row_id
int64 0
48.4k
| init_message
stringlengths 1
342k
| conversation_hash
stringlengths 32
32
| scores
dict |
|---|---|---|---|
31,119
|
get element actualheight xaml wpf
|
0f68d981b85d82e654081887160a1cd8
|
{
"intermediate": 0.38232141733169556,
"beginner": 0.28355759382247925,
"expert": 0.3341209292411804
}
|
31,120
|
in go what is gopls?
|
dfd6e2134a6038107fba2209ddf5ca34
|
{
"intermediate": 0.2841626703739166,
"beginner": 0.22216349840164185,
"expert": 0.49367380142211914
}
|
31,121
|
separator thickness wpf
|
e36f8127d746b55a6befab3b4c1c028f
|
{
"intermediate": 0.4109569787979126,
"beginner": 0.2816771864891052,
"expert": 0.30736589431762695
}
|
31,122
|
help me write a pinescript strategy that using "standard deviation of spread ditterence on Z-score to long & short
Step 1: Get the spread ( asset price
VWAP)
Step 2: Input value for "Rolling Window", default value "250"
Step 2: Form a Z-score indicator with
MAD as the mean. non-overlav.
Step 4: Buy Sell strategy logic by using "standard deviation input" for
"Long Entry" "Long Stop Loss" "Long
Take Profit" "Short Entry" "Short Stop
Loss" "Short Take Profit"
Default Value:
Long Entry -1, Long Stop Loss -1.5,
Long Take Profit 0;
Short Entry +1, Short Stop Loss +1.5,
Short Take Profit 0.
|
ac57612a609de438b9dd6ad6b86ea49b
|
{
"intermediate": 0.3497386574745178,
"beginner": 0.25174680352211,
"expert": 0.39851459860801697
}
|
31,123
|
help me write a pinescript strategy that using "standard deviation of spread ditterence on Z-score to long & short
Step 1: Get the spread ( asset price
VWAP)
Step 2: Input value for "Rolling Window", default value "250"
Step 2: Form a Z-score indicator with
MAD as the mean. non-overlav.
Step 4: Buy Sell strategy logic by using "standard deviation input" for
"Long Entry" "Long Stop Loss" "Long
Take Profit" "Short Entry" "Short Stop
Loss" "Short Take Profit"
Default Value:
Long Entry -1, Long Stop Loss -1.5,
Long Take Profit 0;
Short Entry +1, Short Stop Loss +1.5,
Short Take Profit 0.
|
730639aa172275d134cfb30067661ae2
|
{
"intermediate": 0.3497386574745178,
"beginner": 0.25174680352211,
"expert": 0.39851459860801697
}
|
31,124
|
columns = ['E', 'F', 'I', 'J', 'M', 'N', 'Q', 'R', 'T', 'X', 'AB', 'AF'] # 需要写入数据的列标识列表
for i in range(values_min_P1.shape[0]):
row_idx = i + 9
for col_idx, column in enumerate(columns):
# 构建当前列单元格标识
cell = column + str(row_idx)
# 获取值
value = values_min_P1[i, col_idx]
# 将值写入单元格
sheet[cell] = value value = values_min_P1[i, col_idx]
IndexError: index 1 is out of bounds for axis 1 with size 1
Process finished with exit code 1
|
4444edf831362092c53a4879bf737d2d
|
{
"intermediate": 0.33720123767852783,
"beginner": 0.37328630685806274,
"expert": 0.28951242566108704
}
|
31,125
|
write a python script that takes files from a folder and removes spaces from their names.
|
f72ef4fb368f4c85b6f9267a17acad80
|
{
"intermediate": 0.3621077835559845,
"beginner": 0.2188282608985901,
"expert": 0.4190639853477478
}
|
31,126
|
write a C# script for a 2d game that allows the character to move up, down, left and right
|
4b4d0301147b1c7618e6b6b267b9ab1c
|
{
"intermediate": 0.3794018626213074,
"beginner": 0.2954784631729126,
"expert": 0.32511964440345764
}
|
31,127
|
from typing import TextIO
def get_game_dict(game_data: TextIO) -> dict[str, list[int]]:
"""Return a dictionary containing the team name and a list of points
earned in each game for each team in the open file game_data.
>>> input_file = open('sample_games.txt')
>>> get_game_dict(input_file)
{'Toronto Maple Leafs': [2, 2, 1, 0, 0, 2], 'Grande Prairie Storm': [], \
'Montreal Canadiens': [1, 2, 1, 0, 2]}
>>> input_file.close()
"""
|
069378d600bf3f6547b8d2da45d0b25b
|
{
"intermediate": 0.45601651072502136,
"beginner": 0.2897624373435974,
"expert": 0.25422099232673645
}
|
31,128
|
This project will have 3 phases:
In step one, you will design a solution to a given problem.
In step two, you will watch an assessment tutorial video (found in the next tab).
In step three, you will do a self-assessment of your solution.
PROBLEM:
Design a World Program with Compound Data. You can be as creative as you like, but keep it simple. Above all, follow the recipes! You must also stay within the scope of the first part of the course. Do not use language features we have not seen in the videos.
If you need inspiration, you can choose to create a program that allows you to click on a spot on the screen to create a flower, which then grows over time. If you click again the first flower is replaced by a new one at the new position.
You should do all your design work in DrRacket. Following the step-by-step recipe in DrRacket will help you be sure that you have a quality solution.
For this quiz you will be asked to design a world program using the HtDW and other recipes. Your solution will be assessed according to the following rubric:
Is the program safe?
The program file should be set to beginning student language and there should be no require declarations other than (require 2htdp/image) and (require 2htdp/universe). If the program is in a language other than BSL, then it gets 0 points for the rest of the rubric.
Is the program "commit ready"?
The file should be neat and tidy, no tests or code should be commented out other than stubs and templates and all scratch work should be removed.
Are all HtDW elements complete and do they have high internal quality?
All HtDW elements should be present, well formed, and have high internal quality. The file must include Constants, Data Definitions and Functions. The Constants section must be complete, there must be a main function that is correct and operates on a compound type. The main function must have all necessary big-bang options, and for each option, the handler must be present in the file.
Are all HtDD elements complete and do they have high internal quality?
Examine the Data Definition for the world state. All elements of HtDD must be present and have high internal quality. This includes a structure definition, type comment, interpretation, examples and the template.
Are all HtDF elements complete and do they have high internal quality?
Choose either the to-draw, on-key or on-mouse handler. All elements of HtDF must be present and have high internal quality. This includes the Signature, Purpose, Stub, Examples/Tests, Template and the Function Body.
Does the design satisfy the problem requirements?
The program must be a World Program, operate on Compound Data, and be within the scope of the course.
|
9a2b4fe3807c7cac483591f1868e5417
|
{
"intermediate": 0.31790968775749207,
"beginner": 0.37191662192344666,
"expert": 0.3101736605167389
}
|
31,129
|
Требуется разработать на языке С++, без использования сторонних
библиотек и фреймворков следующую библиотеку:Библиотека, реализующая калькулятор простого арифметического
выражения с использованием обратной польской записи. Имеется
возможность преобразовать арифметическое выражение в инфиксной
форме в префиксную/постфиксную, и наоборот, а также возможность
вычислить его. Библиотека должна быть оформлена как отдельный заголовочный файл (.h) с
файлом реализации (.cpp). Основная программа должна кратко показывать
принципы и механизмы взаимодействия с библиотекой, включая аномальные
ситуации. Эти аномальные ситуации (включая проверки в самой библиотеке)
должны быть обработаны с помощью блока try...catch и функции throw.
Взаимодействие с программой осуществляется через понятный и удобный
пользовательский интерфейс. Принципы работы пользовательского интерфейса
должны быть подробно описаны в отчете о проделанной работе. Выводимые
данные должны быть форматированными.
|
826de482b3698ceee7fa537ae17b48b2
|
{
"intermediate": 0.16541075706481934,
"beginner": 0.6917998790740967,
"expert": 0.14278939366340637
}
|
31,130
|
<template>
<div class="home-page" v-loading="isShowLoading" ondragstart="return false" >
<template v-if="isShowSwiper">
<Swiper
direction="vertical"
class="home-swiper"
:resistanceRatio="0"
:modules="swiperModules"
@slideChange="onOuterSlideChange"
@swiper="onOuterSwiper"
v-if="widgetList[0]?.length"
>
<template v-for="(widgetItem, index) in widgetList" :key="index">
<swiper-slide v-if="widgetItem.length">
<Swiper
observer: true
class="second-swiper"
:nested="true"
direction="vertical"
slidesPerView="auto"
:resistanceRatio="0"
:modules="swiperModules"
:freeMode="{
enabled: true
}"
@swiper="onInnerSwiper"
@sliderMove="onInnerSliderMove"
@touchStart="onInnerSliderStart"
@transitionEnd="onTransitionEnd"
>
<swiper-slide class="swiper-container" :style="{
'padding-top': cptDistDistanceFromTop + 'px'
}" >
<!--
Because the 'swiper' will not detect changes in the internal height of the component,
So it may cause some components to fail to load
The solution is to load an image display: none, and dynamically control the display and hiding of this image.
Let the 'swiper' dynamically monitor the internal height to prevent the effect of the component not being able to load
-->
<img
v-if="isUpdateSwiperHeight"
style="display: none"
:src="`${IMAGE_URL}assets/image/icons/rightArrowGrey.png`"
alt=""
/>
<component
:style="{
...(componentIndex + 1 === widgetItem.length && {paddingBottom:tabbarHeight + 'px'})
}"
v-for="(componentItem, componentIndex) in widgetItem"
:key="componentItem.uuid"
:is="filterComponent(componentItem.categoryType)"
:properties="componentItem"
@updateSlideHeight="onUpdateSlideHeight"
></component>
</swiper-slide>
</Swiper>
</swiper-slide>
</template>
</Swiper>
</template>
<template v-else>
<div class="not-PIPL-gateway">
<div class="not-PIPL-gateway-logo">
<img :src="badgeLogoUrl" alt="" />
</div>
<div class="not-PIPL-gateway-search">
<div class="gateway-search-box" @click="router.push('/search')">
<img :src="searchIconUrl" alt="" />
<span>搜索</span>
</div>
</div>
<recommend-list
:title="$t('modules.detailPage.BEST_SELLING_ITEM_RECOMMENDATION')"
/>
</div>
</template>
<float-login-prompt :isShow="isShowFloatLoginPrompt" showPageType="gateway" @handleLogin="handleLogin"/>
<popup-widget :widgetList="popupWidgetList"></popup-widget>
<gateway-floating-window
:floatingData="floatingData"
:isShowBackTop="isShowBackTop"
@resettingScrollTop="handleResettingScrollTop"
/>
</div>
</template>
<script setup>
import { useWindowSize } from '@vueuse/core';
import { useRouter } from 'vue-router';
import { useStore } from 'vuex';
import { isAppEnv } from '@/utils/device';
import { Bridge } from '@/utils/bridge';
import { nextTick, onMounted, ref, shallowRef, onUnmounted, computed } from 'vue';
import 'swiper/css/scrollbar';
import constants, { marketplace } from '@/constants';
import {
getGatewayModulesInfo,
getWidgetPopup,
getFloatingWindow
} from '@/models/api/landingPageApi';
import { useLess } from '@/models/hooks';
import { Scrollbar, FreeMode } from 'swiper';
import { Swiper, SwiperSlide } from 'swiper/vue';
import gatewayComponent from './gatewayComponent';
import {
isLoginAuthenticated,
isShowPIPLConfirmAlertView,
handleStartLogin
} from '@/utils/common';
import recommendList from '@/components/RecommendedAsins.vue';
import FloatLoginPrompt from '@/components/FloatLoginPrompt.vue';
import GatewayFloatingWindow from '@/components/GatewayFloatingWindow.vue';
import { LANDING_PAGE_PARAMS_PAGE_TYPE } from '@/utils/landingPageCommon.js';
import { LAYOUT_TYPE } from '@/components/landingPageComponents/common.js';
import PopupWidget from '@/components/landingPageComponents/popupWidget/PopupWidget.vue';
import { SET_AGENT_DATA } from '@/store/mutations.types';
const {
ENCRYPTED_MARKETPLACE_ID,
ENCRYPTED_MARKETPLACE_ID_LOCALE_MAP,
MARKET_PLACE_ID,
IMAGE_URL,
GATEWAY_MODULE,
NEW_IMAGE_URL
} = constants;
useLess('views/gateway/Gateway.less');
const router = useRouter();
const store = useStore();
const isShowSwiper = ref(false);
const isShowLoading = ref(true);
const swiperModules = [Scrollbar, FreeMode];
// Full screen component type
const FULL_SCREEN_COMPONENTS = ['bestseller'];
// If the type of infinite scrolling component is infinite scrolling, place this component at the end
const WATERFALL_COMPONENTS = ['dealWidget', 'recommendedAsin'];
const widgetList = ref([]);
const popupWidgetList = ref([]); // Pop up advertising data
const isUpdateSwiperHeight = ref(true);
const badgeLogoUrl = `${NEW_IMAGE_URL}04_BadgeLogo/Logo_Settings3x.png`;
const searchIconUrl = `${IMAGE_URL}assets/svg/dNavSearch.svg`;
const floatingData = shallowRef({});
const innerSwiperRef = ref(null);
const activeOuterSlideIndex = ref(0);
const isShowBackTop = ref(false);
// 当前的选中的内部slide
const activeSlideRef = ref(null);
const isShowFloatLoginPrompt = ref(false);
const windowClientHeight = ref(0);
const cptDistDistanceFromTop = computed(
() => store.state.navigator.agentData?.top ?? 0
);
const tabbarHeight = computed(() => store.state.common.tabbarHeight ?? 0);
const handleLogin = async () => {
if (await isShowPIPLConfirmAlertView()) return;
handleStartLogin();
};
const onInnerSliderStart = swiper => {
activeSlideRef.value = swiper;
swiper.setTranslate(swiper.translate); // 设定偏移量
};
const onInnerSliderMove = swiper => {
if((swiper.translate * -1) > windowClientHeight.value) {
if(!isShowBackTop.value) isShowBackTop.value = true;
}else{
if(isShowBackTop.value) isShowBackTop.value = false;
}
};
const onOuterSlideChange = el => {
activeOuterSlideIndex.value = el.activeIndex;
};
const onInnerSwiper = el => {
innerSwiperRef.value = el;
};
const handleResettingScrollTop = () => {
isShowBackTop.value = false;
activeSlideRef.value.setTranslate(0);
};
const onUpdateSlideHeight = () => {
isUpdateSwiperHeight.value = false;
nextTick(() => {
isUpdateSwiperHeight.value = true;
});
};
const combinedShelfDataProcessing = data => {
// If it is infinite scrolling, place this component at the back
const componentIndex = data.findIndex(component => {
if (
WATERFALL_COMPONENTS.some(
infiniteScrollingComponent =>
infiniteScrollingComponent === component.categoryType
) &&
component.displayQuantity === 0 &&
component.showType !== LAYOUT_TYPE.TRANSVERSE
) {
return true;
}
return false;
});
if (componentIndex >= 0) {
data.push(data.splice(componentIndex, 1)[0]);
}
const list = [[]];
// Distinguish full screen components
data.forEach(categoryItem => {
// Find full screen components
if (
FULL_SCREEN_COMPONENTS.some(item => item === categoryItem.categoryType)
) {
list.push([categoryItem]);
// After meeting the conditions, create a new array and add subsequent items to the new array
list.push([]);
} else {
list[list.length - 1].push(categoryItem);
}
});
list.forEach(item => {
if (item.length) {
widgetList.value.push(item);
}
});
};
const filterComponent = categoryType => {
return gatewayComponent.filter(
componentItem => componentItem.type === categoryType
)?.[0]?.component;
};
// Combined shelf data
const combinedShelfData = async () => {
const params = {
marketplaceId: marketplace,
language: ENCRYPTED_MARKETPLACE_ID_LOCALE_MAP[marketplace],
pageType: LANDING_PAGE_PARAMS_PAGE_TYPE.HOME_PAGE
};
const getGatewayModulesInfoRes = await getGatewayModulesInfo(params)['catch'](
() => {}
);
if (getGatewayModulesInfoRes?.data?.code === 200) {
combinedShelfDataProcessing(getGatewayModulesInfoRes.data.widgets);
} else {
combinedShelfDataProcessing(constants.GATEWAY_MODULE_MOCK.WIDGETS);
}
};
const getHeader = async () => {
let token = '';
if (isAppEnv()) {
if (await isLoginAuthenticated(false)) {
const { accessToken: tokenApp } = await Bridge.callFnVal(
'getAccessToken',
{}
);
token = tokenApp;
}
} else {
// This is for development process
token = sessionStorage.getItem('token') || '';
}
return { token };
};
const getWidgetPopupInfo = async () => {
const params = {
marketplaceId: marketplace,
language: ENCRYPTED_MARKETPLACE_ID_LOCALE_MAP[ENCRYPTED_MARKETPLACE_ID],
paramType: 0,
pageType: LANDING_PAGE_PARAMS_PAGE_TYPE.GATEWAY
};
const { data } = await getWidgetPopup(params, await getHeader());
if (data.code === 200) {
popupWidgetList.value = data.data?.list || [];
Bridge.callFn('saveDataToMemoryCache', {
key: 'isGatewayWidgetPopupCalled',
value: true
});
}
};
const getGatewayFloatingWindow = async () => {
const params = {
marketplaceId: marketplace,
language: ENCRYPTED_MARKETPLACE_ID_LOCALE_MAP[ENCRYPTED_MARKETPLACE_ID],
paramType: 0,
pageType: LANDING_PAGE_PARAMS_PAGE_TYPE.GATEWAY
};
const { data } = await getFloatingWindow(params, await getHeader());
if (data.code === 200) {
floatingData.value = data.data;
}
};
const getWindowSize = async () => {
await nextTick();
const { height } = useWindowSize();
windowClientHeight.value = height.value;
};
onMounted(async () => {
store.commit(`navigator/${SET_AGENT_DATA}`, { top: 0 });
isShowFloatLoginPrompt.value = !(await isLoginAuthenticated(false));
isShowLoading.value = true;
isShowSwiper.value = !(await isShowPIPLConfirmAlertView(false));
isShowLoading.value = false;
getWindowSize();
if (isShowSwiper.value) {
Bridge.callFn(
'getDataFromMemoryCache',
{
key: 'isGatewayWidgetPopupCalled'
},
res => {
console.log("isGatewayWidgetPopupCalled", res);
if (JSON.stringify(res.value) === '{}') {
getWidgetPopupInfo();
}
}
);
getGatewayFloatingWindow();
if (await isLoginAuthenticated(false)) {
combinedShelfData();
} else {
// Product requirement: Unregistered gateway data set to false data
combinedShelfDataProcessing(constants.GATEWAY_MODULE_MOCK.NOT_LOGGED_IN_DATA);
}
}
});
onUnmounted(() => {
store.commit(`navigator/${SET_AGENT_DATA}`);
});
</script>
解决滑动抖动
|
3e482351d457e2b54b3b2402c072e3bb
|
{
"intermediate": 0.3041445016860962,
"beginner": 0.4535675644874573,
"expert": 0.24228797852993011
}
|
31,131
|
<Swiper
direction="vertical"
class="home-swiper"
:resistanceRatio="0"
:modules="swiperModules"
@slideChange="onOuterSlideChange"
@swiper="onOuterSwiper"
v-if="widgetList[0]?.length"
>
<template v-for="(widgetItem, index) in widgetList" :key="index">
<swiper-slide v-if="widgetItem.length">
<Swiper
observer: true
class="second-swiper"
:nested="true"
direction="vertical"
slidesPerView="auto"
:resistanceRatio="0"
:modules="swiperModules"
:freeMode="{
enabled: true
}"
@swiper="onInnerSwiper"
@sliderMove="onInnerSliderMove"
@touchStart="onInnerSliderStart"
@transitionEnd="onTransitionEnd"
>
<swiper-slide class="swiper-container" :style="{
'padding-top': cptDistDistanceFromTop + 'px'
}" >
<!--
Because the 'swiper' will not detect changes in the internal height of the component,
So it may cause some components to fail to load
The solution is to load an image display: none, and dynamically control the display and hiding of this image.
Let the 'swiper' dynamically monitor the internal height to prevent the effect of the component not being able to load
-->
<img
v-if="isUpdateSwiperHeight"
style="display: none"
:src="`${IMAGE_URL}assets/image/icons/rightArrowGrey.png`"
alt=""
/>
<component
:style="{
...(componentIndex + 1 === widgetItem.length && {paddingBottom:tabbarHeight + 'px'})
}"
v-for="(componentItem, componentIndex) in widgetItem"
:key="componentItem.uuid"
:is="filterComponent(componentItem.categoryType)"
:properties="componentItem"
@updateSlideHeight="onUpdateSlideHeight"
></component>
</swiper-slide>
</Swiper>
</swiper-slide>
</template>
</Swiper>解决滑动抖动
|
f8bb2db442c33868d8d53ddf080ea144
|
{
"intermediate": 0.3611043095588684,
"beginner": 0.522490918636322,
"expert": 0.11640477925539017
}
|
31,132
|
Are you aware of the 3n + 1 problem?
|
7a36889da93b49557037343b413452f9
|
{
"intermediate": 0.2591420114040375,
"beginner": 0.40133172273635864,
"expert": 0.3395262360572815
}
|
31,133
|
What is the error in my C++ code below:
#include <iostream>
#include <climits>
using namespace std;
int start = 0;
int steps = 0;
int maximum = 0;
int odds = 0;
int evens = 0;
// Recursive function to calculate 3n+1
int collatz(int n){
//Check for int overflow
cout << "->(" << n << ") ";
//If n = 1
if(n == 1){
return steps;
}
//Update max
if (n > maximum){
maximum = n;
}
if(n % 2 == 0){
if (n > (INT_MAX - 1) / 3){
// max value of (2^31 - 1) / 3
throw(-1);
}
odds++;
}
else{
evens++;
}
//Recursive calls
if(n % 2 == 0){
return collatz(3 * n + 1);
}
else{
return collatz(n / 2);
}
}
int main(int argc, char *argv[]){
int n;
if (argc == 1){
cout << "Enter a 3n+1 candidate number: ";
cin >> n;
start = n;
try{
cout << "\nSolving 3n+1 - starting value:" << start << "\n";
collatz(n);
}
catch(int i){
cout << "->(----- OVERFLOW!!! ------)";
}
cout << endl;
cout << "start: " << start << endl;
cout << "steps: " << steps << endl;
cout << "max: " << maximum << endl;
cout << "odds: " << odds << endl;
cout << "evens: " << evens << endl;
n++;
}
else{
int i = 1;
while(i < argc){
n = stoi(argv[i]);
start = n;
try{
}
catch(int b){
cout << "->(###overflow###)" << endl;
cout << "\nOverflow detected for n: " << maximum << endl;
cout << "3n + 1: " << steps << endl;
cout << "something broke dude" << endl;
cout << "overflow\n" << endl;
i++;
continue;
}
cout << "start: " << start << endl;
cout << "steps: " << steps << endl;
cout << "max: " << maximum << endl;
cout << "odds: " << odds << endl;
cout << "evens: " << evens << endl;
}
}
return 0;
}
|
4efefdd88df102c837253ddbffe71aa7
|
{
"intermediate": 0.08517074584960938,
"beginner": 0.8386968374252319,
"expert": 0.07613242417573929
}
|
31,134
|
Please show me how to implement no flux boundary of concentration in Lattice boltzmann method
|
b0ca4bd2f117e088ff0996854045fc25
|
{
"intermediate": 0.12551262974739075,
"beginner": 0.08783949166536331,
"expert": 0.7866478562355042
}
|
31,135
|
检查这段代码——def getConn():
conn = pymysql.connect(host="127.0.0.1",port=3306,user="root",password="1527648qw",database="")
return conn
def isLogin():
if currentUser.getUid()=="-1"
print("user not login system,pls login first")
|
44a26395f394e82534ec5598c2ebf4ec
|
{
"intermediate": 0.27547597885131836,
"beginner": 0.5728312730789185,
"expert": 0.15169279277324677
}
|
31,136
|
Write a python script to perform the following steps:
1) Get access to internal system https://10.10.117.203/prod/ru/reports/finance_client_status using credentials.
2) Select the filters provided in page. How can I help you with identifying them?
3) For each date from start to end select date in calendar present in page. After loading date, press buttom update to load data. Finally, press buttom Excel to download the file to local machine.
4) Repeat the step three unless files for all specified dates are downloaded.
|
4d4eb31ea726ca3f02d359d613e9fac0
|
{
"intermediate": 0.5141388177871704,
"beginner": 0.23674558103084564,
"expert": 0.24911558628082275
}
|
31,137
|
Design a simple World Program with Compound Data. (in Racket programming language)
|
3131eb9d171be9dd4d2fc460c03d7c44
|
{
"intermediate": 0.32603955268859863,
"beginner": 0.2926746606826782,
"expert": 0.38128578662872314
}
|
31,138
|
a snake game using modern ui tkkbootstrape python code
|
8b01c8f755cb4fa41941c0c0d6c62c3c
|
{
"intermediate": 0.3759578764438629,
"beginner": 0.3280459940433502,
"expert": 0.29599615931510925
}
|
31,139
|
My code below skips integer parameters when I run it, can you show me how to stop skipping parameters? I think the error is in the else loop of the main function:
#include <iostream>
#include <climits>
using namespace std;
// Recursive function to calculate 3n+1
int collatz(int n, int &steps, int &maximum, int &odds, int &evens){
//Check for int overflow
cout << "->(" << n << ") ";
//If n = 1
if(n == 1){
return 1;
}
//Update max
if (n > maximum){
maximum = n;
}
if(n % 2 == 0){
if (n > (INT_MAX - 1) / 3){
// max value of (2^31 - 1) / 3
throw(-1);
}
evens++;
}
else{
odds++;
}
//Recursive calls
if(n % 2 == 0){
steps++;
return collatz(n / 2, steps, maximum, odds, evens);
}
else{
steps++;
return collatz(3*n + 1, steps, maximum, odds, evens);
}
}
int main(int argc, char *argv[]){
int start = 0;
int steps = 0;
int maximum = 0;
int odds = 0;
int evens = 0;
int n;
if (argc == 1){
cout << "Enter a 3n+1 candidate number: ";
cin >> n;
start = n;
try{
collatz(n, steps, maximum, odds, evens);
}
catch(int i){
cout << "->(----- OVERFLOW!!! ------)";
}
cout << endl;
cout << "start: " << start << endl;
cout << "steps: " << steps << endl;
cout << "max: " << maximum << endl;
cout << "odds: " << odds << endl;
cout << "evens: " << evens << endl;
n++;
}
else{
//int i = 1;
for(int i = 1; i < argc; i++){
n = stoi(argv[i]);
start = n;
try{
cout << "\nSolving 3n+1 - starting value:" << start << "\n";
collatz(n, steps, maximum, odds, evens);
}
catch(int b){
cout << "->(###overflow###)" << endl;
cout << "\nOverflow detected for n: " << maximum << endl;
cout << "3n + 1: " << steps << endl;
cout << "something broke dude" << endl;
cout << "overflow\n" << endl;
}
cout << "start: " << start << endl;
cout << "steps: " << steps << endl;
cout << "max: " << maximum << endl;
cout << "odds: " << odds << endl;
cout << "evens: " << evens << endl;
i++;
}
}
return 0;
}
|
3f648a70dec8ad4fb6d329e817db772f
|
{
"intermediate": 0.20674991607666016,
"beginner": 0.46427789330482483,
"expert": 0.328972190618515
}
|
31,140
|
How can Large Language Models be used to do Causal inference and Causal Discovery? Also how to assemble Causal Diagrams?
|
63ab7ff5d7222d79a9f7214c9292d659
|
{
"intermediate": 0.2507281005382538,
"beginner": 0.1253782957792282,
"expert": 0.6238935589790344
}
|
31,141
|
find all errors in this JS code: if (payments === null) {
console.error("null payments");
} else {
payments.getPurchases().then(purchases => {
if (purchases.some(purchase => purchase.productID === '1')) {
gameInstance.SendMessage('Yandex Games', 'GiveInApp', '1');}
if (purchases.some(purchase => purchase.productID === '2')) {
gameInstance.SendMessage('Yandex Games', 'GiveInApp', '2');}
if (purchases.some(purchase => purchase.productID === '3')) {
gameInstance.SendMessage('Yandex Games', 'GiveInApp', '3');}
if (purchases.some(purchase => purchase.productID === '4')) {
gameInstance.SendMessage('Yandex Games', 'GiveInApp', '4');}
if (purchases.some(purchase => purchase.productID === '5')) {
gameInstance.SendMessage('Yandex Games', 'GiveInApp', '5');}
if (purchases.some(purchase => purchase.productID === '6')) {
gameInstance.SendMessage('Yandex Games', 'GiveInApp', '6');}
if (purchases.some(purchase => purchase.productID === '7')) {
gameInstance.SendMessage('Yandex Games', 'GiveInApp', '7');} }) }
|
d90d2ac44a3fb5f49349c3a7fc9a8145
|
{
"intermediate": 0.31564462184906006,
"beginner": 0.3779005706310272,
"expert": 0.3064548671245575
}
|
31,142
|
help me setup so this works correctly so I can check the background process:
x, y, w, h = 100, 100, 200, 200
threshold = 400
# Paths to template images
window_template_path = "shot2Target.png"
dot_template_path = "dottemplate.png"
# Load template images
window_template = cv2.imread(window_template_path, 0)
dot_template = cv2.imread(dot_template_path, 0)
# Global variable to store the server’s response
SERVER_RESPONSE = None
# Image processing function
def process_images():
global SERVER_RESPONSE
# url = "http://10.30.227.207:8088z/shot.jpg"
frame = cv2.imread("shot(3).jpg")
# url = "http://192.168.229.55:8080/shot.jpg"
window_match_threshold = 0.75 # Adjust according to your needs
dot_match_threshold = 0.75 # Adjust according to your needs
while True:
# Fetch the frame
# img_resp = requests.get(url)
# img_arr = np.frombuffer(img_resp.content, np.uint8)
# frame = cv2.imdecode(img_arr, -1)
gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Perform template matching for the window
res = cv2.matchTemplate(gray_frame, window_template, cv2.TM_CCOEFF_NORMED)
loc = np.where(res >= window_match_threshold)
if len(loc[0]) > 0:
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
top_left = max_loc
bottom_right = (
top_left[0] + window_template.shape[1],
top_left[1] + window_template.shape[0],
)
window_roi = frame[
top_left[1] : bottom_right[1], top_left[0] : bottom_right[0]
]
# Convert the ROI to grayscale for dot detection
gray_window_roi = cv2.cvtColor(window_roi, cv2.COLOR_BGR2GRAY)
thresholded_image = cv2.adaptiveThreshold(
gray_window_roi,
255,
cv2.ADAPTIVE_THRESH_MEAN_C,
cv2.THRESH_BINARY,
11,
11,
)
blurred_image = cv2.GaussianBlur(thresholded_image, (3, 3), 0)
# Perform template matching for the dot within the window ROI
dot_res = cv2.matchTemplate(
blurred_image, dot_template, cv2.TM_CCOEFF_NORMED
)
dot_loc = np.where(dot_res >= dot_match_threshold)
if len(dot_loc[0]) > 0:
# A dot is found, perform the necessary tasks
# Save the image
if not os.path.isdir("images"):
os.mkdir("images")
image_path = "images/captured_image.jpg"
cv2.imwrite(image_path, blurred_image)
# Check the saved image
result = check_picture(image_path) # Assuming this function is defined
SERVER_RESPONSE = result
# You can break or continue depending on your process
# break
# If you decide to continue, you can throttle the loop
# time.sleep(1) # Pause the loop for a given time (in seconds)
# Throttle the loop to avoid excessive CPU usage
time.sleep(0.5)
@app.post("/start_processing")
async def start_processing(background_tasks: BackgroundTasks):
background_tasks.add_task(process_images)
return {"message": "Image processing started"}
@app.get("/get_response")
async def get_response():
return {"response": SERVER_RESPONSE}
|
e87a0df1692eeb965f42fe4c671ffc34
|
{
"intermediate": 0.39120492339134216,
"beginner": 0.26849180459976196,
"expert": 0.34030333161354065
}
|
31,143
|
find errors in this JS code: function buy_inapp(inapp_id) {
payments.purchase({ id: inapp_id }).then(purchase => {
if (inapp_id == "5" || inapp_id == "10" || inapp_id == "30" || inapp_id == "50") {payments.consumePurchase(purchase.purchaseToken); }
JsToDef.send("successful", inapp_id);
}}).catch(err => {
});
|
92c53aecc8faea71f5ceb2efcc338578
|
{
"intermediate": 0.42202210426330566,
"beginner": 0.39099109172821045,
"expert": 0.18698683381080627
}
|
31,144
|
I would like to add to an existing VBA code a condition as described below.
If the workbook 'Schedules' is open, then unlock the sheet 'Notes' in the workbook 'Schedules' using the password 'edit'
Can you please suggest.
|
6c5bc3618ef0fdf7410b6c5d2c3d63f6
|
{
"intermediate": 0.43673795461654663,
"beginner": 0.22943688929080963,
"expert": 0.3338252007961273
}
|
31,145
|
if there are several subjects in a data, E1301001, E1301002, E1301003, E1301004, E1301005, how to calculate how many subjects are included in using R
|
d2ca00f43ff466b7cb3a92a2ad47098d
|
{
"intermediate": 0.3724302351474762,
"beginner": 0.209694966673851,
"expert": 0.417874813079834
}
|
31,146
|
请将以下docker-compose.yaml转换为k8s：
apiVersion: app.sealos.io/v1
kind: Instance
metadata:
name: chatgpt-next-web-psfofcgv
labels:
cloud.sealos.io/deploy-on-sealos: chatgpt-next-web-psfofcgv
spec:
gitRepo: https://github.com/Yidadaa/ChatGPT-Next-Web
templateType: inline
title: chatgpt-next-web
url: https://github.com/Yidadaa/ChatGPT-Next-Web
author: sealos
description: >-
A well-designed cross-platform ChatGPT UI (Web / PWA / Linux / Win / MacOS).
一键拥有你自己的跨平台 ChatGPT 应用。
readme: https://raw.githubusercontent.com/Yidadaa/ChatGPT-Next-Web/main/README.md
icon: https://github.com/Yidadaa/ChatGPT-Next-Web/raw/main/docs/images/icon.svg
defaults:
app_host:
type: string
value: undefined
app_name:
type: string
value: chatgpt-next-web-undefined
inputs:
OPENAI_API_KEY:
description: OPENAI_API_KEY
type: string
default: ''
required: true
CODE:
description: Access passsword, separated by comma.
type: string
default: ''
required: false
BASE_URL:
description: Override openai api request base url.
type: string
default: https://api.openai.com
required: false
OPENAI_ORG_ID:
description: Specify OpenAI organization ID.
type: string
default: ''
required: false
HIDE_USER_API_KEY:
description: ''
type: string
default: ''
required: false
DISABLE_GPT4:
description: If you do not want users to use GPT-4, set this value to 1.
type: string
default: ''
required: false
HIDE_BALANCE_QUERY:
description: If you do not want users to query balance, set this value to 1.
type: string
default: ''
required: false
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: chatgpt-next-web-psfofcgv
annotations:
originImageName: yidadaa/chatgpt-next-web
deploy.cloud.sealos.io/minReplicas: '1'
deploy.cloud.sealos.io/maxReplicas: '1'
labels:
cloud.sealos.io/app-deploy-manager: chatgpt-next-web-psfofcgv
app: chatgpt-next-web-psfofcgv
cloud.sealos.io/deploy-on-sealos: chatgpt-next-web-psfofcgv
spec:
replicas: 1
revisionHistoryLimit: 1
selector:
matchLabels:
app: chatgpt-next-web-psfofcgv
strategy:
type: RollingUpdate
rollingUpdate:
maxUnavailable: 1
maxSurge: 0
template:
metadata:
labels:
app: chatgpt-next-web-psfofcgv
spec:
containers:
- name: chatgpt-next-web-psfofcgv
image: yidadaa/chatgpt-next-web
env:
- name: OPENAI_API_KEY
value: null
- name: CODE
value: null
- name: BASE_URL
value: https://api.openai.com
- name: OPENAI_ORG_ID
value: null
- name: HIDE_USER_API_KEY
value: null
- name: DISABLE_GPT4
value: null
resources:
requests:
cpu: 100m
memory: 102Mi
limits:
cpu: 1000m
memory: 1024Mi
command: []
args: []
ports:
- containerPort: 3000
imagePullPolicy: Always
volumeMounts: []
volumes: []
---
apiVersion: v1
kind: Service
metadata:
name: chatgpt-next-web-psfofcgv
labels:
cloud.sealos.io/app-deploy-manager: chatgpt-next-web-psfofcgv
cloud.sealos.io/deploy-on-sealos: chatgpt-next-web-psfofcgv
spec:
ports:
- port: 3000
selector:
app: chatgpt-next-web-psfofcgv
---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: chatgpt-next-web-psfofcgv
labels:
cloud.sealos.io/app-deploy-manager: chatgpt-next-web-psfofcgv
cloud.sealos.io/app-deploy-manager-domain: tkadfekx
cloud.sealos.io/deploy-on-sealos: chatgpt-next-web-psfofcgv
annotations:
kubernetes.io/ingress.class: nginx
nginx.ingress.kubernetes.io/proxy-body-size: 32m
nginx.ingress.kubernetes.io/server-snippet: |
client_header_buffer_size 64k;
large_client_header_buffers 4 128k;
nginx.ingress.kubernetes.io/ssl-redirect: 'false'
nginx.ingress.kubernetes.io/backend-protocol: HTTP
nginx.ingress.kubernetes.io/rewrite-target: /$2
nginx.ingress.kubernetes.io/client-body-buffer-size: 64k
nginx.ingress.kubernetes.io/proxy-buffer-size: 64k
nginx.ingress.kubernetes.io/proxy-send-timeout: '300'
nginx.ingress.kubernetes.io/proxy-read-timeout: '300'
nginx.ingress.kubernetes.io/configuration-snippet: |
if ($request_uri ~* \.(js|css|gif|jpe?g|png)) {
expires 30d;
add_header Cache-Control "public";
}
spec:
rules:
- host: tkadfekx.cloud.sealos.io
http:
paths:
- pathType: Prefix
path: /()(.*)
backend:
service:
name: chatgpt-next-web-psfofcgv
port:
number: 3000
tls:
- hosts:
- tkadfekx.cloud.sealos.io
secretName: wildcard-cloud-sealos-io-cert
|
5427cf90d4acdf461027ef43f7ec5ffa
|
{
"intermediate": 0.3183455467224121,
"beginner": 0.519085705280304,
"expert": 0.16256874799728394
}
|
31,147
|
根据需求修改代码——基本能掌握开发方面的术语，理解需求。
设计功能模块设计图和数据库模块实现，形成一份开发的文档,包括：
1. 用户管理
2. 图书管理
3. 购物车管理
4. 结账管理
5. 图书推荐和销售情况统计
1. 用户管理
1）管理员用户，数据库后台直接插入
2）普通用户注册：接受用户注册信息保存到数据库
3）用户登录：用户输入用户名和密码，数据库校验，通过则记录当前登录用户，否则报错提示
4）用户登出：清空当前系统运行用户信息，并将登出时间等信息更新到用户登录表
5）用户行为分析：统计当日、当周、当月分别有多少用户登录系统，哪些用户登录次数最多等。
2. 图书管理
1）图书录入（针对管理员用户）：支持两种模式：逐个录入和csv文件批量录入
2）图书修改（针对管理员用户）：管理员修改图书信息，如图书价格、库存量等信息。
3）图书查询：支持两种模式：全量查询和基于图书名的模糊查询
4）图书筛选（方便用户购买）：支持根据图书类别、价格范围（最低价格、最高价格）获取满足条件的图书列表
3. 购物车管理
1）查询购物车数据：查询当前加入购物车未付款的数据
2）加入购物车：将图书查询或图书筛选结果中喜欢的图书加入购物车
2）修改购物车数据：如修改购买图书数量等信息
3）删除购物车数据：删除指定的购物车数据
4. 结账管理
1）根据用户指定购买的图书和数量，将付款数据存储到订单表，并更新相应购物车数据和图书表数据（图书数量的变化和用户账户余额的变化）
注：事务级的操作
2）当前用户的消费情况：购买图书数量，消费额，当前账户余额等信息
5. 图书推荐
1）热销图书推荐:查询订单表订单记录排序推荐
2）基于当前用户购买记录进行相关推荐:查询用户的购物车表和订单表，根据已购图书类别进行同类别图书推荐
6. 图书整体报表情况统计
1）当前图书的库存情况：查询books表
1）当日、当周、当月图书的销售情况：查询order_book表import pymysql
import datetime
def getConn():
conn = pymysql.connect(host="127.0.0.1",port=3306,user="root",password="1527648qw",database="book_manage")
return conn
def isLogin():
if currentUser.getUid()=="-1":
print("user not login system,pls login first")
class User:
def __init__(self, username, password):
self.username = username
self.password = password
class Book:
def __init__(self, title, author, price):
self.title = title
self.author = author
self.price = price
class ShoppingCart:
def __init__(self):
self.items = []
def add_item(self, book, quantity):
self.items.append({"book": book, "quantity": quantity})
def remove_item(self, book):
for item in self.items:
if item["book"] == book:
self.items.remove(item)
break
def update_quantity(self, book, quantity):
for item in self.items:
if item["book"] == book:
item["quantity"] = quantity
break
class Order:
def __init__(self, user, shopping_cart):
self.user = user
self.shopping_cart = shopping_cart
class UserManagerment:
def __init__(self):
self.user=[]
def add_addmin_user(self,username,password):
user=User(username,password)
self.user.append(user)
print("Admin user added sucessfully")
def register_user(self):
username = input("Enter username: ")
password = input("Enter password: ")
user = User(username, password)
self.users.append(user)
print("User registered successfully.")
def login(self):
username = input("Enter username: ")
password = input("Enter password: ")
for user in self.users:
if user.username == "ql" and user.password =="1527648qw":
print("User logged in successfully.")
return user
print("Invalid username or password.")
return None
def logout(self, user):
print("User logged out successfully.")
def analyze_user_behavior(self):
pass
class Bookstore:
def __init__(self):
self.users = []
self.books = []
self.shopping_carts = []
self.orders = []
def register_user(self):
username = input("Enter username: ")
password = input("Enter password: ")
user = User(username, password)
self.users.append(user)
print("User registered successfully.")
def login(self):
username = input("Enter username: ")
password = input("Enter password: ")
for user in self.users:
if user.username == "ql" and user.password =="1527648qw":
print("User logged in successfully.")
return user
print("Invalid username or password.")
return None
def logout(self, user):
print("User logged out successfully.")
def add_book(self):
title = input("Enter book title: ")
author = input("Enter book author: ")
price = float(input("Enter book price: "))
book = Book(title, author, price)
self.books.append(book)
print("Book added successfully.")
def update_book(self):
title = input("Enter book title to update: ")
for book in self.books:
if book.title == title:
book.title = input("Enter new book title: ")
book.author = input("Enter new book author: ")
book.price = float(input("Enter new book price: "))
print("Book updated successfully.")
return
print("Book not found.")
def search_book(self):
keyword = input("Enter keyword to search: ")
found_books = []
for book in self.books:
if keyword.lower() in book.title.lower() or keyword.lower() in book.author.lower():
found_books.append(book)
if found_books:
print("Found books:")
for book in found_books:
print(f"Title: {book.title}, Author: {book.author}, Price: {book.price}")
else:
print("No books found.")
def filter_book(self):
maximum_price = float(input("Enter maximum price: "))
filtered_books = []
for book in self.books:
if book.price <= maximum_price:
filtered_books.append(book)
if filtered_books:
print("Filtered books:")
for book in filtered_books:
print(f"Title: {book.title}, Author: {book.author}, Price: {book.price}")
else:
print("No books found.")
class UserBehaviorAnalysis:
def init(self):
self.user=[]
def get_daily_login_count():
conn = get_conn()
cursor = conn.cursor()
cursor.execute("SELECT COUNT(DISTINCT username) FROM users WHERE DATE(last_login) = CURDATE()")
count = cursor.fetchone()[0]
cursor.close()
conn.close()
return count
def get_weekly_login_count():
conn = get_conn()
cursor = conn.cursor()
cursor.execute("SELECT COUNT(DISTINCT username) FROM users WHERE YEARWEEK(last_login, 1) = YEARWEEK(NOW(), 1)")
count = cursor.fetchone()[0]
cursor.close()
conn.close()
return count
def get_monthly_login_count():
conn = get_conn()
cursor = conn.cursor()
cursor.execute("SELECT COUNT(DISTINCT username) FROM users WHERE YEAR(last_login) = YEAR(NOW()) AND MONTH(last_login) = MONTH(NOW())")
count = cursor.fetchone()[0]
cursor.close()
conn.close()
return count
def view_shopping_cart(self, user):
for cart in self.shopping_carts:
if cart.user == user:
if cart.items:
print("Shopping cart:")
for item in cart.items:
book = item["book"]
quantity = item["quantity"]
print(f"Title: {book.title}, Author: {book.author}, Price: {book.price}, Quantity: {quantity}")
else:
print("Shopping cart is empty.")
return
print("Shopping cart not found.")
def add_to_shopping_cart(self, user):
title = input("Enter book title to add to shopping cart: ")
quantity = int(input("Enter quantity: "))
for book in self.books:
if book.title == title:
for cart in self.shopping_carts:
if cart.user == user:
cart.add_item(book, quantity)
print("Book added to shopping cart.")
return
new_cart = ShoppingCart()
new_cart.add_item(book, quantity)
self.shopping_carts.append(new_cart)
print("Book added to shopping cart.")
return
print("Book not found.")
def update_shopping_cart(self, user):
title = input("Enter book title to update in shopping cart: ")
quantity = int(input("Enter new quantity: "))
for cart in self.shopping_carts:
if cart.user == user:
for item in cart.items:
if item["book"].title == title:
cart.update_quantity(item["book"], quantity)
print("Shopping cart updated.")
return
print("Book not found in shopping cart.")
return
print("Shopping cart not found.")
def remove_from_shopping_cart(self, user):
title = input("Enter book title to remove from shopping cart: ")
for cart in self.shopping_carts:
if cart.user == user:
for item in cart.items:
if item["book"].title == title:
cart.remove_item(item["book"])
print("Book removed from shopping cart.")
return
print("Book not found in shopping cart.")
return
print("Shopping cart not found.")
def create_order(self, user):
for cart in self.shopping_carts:
if cart.user == user:
if cart.items:
new_order = Order(user, cart)
self.orders.append(new_order)
self.shopping_carts.remove(cart)
print("Order created successfully.")
else:
print("Shopping cart is empty.")
return
print("Shopping cart not found.")
def search_order(self, user):
for order in self.orders:
if order.user == user:
print("Order details:")
for item in order.shopping_cart.items:
book = item["book"]
quantity = item["quantity"]
print(f"Title: {book.title}, Author: {book.author}, Price: {book.price}, Quantity: {quantity}")
return
print("Order not found.")
def recommend_bestsellers(self):
# TODO: Implement bestsellers recommendation logic
pass
def recommend_data_mining(self):
# TODO: Implement data mining recommendation logic
pass
def generate_inventory_report(self):
print("Inventory report:")
for book in self.books:
print(f"Title: {book.title}, Author: {book.author}, Price: {book.price}")
def generate_sales_report(self):
print("Sales report:")
# TODO: Implement sales report generation logic
def main():
bookstore = Bookstore()
user = None # Add user variable initialization
while True:
print("\n--------- Online Bookstore ---------")
print("1. User Management")
print("2. Book Management")
print("3. Shopping Cart Management")
print("4. Order Management")
print("5. Book Recommendation")
print("6. Book Report and Statistics")
print("0. Exit")
choice = input("Enter your choice: ")
if choice == "1":
print("\n--------- User Management ---------")
print("1. Register User")
print("2. Login")
print("3. Logout")
print("4. User Behavior Analysis")
user_choice = input("Enter your choice: ")
if user_choice == "1":
bookstore.register_user()
elif user_choice == "2":
user = bookstore.login()
elif user_choice == "3":
bookstore.logout(user)
user = None
elif user_choice == "4":
bookstore.analyze_user_behavior()
else:
print("Invalid choice.")
elif choice == "2":
print("\n--------- Book Management ---------")
print("1. Add Book")
print("2. Update Book")
print("3. Search Book")
print("4. Filter Book")
book_choice = input("Enter your choice: ")
if book_choice == "1":
bookstore.add_book()
elif book_choice == "2":
bookstore.update_book()
elif book_choice == "3":
bookstore.search_book()
elif book_choice == "4":
bookstore.filter_book()
else:
print("Invalid choice.")
elif choice == "3":
if user:
print("\n--------- Shopping Cart Management ---------")
print("1. View Shopping Cart")
print("2. Add to Shopping Cart")
print("3. Update Shopping Cart")
print("4. Remove from Shopping Cart")
cart_choice = input("Enter your choice: ")
if cart_choice == "1":
bookstore.view_shopping_cart(user)
elif cart_choice == "2":
bookstore.add_to_shopping_cart(user)
elif cart_choice == "3":
bookstore.update_shopping_cart(user)
elif cart_choice == "4":
bookstore.remove_from_shopping_cart(user)
else:
print("Invalid choice.")
else:
print("You need to log in first.")
elif choice == "4":
if user:
print("\n--------- Order Management ---------")
print("1. Create Order")
print("2. Search Order")
order_choice = input("Enter your choice: ")
if order_choice == "1":
bookstore.create_order(user)
elif order_choice == "2":
bookstore.search_order(user)
else:
print("Invalid choice.")
else:
print("You need to log in first.")
elif choice == "5":
print("\n--------- Book Recommendation ---------")
print("1. Bestsellers Recommendation")
print("2. Data Mining Recommendation")
recommendation_choice = input("Enter your choice: ")
if recommendation_choice == "1":
bookstore.recommend_bestsellers()
elif recommendation_choice == "2":
bookstore.recommend_data_mining()
else:
print("Invalid choice.")
elif choice == "6":
print("\n--------- Book Report and Statistics ---------")
print("1. Inventory Report")
print("2. Sales Report")
report_choice = input("Enter your choice: ")
if report_choice == "1":
bookstore.generate_inventory_report()
elif report_choice == "2":
bookstore.generate_sales_report()
else:
print("Invalid choice.")
elif choice == "0":
break
else:
print("Invalid choice. Please try again.")
if __name__=="__main__":
main()
|
4999fe047266937371ad78df33b44b74
|
{
"intermediate": 0.24381117522716522,
"beginner": 0.5885965824127197,
"expert": 0.16759222745895386
}
|
31,148
|
Develop the following queries using MongoDB fetch tools:
1) Return an ordered list of resource URLs.
|
189be2995cea6aa53b7dc958d8fdb08e
|
{
"intermediate": 0.565994918346405,
"beginner": 0.22175133228302002,
"expert": 0.21225371956825256
}
|
31,149
|
List the three IP addresses that sent the most requests in mongodb
|
5e359e1d75958783118284227de1e5ff
|
{
"intermediate": 0.37487637996673584,
"beginner": 0.2560243010520935,
"expert": 0.36909934878349304
}
|
31,150
|
Define a class ExchangePoint which should be responsible for converting between different currencies; GBP,
EUR and USD. The class should accept in the init method the conversion rates and should also have three
functions; get gbp, get eur, and get usd. All three functions should accept three arguments (‘gbp’, ‘eur’, ‘usd’),
which correspond to the amount from each currency we wish to include in the conversion.
|
d6908fe30e0e92ca2932b2327dd6c82c
|
{
"intermediate": 0.24625708162784576,
"beginner": 0.5691429972648621,
"expert": 0.1845998913049698
}
|
31,151
|
df['DeliveryDate'] = pd.to_datetime(df['DeliveryDate'])
today = datetime.now()
start_date = datetime(today.year + int(today.month/12), (today.month%12) + 1, 1)
end_date = datetime(today.year + int((today.month + 3)/12), ((today.month+3)%12) + 1, 1)
df_months = df[(df['DeliveryDate'] >= start_date) & (df['DeliveryDate'] < end_date)]
print(df_months)
I have the above dataframe in Pandas.
I want to create the following dataframe:
The rows will be months (first month, second,. up to fourth month) and columns will be countries (Slovenia, Hungary and Germany) - those countries are also the only ones in the dataframe. I want to calculate the average prices. So for e.g. the first entry would be the average price from the first month in Slovenia, ...
|
d315c0ee56ffff3166176dac49e0b37b
|
{
"intermediate": 0.38853979110717773,
"beginner": 0.28359851241111755,
"expert": 0.3278616666793823
}
|
31,152
|
#include <iostream>
#include <math.h>
#include <cstring>
using namespace std;
struct movie
{
char name[20];
char director[15];
char genre[15];
double rate;
int price_watch;
};
struct streaming_service {
const int catalog_size;
movie catalog[catalog_size];
};
void ShowResults(movie mov)
{
cout << "Name:" << mov.name << endl;
cout << "Director:" << mov.director<< endl;
cout << "Genre:" << mov.genre << endl;
cout << "Rate:" << mov.rate << endl;
cout << "Price" << mov.price_watch << endl;
}
int main()
{
const int catalog_size = 4;
movie mov1 = { "Interstellar", "Kriss Nolan", "Sci-fi", 8.7, 50 };
movie mov2 = { "Arrival", "Dani Villeneue", "Sci-fi", 7.6, 45 };
movie mov3 = { "Blade Runner", "Dani Villeneue", "Sci-fi", 7.8, 45 };
movie mov4 = { "Fight Club", "D Fincher", "Triller", 8.8, 50 };
streaming_service = { 4, adflkj; };
movies_catalog[0] = mov1;
movies_catalog[1] = mov2;
movies_catalog[2] = mov3;
movies_catalog[3] = mov4;
char request[] = "Interstellar";
for (int i = 0; i < catalog_size; i++)
{
}
return 0;
}помоги сделать структуру массива ч
|
9879ed0bd19fa95a34c6ca94bb4335ce
|
{
"intermediate": 0.34745264053344727,
"beginner": 0.33597543835639954,
"expert": 0.3165718615055084
}
|
31,153
|
{"module": "radar_toolbox", "module_structure": "radar_toolbox\\conf/capture_conf.json;radar_toolbox\\conf/profile_vs1642_exp.cfg;radar_toolbox\\conf/raw_bin_to_numpy.json;radar_toolbox\\TI_data/sensor_com.py;", "module_files_already_generated_doc": [{"file": "radar_toolbox\\fmcw_utils.md", "doc": "# radar_toolbox/fmcw_utils.py Documentation\n\n## Overview\nfmcw_utils.py is a part of the radar_toolbox module and provides utility functions, classes, and constants specifically for frequency modulated continuous wave (FMCW) radar systems. This file is crucial for managing radar models, loading and processing radar data, and preparing captured raw data for analysis.\n\n## Classes\n\n### RadarModel (Enum)\nAn enumeration for the supported radar models.\n\n- IWR1642\n- IWR6843AOP\n- IWRL6432\n- get_model_from_str(string): Static method that takes a string identifier and returns the corresponding RadarModel enum. Raises NotImplementedError if the radar model is not implemented.\n\n### PointsAttributes (Enum)\nEnumeration of possible point cloud attributes\n\n- RANGE\n- AZIMUTH\n- ELEVATION\n- VELOCITY\n- points_attributes_abs(points, attribute_idx): Modifies the given points array by taking the absolute value of the specified attribute.\n\n### AntennaDataSaver\nA helper class for storing calculated FFT data.\n\n- __init__(save_abs_1D_FFTs, save_abs_2D_FFTs): Constructor specifying whether to save FFT data.\n- add_abs_1D_FFTs(FFTs_1D): Stores one-dimensional FFT results.\n- add_abs_2D_FFTs(FFTs_2D): Stores two-dimensional FFT results.\n\n### RadarDataSaver\nDesigned to store common detection matrices for further analysis.\n\n- __init__(save_common_detection_matrices): Constructor specifying whether to save common detection matrices.\n- add_common_detection_matrices(common_detection_matrices): Adds a new common detection matrix.\n\n## Functions\n\n### get_phase_compensation_for_radar_model(model)\nReturns the phase compensation array for a specific radar model. Raises NotImplementedError if the radar model is not handled.\n\n### load_IQ_file(path, is_complex, nb_samples, nb_chirps)\nLoads interleaved I/Q data from a file and returns a numpy array reshaped for chirps and samples. Accommodates complex data if is_complex is True.\n\n### load_IQ_data(path_prefix, is_complex, nb_antennas, nb_samples, nb_chirps)\nLoads interleaved I/Q data across multiple antennas and returns a combined numpy array for further processing.\n\n### raw_capture_bin_preparation(capture_bin_file_path, cfg_file_path, radar, output_bin_file_path, verbose)\nProcesses a binary capture file and prepares it in a structured format suitable for analysis, including handling of missing packets.\n\n### prepared_bin_to_numpy(bin_file_path, cfg_file_path, radar, nb_lanes)\nConverts a prepared binary radar data file to numpy format, taking into account missing packets and ensures only complete frames are returned.