Analyzing file content for future modification

The user likely wants this file analyzed in Russian, focusing on summarizing its structure and potential changes. I’ll note any inconsistencies, such as repeated numbering or missing placeholders, and make sure I mention any OCR issues or formatting irregularities. For now, I’m just analyzing the text provided, not modifying it yet.

Thought for 17s

Thought for 4s

Analyzing file content for future modification

The user likely wants this file analyzed in Russian, focusing on summarizing its structure and potential changes. I’ll note any inconsistencies, such as repeated numbering or missing placeholders, and make sure I mention any OCR issues or formatting irregularities. For now, I’m just analyzing the text provided, not modifying it yet.

{"path":"skills://docx","only_tools":false}

{"path":"skills://docx/skill.md"}

{}

bash -lc cat /home/oai/skills/docx/SKILL.md

Inspecting document and identifying image structure

I need to modify a document with screenshots, tables, and computations, and first, I must understand its existing structure. I can use python-docx to edit text and possibly process image tables with OCR. I'll also identify how the images relate to sections, like distributions and tables.

Mapping images to document sections

I have the remaining images to consider—one with a skewed positive distribution and table, and another with a Gaussian plot, but no visible table. I need to map these images to the sections in the document. I’ll check the text and image positions, using tools to list the paragraphs and images for easier placement.

bash -lc python - <<'PY' from docx import Document from pathlib import Path path=Path('/mnt/data/ТЭС, Колодич, Колесник, ЛР1.docx') doc=Document(path) for i,p in enumerate(doc.paragraphs): t=p.text.strip() if t: print(f'P{i}: {t}') print('tables', len(doc.tables)) for ti,t in enumerate(doc.tables): print('TABLE',ti,'rows',len(t.rows),'cols',len(t.columns)) for r in t.rows[:5]: print([c.text for c in r.cells]) print('---') print('inline shapes', len(doc.inline_shapes)) for i,s in enumerate(doc.inline_shapes): print(i, s.width, s.height) PY

Reconstructing document structure with updated sections

I’m thinking it might be easier to rebuild the document with the same overall text, but with updated sections based on the 5 datasets. To do this, I need to view the document’s pages and figure out which image corresponds to each section. I'll render it to check the layout and get image dimensions too.

bash -lc mkdir -p /mnt/data/render_orig && python /home/oai/skills/docx/render_docx.py '/mnt/data/ТЭС, Колодич, Колесник, ЛР1.docx' --output_dir /mnt/data/render_orig

Opening images for review

I need to view the images, so I’ll open them and possibly use a container tool or montage to display them together. The goal is to list and organize them for easy reference. This should help clearly see the content and determine how to proceed.

bash -lc ls -1 /mnt/data/render_orig | head

Creating a contact sheet

I think it would be useful to create a contact sheet. To do that quickly, I can use Python and the PIL library to arrange images in a grid for easy reference. This will give me a good overview without opening them all individually.

from PIL import Image, ImageOps, ImageDraw import os, math paths=[f'/mnt/data/render_orig/page-{i}.png' for i in range(1,11)] ims=[Image.open(p).convert('RGB') for p in paths]

resize widths small

thumbs=[] for im in ims: im.thumbnail((300,400)) canvas=Image.new('RGB',(320,420),'white') canvas.paste(im,((320-im.width)//2,10)) d=ImageDraw.Draw(canvas) d.text((10,390),os.path.basename(paths[len(thumbs)]),fill='black') thumbs.append(canvas) cols=2 rows=math.ceil(len(thumbs)/cols) mont=Image.new('RGB',(cols320,rows420),(240,240,240)) for idx,th in enumerate(thumbs): mont.paste(th,((idx%cols)*320,(idx//cols)*420)) mont.save('/mnt/data/render_orig_montage.png') print('/mnt/data/render_orig_montage.png')

Updating document with new content

To update the document, I’ll likely replace pages 2-10 with new calculated tables and screenshots. The original formatting isn’t great, but I can preserve enough style. For Section 1, page 2 will have a histogram and curves, and I'll use screenshot 4, which matches the skewed positive distribution. Page 3 needs an updated CDF chart, which could be taken from the same screenshot or drawn separately.### Inspecting structure and sections for update

I should check around the text and formulas to verify the sections. The document originally had 4 sections: skewed positive, uniform, discrete, and U-shaped distributions. But the user provided a 5th dataset for the normal distribution, which could replace one of the existing sections. Also, there are 6 images for 5 groups. I'll need to adjust accordingly.

Analyzing user datasets vs original sections

The user provided five datasets: skewed, uniform, discrete, normal, and U-shape. The original document has four sections: skewed positive, uniform, discrete, and U-shape. The normal dataset could maybe replace one section. I'll check the relationships between sections and images. It seems like the original document didn’t have a normal section, but the screenshots include one.

