dash"),
+        x=[lo, hi], y=[lo, hi], mode="lines",
+        line=dict(color=COLORS["ref"], width=1.2, dash="dash"),
         hoverinfo="skip", showlegend=False
     ))
 
-    # Identical range & ticks to BOTH axes
+    fig.update_layout(
+        width=CROSS_W, height=CROSS_H,
+        paper_bgcolor="#fff", plot_bgcolor="#fff",
+        margin=dict(l=64, r=18, t=10, b=48),
+        hovermode="closest",
+        font=dict(size=FONT_SZ)
+    )
+
+    # Set same range and ticks for both axes
     fig.update_xaxes(
-        range=[lo, hi],
-        tickmode="linear", tick0=tick0, dtick=step,
-        #fixedrange=True,   # remove this if you want zooming
+        title_text="<b>Actual UCS (psi)</b>",
+        range=[lo, hi], tickformat=",.0f",
+        ticks="outside",
         showline=True, linewidth=1.2, linecolor="#444", mirror=True,
-        showgrid=True, gridcolor="rgba(0,0,0,0.12)",
-        title_text="<b>Actual UCS (psi)</b>"
+        showgrid=True, gridcolor="rgba(0,0,0,0.12)", automargin=True
     )
     fig.update_yaxes(
-        range=[lo, hi],
-        tickmode="linear", tick0=tick0, dtick=step,
-        #fixedrange=True,   # remove this if you want zooming
+        title_text="<b>Predicted UCS (psi)</b>",
+        range=[lo, hi], tickformat=",.0f",
+        ticks="outside",
         showline=True, linewidth=1.2, linecolor="#444", mirror=True,
         showgrid=True, gridcolor="rgba(0,0,0,0.12)",
-        scaleanchor="x", scaleratio=1,
-        title_text="<b>Predicted UCS (psi)</b>"
+        scaleanchor="x", scaleratio=1, automargin=True
     )
 
-    fig.update_layout(
-        width=CROSS_W, height=CROSS_H,
-        paper_bgcolor="#fff", plot_bgcolor="#fff",
-        margin=dict(l=64, r=18, t=10, b=48), hovermode="closest",
-        font=dict(size=FONT_SZ)
-    )
     return fig
 
 
+
 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: