{ "cells": [ { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# Using plotly\n", "import plotly.graph_objects as go\n", "import numpy as np" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Define data" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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startendnameordercommentX0LRsizeoverlapoverlap_with
00131072BootROMNaNNaNNaNNaN131072True0.0
1704708_jump_bl1NaNNaNNaNNaN4True0.0
22582425996_boot_usbNaNNaNNaNNaN172True0.0
37584876008auth_bl1NaNNaNNaNNaN160True0.0
43366050833689180Tried debugger spaceNaNNaNNaNNaN28672False4.0
53368944033689448_boot_usb_raNaNNaNNaNNaN8False5.0
63369369633701888BL1NaNNaNNaNNaN8192False6.0
73370188833849344BL31NaNNaNNaNNaN147456True7.0
83377305633773064TTBR0_EL3 address ptrNaNNaNNaNNaN8True7.0
93384934434008336BL2NaNNaNNaNNaN158992True9.0
103384934433872624BL2 empty space?NaNNaNNaNNaN23280True9.0
113387673633876736BL2 copy start/sourceNaNNaNNaNNaN0True9.0
123398451234009088DebuggerNaNNaNNaNNaN24576True9.0
133400833634013184End/Start peripheral space?NaNNaNNaNNaN4848True12.0
143434086434369536Debugger relocatedNaNNaNNaNNaN28672True16.0
153434086434340868_frederic_dest_ptrNaNNaNNaNNaN4True14.0
163434905634508048BL2 load address?NaNNaNNaNNaN158992True16.0
173437158434373632modem_interfaceNaNNaNNaNNaN2048True16.0
18346816512346836992mali@14AC0000NaNNaNNaNNaN20480False18.0
\n", "
" ], "text/plain": [ " start end name order comment X0 LR \\\n", "0 0 131072 BootROM NaN NaN NaN NaN \n", "1 704 708 _jump_bl1 NaN NaN NaN NaN \n", "2 25824 25996 _boot_usb NaN NaN NaN NaN \n", "3 75848 76008 auth_bl1 NaN NaN NaN NaN \n", "4 33660508 33689180 Tried debugger space NaN NaN NaN NaN \n", "5 33689440 33689448 _boot_usb_ra NaN NaN NaN NaN \n", "6 33693696 33701888 BL1 NaN NaN NaN NaN \n", "7 33701888 33849344 BL31 NaN NaN NaN NaN \n", "8 33773056 33773064 TTBR0_EL3 address ptr NaN NaN NaN NaN \n", "9 33849344 34008336 BL2 NaN NaN NaN NaN \n", "10 33849344 33872624 BL2 empty space? NaN NaN NaN NaN \n", "11 33876736 33876736 BL2 copy start/source NaN NaN NaN NaN \n", "12 33984512 34009088 Debugger NaN NaN NaN NaN \n", "13 34008336 34013184 End/Start peripheral space? NaN NaN NaN NaN \n", "14 34340864 34369536 Debugger relocated NaN NaN NaN NaN \n", "15 34340864 34340868 _frederic_dest_ptr NaN NaN NaN NaN \n", "16 34349056 34508048 BL2 load address? NaN NaN NaN NaN \n", "17 34371584 34373632 modem_interface NaN NaN NaN NaN \n", "18 346816512 346836992 mali@14AC0000 NaN NaN NaN NaN \n", "\n", " size overlap overlap_with \n", "0 131072 True 0.0 \n", "1 4 True 0.0 \n", "2 172 True 0.0 \n", "3 160 True 0.0 \n", "4 28672 False 4.0 \n", "5 8 False 5.0 \n", "6 8192 False 6.0 \n", "7 147456 True 7.0 \n", "8 8 True 7.0 \n", "9 158992 True 9.0 \n", "10 23280 True 9.0 \n", "11 0 True 9.0 \n", "12 24576 True 9.0 \n", "13 4848 True 12.0 \n", "14 28672 True 16.0 \n", "15 4 True 14.0 \n", "16 158992 True 16.0 \n", "17 2048 True 16.0 \n", "18 20480 False 18.0 " ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "data = pd.read_csv('stack_and_functions.csv')\n", "\n", "def convert_to_int(value):\n", " try:\n", " if isinstance(value, str) and value.startswith('0x'):\n", " return int(value, 16)\n", " else:\n", " return int(value)\n", " except ValueError:\n", " return value \n", "\n", "data['start'] = data['start'].apply(convert_to_int)\n", "data['end'] = data['end'].apply(convert_to_int)\n", "data['size'] = data['end'] - data['start']\n", "\n", "data.sort_values(by=['size'], inplace=True, ascending=False)\n", "data.sort_values(by=['start'], inplace=True)\n", "\n", "# Inverse the order of the data\n", "data.reset_index(drop=True, inplace=True)\n", "\n", "data['overlap'] = False\n", "\n", "for i, row in data.iterrows():\n", " for j, row2 in data.iterrows():\n", " if i == j:\n", " continue\n", " if row['start'] <= row2['end'] and row['end'] > row2['start']:\n", " if row['end'] - row['start'] >= row2['end'] - row2['start']:\n", " continue\n", " data.at[i, 'overlap'] = True\n", " data.at[j, 'overlap'] = True\n", " data.at[i, 'overlap_with'] = j\n", "\n", "data['overlap_with'] = data['overlap_with'].fillna(data.index.to_series())\n", "data['overlap_with'] = data['overlap_with'].astype(float)\n", "\n", "# Send warnings if sizes are negative\n", "if (data['size'] < 0).any():\n", " print(f'Warning: Negative sizes detected at indices {data[data[\"size\"] < 0].index}')\n", "\n", "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Inherent stacked block diagram" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "marker": { "color": "#0b977d" }, "mode": "text", "name": "BootROM", "text": "BootROM", "textposition": "middle center", "type": "scatter", "x": [ 2.5 ], "y": [ 0.5 ] }, { "marker": { "color": "#0b977d" }, "mode": "text", "showlegend": false, "text": "0x20000", "textposition": "middle center", "type": "scatter", "x": [ 1.1400000000000001 ], "y": [ 3.84 ] }, { "marker": { "color": "#0b977d" }, "mode": "text", "showlegend": false, "text": "0x0", "textposition": "middle center", "type": "scatter", "x": [ 1.1400000000000001 ], "y": [ 0.14 ] }, { "marker": { "color": "#4c1830" }, "mode": "text", "name": "_jump_bl1", "text": "_jump_bl1", "textposition": "middle center", "type": "scatter", "x": [ 2.5 ], "y": [ 1.52 ] }, { "marker": { "color": "#4c1830" }, "mode": "text", "showlegend": false, "text": "0x2c4", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 1.7100000000000002 ] }, { "marker": { "color": "#4c1830" }, "mode": "text", "showlegend": false, "text": "0x2c0", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 1.1600000000000001 ] }, { "marker": { "color": "#5d2e02" }, "mode": "text", "name": "_boot_usb", "text": "_boot_usb", "textposition": "middle center", "type": "scatter", "x": [ 2.5 ], "y": [ 2.52 ] }, { "marker": { "color": "#5d2e02" }, "mode": "text", "showlegend": false, "text": "0x658c", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 2.71 ] }, { "marker": { "color": "#5d2e02" }, "mode": "text", "showlegend": false, "text": "0x64e0", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 2.16 ] }, { "marker": { "color": "#5e6e3f" }, "mode": "text", "name": "auth_bl1", "text": "auth_bl1", "textposition": "middle center", "type": "scatter", "x": [ 2.5 ], "y": [ 3.52 ] }, { "marker": { "color": "#5e6e3f" }, "mode": "text", "showlegend": false, "text": "0x128e8", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 3.71 ] }, { "marker": { "color": "#5e6e3f" }, "mode": "text", "showlegend": false, "text": "0x12848", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 3.16 ] }, { "marker": { "color": "#85ca4e" }, "mode": "text", "name": "Tried debugger space", "text": "Tried debugger space", "textposition": "middle center", "type": "scatter", "x": [ 2.5 ], "y": [ 4.5 ] }, { "marker": { "color": "#85ca4e" }, "mode": "text", "showlegend": false, "text": "0x2020e5c", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 4.84 ] }, { "marker": { "color": "#85ca4e" }, "mode": "text", "showlegend": false, "text": "0x2019e5c", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 4.14 ] }, { "marker": { "color": "#d2f956" }, "mode": "text", "name": "_boot_usb_ra", "text": "_boot_usb_ra", "textposition": "middle center", "type": "scatter", "x": [ 2.5 ], "y": [ 5.5 ] }, { "marker": { "color": "#d2f956" }, "mode": "text", "showlegend": false, "text": "0x2020f68", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 5.84 ] }, { "marker": { "color": "#d2f956" }, "mode": "text", "showlegend": false, "text": "0x2020f60", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 5.14 ] }, { "marker": { "color": "#55fe0e" }, "mode": "text", "name": "BL1", "text": "BL1", "textposition": "middle center", "type": "scatter", "x": [ 2.5 ], "y": [ 6.5 ] }, { "marker": { "color": "#55fe0e" }, "mode": "text", "showlegend": false, "text": "0x2024000", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 6.84 ] }, { "marker": { "color": "#55fe0e" }, "mode": "text", "showlegend": false, "text": "0x2022000", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 6.14 ] }, { "marker": { "color": "#b0d635" }, "mode": "text", "name": "BL31", "text": "BL31", "textposition": "middle center", "type": "scatter", "x": [ 2.5 ], "y": [ 7.5 ] }, { "marker": { "color": "#b0d635" }, "mode": "text", "showlegend": false, "text": "0x2048000", "textposition": "middle center", "type": "scatter", "x": [ 1.1400000000000001 ], "y": [ 8.84 ] }, { "marker": { "color": "#b0d635" }, "mode": "text", "showlegend": false, "text": "0x2024000", "textposition": "middle center", "type": "scatter", "x": [ 1.1400000000000001 ], "y": [ 7.14 ] }, { "marker": { "color": "#beec90" }, "mode": "text", "name": "TTBR0_EL3 address ptr", "text": 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"scatter", "x": [ 1.1400000000000001 ], "y": [ 9.14 ] }, { "marker": { "color": "#177b8d" }, "mode": "text", "name": "BL2 empty space?", "text": "BL2 empty space?", "textposition": "middle center", "type": "scatter", "x": [ 2.5 ], "y": [ 10.52 ] }, { "marker": { "color": "#177b8d" }, "mode": "text", "showlegend": false, "text": "0x204daf0", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 10.709999999999999 ] }, { "marker": { "color": "#177b8d" }, "mode": "text", "showlegend": false, "text": "0x2048000", "textposition": "middle center", "type": "scatter", "x": [ 1.2400000000000002 ], "y": [ 10.16 ] }, { "marker": { "color": "#9e7028" }, "mode": "text", "name": "BL2 copy start/source", "text": "BL2 copy start/source", "textposition": "middle center", "type": "scatter", "x": [ 2.5 ], "y": [ 11.52 ] }, { "marker": { "color": "#9e7028" }, "mode": "text", "showlegend": false, "text": "0x204eb00", "textposition": "middle center", "type": "scatter", "x": 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"" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "width": 1200, "xaxis": { "range": [ 0, 5 ], "showgrid": false, "showticklabels": false, "tickvals": [ 0, 1, 2, 3, 4, 5 ] }, "yaxis": { "autorange": "reversed", "gridcolor": "black", "griddash": "longdashdot", "gridwidth": 0, "showgrid": false, "showticklabels": true, "tickvals": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 ] } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import plotly.graph_objects as go\n", "import random\n", "\n", "tickpointers = []\n", "vertical_len = len(data['overlap_with'].unique())\n", "vertical_gap_percentage = 0.08\n", "horizontal_gap = 0.1\n", "labels = pd.DataFrame()\n", "\n", "def random_color():\n", " return f'#{random.randint(0, 0xFFFFFF):06x}'\n", "\n", "fig = go.Figure()\n", "\n", "for i, d in data.iterrows():\n", " fillcolor = random_color()\n", " data.at[i, 'fillcolor'] = fillcolor\n", " \n", " x0=1\n", " x1=4\n", "\n", " if d['overlap'] == False:\n", " y0=d['overlap_with']\n", " y1=d['overlap_with']+1\n", " elif d['overlap'] == True:\n", " overlaps = data.loc[data['overlap_with'] == d['overlap_with']].shape[0]\n", "\n", " # Calculate relative size of the overlap\n", " overlap_sizes = data.loc[data['overlap_with'] == d['overlap_with']].iloc[1:]['size'].sum()\n", "\n", " if d['overlap_with'] == i:\n", " y0=i\n", " y1=overlaps+i\n", " if i != data.shape[0]+1:\n", " if d['end'] > data.iloc[i+1].start and d['end'] < data.iloc[i+1].end:\n", " y1=overlaps+i-0.5\n", " x0=x0-horizontal_gap\n", " x1=x1+horizontal_gap\n", " else:\n", " y0=0.02+i\n", " y1=0.87+i\n", " else:\n", " print(f'Something went wrong with {d}. Skipping')\n", " continue\n", "\n", " fig.add_shape(\n", " type=\"rect\",\n", " x0=x0,\n", " x1=x1,\n", " y0=y0+vertical_gap_percentage,\n", " y1=y1-vertical_gap_percentage,\n", " line=dict(width=2),\n", " fillcolor=fillcolor,\n", " opacity=0.5,\n", " layer=\"below\",\n", " )\n", "\n", " # Add middle text\n", " fig.add_trace(go.Scatter\n", " (\n", " x=[(x0+x1)/2],\n", " y=[y0+0.5],\n", " text=d['name'],\n", " mode=\"text\",\n", " textposition=\"middle center\",\n", " name=d['name'],\n", " marker=dict(\n", " color=fillcolor,\n", " ),\n", " ))\n", "\n", " # Add top-left text with d['end']\n", " fig.add_trace(go.Scatter\n", " (\n", " x=[(x0+0.14+horizontal_gap)],\n", " y=[y1-0.16],\n", " text=hex(d['end']),\n", " mode=\"text\",\n", " textposition=\"middle center\",\n", " marker=dict(\n", " color=fillcolor,\n", " ),\n", " showlegend=False,\n", " ))\n", "\n", " # Add bottom-left text with d['end']\n", " fig.add_trace(go.Scatter\n", " (\n", " x=[(x0+0.14+horizontal_gap)],\n", " y=[y0+0.14],\n", " text=hex(d['start']),\n", " mode=\"text\",\n", " textposition=\"middle center\",\n", " marker=dict(\n", " color=fillcolor,\n", " ),\n", " showlegend=False,\n", " ))\n", "\n", "fig.update_xaxes(\n", " range=[0, 5],\n", " tickvals=[0, 1, 2, 3, 4, 5],\n", ")\n", "\n", "start_values = data['start'].sort_values()\n", "end_values = data['end'].sort_values()\n", "\n", "labels = []\n", "\n", "for i, d in data.iterrows():\n", " if i == 0:\n", " labels.append(f'{hex(start_values.iloc[i])}')\n", " elif i == len(data)-1:\n", " labels.append(f'{hex(end_values.iloc[i])}')\n", " else:\n", " labels.append(f'{hex(start_values.iloc[i])}
{hex(end_values.iloc[i-1])}')\n", "\n", "tickpointers = [i for i in range(len(data))]\n", "\n", "fig.update_yaxes(\n", " # tickvals=[i for i in range(len(data)+1)], \n", " tickvals = tickpointers,\n", " # ticktext= labels,\n", " griddash=\"longdashdot\",\n", " gridwidth=0,\n", " gridcolor=\"black\",\n", " showgrid=False,\n", " showticklabels=True,\n", " autorange='reversed',\n", ")\n", "\n", "fig.update_xaxes(\n", " showgrid=False,\n", " showticklabels=False,\n", ")\n", "\n", "fig.update_layout(\n", " width=1200,\n", " height=1200,\n", " autosize=True,\n", " margin=dict(l=200, r=20, t=20, b=20),\n", " font=dict(\n", " size=18,\n", " ),\n", " # Legend being the name of the function\n", " legend_title_text=\"Function/Locations\",\n", ")\n", "\n", "fig.show()" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "# Save to html\n", "fig.write_html(\"stack_and_functions.html\")" ] } ], "metadata": { "kernelspec": { "display_name": "venv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" } }, "nbformat": 4, "nbformat_minor": 2 }