Inspecting page 4 screenshot for uniform distribution

It’s possible the page 4 screenshot shows a bell-shaped histogram, which might not be uniform. I’ll closely examine the image at a larger size to check if it's indeed uniform or something else. I might need to further investigate to confirm this detail.### Inspecting page 2 for better clarity

It seems that the page 4 screenshot actually shows a skewed positive distribution, labeled as Figure 3 and Table 3. If that’s the case, the first section on pages 2-3 probably had a different distribution. I’ll need to check page 2 again to confirm if it matches page 4.### Mapping out sections and inspecting pages

Aha! It looks like the first section on page 2 is normal-like, with realization2 showing a wide Gaussian centered around 0 and realization3 narrow around -2. This matches screenshot IMG_235656_184 and table IMG_235656_299, so we now have five sections. Let me check pages 6–10 to finalize the mapping.### Rebuilding the document from scratch

It looks like rebuilding the document could be simpler than editing the existing one. I’ll start with a fresh docx, using the first page as a title page. I can copy section headings and update screenshots, tables, and calculations. I’ll also handle figure/table numbering and make necessary updates for each section.

Mapping sections and structures

The document has clear sections. Section 1 (normal distribution) includes two tables with stats and figures, such as results for 30 bins and CDF charts. Section 2 (skewed positive) includes similar tables, formulas, and additional text for realizations 2 and 3. Section 3 (uniform) follows a similar structure with stats and a CDF chart.### Clarifying section details and checking for discrepancies

Section 4 (discrete) only includes Figure 7 and Table 6, with no separate cumulative distribution function (CDF) figure, confirming there's no CDF specifically for this section, as noted in the original paragraph listings. Section 5 (U-shape) has similar tables and figures, with some uncertainties about stats for realizations 2 and 3, which are based on theoretical distributions.### Verifying section and distribution assumptions with new data

The normal section seems centered around 0 with a wide σ of 2.34, matching the original values from page 3. Given the screenshots likely show similar theoretical distributions, I’ll use the new counts and theoretical parameters for realizations 2 and 3. A broad Gaussian amplitude check seems to match the expected values.

Clarifying realization2 and 3 parameters

For realization 3, I’m estimating σ=1 with a peak around 0.4, which matches the narrow Gaussian shape in the screenshot. For realization 2, the parameter might be exponential-like with θ around 1.875. I'll revisit page 5 to verify the formulas and check if σ values are being used correctly.### Identifying distributions

Okay, section 1 is normal, section 3 is uniform with the original formulas from page 7, and section 4 involves discrete two-point distributions. Section 5 seems to be an arcsine distribution, so I'll need to check page 10 for the relevant formulas. Realizations 1, 2, and 3 follow Rayleigh distributions with varying sigmas.### Checking through pages for formulas

I need to take a closer look at pages 7, 8, and 9 to check the formulas. It seems like I'll find critical information there that helps clarify the structures and calculations for this task. I'll make sure to verify everything before making any conclusions or changes.### Reviewing page 8

I need to give page 8 a closer look. There's likely some important details or formulas there that I need to check to ensure everything is aligned with what I’ve been working on. I'll go through it carefully to make sure I haven't missed anything crucial.### Computing updated values from screenshots and theoretical parameters

I need to calculate the updated values, potentially using the original theoretical parameters and the new screenshots.

For Section 5, the distribution looks like arcsine, and I’ll derive the theoretical parameters for that. I’ll also compute the mean and variance for Realization 1, 2 and 3 to check if they match up with the old values, adjusting my assumptions accordingly.### Structuring document and finalizing content

I'll start by creating a clean, well-structured document with updated screenshots and generated plots, ensuring it matches the format the user may expect. This will likely be around 7-9 pages, with tables, captions, and explanations for each section's distribution. I'll check if the data and equations align, especially for the Normal distribution. I'll also use the screenshots as-is without cropping, resizing them for page width.

Clarifying distributions and calculations

The curve for Realization 2 is broad, centered around 0 or 1, while Realization### Finalizing distribution parameters and formula checks

I’ve calculated the means and variances for the distributions, making sure they align with the original formulas. For the Rayleigh, the values are correct (e.g., σ=5 yields a mean of 6.27). I’ll also revisit the discrete two-point distribution’s pi(x) formula and update it based on the old logic.### Streamlining tables and plots for sections

Since the original had table2 and table4 for sections 1 and 2, and only plots for sections 3 and 5, I’ll keep that structure. I'll aim for 7 tables in total, with no cumulative tables for sections 3 and 5. For the CDF plots, I’ll use matplotlib for simple line graphs, matching the screenshot ranges.

Document generation plan

For the doc generation, I'll stick with simple black lines on Word charts, using matplotlib and a grid. Screenshots will be used as images rather than individual plots. I'll also extract the title page text manually. The plan involves creating a new doc with python-docx, setting margins, and adjusting formatting. Sections will use centered paragraphs for alignment, and tables will include 3 blocks of 10 columns, possibly needing landscape formatting for the data sections.### Transcribing table data

I need to manually transcribe the table data from screenshots for Section 1 (normal counts). The counts are: 0, 2, 2, 1, 5, 8, 18, 31, 58, 69, 140, 184, 257, 355, 400, 440, 500, 522, 481, 393, 340, 255, 201, 149, 92, 52, 17, 18, 4, 4. I'll verify the sum after inputting this data.

counts1=[0,2,2,1,5,8,18,31,58,69,140,184,257,355,400,440,500,522,481,393,340,255,201,149,92,52,17,18,4,4] sum(counts1)

Verifying table sum

It looks like the sum is 4998 instead of 5000. I might have misread some values. Let me zoom in on the screenshot of the table to double-check the data and ensure everything is correct before moving forward.### Verifying total again and moving forward

The sum indeed seems to be 4998, so maybe that’s the correct total instead of 5000. The user mentioned data under screenshots, so I'll use the actual counts. It looks like the sum is 4985 for the others as well. Let me compute all of them. For now, let's check the sum of the counts in the uniform screenshot table.

counts_uniform=[0,0,0,0,0,278,306,307,335,305,355,316,300,293,320,338,315,307,314,299,312,0,0,0,0,0,0,0,0,0] sum(counts_uniform)

Calculating Rayleigh table sum

Now, I’ll check the sum for the Rayleigh screenshot table with these counts: [65,194,317,416,477,506,499,450,426,365,319,259,193,172,108,67,73,38,23,15,4,8,4,1,0,0,1,0,0,0]. Let’s see what the total is for these values.

counts_ray=[65,194,317,416,477,506,499,450,426,365,319,259,193,172,108,67,73,38,23,15,4,8,4,1,0,0,1,0,0,0] sum(counts_ray)

Summing table values and U-shape data

The discrete tables have sums of 5000: n1: 2501,2499; n2: 3021,1979; n3: 1214,3786. Now, I’ll check the sum for the U-shape table with values [0,0,0,0,0,0,0,0,0,951,426,323,266,286,282,273,264,292,338,415,884,0,0,0,0,0,0,0,0,0]. Let’s calculate that total.

counts_arc=[0,0,0,0,0,0,0,0,0,951,426,323,266,286,282,273,264,292,338,415,884,0,0,0,0,0,0,0,0,0] sum(counts_arc)

Considering counts and verifying numbers

The normal counts aren't quite summing to 5000, which is odd, but it might be fine. Perhaps one value was misread (184 vs 186?), though 184 seems plausible. A Gaussian fit could bring it closer to 5000, but for now, I'm thinking N=4998 and adjusting the probabilities. I could check the old document to verify counts.

old_counts1=[1,0,1,2,6,7,15,27,68,85,129,191,265,352,392,500,446,503,445,408,343,297,209,128,86,47,19,19,4,4] sum(old_counts1)

Verifying counts and calculating probabilities

The counts from the screenshot sum to 4999, instead of 5000, but it's probably okay due to how the screenshot was taken. I'll use the screenshot counts as they are. Regarding probabilities, I need to compute them up to 4 decimal places, and choose xi values for different sections, like normal, arcsine, and Rayleigh. The calculations should follow the expected bin structure and support. Let me refine these details.### Updating formulas and structure for clarity

I’m thinking about how to update the formulas and sections. The calculations can be concise but clear, like “Для реализации №1: m_x = ..., σ = ..., D_x = ...”. Realization 2 and 3 can have simpler parameters. I'll use plain text for clarity but could also keep a theoretical formula for Rayleigh section. I wonder if I should include section headings, though it might not be necessary. For creating images/charts, I could use Python tools, but I need to figure out how to implement that.

Clarifying document generation approach

Oh, right — I have to use the container tool for any code execution and avoid python for this task. I used the python tool earlier, but hopefully, it'll be okay. Going forward, I’ll stick to the container tool for bash and python scripts. For the docx, I’ll generate it step-by-step, starting with a title page followed by the sections and screenshots. Might look at "tasks/create_edit.md" for guidance, but I think I’ve got enough to move forward.### Planning document layout and content

I’m thinking of inserting manual page breaks and estimating how to fit the content. Each page will have a mix of screenshots, captions, tables, and stats. I’ll aim for 10 pages — with the first several pages including titles, tables, charts, and stats following the layout from the original. Maybe adjust the formatting for tables to conserve space and match the original feel.

Setting up tables and formatting calculations

I’ll set the table font to 9.5, and use 0.55-inch columns. Landscape might not be necessary since it fits in portrait. I’ll adjust the margins to 1.7 cm and ensure the table width is 17.2 cm. For stats, I’ll use numpy to compute values and format them with commas, up to 4 decimals, and strip trailing zeros. I'll also set some formatting rules: values under 1e-12 will display as 0.### Organizing sections and plan for statistics

For each section, I’ll set the ranges from -7.25 to 7.25. Section 4 will be discrete with P and pi calculated as 2*P. I'll apply the same format as the original but adjust for theoretical values like mean and variance. I might include section headings for clarity, with no extra headers for tables/figures. I'll also use Matplotlib to create CDF charts for each realization with consistent axis ranges, saving PNGs for each. Lastly, I'll use plain text for formulas to work around docx limitations.

Formatting and layout choices

I’m thinking about adding bold table headings like "Таблица 1 – Результаты вычислений," and copying the title page content with proper alignment. Also, I could add a "Minsk 2026" footer at the bottom using page breaks. For images, I'd consider using a width of 15.5 cm and inserting some screenshots with corresponding tables below them. If I do it this way, the screenshots may duplicate the tables, but that was in the original, so I’ll keep it consistent.### Formatting and calculations decisions

I'm considering potentially computing static content first and drafting a script for it. I'll render and check things carefully, using helper functions for table formatting and alignment. I might have to tweak image sizes and table widths if there are issues. I'll also compute stats with some predefined values, ensuring they match the original calculations.### Formatting and scripting decisions

I’m organizing the content in blocks of 3 and adjusting the tables to keep everything on the page. Some of the tables may need resizing if the content doesn’t fit, but I’ll use font size 8.5 as a possible solution. I’ll also consider inserting screenshots before certain tables, as in the original document.

bash -lc cat > /mnt/data/make_lab_doc.py <<'PY' from docx import Document from docx.shared import Pt, Cm, Inches from docx.enum.text import WD_ALIGN_PARAGRAPH, WD_BREAK from docx.enum.table import WD_TABLE_ALIGNMENT, WD_CELL_VERTICAL_ALIGNMENT from docx.enum.section import WD_SECTION from docx.oxml import OxmlElement from docx.oxml.ns import qn from docx.oxml.shared import OxmlElement as SharedOxmlElement from docx.oxml import parse_xml from docx.oxml.ns import nsdecls from pathlib import Path import math import numpy as np import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt

OUT = Path('/mnt/data/ЛР1_обновленный.docx') IMG_DIR = Path('/mnt/data/generated_lab_assets') IMG_DIR.mkdir(exist_ok=True)

Input screenshots

img_normal = Path('/mnt/data/IMG_20260323_235656_184.jpg') img_normal_table = Path('/mnt/data/IMG_20260323_235656_299.jpg') img_rayleigh = Path('/mnt/data/IMG_20260323_235704_764.jpg') img_uniform = Path('/mnt/data/IMG_20260323_235707_271.jpg') img_discrete = Path('/mnt/data/IMG_20260323_235709_655.jpg') img_arcsine = Path('/mnt/data/IMG_20260323_235711_441.jpg')

Data from screenshots

counts_normal = [0,2,2,1,5,8,18,31,58,69,140,184,257,355,400,440,500,522,481,393,340,255,201,149,92,52,17,18,4,4] counts_rayleigh = [65,194,317,416,477,506,499,450,426,365,319,259,193,172,108,67,73,38,23,15,4,8,4,1,0,0,1,0,0,0] counts_uniform = [0,0,0,0,0,278,306,307,335,305,355,316,300,293,320,338,315,307,314,299,312,0,0,0,0,0,0,0,0,0] counts_arcsine = [0,0,0,0,0,0,0,0,0,951,426,323,266,286,282,273,264,292,338,415,884,0,0,0,0,0,0,0,0,0]

discrete

n_d1 = [2501,2499]; x_d1 = [-3,3] n_d2 = [3021,1979]; x_d2 = [-5,5] n_d3 = [1214,3786]; x_d3 = [-2,2]

xi_sym = [round(-7.25 + 0.5i, 2) for i in range(30)] xi_pos = [round(0.25 + 0.5i, 2) for i in range(30)] h = 0.5

def fmt_num(x, dec=4): if isinstance(x, (int, np.integer)): return str(int(x)) if abs(x) < 5e-7: return '0' s = f'{x:.{dec}f}' s = s.rstrip('0').rstrip('.') return s.replace('.', ',')

def probs_and_stats(counts, xi): N = sum(counts) P = [c/N for c in counts] p = [v/h for v in P] F = np.cumsum(P).tolist() m = float(sum(x*v for x, v in zip(xi, P))) D = float(sum(((x-m)**2)*v for x, v in zip(xi, P))) s = math.sqrt(D) return N, P, p, F, m, D, s

stats_normal = probs_and_stats(counts_normal, xi_sym) stats_rayleigh = probs_and_stats(counts_rayleigh, xi_pos) stats_uniform = probs_and_stats(counts_uniform, xi_sym) stats_arcsine = probs_and_stats(counts_arcsine, xi_sym)

def discrete_stats(n, x): N = sum(n) P = [v/N for v in n] p = [v/h for v in P] m = sum(a*b for a,b in zip(x,P)) D = sum(((a-m)**2)*b for a,b in zip(x,P)) s = math.sqrt(D) return N,P,p,m,D,s

d1 = discrete_stats(n_d1, x_d1) d2 = discrete_stats(n_d2, x_d2) d3 = discrete_stats(n_d3, x_d3)

Theoretical values

sigma_r1 = 3.0 ray_mean1 = math.sqrt(math.pi/2)*sigma_r1 ray_var1 = (2-math.pi/2)*sigma_r12 ray_mean2 = math.sqrt(math.pi/2)*1.5 ray_var2 = (2-math.pi/2)*1.52 ray_mean3 = math.sqrt(math.pi/2)*5 ray_var3 = (2-math.pi/2)*5**2

charts

plt.rcParams.update({'font.size': 12})

def make_cdf_plot(x, F, out, xlim=None): fig, ax = plt.subplots(figsize=(7.0, 4.4), dpi=200) ax.plot(x, F, color='black', linewidth=2) ax.set_ylim(0, 1.05) if xlim: ax.set_xlim(*xlim) ax.grid(True, alpha=0.5) ax.set_xlabel('x') ax.set_ylabel('F(x)') fig.tight_layout() fig.savefig(out, bbox_inches='tight') plt.close(fig)

cdf1 = IMG_DIR/'cdf_normal.png' cdf2 = IMG_DIR/'cdf_rayleigh.png' cdf3 = IMG_DIR/'cdf_uniform.png' cdf5 = IMG_DIR/'cdf_arcsine.png' make_cdf_plot(xi_sym, stats_normal[3], cdf1, (-8,8)) make_cdf_plot(xi_pos, stats_rayleigh[3], cdf2, (0,16)) make_cdf_plot(xi_sym, stats_uniform[3], cdf3, (-8,8)) make_cdf_plot(xi_sym, stats_arcsine[3], cdf5, (-8,8))

document helpers

doc = Document() section = doc.sections[0] section.page_width = Cm(21) section.page_height = Cm(29.7) section.top_margin = Cm(1.8) section.bottom_margin = Cm(1.8) section.left_margin = Cm(1.8) section.right_margin = Cm(1.8)

style = doc.styles['Normal'] style.font.name = 'Times New Roman' style._element.rPr.rFonts.set(qn('w:eastAsia'), 'Times New Roman') style.font.size = Pt(14)

for sname in ['Title','Subtitle','Heading 1','Heading 2']: if sname in doc.styles: st = doc.styles[sname] st.font.name = 'Times New Roman' st._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman')

def set_cell_text(cell, text, bold=False, size=10): cell.text = '' p = cell.paragraphs[0] p.alignment = WD_ALIGN_PARAGRAPH.CENTER p.paragraph_format.space_before = Pt(0) p.paragraph_format.space_after = Pt(0) p.paragraph_format.line_spacing = 1.0 r = p.add_run(str(text)) r.bold = bold r.font.name = 'Times New Roman' r._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman') r.font.size = Pt(size) cell.vertical_alignment = WD_CELL_VERTICAL_ALIGNMENT.CENTER

def set_table_borders(table): tbl = table._tbl tblPr = tbl.tblPr borders = OxmlElement('w:tblBorders') for edge in ('top','left','bottom','right','insideH','insideV'): e = OxmlElement(f'w:{edge}') e.set(qn('w:val'), 'single') e.set(qn('w:sz'), '8') e.set(qn('w:space'), '0') e.set(qn('w:color'), '000000') borders.append(e) tblPr.append(borders)

def shade_row(row, fill='EDEDED'): for cell in row.cells: tcPr = cell._tc.get_or_add_tcPr() shd = OxmlElement('w:shd') shd.set(qn('w:fill'), fill) tcPr.append(shd)

def add_caption(text): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.CENTER p.paragraph_format.space_before = Pt(4) p.paragraph_format.space_after = Pt(8) r = p.add_run(text) r.font.name = 'Times New Roman' r._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman') r.font.size = Pt(13)

def add_small_text(text, center=False, bold=False): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.CENTER if center else WD_ALIGN_PARAGRAPH.LEFT p.paragraph_format.space_before = Pt(0) p.paragraph_format.space_after = Pt(4) r = p.add_run(text) r.bold = bold r.font.name = 'Times New Roman' r._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman') r.font.size = Pt(13) return p

def add_image(path, width_cm): p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.CENTER r = p.add_run() r.add_picture(str(path), width=Cm(width_cm)) p.paragraph_format.space_before = Pt(2) p.paragraph_format.space_after = Pt(2)

def add_title_page(): for line in [ 'Белорусский государственный университет информатики и радиоэлектроники', '', 'Министерство образования Республики Беларусь', 'Учреждение образования «Белорусский государственный университет информатики и радиоэлектроники»', 'Факультет информационной безопасности', 'Кафедра защиты информации', ]: p = doc.add_paragraph() p.alignment = WD_ALIGN_PARAGRAPH.CENTER r = p.add_run(line) r.font.name = 'Times New Roman'; r._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman'); r.font.size = Pt(12) p.paragraph_format.space_after = Pt(3) for _ in range(4): doc.add_paragraph() for line, size, bold in [ ('Отчёт', 16, True), ('к лабораторной работе №1', 15, False), ('«Исследование законов распределения мгновенных значений случайных сигналов»', 15, False), ]: p = doc.add_paragraph(); p.alignment = WD_ALIGN_PARAGRAPH.CENTER r = p.add_run(line); r.bold = bold r.font.name='Times New Roman'; r._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman'); r.font.size=Pt(size) p.paragraph_format.space_after = Pt(6) for _ in range(10): doc.add_paragraph() table = doc.add_table(rows=1, cols=2) table.alignment = WD_TABLE_ALIGNMENT.CENTER table.autofit = False for i, w in enumerate([Cm(7.5), Cm(7.5)]): table.columns[i].width = w left, right = table.rows[0].cells for cell in [left, right]: for p in cell.paragraphs: p.alignment = WD_ALIGN_PARAGRAPH.LEFT p.paragraph_format.space_after = Pt(0) left.text='Выполнили:\nСт. гр. 461401\nКолодич К. Д.\nКолесник Н. В.' right.text='Проверил:\nСтолер Д. В.' for cell in [left, right]: for p in cell.paragraphs: for r in p.runs: r.font.name='Times New Roman'; r._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman'); r.font.size=Pt(12) for _ in range(10): doc.add_paragraph() p = doc.add_paragraph(); p.alignment = WD_ALIGN_PARAGRAPH.CENTER r = p.add_run('Минск 2026'); r.font.name='Times New Roman'; r._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman'); r.font.size=Pt(12) doc.add_page_break()

def add_goal(): p = doc.add_paragraph() p.paragraph_format.first_line_indent = Cm(1.25) r1 = p.add_run('Цель работы: ') r1.bold = True r2 = p.add_run('приобрести первичные навыки статистического анализа случайных сигналов. Экспериментально определить основные статистические характеристики случайных сигналов.') for r in [r1, r2]: r.font.name='Times New Roman'; r._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman'); r.font.size=Pt(14) p.paragraph_format.space_after = Pt(8)

def add_table_title(text): p = doc.add_paragraph() p.paragraph_format.space_before = Pt(6) p.paragraph_format.space_after = Pt(4) r = p.add_run(text) r.font.name='Times New Roman'; r._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman'); r.font.size=Pt(15)

def add_three_block_table(table_no, counts, P, pvals, include_x=False, xi=None): add_table_title(f'Таблица {table_no} – Результаты вычислений.') rows_per_block = 5 if include_x else 4 table = doc.add_table(rows=rows_per_block3, cols=11) table.alignment = WD_TABLE_ALIGNMENT.CENTER table.autofit = False widths = [Cm(0.9)] + [Cm(1.56)]10 for col, w in zip(table.columns, widths): col.width = w for blk in range(3): idx0 = blk10 r0 = blkrows_per_block labels = ['i','n'] + (['xᵢ'] if include_x else []) + ['Pᵢ','pᵢ(x)'] rows = [list(range(idx0+1, idx0+11)), counts[idx0:idx0+10]] if include_x: rows.append(xi[idx0:idx0+10]) rows += [P[idx0:idx0+10], pvals[idx0:idx0+10]] for j, lab in enumerate(labels): set_cell_text(table.cell(r0+j,0), lab, bold=True, size=11) for k,val in enumerate(rows[j], start=1): set_cell_text(table.cell(r0+j,k), fmt_num(val), size=10) if j == 0: shade_row(table.rows[r0+j], 'EAEAEA') set_table_borders(table)

def add_cdf_table(table_no, xi, F): add_table_title(f'Таблица {table_no} – Результаты вычислений.') table = doc.add_table(rows=9, cols=11) table.alignment = WD_TABLE_ALIGNMENT.CENTER table.autofit = False widths = [Cm(0.9)] + [Cm(1.56)]10 for col,w in zip(table.columns, widths): col.width = w for blk in range(3): idx0 = blk10 r0 = blk*3 entries = [('i', list(range(idx0+1, idx0+11))), ('xᵢ', xi[idx0:idx0+10]), ('F(x)', F[idx0:idx0+10])] for j, (lab, vals) in enumerate(entries): set_cell_text(table.cell(r0+j,0), lab, bold=True, size=11) for k,val in enumerate(vals, start=1): set_cell_text(table.cell(r0+j,k), fmt_num(val), size=10) if j == 0: shade_row(table.rows[r0+j], 'EAEAEA') set_table_borders(table)

def add_discrete_table(): add_table_title('Таблица 6 – Результаты вычислений.') table = doc.add_table(rows=5, cols=7) table.alignment = WD_TABLE_ALIGNMENT.CENTER table.autofit = False widths = [Cm(1.2)] + [Cm(2.6)]*6 for col,w in zip(table.columns, widths): col.width = w header = ['i',10,22,6,26,12,20] row2 = ['n',2501,2499,3021,1979,1214,3786] row3 = ['xᵢ',-3,3,-5,5,-2,2] # Match legacy convention pi(x)=Pi/h with h=0.5 probs = [2501/5000,2499/5000,3021/5000,1979/5000,1214/5000,3786/5000] row4 = ['Pᵢ'] + [fmt_num(v) for v in probs] row5 = ['pᵢ(x)'] + [fmt_num(v/0.5) for v in probs] rows = [header,row2,row3,row4,row5] for i,row in enumerate(rows): for j,val in enumerate(row): set_cell_text(table.cell(i,j), val, bold=(j==0), size=11 if i==0 else 10) if i==0: shade_row(table.rows[i], 'EAEAEA') set_table_borders(table)

Compose document

add_title_page() add_goal()

Section 1: Normal

N1,P1,p1,F1,m1,D1,s1 = stats_normal add_three_block_table(1, counts_normal, P1, p1, include_x=False) add_image(img_normal, 16.3) add_caption('Рисунок 1 – Гистограмма и графики плотности распределения') doc.add_page_break() add_cdf_table(2, xi_sym, F1) add_image(cdf1, 11.0) add_caption('Рисунок 2 – График интегрального закона распределения F(x) (функции распределения)') add_small_text(f'Для реализации №1: mₓ = Σ xᵢ·Pᵢ = {fmt_num(m1)}, σ = {fmt_num(s1)}, Dₓ = {fmt_num(D1)}.') add_small_text('Для реализации №2: mₓ = 0, σ = 2,34, Dₓ = 5,45.') add_small_text('Для реализации №3: mₓ = -2, σ = 1, Dₓ = 1.') doc.add_page_break()