\n\n### coordinates_from_range_and_angles(azimuths, elevations, ranges)\nCalculates Cartesian coordinates from radar data specified by ranges, azimuths, and elevation angles.\n\n### read_cfg_file(path, radar_model, verbose)\nReads a .cfg file and returns a configuration dictionary with key parameters for the radar operation. Handles different radar models.\n\n### describe_config(config)\nPrints the configuration dictionary in a readable format for better understanding of the radar setup.\n\n### safe_memmap(filename, mode, dtype, shape)\nCreates a memory-mapped file for large arrays ensuring compatibility with the numpy .npy format.\n\n### Frame\nA class managing the construction of radar frames from raw data, handling cross-frame packet scenarios.\n\n- __init__( ...): Initializes the Frame object, which holds data for a single radar frame.\n- is_complete(): Returns whether the frame is complete.\n- add_values(data_to_append): Appends new data to the current frame.\n- get_frame_values(): Retrieves the final frame values.\n- get_next_frame(): Builds and returns a new frame with the remaining data if the current frame is complete.\n- get_frame_index(): Returns the index of the current frame.\n- get_nb_values_in_frame(): Returns the number of values in a frame.\n- order_frame(flat_unordered_frame): Orders a flat unordered frame into a structured numpy array.\n\n### AntennaConfig\nRepresents the configuration of an FMCW radar antenna, with attributes like start frequency, sampling rate, etc.\n\n- __init__( ...): Initializes the AntennaConfig instance with radar parameters.\n- get_antenna_parameters_from_config_file(config): Static method that creates an instance of AntennaConfig from radar configuration parameters.\n\n## Data Flow\nThe individual functions and classes deal with various stages of data acquisition, preprocessing, and transformation into formats that can be utilized for subsequent analysis. It goes from reading radar configurations, capturing raw binary data, preprocessing the data, extracting I/Q samples, organizing data into frames, and finally converting into coordinates relevant for point cloud generation.\n\n## Usage\nA developer would typically use these utilities to interface with FMCW radar hardware, manage radar configurations, process captured radar signals, and transform them into more analytical forms for further tasks such as object detection or tracking.\n"}, {"file": "radar_toolbox\\utils.md", "doc": "# radar_toolbox/utils.py Documentation\n\n## Overview\n`utils.py` is a module within the `radar_toolbox` that houses utility functions and classes essential for various aspects of the FMCW radar project. These utilities include configuration file handling, data loading, configuration parsing, and more.\n\n## Classes\n\n### GridSize\nA data class representing the size of a grid in three dimensions - x, y, and z.\n\n- `x`: Number of grid elements along the x-axis.\n- `y`: Number of grid elements along the y-axis.\n- `z`: Number of grid elements along the z-axis.\n\n#### Methods\n\n- `get_shape()`: Returns the shape of the grid as a tuple (x, y, z).\n\n### CaptureBoundaries\nA data class representing the boundaries of a capture session in three dimensions - x, y, and z.\n\n- `x_min`: Minimum value along the x-axis.\n- `x_max`: Maximum value along the x-axis.\n- `y_min`: Minimum value along the y-axis.\n- `y_max`: Maximum value along the y-axis.\n- `z_min`: Minimum value along the z-axis.\n- `z_max`: Maximum value along the z-axis.\n\n### Other Utility Functions\n\n- `chunks(lst, n)`: Yields successive n-sized chunks from a list.\n- `configure_argument_parser_for_conf_file()`: Configures an argument parser for handling configuration files.\n- `dict_deepmerge(x, y)`: Deep merges two dictionaries.\n- `load_conf(config_file)`: Loads a configuration file, merging it with additional configurations if specified.\n- `get_class(cls)`: Dynamically loads a class from a module.\n- `load_data_from_conf(config_dataloader)`: Loads data from a specified data loader configuration.\n- `create_pytorch_estimator(...)`: Creates a PyTorch estimator for model training.\n- `create_custom_estimator(...)`: Creates a custom estimator for model training.\n- `get_image_uri(...)`: Constructs the URI for a Docker image.\n- `parse_extra_args(args, extra_args)`: Parses extra arguments and adds them to the argument dictionary.\n- `csv_capture_player(config)`: Generator function for reading a CSV file of a capture session.\n- `get_callbacks_from_params(callbacks_params)`: Constructs callbacks for model training based on specified parameters.\n- `get_reader_from_config(config)`: Retrieves a radar data reader based on the radar model specified in the configuration.\n- `coord_rotation(first_axis_values, second_axis_values, theta)`: Rotates coordinates anti-clockwise through an angle theta about the origin.\n- `points_inclination_correction(points, horizontal_inclination, vertical_inclination)`: Corrects inclinations in the width-depth and height-depth planes for given XYZ coordinates.\n\n## Data Flow\nThe utility functions and classes in `utils.py` contribute to the broader data flow within the FMCW radar project. They handle configuration loading, data preprocessing, model training, and coordinate transformations. The data flow generally involves reading configuration files, loading and processing radar data, and preparing it for analysis or model training.\n\n## Usage\nDevelopers can leverage `utils.py` to streamline various aspects of the FMCW radar project. This includes handling configuration files, loading and preprocessing radar data, training machine learning models, and correcting coordinate inclinations."}, {"file": "radar_toolbox\\capture_session\\main.md", "doc": "# radar_toolbox/capture_session/main.py Documentation\n\n## Overview\n`main.py` is a crucial component of the `radar_toolbox` module, specifically within the `capture_session` submodule. This module is responsible for recording raw radar captures and serves as the entry point for capturing data from the FMCW radar system. The file contains functionalities for configuring the radar, initiating recording sessions, and handling raw data acquisition.\n\n## Functionality\n\n### `get_record_file_path(data_folder, person, session_type)`\nThis function generates the file path for saving raw radar data based on the provided parameters. It ensures proper organization of data by creating folders for each person and session type, and it increments the session index to avoid overwriting existing sessions.\n\n### Main Execution\nThe main part of the script is executed when the file is run. It performs the following steps:\n\n1. **Argument Parsing:** Parses command line arguments, specifically the configuration file path.\n2. **Configuration Loading:** Loads configuration settings from the specified file.\n3. **File Path Generation:** Calls `get_record_file_path` to determine the file path for saving the raw radar data.\n4. **Radar Configuration:** Reads the radar model and configuration from the specified configuration file.\n5. **Data Reader Initialization:** Initializes the data reader based on the radar model and connects to the radar system.\n6. **Recording Setup:** Configures the radar system for recording, including sending the configuration file.\n7. **Data Capture:** Initiates the recording process, capturing raw data packets and saving them to the specified file.\n\n### Interrupt Handling\nThe script is designed to handle keyboard interrupts (e.g., user pressing Ctrl+C) gracefully. It ensures that the recording is stopped, and the data reader is disconnected before exiting.\n\n## Dependencies\n- **Modules from radar_toolbox:**\n - `fmcw_utils`: Utilized for radar model enumeration, reading configuration files, and handling radar configurations.\n - `raw_data.adc`: Imports the `DCA1000` class for configuring and interacting with the ADC (Analog-to-Digital Converter).\n - `utils`: Utilizes utility functions for configuration file handling and data loading.\n\n## Usage\nTo use `main.py`, run the script with the necessary command line arguments, such as the path to the configuration file. For example:\n
|
a2fdf42e0ad0be2f6a734526bebf98a0
|
{
"intermediate": 0.3353692293167114,
"beginner": 0.39771151542663574,
"expert": 0.26691925525665283
}
|
31,154
|
make it print everytime the frame has been the same as before for 1.5 seconds
|
bf9ae33d0248dbe88e971f99681dd168
|
{
"intermediate": 0.35299229621887207,
"beginner": 0.21586647629737854,
"expert": 0.4311412572860718
}
|
31,155
|
df['DeliveryDate'] = pd.to_datetime(df['DeliveryDate'])
today = datetime.now()
start_date = datetime(today.year + int(today.month/12), (today.month%12) + 1, 1)
end_date = datetime(today.year + int((today.month + 3)/12), ((today.month+3)%12) + 1, 1)
df_months = df[(df['DeliveryDate'] >= start_date) & (df['DeliveryDate'] < end_date)]
df_avg_prices = pd.pivot_table(df_months, values= 'Price', index=df_months['DeliveryDate'].dt.month, columns='Country', aggfunc='mean')
the pivot_table is causing me errors, can you fix the arguments so that it is correct
|
47d218df6d1fbecbde503948b10d2d51
|
{
"intermediate": 0.46352237462997437,
"beginner": 0.25176528096199036,
"expert": 0.28471237421035767
}
|
31,156
|
#include <iostream>
#include <math.h>
#include <cstring>
using namespace std;
struct movie
{
char name[20];
char director[15];
char genre[15];
double rate;
int price_watch;
};
struct streaming {
movie* catalog;
int size;
};
void ShowResults(streaming stream, char* request )
{
for (int i = 0; i < stream.size; i++)
{
if (stream.catalog[i].name == request)
{
cout << "Name:" << stream.catalog[i].name << endl;
cout << "Director:" << stream.catalog[i].director << endl;
cout << "Genre:" << stream.catalog[i].genre << endl;
cout << "Rate:" << stream.catalog[i].rate << endl;
cout << "Price" << stream.catalog[i].price_watch << endl;
break;
}
}
}
int main()
{
const int catalog_size = 4;
movie mov1 = { "Interstellar", "Kriss Nolan", "Sci-fi", 8.7, 50 };
movie mov2 = { "Arrival", "Dani Villeneue", "Sci-fi", 7.6, 45 };
movie mov3 = { "Blade Runner", "Dani Villeneue", "Sci-fi", 7.8, 45 };
movie mov4 = { "Fight Club", "D Fincher", "Triller", 8.8, 50 };
movie movies_catalog[catalog_size];
movies_catalog[0] = mov1;
movies_catalog[1] = mov2;
movies_catalog[2] = mov3;
movies_catalog[3] = mov4;
streaming struct_catalog = {movies_catalog,catalog_size};
char request[] = "Arrival";
ShowResults(struct_catalog, request);
return 0;
}
исправь код чтобы выводилась информация о фильно, название которого было введено в request
|
54a4994510788f0b1334a67d97c09470
|
{
"intermediate": 0.3858548402786255,
"beginner": 0.37948092818260193,
"expert": 0.23466426134109497
}
|
31,157
|
Instructions:
The project focuses on the use of FMCW radar.
It is used for data collection, point detection, tracking and other functions.
The project is broken down into several modules.
The aim of this division is to decouple as much as possible the functionalities present in each module, and make the development of new functionalities more flexible and rapid.
Some information will be presented to you in json format:
- module: the name of the module
- module_structure: the structure of the module (the files making up the module and their hierarchy)
- module_files_already_generated_doc: the documentation of the module's files if already generated
- other_modules_doc: the documentation of the other modules on which the module depends (possibly none at all)
- gen_doc_of_file: the file you will be given to generate the documentation of. If no file is given, the documentation of the entire module must be generated.
Your goal is to create a markdown documentation of the file you will be given, or the entire module if no file is given.
This documentation is intended to guide a developer who is new to the project, you can therefore add whatever you feel is relevant for this task.
Informations:
{"module": "radar_tracking", "module_structure": "radar_tracking/tracking_utils.py;radar_tracking\\conf/tracking.json;radar_tracking\\inference/example_kalman_filter.py;radar_tracking\\inference/example_tracking.py;radar_tracking\\models/kalman.py;radar_tracking\\models/tracking.py;radar_tracking\\models\\clustering/cluster.py;radar_tracking\\models\\clustering/cluster_predictor.py;radar_tracking\\models\\clustering/optimizer.py;radar_tracking\\models\\clustering\\algos/clustering_alogirthm.py;radar_tracking\\models\\clustering\\algos/dbscan.py;radar_tracking\\models\\clustering\\algos/gaussian_mixture.py;radar_tracking\\models\\clustering\\algos/meanshift.py;radar_tracking\\visuals/display.py;", "module_files_already_generated_doc": [{"file": "radar_tracking\\tracking_utils.md", "doc": "# radar_tracking/tracking_utils.py Documentation\n\n## Overview\n\nThe tracking_utils.py script is part of the radar_tracking module, which is focused on the tracking aspect of FMCW radar applications. It provides utility functions to configure and instantiate key components of the radar tracking system, such as cluster trackers and clustering algorithms. The script draws from the configuration files to create instances that adhere to the pre-defined parameters for the tracking functionality.\n\n## Functions\n\n### get_capture_limits_from_conf\n\nThis function extracts capture limits from the provided configuration object. It converts the configuration values into a structured NumPy array specifying the range (min-max) for the x, y, and z dimensions.\n\nParameters:\n- config: Configuration object with capture limits for x, y, and z axes.\n\nReturns:\n- capture_limits_array: A NumPy array with shape (min-max values, xyz).\n\n### get_cluster_tracker_from_conf\n\nThis function initializes a ClusterTracker object using the tracking-related settings from the configuration.\n\nParameters:\n- config: A configuration object that contains frame grouping size, frame interval, and tracking settings like max_height_w and others.\n\nReturns:\n- An instance of ClusterTracker with the provided weights and configurations.\n\n### get_clustering_algo_from_conf\n\nThis function sets up a clustering algorithm according to the defined configuration. It supports adjusting parameters like the vertical scale, trajectory memory duration, and others specific to the chosen clustering algorithm (DBSCAN in this instance).\n\nParameters:\n- config: Configuration object specifying clustering and tracking parameters, e.g., min_cluster_points, eps, nb_persons, etc.\n\nReturns:\n- An instance of ClusteringPredictor ready to be used for clustering and tracking purposes.\n\n## Usage\n\nThese utility functions are intended to be called with the appropriate configuration objects to dynamically create configured instances for tracking:\n\n
|
9b28036e271b5e43557ca0807624cfce
|
{
"intermediate": 0.3972564935684204,
"beginner": 0.3664591312408447,
"expert": 0.23628439009189606
}
|
31,158
|
python code using BiLSTM encoder and decoder rnn to translate English text to Arabic text by splitting example data into train. validate and test ,Tokenize the sentences and convert them into numerical representations ,Pad or truncate the sentences to a fixed length and use test data to evaluate and example translation from test
|
446c1ba511814b087900a7f0b0e51708
|
{
"intermediate": 0.40019652247428894,
"beginner": 0.11380255967378616,
"expert": 0.4860009253025055
}
|
31,159
|
Instructions:
The project focuses on the use of FMCW radar.
It is used for data collection, point detection, tracking and other functions.
The project is broken down into several modules.
The aim of this division is to decouple as much as possible the functionalities present in each module, and make the development of new functionalities more flexible and rapid.
Some information will be presented to you in json format:
- module: the name of the module
- module_structure: the structure of the module (the files making up the module and their hierarchy)
- module_files_already_generated_doc: the documentation of the module's files if already generated
- other_modules_doc: the documentation of the other modules on which the module depends (possibly none at all)
- gen_doc_of_file: the file you will be given to generate the documentation of. If no file is given, the documentation of the entire module must be generated.
Your goal is to create a markdown documentation of the file you will be given, or the entire module if no file is given.
This documentation is intended to guide a developer who is new to the project, you can therefore add whatever you feel is relevant for this task.
Informations:
{"module": "radar_tracking", "module_structure": "radar_tracking/tracking_utils.py;radar_tracking\\conf/tracking.json;radar_tracking\\inference/example_kalman_filter.py;radar_tracking\\inference/example_tracking.py;radar_tracking\\models/kalman.py;radar_tracking\\models/tracking.py;radar_tracking\\models\\clustering/cluster.py;radar_tracking\\models\\clustering/cluster_predictor.py;radar_tracking\\models\\clustering/optimizer.py;radar_tracking\\models\\clustering\\algos/clustering_alogirthm.py;radar_tracking\\models\\clustering\\algos/dbscan.py;radar_tracking\\models\\clustering\\algos/gaussian_mixture.py;radar_tracking\\models\\clustering\\algos/meanshift.py;radar_tracking\\visuals/display.py;", "module_files_already_generated_doc": [{"file": "radar_tracking\\tracking_utils.md", "doc": "# radar_tracking/tracking_utils.py Documentation\n\n## Overview\n\nThe tracking_utils.py script is part of the radar_tracking module, which is focused on the tracking aspect of FMCW radar applications. It provides utility functions to configure and instantiate key components of the radar tracking system, such as cluster trackers and clustering algorithms. The script draws from the configuration files to create instances that adhere to the pre-defined parameters for the tracking functionality.\n\n## Functions\n\n### get_capture_limits_from_conf\n\nThis function extracts capture limits from the provided configuration object. It converts the configuration values into a structured NumPy array specifying the range (min-max) for the x, y, and z dimensions.\n\nParameters:\n- config: Configuration object with capture limits for x, y, and z axes.\n\nReturns:\n- capture_limits_array: A NumPy array with shape (min-max values, xyz).\n\n### get_cluster_tracker_from_conf\n\nThis function initializes a ClusterTracker object using the tracking-related settings from the configuration.\n\nParameters:\n- config: A configuration object that contains frame grouping size, frame interval, and tracking settings like max_height_w and others.\n\nReturns:\n- An instance of ClusterTracker with the provided weights and configurations.\n\n### get_clustering_algo_from_conf\n\nThis function sets up a clustering algorithm according to the defined configuration. It supports adjusting parameters like the vertical scale, trajectory memory duration, and others specific to the chosen clustering algorithm (DBSCAN in this instance).\n\nParameters:\n- config: Configuration object specifying clustering and tracking parameters, e.g., min_cluster_points, eps, nb_persons, etc.\n\nReturns:\n- An instance of ClusteringPredictor ready to be used for clustering and tracking purposes.\n\n## Usage\n\nThese utility functions are intended to be called with the appropriate configuration objects to dynamically create configured instances for tracking:\n\n
|
bafb26bae6778a0060eb960d797b2135
|
{
"intermediate": 0.3972564935684204,
"beginner": 0.3664591312408447,
"expert": 0.23628439009189606
}
|
31,160
|
What is MongoDB?
|
6abb8a38ce5702e1cb014ecc1408ae77
|
{
"intermediate": 0.5232462286949158,
"beginner": 0.25498318672180176,
"expert": 0.22177059948444366
}
|
31,161
|
#include <iostream>
#include <math.h>
#include <cstring>
using namespace std;
struct movie
{
char name[20];
char director[15];
char genre[15];
double rate;
int price_watch;
};
struct streaming {
movie* movies;
int size;
};
void ShowResults_Name(streaming stream, char* request )
{
for (int i = 0; i < stream.size; i++)
{
if (strcmp(stream.movies[i].name, request) == 0)
{
cout << "Name:" << stream.movies[i].name << endl;
cout << "Director:" << stream.movies[i].director << endl;
cout << "Genre:" << stream.movies[i].genre << endl;
cout << "Rate:" << stream.movies[i].rate << endl;
cout << "Price" << stream.movies[i].price_watch << endl;
break;
}
}
}
void ShowResults_Genre(streaming stream, char* request)
{
for (int i = 0; i < stream.size; i++)
{
if (strcmp(stream.movies[i].genre, request) == 0)
{
cout << "Name:" << stream.movies[i].name << endl;
cout << "Director:" << stream.movies[i].director << endl;
cout << "Genre:" << stream.movies[i].genre << endl;
cout << "Rate:" << stream.movies[i].rate << endl;
cout << "Price:" << stream.movies[i].price_watch << endl;
cout << "-----------------"<< endl;
}
}
}
void AddMovie(streaming& serv, movie mv)
{
movie* newArr = new movie[serv.size + 1];
delete[] serv.movies;
serv.movies = newArr;
serv.size++;
}
int main()
{
movie mov1 = { "Interstellar", "Kriss Nolan", "Sci-fi", 8.7, 50 };
movie mov2 = { "Arrival", "Dani Villeneue", "Sci-fi", 7.6, 45 };
movie mov3 = { "Blade Runner", "Dani Villeneue", "Sci-fi", 7.8, 45 };
movie mov4 = { "Fight Club", "D Fincher", "Triller", 8.8, 50 };
streaming struct_catalog;
size_t size = 4;
struct_catalog.size = size;
struct_catalog.movies = new movie[size];
AddMovie(struct_catalog, mov1);
AddMovie(struct_catalog, mov2);
AddMovie(struct_catalog, mov3);
AddMovie(struct_catalog, mov4);
//ShowResults_Name(struct_catalog, "Interstellar");
cout << endl;
char request2[20];
cout << "Enter Genre: ";
cin >> request2;
ShowResults_Genre(struct_catalog, request2);
return 0;
}
исправь код чтобы выводился каталог фильмов по жанрам
|
8628da554bb33c6723e41612c63e6270
|
{
"intermediate": 0.27549391984939575,
"beginner": 0.5374174118041992,
"expert": 0.18708869814872742
}
|
31,162
|
#include <iostream> #include <math.h> #include <cstring> using namespace std; struct movie { char name[20]; char director[15]; char genre[15]; double rate; int price_watch; }; struct streaming { movie* movies; int size; }; void ShowResults_Name(streaming stream, char* request ) { for (int i = 0; i < stream.size; i++) { if (strcmp(stream.movies[i].name, request) == 0) { cout << "Name:" << stream.movies[i].name << endl; cout << "Director:" << stream.movies[i].director << endl; cout << "Genre:" << stream.movies[i].genre << endl; cout << "Rate:" << stream.movies[i].rate << endl; cout << "Price" << stream.movies[i].price_watch << endl; break; } } } void ShowResults_Genre(streaming stream, char* request) { for (int i = 0; i < stream.size; i++) { if (strcmp(stream.movies[i].genre, request) == 0) { cout << "Name:" << stream.movies[i].name << endl; cout << "Director:" << stream.movies[i].director << endl; cout << "Genre:" << stream.movies[i].genre << endl; cout << "Rate:" << stream.movies[i].rate << endl; cout << "Price:" << stream.movies[i].price_watch << endl; cout << "-----------------"<< endl; } } } void AddMovie(streaming& serv, movie mv) { movie* newArr = new movie[serv.size + 1]; delete[] serv.movies; serv.movies = newArr; serv.size++; } int main() { movie mov1 = { "Interstellar", "Kriss Nolan", "Sci-fi", 8.7, 50 }; movie mov2 = { "Arrival", "Dani Villeneue", "Sci-fi", 7.6, 45 }; movie mov3 = { "Blade Runner", "Dani Villeneue", "Sci-fi", 7.8, 45 }; movie mov4 = { "Fight Club", "D Fincher", "Triller", 8.8, 50 }; streaming struct_catalog; size_t size = 4; struct_catalog.size = size; struct_catalog.movies = new movie[size]; AddMovie(struct_catalog, mov1); AddMovie(struct_catalog, mov2); AddMovie(struct_catalog, mov3); AddMovie(struct_catalog, mov4); //ShowResults_Name(struct_catalog, "Interstellar"); cout << endl; char request2[20]; cout << "Enter Genre: "; cin >> request2; ShowResults_Genre(struct_catalog, request2); return 0; } исправь код чтобы выводился каталог фильмов по жанрам
|
d33a9d849be5b90b8661b49e2e5fdef3
|
{
"intermediate": 0.38163772225379944,
"beginner": 0.4028191864490509,
"expert": 0.21554313600063324
}
|
31,163
|
y = (x+3/sqrt(x-5)) make it c++ table from x -5 to x 10
|
991aae450c019576fd0e35ad7db7a7eb
|
{
"intermediate": 0.3209778666496277,
"beginner": 0.31025516986846924,
"expert": 0.3687669336795807
}
|
31,164
|
Instructions:
The project focuses on the use of FMCW radar.
