vault backup: 2023-04-14 10:25:25

This commit is contained in:
2023-04-14 10:25:25 +02:00
parent 1a05c47564
commit d92c3be78b
41 changed files with 100715 additions and 208 deletions

View File

@@ -0,0 +1,776 @@
---
excalidraw-plugin: parsed
tags: [excalidraw]
---
==⚠ Switch to EXCALIDRAW VIEW in the MORE OPTIONS menu of this document. ⚠==
# Text Elements
%%
# Drawing
```compressed-json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=
```
%%

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,992 @@
---
excalidraw-plugin: parsed
tags: [excalidraw]
---
==⚠ Switch to EXCALIDRAW VIEW in the MORE OPTIONS menu of this document. ⚠==
# Text Elements
%%
# Drawing
```compressed-json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```
%%

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,670 @@
---
excalidraw-plugin: parsed
tags: [excalidraw]
---
==⚠ Switch to EXCALIDRAW VIEW in the MORE OPTIONS menu of this document. ⚠==
# Text Elements
%%
# Drawing
```compressed-json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=
```
%%

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,380 @@
---
excalidraw-plugin: parsed
tags: [excalidraw]
---
==⚠ Switch to EXCALIDRAW VIEW in the MORE OPTIONS menu of this document. ⚠==
# Text Elements
%%
# Drawing
```compressed-json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```
%%

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,208 @@
/*
IF YOU ACCIDENTLY MODIFY THIS FILE AND IT STOPS WORKING, SIMPLY DOWNLOAD IT AGAIN FROM THE SCRIPT LIBRARY.
![](https://raw.githubusercontent.com/zsviczian/obsidian-excalidraw-plugin/master/images/scripts-alternative-pens.jpg)
# How to create a new pen template
It takes a bit of experimentation and skill to create a new pen, so be patient.
1. Create a folder in your Vault for your pen options. The default is `Excalidraw/Pens`.
2. Create a new markdown file in your in the `pen folder` (e.g. `My pen`).
3. Copy the following template to the markdown file.
```json
{
"highlighter": true,
"constantPressure": false,
"hasOutline": true,
"outlineWidth": 4,
"options": PASTE_PREFECT_FREEHAND_OPTIONS_HERE
}
```
4. If you don't want your pen to have an outline around your line, change `hasOutline` to `false`. You can also modify `outlineWidth` if you want a thinner or thicker outline around your line.
5. If you want your pen to be pressure sensitive (when drawing with a mouse the pressure is simulated based on the speed of your hand) leave `constantPressure` as `false`. If you want a constant line width regardless of speed and pen pressure, change it to `true`.
6. `highlighter` true will place the new line behind the existing strokes (i.e. like a highlighter pen). If `highlighter` is missing or it is set to `false` the new line will appear at the top of the existing strokes (the default behavior of Excalidraw pens).
7. Go to https://perfect-freehand-example.vercel.app/ and configure your pen.
8. Click `Copy Options`.
9. Go back to the pen file you created in step No.2 and replace the placeholder text with the options you just copied from perfect-freehand.
10. Look for `easing` in the file and replace the function e.g. `(t) => t*t,` with the name of the function in brackets (in this example it would be `easeInQuad`). You will find the function name on the perfect-freehand website, only change the first letter to be lower case.
11. Test your pen in Excalidraw by clicking the `Alternative Pens` script and selecting your new pen.
# Example pens
My pens: https://github.com/zsviczian/obsidian-excalidraw-plugin/tree/master/ea-scripts/pens
**Fine tipped pen:**
```json
{
constantPressure: true,
options: {
smoothing: 0.4,
thinning: -0.5,
streamline: 0.4,
easing: "linear",
start: {
taper: 5,
cap: false,
},
end: {
taper: 5,
cap: false,
},
}
}
```
**Thick marker:**
```json
{
constantPressure: true,
hasOutline: true,
outlineWidth: 4,
options: {
thinning: 1,
smoothing: 0.5,
streamline: 0.5,
easing: "linear",
start: {
taper: 0,
cap: true
},
end: {
taper: 0,
cap: true
}
}
}
```
**Fountain pen:**
```json
{
options: {
smoothing: 0.22,
thinning: 0.8,
streamline: 0.22,
easing: "easeInQuad",
start: {
taper: true,
cap: true,
},
end: {
taper: 1,
cap: true,
},
}
}
```
# Notes about the pen options
Note, that custom pens are currently not supported by Excalidraw.com. I've submitted a [PR](https://github.com/excalidraw/excalidraw/pull/6069) but there is no guarantee that it will get pushed to production. Your Excalidraw drawing can still be loaded to Excalidraw, but the special pen effects will not be visible there.
If you set a pen in your Excalidraw template file, that pen will be loaded automatically when you create a file using that template. Similarly, when you save a document, it will save your current pen settings as well. The next time you open the document, you can continue to use the same pen.
Pen options are saved with the stroke. This means, that even if you change the ped definition later on, your existing drawings will not be effected.
`outlineWidth` is relative to `strokeWidth`. i.e. if you make the stroke thinner in Excalidraw, the outline will become proportionally thinner as well. `outlineWidth` is only used if `hasOutline` is set to true.
If you don't want your pen to be pressure/speed sensitive, set `constantPressure` to `true`. Setting `constantPressure` to `true` automatically sets `simulatePressure` to `false`.
If you want your pen to be speed sensitive (i.e. the faster you draw the line the thinner it gets), set `options.simulatePressure` to `true`. If you omit `simulatePressure` from `options` then excalidraw will detect if you are drawing with a mouse or a pen and use pen pressures if available.
You can read more about configuring perfect freehand here: https://github.com/steveruizok/perfect-freehand#documentation
Excalidraw supports all of the easing functions listed here: https://easings.net/#, plus "linear". You can also find details about these easing functions here:
https://github.com/ai/easings.net/blob/master/src/easings/easingsFunctions.ts
From a performance perspective I recommend linear easing.
# The script
```javascript */
//--------------------------
// Load settings
//--------------------------
if(!ea.verifyMinimumPluginVersion || !ea.verifyMinimumPluginVersion("1.8.8")) {
new Notice("This script requires a newer version of Excalidraw. Please install the latest version.");
return;
}
const api = ea.getExcalidrawAPI();
let settings = ea.getScriptSettings();
//set default values on first run
if(!settings["Pen folder"]) {
settings = {
"Pen folder" : {
value: "Excalidraw/Pens",
description: "The path to the folder where you store the perfect freehand options"
}
};
ea.setScriptSettings(settings);
}
let penFolder = settings["Pen folder"].value.toLowerCase();
if(penFolder === "" || penFolder === "/") {
new Notice("The pen folder cannot be the root folder of your vault");
return;
}
if(!penFolder.endsWith("/")) penFolder += "/";
//--------------------------
// Select pen
//--------------------------
const pens = app.vault.getFiles()
.filter(f=>f.extension === "md" && f.path.toLowerCase() === penFolder + f.name.toLowerCase())
.sort((a,b)=>a.basename.toLowerCase()<b.basename.toLowerCase()?-1:1);
if(pens.length === 0) {
const notice = new Notice(`You don't seem to have any pen definition files. Click this message to open the how-to guide.`,4000);
notice.noticeEl.onclick = async () => app.workspace.openLinkText(utils.scriptFile.path,"","tab");
return;
}
const file = await utils.suggester(["Excalidraw Default"].concat(pens.map(f=>(f.name.slice(0,f.name.length-3)))),["Default"].concat(pens), "Choose a pen preset, press ESC to abort");
if(!file) return;
if(file === "Default") {
api.updateScene({
appState: {
currentStrokeOptions: undefined
}
});
return;
}
//--------------------------
// Load pen
//--------------------------
const pen = await app.vault.read(file);
const parseJSON = (data) => {
try {
return JSON.parse(data);
} catch(e) {
try {
return JSON.parse(data.replaceAll(/\s(\w*)\:\s/g,' "$1": ').replaceAll(/,([^\w]*?})/gm,"$1"));
} catch(ee) {
const notice = new Notice(`Error loading the pen file. Maybe you accidently copy/pasted the easing function from perfect freehand website? Check the error message in Developer Console.\n(click=dismiss, right-click=Info) `,5000);
notice.noticeEl.oncontextmenu = async () => app.workspace.openLinkText(utils.scriptFile.path,"","tab");
console.error(ee);
console.error(data.replaceAll(/\s(\w*)\:\s/g,' "$1": ').replaceAll(/,([^\w]*?})/gm,"$1"));
return;
}
}
}
penJSON = parseJSON(pen);
if(!penJSON || typeof penJSON !== 'object') return;
//--------------------------
// Apply pen
//--------------------------
await api.updateScene({
appState: {
currentStrokeOptions: penJSON
}
});
api.setActiveTool({type:"freedraw"});

View File

@@ -0,0 +1 @@
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Pro 6.2.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license (Commercial License) Copyright 2022 Fonticons, Inc. --><path d="M373.5 27.1C388.5 9.9 410.2 0 433 0c43.6 0 79 35.4 79 79c0 22.8-9.9 44.6-27.1 59.6L277.7 319l-10.3-10.3-64-64L193 234.3 373.5 27.1zM170.3 256.9l10.4 10.4 64 64 10.4 10.4-19.2 83.4c-3.9 17.1-16.9 30.7-33.8 35.4L24.4 510.3l95.4-95.4c2.6 .7 5.4 1.1 8.3 1.1c17.7 0 32-14.3 32-32s-14.3-32-32-32s-32 14.3-32 32c0 2.9 .4 5.6 1.1 8.3L1.7 487.6 51.5 310c4.7-16.9 18.3-29.9 35.4-33.8l83.4-19.2z"/></svg>

After

Width:  |  Height:  |  Size: 632 B

View File

@@ -0,0 +1,127 @@
/*
![](https://raw.githubusercontent.com/zsviczian/obsidian-excalidraw-plugin/master/images/scripts-download-raw.jpg)
Download this file and save to your Obsidian Vault including the first line, or open it in "Raw" and copy the entire contents to Obsidian.
![](https://raw.githubusercontent.com/zsviczian/obsidian-excalidraw-plugin/master/images/scripts-fixed-inner-distance.png)
This script arranges selected elements and groups with a fixed inner distance.
Tips: You can use the `Box Selected Elements` and `Dimensions` scripts to create rectangles of the desired size, then use the `Change shape of selected elements` script to convert the rectangles to ellipses, and then use the `Fixed inner distance` script regains a desired inner distance.
Inspiration: #394
See documentation for more details:
https://zsviczian.github.io/obsidian-excalidraw-plugin/ExcalidrawScriptsEngine.html
```javascript
*/
if(!ea.verifyMinimumPluginVersion || !ea.verifyMinimumPluginVersion("1.5.21")) {
new Notice("This script requires a newer version of Excalidraw. Please install the latest version.");
return;
}
settings = ea.getScriptSettings();
//set default values on first run
if(!settings["Default distance"]) {
settings = {
"Prompt for distance?": true,
"Default distance" : {
value: 10,
description: "Fixed horizontal distance between centers"
},
"Remember last distance?": false
};
ea.setScriptSettings(settings);
}
let distanceStr = settings["Default distance"].value.toString();
const rememberLastDistance = settings["Remember last distance?"];
if(settings["Prompt for distance?"]) {
distanceStr = await utils.inputPrompt("distance?","number",distanceStr);
}
const borders = ["top", "bottom", "left", "right"];
const fromBorder = await utils.suggester(borders, borders, "from border?");
if(!fromBorder) {
return;
}
const distance = parseInt(distanceStr);
if(isNaN(distance)) {
return;
}
if(rememberLastDistance) {
settings["Default distance"].value = distance;
ea.setScriptSettings(settings);
}
const elements=ea.getViewSelectedElements();
const topGroups = ea.getMaximumGroups(elements)
.filter(els => !(els.length === 1 && els[0].type ==="arrow")) // ignore individual arrows
.filter(els => !(els.length === 1 && (els[0].containerId))); // ignore text in stickynote
if(topGroups.length <= 1) {
new Notice("At least 2 or more elements or groups should be selected.");
return;
}
if(fromBorder === 'top') {
const groups = topGroups.sort((lha,rha) => Math.min(...lha.map(t => t.y)) - Math.min(...rha.map(t => t.y)));
const firstGroupTop = Math.min(...groups[0].map(el => el.y));
for(var i=0; i<groups.length; i++) {
if(i > 0) {
const curGroup = groups[i];
const moveDistance = distance * i;
for(const curEl of curGroup) {
curEl.y = firstGroupTop + moveDistance;
}
}
}
}
else if(fromBorder === 'bottom') {
const groups = topGroups.sort((lha,rha) => Math.min(...lha.map(t => t.y + t.height)) - Math.min(...rha.map(t => t.y + t.height))).reverse();
const firstGroupBottom = Math.max(...groups[0].map(el => el.y + el.height));
for(var i=0; i<groups.length; i++) {
if(i > 0) {
const curGroup = groups[i];
const moveDistance = distance * i;
for(const curEl of curGroup) {
curEl.y = firstGroupBottom - moveDistance - curEl.height;
}
}
}
}
else if(fromBorder === 'left') {
const groups = topGroups.sort((lha,rha) => Math.min(...lha.map(t => t.x)) - Math.min(...rha.map(t => t.x)));
const firstGroupLeft = Math.min(...groups[0].map(el => el.x));
for(var i=0; i<groups.length; i++) {
if(i > 0) {
const curGroup = groups[i];
const moveDistance = distance * i;
for(const curEl of curGroup) {
curEl.x = firstGroupLeft + moveDistance;
}
}
}
}
else if(fromBorder === 'right') {
const groups = topGroups.sort((lha,rha) => Math.min(...lha.map(t => t.x + t.width)) - Math.min(...rha.map(t => t.x + t.width))).reverse();
const firstGroupRight = Math.max(...groups[0].map(el => el.x + el.width));
for(var i=0; i<groups.length; i++) {
if(i > 0) {
const curGroup = groups[i];
const moveDistance = distance * i;
for(const curEl of curGroup) {
curEl.x = firstGroupRight - moveDistance - curEl.width;
}
}
}
}
ea.copyViewElementsToEAforEditing(elements);
await ea.addElementsToView(false, false);

View File

@@ -0,0 +1 @@
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 130 130" stroke="#000"><path fill="none" stroke-linecap="round" stroke-width="4" d="M120 65a55.086 55.086 0 0 1-1.87 14.24c-.62 2.31-1.4 4.6-2.32 6.81-.91 2.21-1.98 4.38-3.18 6.45-1.2 2.07-2.54 4.08-4 5.98-1.45 1.9-3.05 3.72-4.74 5.41a54.136 54.136 0 0 1-5.41 4.74c-1.9 1.46-3.91 2.8-5.98 4-2.07 1.2-4.24 2.27-6.45 3.18-2.21.92-4.5 1.7-6.81 2.32A55.086 55.086 0 0 1 65 120a55.086 55.086 0 0 1-14.24-1.87c-2.31-.62-4.6-1.4-6.81-2.32-2.21-.91-4.38-1.98-6.45-3.18-2.07-1.2-4.08-2.54-5.98-4-1.9-1.45-3.72-3.05-5.41-4.74a54.136 54.136 0 0 1-4.74-5.41c-1.46-1.9-2.8-3.91-4-5.98-1.2-2.07-2.27-4.24-3.18-6.45-.92-2.21-1.7-4.5-2.32-6.81A55.086 55.086 0 0 1 10 65a55.086 55.086 0 0 1 1.87-14.24c.62-2.31 1.4-4.6 2.32-6.81.91-2.21 1.98-4.38 3.18-6.45 1.2-2.07 2.54-4.08 4-5.98 1.45-1.9 3.05-3.72 4.74-5.41 1.69-1.69 3.51-3.29 5.41-4.74 1.9-1.46 3.91-2.8 5.98-4 2.07-1.2 4.24-2.27 6.45-3.18 2.21-.92 4.5-1.7 6.81-2.32A55.086 55.086 0 0 1 65 10a55.086 55.086 0 0 1 14.24 1.87c2.31.62 4.6 1.4 6.81 2.32 2.21.91 4.38 1.98 6.45 3.18 2.07 1.2 4.08 2.54 5.98 4 1.9 1.45 3.72 3.05 5.41 4.74 1.69 1.69 3.29 3.51 4.74 5.41 1.46 1.9 2.8 3.91 4 5.98 1.2 2.07 2.27 4.24 3.18 6.45.92 2.21 1.7 4.5 2.32 6.81.62 2.32 1.09 4.69 1.4 7.06.31 2.37.39 5.98.47 7.18.08 1.2.08-1.2 0 0"/><path fill="none" stroke-linecap="round" stroke-width="4" d="M110 70c0 1.9-.14 3.81-.41 5.69-.27 1.88-.68 3.76-1.21 5.58-.53 1.82-1.21 3.62-1.99 5.35-.79 1.72-1.71 3.41-2.74 5.01a41.072 41.072 0 0 1-3.42 4.56c-1.24 1.44-2.6 2.8-4.04 4.04a41.072 41.072 0 0 1-4.56 3.42c-1.6 1.03-3.29 1.95-5.01 2.74-1.73.78-3.53 1.46-5.35 1.99-1.82.53-3.7.94-5.58 1.21S71.9 110 70 110c-1.9 0-3.81-.14-5.69-.41-1.88-.27-3.76-.68-5.58-1.21-1.82-.53-3.62-1.21-5.35-1.99-1.72-.79-3.41-1.71-5.01-2.74a41.072 41.072 0 0 1-4.56-3.42c-1.44-1.24-2.8-2.6-4.04-4.04a41.072 41.072 0 0 1-3.42-4.56c-1.03-1.6-1.95-3.29-2.74-5.01-.78-1.73-1.46-3.53-1.99-5.35-.53-1.82-.94-3.7-1.21-5.58A40.12 40.12 0 0 1 30 70c0-1.9.14-3.81.41-5.69.27-1.88.68-3.76 1.21-5.58.53-1.82 1.21-3.62 1.99-5.35.79-1.72 1.71-3.41 2.74-5.01 1.03-1.59 2.18-3.13 3.42-4.56 1.24-1.44 2.6-2.8 4.04-4.04 1.43-1.24 2.97-2.39 4.56-3.42 1.6-1.03 3.29-1.95 5.01-2.74 1.73-.78 3.53-1.46 5.35-1.99 1.82-.53 3.7-.94 5.58-1.21S68.1 30 70 30c1.9 0 3.81.14 5.69.41 1.88.27 3.76.68 5.58 1.21 1.82.53 3.62 1.21 5.35 1.99 1.72.79 3.41 1.71 5.01 2.74 1.59 1.03 3.13 2.18 4.56 3.42 1.44 1.24 2.8 2.6 4.04 4.04 1.24 1.43 2.39 2.97 3.42 4.56 1.03 1.6 1.95 3.29 2.74 5.01.78 1.73 1.46 3.53 1.99 5.35.53 1.82.94 3.7 1.21 5.58s.34 4.74.41 5.69c.07.95.07-.95 0 0"/><path fill="none" stroke-linecap="round" stroke-width="4" d="M100 75c0 1.45-.13 2.92-.38 4.34-.25 1.43-.63 2.85-1.13 4.21a24.875 24.875 0 0 1-4.34 7.52c-.93 1.11-1.97 2.15-3.08 3.08a24.875 24.875 0 0 1-7.52 4.34c-1.36.5-2.78.88-4.21 1.13-1.42.25-2.89.38-4.34.38-1.45 0-2.92-.13-4.34-.38-1.43-.25-2.85-.63-4.21-1.13a24.875 24.875 0 0 1-7.52-4.34c-1.11-.93-2.15-1.97-3.08-3.08a24.875 24.875 0 0 1-4.34-7.52c-.5-1.36-.88-2.78-1.13-4.21-.25-1.42-.38-2.89-.38-4.34 0-1.45.13-2.92.38-4.34.25-1.43.63-2.85 1.13-4.21a24.875 24.875 0 0 1 4.34-7.52c.93-1.11 1.97-2.15 3.08-3.08a24.875 24.875 0 0 1 7.52-4.34c1.36-.5 2.78-.88 4.21-1.13 1.42-.25 2.89-.38 4.34-.38 1.45 0 2.92.13 4.34.38 1.43.25 2.85.63 4.21 1.13a24.875 24.875 0 0 1 7.52 4.34c1.11.93 2.15 1.97 3.08 3.08a24.875 24.875 0 0 1 4.34 7.52c.5 1.36.88 2.78 1.13 4.21.25 1.42.32 3.62.38 4.34.06.72.06-.72 0 0"/></svg>

After

Width:  |  Height:  |  Size: 3.4 KiB

View File

@@ -0,0 +1,91 @@
/*
![](https://raw.githubusercontent.com/zsviczian/obsidian-excalidraw-plugin/master/images/scripts-normalize-selected-arrows.png)
This script will reset the start and end positions of the selected arrows. The arrow will point to the center of the connected box and will have a gap of 8px from the box.
Tips: If you are drawing a flowchart, you can use `Normalize Selected Arrows` script to correct the position of the start and end points of the arrows, then use `Elbow connectors` script, and you will get the perfect connecting line!
```javascript
*/
if(!ea.verifyMinimumPluginVersion || !ea.verifyMinimumPluginVersion("1.5.21")) {
new Notice("This script requires a newer version of Excalidraw. Please install the latest version.");
return;
}
settings = ea.getScriptSettings();
//set default values on first run
if(!settings["Gap"]) {
settings = {
"Gap" : {
value: 8,
description: "The value of the gap between the connection line and the element, which must be greater than 0. If you want the connector to be next to the element, set it to 1."
}
};
ea.setScriptSettings(settings);
}
let gapValue = settings["Gap"].value;
const selectedIndividualArrows = ea.getMaximumGroups(ea.getViewSelectedElements())
.reduce((result, g) => [...result, ...g.filter(el => el.type === 'arrow')], []);
const allElements = ea.getViewElements();
for(const arrow of selectedIndividualArrows) {
const startBindingEl = allElements.filter(el => el.id === (arrow.startBinding||{}).elementId)[0];
const endBindingEl = allElements.filter(el => el.id === (arrow.endBinding||{}).elementId)[0];
if(startBindingEl) {
recalculateStartPointOfLine(arrow, startBindingEl, endBindingEl, gapValue);
}
if(endBindingEl) {
recalculateEndPointOfLine(arrow, endBindingEl, startBindingEl, gapValue);
}
}
ea.copyViewElementsToEAforEditing(selectedIndividualArrows);
await ea.addElementsToView(false,false);
function recalculateStartPointOfLine(line, el, elB, gapValue) {
const aX = el.x + el.width/2;
const bX = (line.points.length <=2 && elB) ? elB.x + elB.width/2 : line.x + line.points[1][0];
const aY = el.y + el.height/2;
const bY = (line.points.length <=2 && elB) ? elB.y + elB.height/2 : line.y + line.points[1][1];
line.startBinding.gap = gapValue;
line.startBinding.focus = 0;
const intersectA = ea.intersectElementWithLine(
el,
[bX, bY],
[aX, aY],
line.startBinding.gap
);
if(intersectA.length > 0) {
line.points[0] = [0, 0];
for(var i = 1; i<line.points.length; i++) {
line.points[i][0] -= intersectA[0][0] - line.x;
line.points[i][1] -= intersectA[0][1] - line.y;
}
line.x = intersectA[0][0];
line.y = intersectA[0][1];
}
}
function recalculateEndPointOfLine(line, el, elB, gapValue) {
const aX = el.x + el.width/2;
const bX = (line.points.length <=2 && elB) ? elB.x + elB.width/2 : line.x + line.points[line.points.length-2][0];
const aY = el.y + el.height/2;
const bY = (line.points.length <=2 && elB) ? elB.y + elB.height/2 : line.y + line.points[line.points.length-2][1];
line.endBinding.gap = gapValue;
line.endBinding.focus = 0;
const intersectA = ea.intersectElementWithLine(
el,
[bX, bY],
[aX, aY],
line.endBinding.gap
);
if(intersectA.length > 0) {
line.points[line.points.length - 1] = [intersectA[0][0] - line.x, intersectA[0][1] - line.y];
}
}

View File

@@ -0,0 +1 @@
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 100 100" stroke="#000"><path fill="none" stroke-linecap="round" stroke-width="4" d="M10 10h80m-80 0h80m0 0v40m0-40v40m0 0H10m80 0H10m0 0V10m0 40V10"/><g stroke-linecap="round"><path fill="none" stroke-width="4" d="M10 90c4.5-6.67 22.5-33.33 27-40M10 90c4.5-6.67 22.5-33.33 27-40"/><path fill-rule="evenodd" stroke-width="0" d="m37 50-2.35 14.81-10.51-7.09L37 50"/><path fill="none" stroke-width="4" d="M37 50c-.55 3.44-1.09 6.89-2.35 14.81M37 50c-.9 5.69-1.81 11.39-2.35 14.81m0 0c-4.05-2.73-8.1-5.46-10.51-7.09m10.51 7.09c-2.73-1.83-5.45-3.67-10.51-7.09m0 0C26.78 56.13 29.43 54.55 37 50m-12.86 7.72C29.26 54.65 34.39 51.57 37 50m0 0s0 0 0 0m0 0s0 0 0 0"/></g><g stroke-linecap="round"><path fill="none" stroke-width="4" d="M90 90 63 51.67M90 90 63 51.67"/><path fill-rule="evenodd" stroke-width="0" d="m63 51.67 13.01 7.46-10.36 7.3L63 51.67"/><path fill="none" stroke-width="4" d="M63 51.67c3.02 1.73 6.03 3.46 13.01 7.46M63 51.67c3.43 1.97 6.87 3.94 13.01 7.46m0 0c-3.33 2.34-6.65 4.69-10.36 7.3m10.36-7.3c-3.43 2.42-6.86 4.84-10.36 7.3m0 0c-.96-5.35-1.92-10.7-2.65-14.76m2.65 14.76c-.9-4.99-1.79-9.98-2.65-14.76m0 0s0 0 0 0m0 0s0 0 0 0"/></g><g stroke-linecap="round"><path fill="none" stroke-width="4" d="M50 90V50m0 40V50"/><path fill-rule="evenodd" stroke-width="0" d="m50 50 6.34 13.59H43.66L50 50"/><path fill="none" stroke-width="4" d="M50 50c2.27 4.86 4.53 9.72 6.34 13.59M50 50c1.62 3.47 3.24 6.95 6.34 13.59m0 0H43.66m12.68 0H43.66m0 0C46.18 58.2 48.69 52.81 50 50m-6.34 13.59C45.75 59.12 47.84 54.64 50 50m0 0s0 0 0 0m0 0s0 0 0 0"/></g></svg>

After

Width:  |  Height:  |  Size: 1.6 KiB

View File

@@ -23,5 +23,6 @@
"juggl",
"obsidian-functionplot",
"obsidian-tikzjax",
"obsidian-export-image"
"obsidian-export-image",
"obsidian-graphviz"
]

14
.obsidian/plugins/3d-graph/data.json vendored Normal file
View File

@@ -0,0 +1,14 @@
{
"filters": {
"doShowOrphans": true
},
"groups": {
"groups": []
},
"display": {
"nodeSize": 1,
"linkThickness": 2,
"particleSize": 6,
"particleCount": 20
}
}

View File

@@ -2715,6 +2715,7 @@ odpowiadające
oporze
okładkami
obszaru
ostrzegawczym
GoTo
GS
Gl
@@ -6679,6 +6680,7 @@ entropia
energię
elektryczną
energii
edge
Length
Link
LN
@@ -7983,6 +7985,7 @@ Layout
Layers
Laboratoria
Laplace
Latch
Filter
FlateDecode
Font
@@ -10735,6 +10738,13 @@ sprawność
siatce
strukturalny
strukturze
sekwencja
symboli
stanu
stosunew
stosunek
sterującego
sygnał
JQ
Js
JX
@@ -13336,6 +13346,8 @@ xsN
xsG
xoz
xcD
xjxi
xixj
QL
QW
QQx
@@ -18722,6 +18734,7 @@ TWP
Transformatory
Transformator
Tylko
Transmitancja
Annots
Annot
Aac
@@ -20013,6 +20026,8 @@ Ależ
Algorithm
Array
Arrows
Automaty
Apply
Subtype
SGw
SI
@@ -21334,6 +21349,7 @@ Szachownica
SHS
Statyczny
SHF
Synteza
Rect
Re
Resources
@@ -22645,6 +22661,8 @@ Rekurencyjny
Rezystory
Rezystancja
Rodzaje
Rzeczywisty
Realizacja
Navigation
No
Nj
@@ -33241,6 +33259,8 @@ Domowe
Duża
Dławik
DHS
Dane
Działanie
dA
dET
dg
@@ -34632,6 +34652,7 @@ długotrawale
dobroć
dopuszczalna
dużej
dające
YI
YT
Yv
@@ -35966,6 +35987,7 @@ YRm
Yib
YuL
YeoQT
YhKB
cVuiT
cJ
cN
@@ -37325,6 +37347,12 @@ cena
cewka
czyli
częstotliwości
ciągłej
całkujący
czujniki
czujnik
cofa
cpG
bI
bx
bM
@@ -38705,6 +38733,7 @@ bin
będą
bezstykowo
bramek
bezpamięciowego
jW
je
jz
@@ -39989,6 +40018,7 @@ jednakowo
jednakowych
jaką
jomega
jazdy
ac
af
ao
@@ -41333,6 +41363,8 @@ appendChild
allElements
arytmetycznego
admin
automatu
asynchronicznoego
uH
uS
uVn
@@ -42649,6 +42681,7 @@ uszkodzeń
upływność
upływu
uśrednianie
układu
Mh
MediaBox
MI
@@ -44010,6 +44043,8 @@ Maciej
Malczyk
Matlab
Małej
Moore
Mealy
lauG
lc
lS
@@ -47950,6 +47985,7 @@ Internet
Indukcja
Indukcyjność
Izolacja
Idealny
qF
qIF
qy
@@ -51915,6 +51951,14 @@ resistor
rdzeniem
rezonansu
rdzenia
równoprawdopodobne
rozkład
równomierny
rzędu
realizuje
różne
różniczkujący
rising
tI
tU
ta
@@ -53259,6 +53303,10 @@ temperaturą
temperatur
tyg
trident
tabelką
transmitancję
tablicę
torach
wo
wHJ
wKe
@@ -54568,6 +54616,14 @@ wykrywa
własnego
wejsciowy
wykresami
wystarcza
warunkowe
wejść
wyjściu
wyjścia
wejścia
wyjść
wjedzie
pDJ
parenleftbigg
parenrightbigg
@@ -56012,6 +56068,15 @@ powietrzne
przekładnia
przyczyna
pole
przy
pamięcią
prawdopodobieństwa
pxi
pxjxi
programujących
przejść
przejeździe
pociąg
HD
Ho
Hg
@@ -58581,6 +58646,7 @@ UqX
Uob
Uchyb
UNDEFINED
Utwórz
yr
yukC
yF
@@ -61202,6 +61268,9 @@ Zastępcza
Zakres
Znamionowa
Zasilające
Zakładając
Zaprojektować
Załóż
mD
ma
mj
@@ -62559,6 +62628,7 @@ maksymalne
maleje
magnettcznym
multiplekserze
markowa
nD
nF
nZ
@@ -63898,6 +63968,11 @@ nieliniowy
niezawodność
nieliniowość
nieergodyczne
niezależne
niestrzeżonym
nad
nimi
narastające
gNx
gHI
gri
@@ -65236,6 +65311,8 @@ grzałki
gray
gromadzi
galwaniczna
generuje
gęstości
kXk
kQ
kx
@@ -66627,6 +66704,8 @@ kOhm
który
końcó
konwersji
kolejowym
kierunku
üx
ün
ür
@@ -69346,6 +69425,16 @@ zmian
zmienne
zniamionowe
zawartego
założeniach
zmiennej
zapisania
zależnie
zgodnie
zainstalowano
znajduje
zapalić
zgasnąć
zbocze
ÜI
Üj
ÜX
@@ -69431,6 +69520,7 @@ zawartego
ŻP
ŻU
ŻJ
Żródło
ńE
ńk
ńq
@@ -69686,6 +69776,7 @@ zawartego
ścieżką
ślizgaczem
światłoczuły
światłem
ŃI
ŃMZo
ŃO
@@ -69835,6 +69926,7 @@ zawartego
źródle
źródła
źródeł
źrodło
ÖBq
ÖS
ÖH
@@ -69904,6 +69996,7 @@ zawartego
Śf
Śi
Średnia
Światło
öQD
öL
öQ

File diff suppressed because one or more lines are too long

View File

@@ -1,7 +1,7 @@
{
"id": "obsidian-desmos",
"name": "Desmos",
"version": "0.6.4",
"version": "0.6.5",
"minAppVersion": "0.9.12",
"description": "Embed Desmos graphs into your notes",
"author": "Nigecat"

File diff suppressed because it is too large Load Diff

File diff suppressed because one or more lines are too long

View File

@@ -1,7 +1,7 @@
{
"id": "obsidian-excalidraw-plugin",
"name": "Excalidraw",
"version": "1.8.20",
"version": "1.8.21",
"minAppVersion": "1.1.6",
"description": "An Obsidian plugin to edit and view Excalidraw drawings",
"author": "Zsolt Viczian",

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,10 @@
{
"id": "obsidian-graphviz",
"name": "Obsidian Graphviz",
"version": "1.0.5",
"minAppVersion": "0.11.5",
"description": "Render Graphviz Diagrams",
"author": "Feng Peng",
"authorUrl": "https://QAMichaelPeng.github.io",
"isDesktopOnly": true
}

View File

@@ -0,0 +1,4 @@
.d3graphvizError{
color: red;
border: 1px solid red;
}

View File

@@ -4,35 +4,22 @@
"type": "split",
"children": [
{
"id": "0151c4c9984436ee",
"id": "52816fca565e1ce6",
"type": "tabs",
"children": [
{
"id": "d1df4f21c129a033",
"id": "5fd45b8bad028c1b",
"type": "leaf",
"state": {
"type": "markdown",
"state": {
"file": "TIiK/Wykład/3. Łańcuchy markowa.md",
"mode": "source",
"source": false
}
}
},
{
"id": "8b7988c9bc4c348d",
"type": "leaf",
"state": {
"type": "markdown",
"state": {
"file": "TIiK/Ćwiczenia/2. Markow.md",
"file": "TC/Wykład/7..md",
"mode": "source",
"source": false
}
}
}
],
"currentTab": 1
]
}
],
"direction": "vertical"
@@ -98,7 +85,7 @@
"state": {
"type": "backlink",
"state": {
"file": "TIiK/Ćwiczenia/2. Markow.md",
"file": "TC/Wykład/7..md",
"collapseAll": false,
"extraContext": false,
"sortOrder": "alphabetical",
@@ -115,7 +102,7 @@
"state": {
"type": "outgoing-link",
"state": {
"file": "TIiK/Ćwiczenia/2. Markow.md",
"file": "TC/Wykład/7..md",
"linksCollapsed": false,
"unlinkedCollapsed": true
}
@@ -138,7 +125,7 @@
"state": {
"type": "outline",
"state": {
"file": "TIiK/Ćwiczenia/2. Markow.md"
"file": "TC/Wykład/7..md"
}
}
},
@@ -216,45 +203,48 @@
"markdown-importer:Open format converter": false,
"zk-prefixer:Create new unique note": false,
"audio-recorder:Start/stop recording": false,
"obsidian-excalidraw-plugin:Create new drawing": false,
"3d-graph:3D Graph": false,
"juggl:Juggl global graph": false,
"obsidian-excalidraw-plugin:Create new drawing": false,
"breadcrumbs:Breadcrumbs Visualisation": false
}
},
"active": "8b7988c9bc4c348d",
"active": "5fd45b8bad028c1b",
"lastOpenFiles": [
"TIiK/Wykład/3. Łańcuchy markowa.md",
"TIiK/Ćwiczenia/2. Markow.md",
"TIiK/Wykład/2..md",
"TIiK/Wykład/1..md",
"TIiK/Ćwiczenia/1. Logarytmy.md",
"TIiK/TIiK.md",
"AMiAL/AMiAL.md",
"!Załączniki/7. 2023-04-12 11.26.22.excalidraw.md",
"TC/Wykład/7..md",
"!Załączniki/7. 2023-04-12 09.22.20.excalidraw.md",
"TC/Wykład/6. Układy Sekwencyjne.md",
"!Załączniki/7. 2023-04-12 09.20.18.excalidraw.md",
"!Załączniki/7. 2023-04-12 09.15.24.excalidraw.md",
"TC/Wykład/Wykład.md",
"!Załączniki/7. 2023-04-12 09.03.55.excalidraw.md",
"TC/Wykład/2. Optymalizacja ze stanem nieokreślonym.md",
"TC/Wykład/1. Optymalizacja.md",
"TC/Wykład/3. ?.md",
"TC/Wykład/4. ?.md",
"AMiAL/Ćwiczenia/Zadania/Całki_Zast/Zadanie 2.md",
"AiSD/AiSD.md",
"TC/Wykład/5..md",
"!Załączniki/7. 2023-04-12 08.50.21.excalidraw.md",
"!Załączniki/7. 2023-04-12 08.31.18.excalidraw.md",
"!Załączniki/7. 2023-04-12 08.17.20.excalidraw.md",
"TC/Wykład/0. Wstęp.md",
"!Załączniki/1. Optymalizacja 2023-03-01 10.20.27.excalidraw.md",
"TC/TC.md",
"AMiAL/Ćwiczenia/Zadania/Całki/Zadanie 1.md",
"AMiAL/Ćwiczenia/Zadania/Untitled 1.md",
"AiSD/Ćwiczenia/1. Rozwiązywanie równań rekurencyjnych.md",
"AiSD/Ćwiczenia/2. Ćwiczenia.md",
"AMiAL/AMiAL.md",
"EiM/EiM.md",
"AiSD/AiSD.md",
"Elektrotechnika/Ćwiczenia/20230331101912.md",
"!Załączniki/20230331101912 2023-03-31 11.19.09.excalidraw.md",
"!Załączniki/Excalidraw/Scripts/Downloaded/Normalize Selected Arrows.svg",
"!Załączniki/Excalidraw/Scripts/Downloaded/Normalize Selected Arrows.md",
"!Załączniki/Excalidraw/Scripts/Downloaded/Fixed inner distance.svg",
"!Załączniki/Excalidraw/Scripts/Downloaded/Fixed inner distance.md",
"!Załączniki/Excalidraw/Scripts/Downloaded/Alternative Pens.svg",
"AMiAL/!Materiały/calki_1.pdf",
"AMiAL/Ćwiczenia/Zadania/Całki_Zast/Zadanie 2.tex",
"AMiAL/Ćwiczenia/Zadania/Całki_Zast",
"TC/Wykład/5..md",
"!Załączniki/5. 2023-03-22 10.19.43.excalidraw.md",
"TC/Wykład/3. ?.md",
"TC/Wykład/Wykład.md",
"EiM/EiM.md",
"EiM/Wykłady/2. Elementy bierne.md",
"EiM/Wykłady/3. Półprzewodniki oraz złącze pn.md",
"AMiAL/Wykłady/2 SEM/10. Całka niewłaściwa.md",
"Elektrotechnika/Ćwiczenia/20230317101750.md",
"!Załączniki/20230317101750 2023-03-17 11.25.47.excalidraw.md",
"!Załączniki/20230317101750 2023-03-17 11.06.40.excalidraw.md",
"Fizyka/Laboratoria",
"!Załączniki/Pasted image 20230314104143.png",
"AMiAL/!Materiały/calki_1.pdf",
"PI/Wykłady/2 SEM",
"AiSD/Ćwiczenia",
"!Załączniki/Excalidraw/Scripts/Downloaded/Box Selected Elements.svg",
@@ -263,11 +253,9 @@
"!Załączniki/Excalidraw/Scripts/Downloaded/Elbow connectors.svg",
"!Załączniki/Excalidraw/Scripts/Downloaded/Convert freedraw to line.svg",
"!Załączniki/Excalidraw/Scripts/Downloaded/Connect elements.svg",
"!Załączniki/Excalidraw/Scripts/Downloaded/Auto Layout.svg",
"!Załączniki/Excalidraw/Scripts/Downloaded",
"!Załączniki/Excalidraw/Scripts",
"!Załączniki/Recording 20230307101855.webm",
"!Załączniki/Drawing 2022-10-28 10.29.21.excalidraw.svg",
"!Załączniki/Recording 20230307101521.webm",
"TC/Untitled.canvas"
]

View File

@@ -49,6 +49,15 @@ $$
$$
\begin{gather}
\int \frac{1}{\sqrt[3]{x^{2}}}dx=\int\sqrt[3]{x^{2}}^{-1}dx=\int ((x^{2})^{\frac{1}{3}})^{-1}dx=\int x^{-\frac{2}{3}}dx=3x^{\frac{1}{3}}+C
\end{gather}
$$
## 14.
$$
\begin{gather}
\int\frac{x^{2}-x-2}{\sqrt[3]{x^{2}}}dx=\int\frac{x^{2}-x-2}{x^{\frac{2}{3}}}dx=\int \frac{x^{2}}{x^{\frac{2}{3}}}dx-\int \frac{x}{x^{\frac{2}{3}}}dx-\int \frac{2}{x^{\frac{2}{3}}}dx=\\
