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fix(decompile): honour <c:delete> and <c:dLbls> on bar charts #21

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fix(decompile): honour <c:delete> and <c:dLbls> on bar charts #21

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146 changes: 94 additions & 52 deletions feinschliff/lib/dsl/pptx_svg_decompile.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1904,43 +1904,83 @@ def _emit_chart(chart_part, x0, y0, fw, fh, shapes, cmap, theme, palette):
else:
axis_max = math.ceil(data_max + 0.5) if data_max > 0 else 5

# Plot-area extents inside the frame (EMU). Match PowerPoint defaults:
# ~7% left for y-axis labels, ~12% top for cat labels, ~22% bottom for legend.
plot_x = x0 + int(fw * 0.07)
plot_y = y0 + int(fh * 0.12)
plot_w = int(fw * 0.91)
plot_h = int(fh * 0.66)

# Y-axis numeric labels on the left.
n_ticks = axis_max + 1
for i in range(n_ticks):
v = axis_max - i # top→bottom
ty = plot_y + int(plot_h * i / axis_max)
shapes.append(Shape(
kind="text",
x=cmap.x(x0 + int(fw * 0.005)),
y=cmap.y(ty - 180000),
w=cmap.w(int(fw * 0.05)),
h=cmap.h(360000),
text_runs=[TextRun(text=str(v), pt=14)],
))
# Axis visibility — `<c:valAx><c:delete val="1"/>` and `<c:catAx>
# <c:delete val="1"/>` hide the respective axis at render time. Many
# showcase charts use this for a clean look: bars/segments alone, no
# tick labels or category strings. Reading the flag from the source
# XML is much better than always emitting ticks (and then mismatching
# source pixels at every tick position).
val_axis_hidden = False
cat_axis_hidden = False
for ax in root.findall(f".//{{{CHART_NS}}}valAx"):
d = ax.find(f"{{{CHART_NS}}}delete")
if d is not None and d.get("val") in ("1", "true"):
val_axis_hidden = True
break
for ax in root.findall(f".//{{{CHART_NS}}}catAx"):
d = ax.find(f"{{{CHART_NS}}}delete")
if d is not None and d.get("val") in ("1", "true"):
cat_axis_hidden = True
break

# Data-label flags — `<c:dLbls>` controls whether value/category/series
# text gets drawn next to each bar. PowerPoint's structure puts this
# on the bar chart element itself (and optionally per-series). Read
# the top-level flags only for now; missing flags default to PPT's
# behaviour (no labels unless set).
def _dlbl_flag(parent, name: str) -> bool:
el = parent.find(f"{{{CHART_NS}}}dLbls/{{{CHART_NS}}}{name}")
return el is not None and el.get("val") in ("1", "true")
show_val_labels = _dlbl_flag(bar, "showVal")
show_cat_labels = _dlbl_flag(bar, "showCatName")

# Plot-area extents inside the frame (EMU). When the axes are hidden
# the plot can fill the frame edge-to-edge; otherwise reserve
# PowerPoint's typical insets for tick/category labels.
if val_axis_hidden and cat_axis_hidden:
plot_x = x0
plot_y = y0
plot_w = fw
plot_h = fh
else:
plot_x = x0 + int(fw * 0.07) if not val_axis_hidden else x0
plot_y = y0 + int(fh * 0.12) if not cat_axis_hidden else y0
plot_w = int(fw * (1.0 - 0.07 - 0.02)) if not val_axis_hidden else fw
plot_h = int(fh * (1.0 - 0.12 - 0.22)) if not cat_axis_hidden else int(fh * (1.0 - 0.22))

# Y-axis numeric labels — only when the value axis isn't hidden.
if not val_axis_hidden:
n_ticks = axis_max + 1
for i in range(n_ticks):
v = axis_max - i # top→bottom
ty = plot_y + int(plot_h * i / axis_max)
shapes.append(Shape(
kind="text",
x=cmap.x(x0 + int(fw * 0.005)),
y=cmap.y(ty - 180000),
w=cmap.w(int(fw * 0.05)),
h=cmap.h(360000),
text_runs=[TextRun(text=str(v), pt=14)],
))

# Skip gridlines: source has barely-visible hairlines; rendering them at
# 0.75pt over a 1240px-wide plot adds heavy diff pixels and emit_dsl
# orders lines after rects, so they paint OVER the bars producing stripes.