Section 2: Rayleigh

N2,P2,p2,F2,m2,D2,s2 = stats_rayleigh add_image(img_rayleigh, 16.3) add_caption('Рисунок 3 – Гистограмма и графики плотности распределения') add_three_block_table(3, counts_rayleigh, P2, p2, include_x=False) add_small_text(f'Для реализации №1: mₓ = {fmt_num(m2)}, σ = {fmt_num(s2)}, Dₓ = {fmt_num(D2)}.') doc.add_page_break() add_cdf_table(4, xi_pos, F2) add_image(cdf2, 11.0) add_caption('Рисунок 4 – График интегрального закона распределения F(x) (функции распределения)') add_small_text(f'Для реализации №1 (по формуле Рэлея при σ = 3): mₓ = {fmt_num(ray_mean1)}, Dₓ = {fmt_num(ray_var1)}.') add_small_text(f'Для реализации №2: σ = 1,5, mₓ = {fmt_num(ray_mean2)}, Dₓ = {fmt_num(ray_var2)}.') add_small_text(f'Для реализации №3: σ = 5, mₓ = {fmt_num(ray_mean3)}, Dₓ = {fmt_num(ray_var3)}.') doc.add_page_break()

Section 3: Uniform

N3,P3,p3,F3,m3,D3,s3 = stats_uniform add_image(img_uniform, 16.3) add_caption('Рисунок 5 – Гистограмма и графики плотности распределения') add_three_block_table(5, counts_uniform, P3, p3, include_x=True, xi=xi_sym) add_small_text(f'Для реализации №1: mₓ = {fmt_num(m3)}, σ = {fmt_num(s3)}, Dₓ = {fmt_num(D3)}.') doc.add_page_break() add_image(cdf3, 11.0) add_caption('Рисунок 6 – График интегрального закона распределения F(x) (функции распределения)') add_small_text('Для реализации №2: a = 1, b = 4, mₓ = (a+b)/2 = 2,5, Dₓ = (b-a)²/12 = 0,75.') add_small_text('Для реализации №3: a = -4, b = 6, mₓ = (a+b)/2 = 1, Dₓ = (b-a)²/12 = 8,3333.') add_image(img_discrete, 16.3) add_caption('Рисунок 7 – Гистограмма и графики плотности распределения') doc.add_page_break()

Section 4: Discrete

add_discrete_table() add_small_text(f'Для реализации №1: mₓ = {fmt_num(d1[3])}, σ = {fmt_num(d1[5])}, Dₓ = {fmt_num(d1[4])}.') add_small_text(f'Для реализации №2: mₓ = {fmt_num(d2[3])}, σ = {fmt_num(d2[5])}, Dₓ = {fmt_num(d2[4])}.') add_small_text(f'Для реализации №3: mₓ = {fmt_num(d3[3])}, σ = {fmt_num(d3[5])}, Dₓ = {fmt_num(d3[4])}.') doc.add_page_break()

Section 5: arcsine

N5,P5,p5,F5,m5,D5,s5 = stats_arcsine add_image(img_arcsine, 16.3) add_caption('Рисунок 8 – Гистограмма и графики плотности распределения') add_three_block_table(7, counts_arcsine, P5, p5, include_x=True, xi=xi_sym) add_small_text(f'Для реализации №1: mₓ = {fmt_num(m5)}, σ = {fmt_num(s5)}, Dₓ = {fmt_num(D5)}.') doc.add_page_break() add_image(cdf5, 11.0) add_caption('Рисунок 9 – График интегрального закона распределения F(x) (функции распределения)') add_small_text('Для реализации №2: a = -7, b = 3, mₓ = -2, Dₓ = (b-a)²/8 = 12,5.') add_small_text('Для реализации №3: a = -2, b = 6, mₓ = 2, Dₓ = (b-a)²/8 = 8.')

p = doc.add_paragraph() p.paragraph_format.first_line_indent = Cm(1.25) r1 = p.add_run('Вывод: '); r1.bold = True r2 = p.add_run('освоили базовые навыки статистического анализа случайных сигналов и экспериментальным путём определили их основные статистические характеристики.') for r in [r1,r2]: r.font.name='Times New Roman'; r._element.rPr.rFonts.set(qn('w:eastAsia'),'Times New Roman'); r.font.size=Pt(14)

save

doc.save(OUT) print(OUT) print('normal stats', N1, m1, D1, s1) print('rayleigh stats', N2, m2, D2, s2) print('uniform stats', N3, m3, D3, s3) print('discrete', d1, d2, d3) print('arcsine', N5, m5, D5, s5) PY python /mnt/data/make_lab_doc.py

Rendering and inspection

I need to render the content and then inspect it carefully for any issues before finalizing. This will allow me to adjust things like formatting or alignment as needed, ensuring everything looks good and is fully functional. Just needing to check it before moving forward.

bash -lc mkdir -p /mnt/data/render_new && python /home/oai/skills/docx/render_docx.py '/mnt/data/ЛР1_обновленный.docx' --output_dir /mnt/data/render_new

Creating a montage for inspection

I’ll need to create a montage so I can inspect the content more easily. A container, like a Python script, might help organize everything for better review. This will allow me to make sure everything is in place before finalizing or making adjustments.

bash -lc python - <<'PY' from PIL import Image, ImageDraw from pathlib import Path import math paths=sorted(Path('/mnt/data/render_new').glob('page-.png'), key=lambda p:int(p.stem.split('-')[1])) ims=[] for p in paths: im=Image.open(p).convert('RGB') im.thumbnail((300,420)) canvas=Image.new('RGB',(320,450),'white') canvas.paste(im,((320-im.width)//2,10)) d=ImageDraw.Draw(canvas) d.text((10,425),p.name,fill='black') ims.append(canvas) cols=2 rows=math.ceil(len(ims)/cols) out=Image.new('RGB',(cols320,rows*450),(240,240,240)) for i,im in enumerate(ims): out.paste(im,((i%cols)*320,(i//cols)*450)) out.save('/mnt/data/render_new_montage.png') print('/mnt/data/render_new_montage.png', len(paths)) PY

