From 3ee25f9e33c9591396c4202fe7595c8c621ba073 Mon Sep 17 00:00:00 2001 From: Luigi Maiorano Date: Thu, 29 Jan 2026 15:36:34 +0100 Subject: [PATCH] ppt function to replace images --- 02_quant_analysis.py | 176 ++++++++++++++++++--------------------- 03_ppt_replace_images.py | 63 ++++++++++++++ plots.py | 2 +- pyproject.toml | 1 + utils.py | 83 ++++++++++++++++++ uv.lock | 97 +++++++++++++++++++++ 6 files changed, 326 insertions(+), 96 deletions(-) create mode 100644 03_ppt_replace_images.py diff --git a/02_quant_analysis.py b/02_quant_analysis.py index d997e26..43db699 100644 --- a/02_quant_analysis.py +++ b/02_quant_analysis.py @@ -29,18 +29,6 @@ def _(): @app.cell(hide_code=True) -def _(mo): - mo.outline(label="Table of Contents") - return - - -@app.cell -def _(): - # Select Dataset - return - - -@app.cell def _(mo): file_browser = mo.ui.file_browser( initial_path="./data/exports", multiple=False, restrict_navigation=True, filetypes=[".csv"], label="Select 'Labels' File" @@ -59,12 +47,6 @@ def _(Path, file_browser, mo): return QSF_FILE, RESULTS_FILE -@app.cell -def _(RESULTS_FILE, mo): - mo.stop(not RESULTS_FILE.name.lower().endswith('labels.csv'), mo.md("**⚠️ Make sure you select a `_Labels.csv` file above**")) - return - - @app.cell def _(JPMCSurvey, QSF_FILE, RESULTS_FILE, mo): S = JPMCSurvey(RESULTS_FILE, QSF_FILE) @@ -76,12 +58,6 @@ def _(JPMCSurvey, QSF_FILE, RESULTS_FILE, mo): @app.cell -def _(): - # check_straight_liners(S.get_ss_green_blue(data_all)[0]) - return - - -@app.cell(hide_code=True) def _(Path, RESULTS_FILE, mo): mo.md(f""" @@ -112,6 +88,26 @@ def _(check_progress, data_all, duration_validation, mo): return +@app.cell +def _(mo): + mo.md(r""" + ### ⚠️ ToDo: "straight-liner" detection and removal + """) + return + + +@app.cell +def _(mo): + mo.md(r""" + --- + + # Data Filter + + Use to select a subset of the data for the following analysis + """) + return + + @app.cell(hide_code=True) def _(S, mo): filter_form = mo.md(''' @@ -147,7 +143,7 @@ def _(S, mo): return (filter_form,) -@app.cell(hide_code=True) +@app.cell def _(S, data_all, filter_form, mo): mo.stop(filter_form.value is None, mo.md("**Please submit filter above to proceed**")) _d = S.filter_data(data_all, age=filter_form.value['age'], gender=filter_form.value['gender'], income=filter_form.value['income'], ethnicity=filter_form.value['ethnicity'], consumer=filter_form.value['consumer']) @@ -173,6 +169,20 @@ def _(S, data, mo): return (char_rank,) +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + + """) + return + + +@app.cell(hide_code=True) +def _(): + # char_rank = S.get_character_ranking(data)[0] + return + + @app.cell def _(S, char_rank, mo): mo.md(f""" @@ -218,6 +228,13 @@ def _(S, data, mo): return (v_18_8_3,) +@app.cell(hide_code=True) +def _(): + + # print(v_18_8_3.head()) + return + + @app.cell(hide_code=True) def _(S, mo, v_18_8_3): mo.md(f""" @@ -240,7 +257,7 @@ def _(S, mo, v_18_8_3): return -@app.cell(hide_code=True) +@app.cell def _(S, calculate_weighted_ranking_scores, data): top3_voices = S.get_top_3_voices(data)[0] top3_voices_weighted = calculate_weighted_ranking_scores(top3_voices) @@ -284,6 +301,11 @@ def _(S, mo, top3_voices): @app.cell +def _(): + return + + +@app.cell(hide_code=True) def _(S, data, mo, utils): ss_or, choice_map_or = S.get_ss_orange_red(data) ss_gb, choice_map_gb = S.get_ss_green_blue(data) @@ -322,12 +344,12 @@ def _(S, mo, pl, ss_long): return -@app.cell(hide_code=True) +@app.cell def _(): return -@app.cell +@app.cell(hide_code=True) def _(S, data, mo): vscales = S.get_voice_scale_1_10(data)[0] # plot_average_scores_with_counts(vscales, x_label='Voice', width=1000) @@ -337,7 +359,7 @@ def _(S, data, mo): return (vscales,) -@app.cell +@app.cell(hide_code=True) def _(S, mo, vscales): mo.md(f""" ### How does each voice score on a scale from 1-10? @@ -352,7 +374,7 @@ def _(): return -@app.cell(hide_code=True) +@app.cell def _(mo): mo.md(r""" @@ -360,7 +382,7 @@ def _(mo): return -@app.cell(hide_code=True) +@app.cell def _(mo): mo.md(r""" @@ -400,7 +422,7 @@ def _(choice_map, mo, ss_all, utils, vscales): return df_style, joined_df -@app.cell +@app.cell(hide_code=True) def _(S, SPEAKING_STYLES, joined_df, mo): _content = """### Total Results @@ -431,34 +453,18 @@ def _(mo): - [ ] 4 correlation diagrams considering each speaking style (4) and all female voice results. - [ ] 4 correlation diagrams considering each speaking style (4) and all male voice results. - """) - return -@app.cell(hide_code=True) -def _(mo): - mo.md(r""" + ## Correlations Voice Speaking Styles <-> Voice Ranking Points - """) - return - -@app.cell(hide_code=True) -def _(mo): - mo.md(r""" Let’s show how scoring better on these speaking styles correlates (or not) with better Vocie Ranking results. For each speaking style we show how the traits in these speaking styles correlate with voice ranking points. This gives us a total of 4 correlation diagrams. Example for speaking style green: - Trait 1: Friendly | Conversational | Down-to-earth - Trait 2: Approachable | Familiar | Warm - Trait 3: Optimistic | Benevolent | Positive | Appreciative - """) - return - -@app.cell(hide_code=True) -def _(mo): - mo.md(r""" ### Total Results - [ ] 4 correlation diagrams @@ -466,7 +472,31 @@ def _(mo): return -@app.cell +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + + """) + return + + +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + + """) + return + + +@app.cell(hide_code=True) +def _(mo): + mo.md(r""" + + """) + return + + +@app.cell(hide_code=True) def _(S, SPEAKING_STYLES, df_style, mo, top3_voices, utils): df_ranking = utils.process_voice_ranking_data(top3_voices) joined = df_style.join(df_ranking, on=['_recordId', 'Voice'], how='inner') @@ -490,7 +520,7 @@ def _(S, SPEAKING_STYLES, df_style, mo, top3_voices, utils): return -@app.cell(hide_code=True) +@app.cell def _(mo): mo.md(r""" ### Female / Male Voices considered seperately @@ -501,49 +531,5 @@ def _(mo): return -@app.cell(hide_code=True) -def _(mo): - mo.md(r""" - ## Correlation Heatmap all evaluations <-> voice acoustic data - - - [ ] Heatmap for male voices - - [ ] Heatmap for female voices - """) - return - - -@app.cell(hide_code=True) -def _(mo): - mo.md(r""" - ## Most Prominent Character Personality Traits - """) - return - - -@app.cell(hide_code=True) -def _(mo): - mo.md(r""" - The last question of the survey is about traits for the described character's personality. For each Character personality, we want to display the 8 most chosen character personality traits. This will give us a total of 4 diagrams, one for each character personality included in the test. - - - [ ] Bank Teller - - [ ] Familiar Friend - - [ ] The Coach - - [ ] Personal Assistant - """) - return - - -@app.cell -def _(mo): - mo.md(r""" - --- - - # Results per subgroup - - Use the dropdown selector at the top to filter the data and generate all the plots again - """) - return - - if __name__ == "__main__": app.run() diff --git a/03_ppt_replace_images.py b/03_ppt_replace_images.py new file mode 100644 index 0000000..1ff248b --- /dev/null +++ b/03_ppt_replace_images.py @@ -0,0 +1,63 @@ +import marimo + +__generated_with = "0.19.2" +app = marimo.App(width="medium") + +with app.setup: + import marimo as mo + from pathlib import Path + import utils + + +@app.cell +def _(): + PPT_FILE = Path('data/Presentation.pptx') + UPDATED_PPT_FILE = Path('data/Updated_Presentation.pptx') + return PPT_FILE, UPDATED_PPT_FILE + + +@app.cell +def _(): + IMAGE_FILE = Path('figures/OneDrive_2026-01-28/Cons-Early_Professional/cold_distant_approachable_familiar_warm.png') + return (IMAGE_FILE,) + + +@app.function +def image_alt_text_converter(fpath): + """convert image file path to alt text + """ + + if not isinstance(fpath, Path): + fpath = Path(fpath) + + fparts = fpath.parts + assert fparts[0] == 'figures', "Image file path must start with 'figures'" + + return Path('/'.join(fparts[2:])).as_posix() + + +@app.cell +def _(IMAGE_FILE): + img_alt_txt = image_alt_text_converter(IMAGE_FILE) + img_alt_txt + return (img_alt_txt,) + + +@app.cell +def _(IMAGE_FILE, PPT_FILE, UPDATED_PPT_FILE, img_alt_txt): + utils.pptx_replace_named_image( + presentation_path=PPT_FILE, + target_tag=img_alt_txt, + new_image_path=IMAGE_FILE, + save_path=UPDATED_PPT_FILE) + return + + +@app.cell +def _(P): + print(P.slides[10]) + return + + +if __name__ == "__main__": + app.run() diff --git a/plots.py b/plots.py index fd6861a..8c68bd6 100644 --- a/plots.py +++ b/plots.py @@ -496,7 +496,7 @@ class JPMCPlotsMixin: # Bar chart bars = alt.Chart(weighted_df).mark_bar(color=color).encode( - x=alt.X('Character:N', title=x_label), + x=alt.X('Character:N', title=x_label, sort='-y'), y=alt.Y('Weighted Score:Q', title=y_label), tooltip=[ alt.Tooltip('Character:N'), diff --git a/pyproject.toml b/pyproject.toml index 5fb45e7..8fe275d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -17,6 +17,7 @@ dependencies = [ "polars>=1.37.1", "pyarrow>=23.0.0", "pysqlite3>=0.6.0", + "python-pptx>=1.0.2", "pyzmq>=27.1.0", "requests>=2.32.5", "taguette>=1.5.1", diff --git a/utils.py b/utils.py index 757082d..a235a63 100644 --- a/utils.py +++ b/utils.py @@ -8,6 +8,89 @@ from plots import JPMCPlotsMixin import marimo as mo +from pptx import Presentation +from pptx.enum.shapes import MSO_SHAPE_TYPE + +def pptx_replace_named_image(presentation_path, target_tag, new_image_path, save_path): + """ + Finds and replaces specific images in a PowerPoint presentation while + preserving their original position, size, and aspect ratio. + + This function performs a 'surgical' replacement: it records the coordinates + of the existing image, removes it from the slide's XML, and inserts a + new image into the exact same bounding box. It identifies the target + image by searching for a specific string within the Shape Name + (Selection Pane) or Alt Text. + + Args: + presentation_path (str): The file path to the source .pptx file. + target_tag (str): The unique identifier to look for (e.g., 'HERO_IMAGE'). + This is case-sensitive and checks both the shape name and alt text. + new_image_path (str): The file path to the new image (PNG, JPG, etc.). + save_path (str): The file path where the modified presentation will be saved. + + Returns: + None: Saves the file directly to the provided save_path. + + Raises: + FileNotFoundError: If the source presentation or new image is not found. + PermissionError: If the save_path is currently open or locked. + """ + prs = Presentation(presentation_path) + + for i, slide in enumerate(prs.slides): + # Iterate over a list copy of shapes to safely modify the slide during iteration + print(f"Processing Slide {i + 1}...") + print(f"Total Shapes: {len(slide.shapes)} shapes") + + for shape in list(slide.shapes): + print(f"Checking shape: {shape.name} of type {shape.shape_type}...") + + shape_name = shape.name or "" + alt_text = "" + + # More robust strategy: Check for alt text in ANY valid element property + # This allows replacing Pictures, Placeholders, GraphicFrames, etc. + try: + # Check for common property names used by python-pptx elements to store non-visual props + # nvPicPr (Picture), nvSpPr (Shape/Placeholder), nvGrpSpPr (Group), + # nvGraphicFramePr (GraphicFrame), nvCxnSpPr (Connector) + nvPr = None + for attr in ['nvPicPr', 'nvSpPr', 'nvGrpSpPr', 'nvGraphicFramePr', 'nvCxnSpPr']: + if hasattr(shape._element, attr): + nvPr = getattr(shape._element, attr) + break + + if nvPr is not None and hasattr(nvPr, 'cNvPr'): + alt_text = nvPr.cNvPr.get("descr", "") + except Exception: + pass + + print(f"Alt Text for shape '{shape_name}': {alt_text}") + + if target_tag in shape_name or target_tag in alt_text: + print(f"Found it! Replacing {shape_name}...") + + try: + # Record coordinates + left, top, width, height = shape.left, shape.top, shape.width, shape.height + + # Remove old shape + old_element = shape._element + old_element.getparent().remove(old_element) + + # Add new image at the same spot + slide.shapes.add_picture(str(new_image_path), left, top, width, height) + except AttributeError: + print(f"Could not replace {shape_name} - might be missing dimensions.") + + else: + print(f"Skipping shape '{shape_name}' with alt text '{alt_text}'") + + prs.save(save_path) + print(f"Successfully saved to {save_path}") + + def extract_voice_label(html_str: str) -> str: """ Extract voice label from HTML string and convert to short format. diff --git a/uv.lock b/uv.lock index 0883f2b..3f6334c 100644 --- a/uv.lock +++ b/uv.lock @@ -840,6 +840,86 @@ wheels = [ { url = 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