=
\end{gather}
$$
## 18.

View File

@@ -0,0 +1,16 @@
Transmitancja - stosunek wyjścia do wejścia
![[20230331101912 2023-03-31 10.19.16.excalidraw]]
1 wyznaczyć transmitancję układu
![[20230331101912 2023-03-31 10.23.29.excalidraw]]
Rzeczywisty układ całkujący = $\frac{1}{1+sT}$
Idealny = $K(s)=\frac{1}{sT}$
Rzeczywisty układ różniczkujący
$K(S)=\frac{sT}{1+sT}$
Idealny $sT$
Apply]]

View File

@@ -0,0 +1,26 @@
![[6. Układy Sekwencyjne 2023-03-29 08.31.04.excalidraw]]
Automaty Moore'a i Mealy'ego
```dot
digraph{
layout=circo
splines=true
1 [label="1/1"]
2 [label="2/1"]
3 [label="3/0"]
4 [label="4/0"]
1->1 [label="ab=11"]
1->2 [label="ab=10"]
2->2 [label="10"]
2->3 [label="00"]
3->3 [label="00"]
3->4 [label="10"]
4->4 [label="10"]
4->1 [label="11"]
}
```
|||||
![[6. Układy Sekwencyjne 2023-03-29 08.48.57.excalidraw]]

36
TC/Wykład/7..md Normal file
View File

@@ -0,0 +1,36 @@
---
Date: [20230412081511]
---
# SR Latch
## Działanie
![[7. 2023-04-12 08.17.20.excalidraw]]
## Realizacja
![[7. 2023-04-12 08.31.18.excalidraw]]
![[7. 2023-04-12 08.50.21.excalidraw]]
# Synteza układów
## 1.
### Utwórz tablicę przejść wyjść automatu asynchronicznoego sterującego światłem ostrzegawczym na niestrzeżonym przejeździe kolejowym.
Na torach zainstalowano czujniki *a* i *b* dające sygnał **1** gdy nad nimi znajduje się pociąg. Światło ma się zapalić gdy pociąg wjedzie nad czujnik a(b), a zgasnąć gdy wjedzie na b(a) w zależności od kierunku jazdy. Załóż że pociąg nigdy się nie cofa.
![[7. 2023-04-12 09.03.55.excalidraw]]
![[7. 2023-04-12 09.15.24.excalidraw]]
![[7. 2023-04-12 09.20.18.excalidraw]]
![[7. 2023-04-12 09.22.20.excalidraw]]
# D Latch
TODO
![[7. 2023-04-12 11.26.22.excalidraw]]

View File

@@ -0,0 +1,3 @@
![[3. Układy iteracyjne 2023-03-29 10.28.25.excalidraw]]
Zaprojektować układ który zależnie od stanu wejść programujących x1 i x2 realizuje na wyjściu różne funkcje Z argumentów x3 i x4 zgodnie z tabelką

32
TIiK/Wykład/4..md Normal file
View File

@@ -0,0 +1,32 @@
1100 1000 1110 1001 101 | 11
Dane jest sekwencja. Zakładając że 19 symboli wystarcza do zapisania
Entropia w przypadku bezpamięciowego źródła:
p0=9/19
p1=10/19
Hx=-9/19 ld 9/19 - 10/19 ld 10/19= 0.998bit
Źródło markowa 1 rzędu
0 1
p(0/0)=4/9
p(1/0)=5/9
p(0/1)=5/10
p(1/1)=5/10
```dot
digraph {
rankdir=TB;
node [ shape = circle ];
0->0 [label="4/9"]
0->1 [label="5/9"]
1->1 [label="5/10"]
1->0 [label="5/10", minlen=3]
}
```
|xi|xj|Pxj|pxi/xj|pxjxi|
|-|-|-|-|-|
|0|0|9/19|4/9|4/19|
|0|1|9/19|5/9|5/19|
|1|0|10/19|5/10|5/19|
|1|1|10/19|5/10|5/19|

View File

@@ -0,0 +1,29 @@
Żródło generuje wiadomości 0, 1
Entropia źródła przy założeniach:
a) równoprawdopodobne i niezależne -
x={0,1}
P_xi(1/2,1/2)
H(X)=ld 2 = 1 bit
b) niezależne - p0=3/4 p1=1/4
H(x)=-3/4ld3/4-1/4ld1/4=0.81 Hb\<Ha
c) źrodło z pamięcią, równo prawdopodobne
P(0/1)=P(1/0)=1/3
P(0)=P(1)=1/2
![[2. Markow 2023-03-24 12.34.20.excalidraw]]
$P(0)=\frac{2}{3}P(0)+ \frac{1}{3}P(1)$
$P(1)=\frac{2}{3}P(1)+ \frac{1}{3}P(0)$
$P0+P1=1$
p0=1/2=P1
$H_{1}(x)=-\sum\sum P(x_{i}x_{j})ld P(x_{i}/x_{j )=}0.688$
|xjxi|P(xj)|P(xi/xj)|p(xixj)|
|-|-|-|-|
|00|1/2|2/3|1/3|
|01|1/2|1/3|1/6|
|10|1/2|1/3|1/6|
|11|1/2|2/3|1/3|
Funkcja gęstości prawdopodobieństwa dla zmiennej ciągłej rozkład równomierny 0,2
![[2. Markow 2023-03-24 13.21.16.excalidraw]]