Inspecting weird page breaks

Montage seems to show some weird blank spaces on page 1 and 2. It could be due to the arrangement with 11 pages getting sorted. Maybe the title page is split across two pages, with page 1 showing the title, and page 2 only having the "Минск 2026" text. I'll need to check the first two pages closely.### Checking page 2 for "Минск 2026"

It seems like page 1 is missing "Минск 2026," so I think it might only appear on page 2. I'll open up page 2 to confirm if that's the case and ensure the text is properly placed.### Fixing title page and inspecting page setups

Looks like the extra page was caused by too many blank paragraphs on the title page. I need to adjust the layout to fit "Минск" on page 1. The section shifts also led to an extra page. I’ll remove the blank paragraphs, possibly add a page break after "Минск," and check page 3 onward. Page 5 may have an issue with an image causing overflow, so I’ll take a closer look at that as well.### Reducing image width on page 5 and checking other pages

The image on page 5 is clipped on the right, so it looks like I need to reduce its width from 16.3 to something like 15.8 or 15.5. I should also check pages 7 and 10 to see if they're affected in a similar way. Let me inspect page 7.### Checking image on page 10

Page 7 looks fine. I’ll now check page 10 to see if the image is also too wide like on page 5. Let’s take a closer look at that page and confirm whether the image overlaps or gets clipped.### Reviewing page 9 and title page adjustments

Page 10 might be fine after all. Now, I’ll focus on adjusting the title page and see if the table on page 9 needs any tweaking. Let's open page 9 and check whether there’s any issue with the layout or table placement that needs fixing.### Finalizing layout adjustments and image widths

Page 9 might work as is, though I could combine it with the next section. The title page needs extra blank space removed, and I might shift section numbering. For image widths, most snapshots can go down to 15.9, with larger ones set to 15.8 to prevent clipping. I'll also adjust the title’s spacing, reducing blank paragraphs to 8 instead of 10. Finally, a table at the bottom may help with placing "Minsk 2026."

Finalizing layout adjustments and contents

On page 1, I’ll add a single blank paragraph followed by "Minsk," without pushing it to the bottom. For page 3, the table and screenshot should fit. Page 4 works with table and chart. On page 5, I'll fix the image clipping. By removing the blank page, I’ll finalize the last 10 pages. Time to update everything!

bash -lc python - <<'PY' from pathlib import Path p=Path('/mnt/data/make_lab_doc.py') text=p.read_text() text=text.replace(" for _ in range(10):\n doc.add_paragraph()\n table = doc.add_table(rows=1, cols=2)", " for _ in range(6):\n doc.add_paragraph()\n table = doc.add_table(rows=1, cols=2)") text=text.replace(" for _ in range(10):\n doc.add_paragraph()\n p = doc.add_paragraph(); p.alignment = WD_ALIGN_PARAGRAPH.CENTER", " for _ in range(2):\n doc.add_paragraph()\n p = doc.add_paragraph(); p.alignment = WD_ALIGN_PARAGRAPH.CENTER") text=text.replace("add_image(img_normal, 16.3)", "add_image(img_normal, 15.8)") text=text.replace("add_image(img_rayleigh, 16.3)", "add_image(img_rayleigh, 15.8)") text=text.replace("add_image(img_uniform, 16.3)", "add_image(img_uniform, 15.8)") text=text.replace("add_image(img_discrete, 16.3)", "add_image(img_discrete, 15.8)") text=text.replace("add_image(img_arcsine, 16.3)", "add_image(img_arcsine, 15.8)") p.write_text(text) print('patched') PY python /mnt/data/make_lab_doc.py

bash -lc rm -rf /mnt/data/render_new && mkdir -p /mnt/data/render_new && python /home/oai/skills/docx/render_docx.py '/mnt/data/ЛР1_обновленный.docx' --output_dir /mnt/data/render_new && python - <<'PY' from PIL import Image, ImageDraw from pathlib import Path import math paths=sorted(Path('/mnt/data/render_new').glob('page-.png'), key=lambda p:int(p.stem.split('-')[1])) ims=[] for p in paths: im=Image.open(p).convert('RGB') im.thumbnail((300,420)) canvas=Image.new('RGB',(320,450),'white') canvas.paste(im,((320-im.width)//2,10)) d=ImageDraw.Draw(canvas) d.text((10,425),p.name,fill='black') ims.append(canvas) cols=2 rows=math.ceil(len(ims)/cols) out=Image.new('RGB',(cols320,rows*450),(240,240,240)) for i,im in enumerate(ims): out.paste(im,((i%cols)*320,(i//cols)*450)) out.save('/mnt/data/render_new_montage.png') print('pages',len(paths)) PY

Checking images for clipping

I need to make sure there are no clipped images. The montage seems fine. Let me quickly check pages 4 and 9 to inspect the screenshots. For page 4, it looks like the Rayleigh image is no longer clipped, which is great. I'll just verify that and move forward.

Thought for 14m 45s