# Category labels above each group.
# Category labels above each group — only when the category axis
# isn't hidden AND the source explicitly enables them via dLbls.
cat_w = plot_w // n_cats if n_cats else plot_w
for ci in range(n_cats):
cx = plot_x + ci * cat_w + cat_w // 4
shapes.append(Shape(
kind="text",
x=cmap.x(cx),
y=cmap.y(plot_y - int(fh * 0.07)),
w=cmap.w(cat_w // 2),
h=cmap.h(int(fh * 0.06)),
text_runs=[TextRun(text=cats[ci] if ci < len(cats) else "", pt=14)],
))
if not cat_axis_hidden:
for ci in range(n_cats):
cx = plot_x + ci * cat_w + cat_w // 4
shapes.append(Shape(
kind="text",
x=cmap.x(cx),
y=cmap.y(plot_y - int(fh * 0.07)),
w=cmap.w(cat_w // 2),
h=cmap.h(int(fh * 0.06)),
text_runs=[TextRun(text=cats[ci] if ci < len(cats) else "", pt=14)],
))

# Bars: each category has n_series side-by-side bars. PowerPoint sizes
# them via `<c:gapWidth val="N"/>` where N is the inter-group gap as a
Expand Down Expand Up @@ -2008,16 +2048,17 @@ def _emit_chart(chart_part, x0, y0, fw, fh, shapes, cmap, theme, palette):
w=cmap.w(bw_), h=cmap.h(bar_h),
fill=color,
))
label = str(v).rstrip("0").rstrip(".") if "." in str(v) else str(v)
label = label.replace(".", ",")
shapes.append(Shape(
kind="text",
x=cmap.x(bx_ + bw_ + 50000),
y=cmap.y(by_),
w=cmap.w(int(fw * 0.08)),
h=cmap.h(int(bar_h)),
text_runs=[TextRun(text=label, pt=14)],
))
if show_val_labels:
label = str(v).rstrip("0").rstrip(".") if "." in str(v) else str(v)
label = label.replace(".", ",")
shapes.append(Shape(
kind="text",
x=cmap.x(bx_ + bw_ + 50000),
y=cmap.y(by_),
w=cmap.w(int(fw * 0.08)),
h=cmap.h(int(bar_h)),
text_runs=[TextRun(text=label, pt=14)],
))
else:
bar_w = int(cat_w / (n_series + gap_pct / 100))
group_w = bar_w * n_series
Expand All @@ -2034,17 +2075,18 @@ def _emit_chart(chart_part, x0, y0, fw, fh, shapes, cmap, theme, palette):
w=cmap.w(bar_w), h=cmap.h(bh),
fill=color,
))
# Value label above the bar.
label = str(v).rstrip("0").rstrip(".") if "." in str(v) else str(v)
label = label.replace(".", ",")
shapes.append(Shape(
kind="text",
x=cmap.x(bx - bar_w // 2),
y=cmap.y(by - 400000),
w=cmap.w(bar_w * 2),
h=cmap.h(360000),
text_runs=[TextRun(text=label, pt=14)],
))
# Value label above the bar — only when source enables it.
if show_val_labels:
label = str(v).rstrip("0").rstrip(".") if "." in str(v) else str(v)
label = label.replace(".", ",")
shapes.append(Shape(
kind="text",
x=cmap.x(bx - bar_w // 2),
y=cmap.y(by - 400000),
w=cmap.w(bar_w * 2),
h=cmap.h(360000),
text_runs=[TextRun(text=label, pt=14)],
))

# Legend at bottom-left.
legend_y = y0 + fh - int(fh * 0.12)
Expand Down
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