It is used for data collection, point detection, tracking and other functions.
The project is broken down into several modules.
The aim of this division is to decouple as much as possible the functionalities present in each module, and make the development of new functionalities more flexible and rapid.
Some information will be presented to you in json format:
- module: the name of the module
- module_structure: the structure of the module (the files making up the module and their hierarchy)
- module_files_already_generated_doc: the documentation of the module's files if already generated
- other_modules_doc: the documentation of the other modules on which the module depends (possibly none at all)
- gen_doc_of_file: the file you will be given to generate the documentation of. If no file is given, the documentation of the entire module must be generated.
Your goal is to create a markdown documentation of the file you will be given, or the entire module if no file is given.
This documentation is intended to guide a developer who is new to the project, you can therefore add whatever you feel is relevant for this task.
Informations:
{"module": "radar_area_detection", "module_structure": "radar_area_detection/detection.py;radar_area_detection/display.py;radar_area_detection/live_area_detection.py;radar_area_detection\\comm/camera_alert.py;radar_area_detection\\comm/rabbitmq.py;radar_area_detection\\conf/6432_ti_config.cfg;radar_area_detection\\conf/6843_ti_config.cfg;radar_area_detection\\conf/detection_conf.json;radar_area_detection\\conf/live_area_detection.json;radar_area_detection\\conf/rabbitmq_conf.json;radar_area_detection\\conf/tracking_conf.json;", "module_files_already_generated_doc": [{"file": "radar_area_detection\\detection.md", "doc": "# radar_area_detection/detection.py Module Documentation\n\n## Overview\n\nThe detection.py script is part of the radar_area_detection module, which is responsible for the area detection functionality using Frequency Modulated Continuous Wave (FMCW) radar technology. This module aids in the detection of points, tracking, and implementation of alert systems for certain areas within the radar\u00e2\u20ac\u2122s detection range.\n\n## File Structure\n\ndetection.py includes the following classes:\n\n- Area: A simple data structure representing a rectangular detection area.\n- Alert: An abstract base class that defines the structure for raising and clearing alerts.\n- AreaDetector: The primary class that manages detection areas and processes radar data to trigger alerts.\n\n### Area Class\n\nThe Area class serves as a representation of a detection zone, defined by its boundaries in Cartesian coordinates.\n\n#### Attributes\n\n- xl: Float. Represents the x-coordinate of the left boundary of the area.\n- xr: Float. Represents the x-coordinate of the right boundary of the area.\n- yb: Float. Represents the y-coordinate of the bottom boundary of the area.\n- yt: Float. Represents the y-coordinate of the top boundary of the area.\n\n#### Methods\n\n- serialize: Serializes area\u00e2\u20ac\u2122s attributes into a dictionary format.\n\n### Alert Abstract Class\n\nThe Alert class provides a blueprint for implementing the alert system that will respond to detection events.\n\n#### Methods (Abstract)\n\n- RaiseAlert: Abstract method to be defined to specify the actions required when an alert is raised.\n- ClearAlert: Abstract method to be defined to specify the actions required when an alert is cleared.\n\n### AreaDetector Class\n\nAreaDetector is the central class that orchestrates the area detection and alerting process.\n\n#### Constructor\n\n- __init__(areas, alerts=None): Initializes the detector with a list of areas and optional alert mechanisms.\n\n#### Attributes\n\n- alerts: List of Alert objects. Used to handle alerts when a tracked object enters a detection area.\n- areas: List of Area objects. These define the detection areas within the radar\u00e2\u20ac\u2122s field of view.\n- ok_areas: List of Area objects that are considered clear of tracked objects.\n- alert_areas: List of Area objects where alerts have been triggered due to the presence of tracked objects.\n- alert_triggered: Boolean indicating if an alert has been triggered.\n\n#### Methods\n\n- update(clusters_up_to_date): Updates the state of each detection area based on the latest tracked clusters information.\n- serialize: Serializes the status of ok_areas and alert_areas into a dictionary format.\n\n## Integration with Other Modules\n\nThe detection.py script in the radar_area_detection module works in coordination with the radar_tracking module (tracks objects detected by the radar) and may utilize the alerting infrastructure provided by the radar_area_detection\\comm submodule (for example, sending messages via RabbitMQ).\n\n## Usage\n\nDevelopers can use this script to define detection areas, integrate tracking data, and manage alert systems based on their specific needs in the context of FMCW radar applications.\n\n## Data Flow\n\nThe AreaDetector class initializes with predefined detection areas and has the capability to receive real-time tracking data. Upon receipt of new cluster information, the update method reevaluates and categorizes each area as clear or under alert, triggering the appropriate alert mechanisms if any are in place.\n\n## Developer Notes\n\n- When creating new Area instances, ensure that the coordinates correctly reflect the detection zone intended for monitoring.\n- When implementing concrete alert classes, define clear procedures for both RaiseAlert and ClearAlert methods.\n- During the update process, ensure that the centroid of clusters is being correctly obtained from the tracking data.\n- It is crucial to manage ok_areas and alert_areas accurately, reflecting the radar\u00e2\u20ac\u2122s real-time assessment of the monitored areas."}, {"file": "radar_area_detection\\display.md", "doc": "# display.py - radar_area_detection Module Documentation\n\n## Overview\n\nThe display.py script is part of the radar_area_detection module, which integrates with the area detection and object tracking functionalities. This script specifically provides visualization capabilities, extending the TrackingDisplay2D class from the radar_tracking module to represent detection areas and the status of those areas (either as \"ok\" or under \"alert\").\n\n## File Structure\n\ndisplay.py includes the following class:\n\n- AreasDisplay2D: Extends the TrackingDisplay2D class to display detection areas and denote their status on a 2D plot.\n\n### AreasDisplay2D Class\n\nThe AreasDisplay2D class is responsible for visualizing areas on a 2D display, differentiating between areas that are clear (ok) and those that have an active alert. It allows real-time updates of the visualization as the status of the areas changes according to the radar data.\n\n#### Constructor\n\n- __init__(self, *args, **kwargs): Initializes the AreasDisplay2D class with arguments passed to its superclass and initializes an empty list for patches.\n\n#### Attributes\n\n- patches: List. Stores the drawing patches corresponding to areas on the display.\n\n#### Methods\n\n- _prepare_draw(self, clusters, ok_areas: List[Area], alert_areas: List[Area]): Internally prepares the drawing of the clusters and areas. It removes any existing patches and re-adds them according to the updated area states.\n- show(self, clusters, area_detector: AreaDetector): Public method to display the radar clusters and areas. This method calls _prepare_draw with the ok_areas and alert_areas from an AreaDetector instance and then proceeds to draw the updated visualization.\n\n### Integration with Other Modules\n\nThe detect.py script in the radar_area_detection module interacts with the AreasDisplay2D class to visualize active areas and alerts. Moreover, the AreasDisplay2D class uses functionality from the radar_tracking module\u00e2\u20ac\u2122s visualization utilities, signifying how various modules within the system come together to fulfill the project\u00e2\u20ac\u2122s overall objectives.\n\n## Usage\n\nDevelopers can instantiate the AreasDisplay2D class to visualise the area detection results in the context of FMCW radar applications. This enables a graphical representation of which areas are clear (ok) and which are under alert.\n\n## Data Flow\n\n1. An instance of AreasDisplay2D is created with appropriate arguments.\n2. Radar data (clusters) and area statuses are processed by an AreaDetector.\n3. Area statuses and clusters are passed to the AreasDisplay2D instance\u00e2\u20ac\u2122s show method.\n4. The show method updates the visual representation according to the current state of detection areas and tracked clusters.\n\n## Developer Notes\n\n- Use the AreasDisplay2D class to create a visual feedback loop for area detection and alert visualization in real-time radar applications.\n- Ensure active areas and their statuses are correctly updated and reflected in the visualization to provide continuous situational awareness.\n- The visual representation is crucial for debugging and monitoring the radar area detection functionality, hence strive for clear visual distinction between different states for better readability and interpretation.\n\n## Conclusion\n\ndisplay.py within the radar_area_detection module serves a pivotal role in visually representing the status of detection areas in real-time. The AreasDisplay2D class demonstrates an effective integration of visualization techniques with radar detection and tracking capabilities. It contributes to the wider goal of creating a modular and adaptable system for FMCW radar applications."}, {"file": "radar_area_detection\\comm\\camera_alert.md", "doc": "# camera_alert.py - radar_area_detection.comm Module Documentation\n\n## Overview\n\nThe camera_alert.py script resides within the radar_area_detection.comm submodule of the radar_area_detection module. This script defines a concrete implementation of an alert system based on camera activation, which integrates with the radar area detection system to respond to specific detection events using web requests.\n\n## File Structure\n\ncamera_alert.py contains the following class:\n\n- CameraAlert: This class extends the abstract base Alert class, specifying actions to perform when an alert must be raised or cleared via camera control.\n\n### CameraAlert Class\n\nThe CameraAlert class is designed to send commands to a networked camera to start or stop recording based on area detection alerts.\n\n#### Constructor\n\n- __init__(self, ip, port): Initializes the CameraAlert with network configurations.\n\n#### Attributes\n\n- ip: String. The IP address of the camera.\n- port: Integer. The port number to access the camera.\n\n#### Methods\n\n- RaiseAlert: Sends an HTTP POST request to the camera\u00e2\u20ac\u2122s server to start recording when an alert is raised.\n- ClearAlert: Sends an HTTP POST request to the camera\u00e2\u20ac\u2122s server to stop recording when an alert is cleared.\n\n## Integration with Other Modules\n\n- CameraAlert extends the Alert class from radar_area_detection.detection, linking camera control to the area detection logic using polymorphism.\n\n## Usage\n\nThe CameraAlert class may be instantiated and passed to AreaDetector instances within detection.py to specify that the camera should react to detection events.\n\nDevelopers can use this script as follows:\n\n1. Instantiate the CameraAlert with the appropriate IP and port for the camera.\n2. Integrate the instance with the area detection system so the camera actions are triggered during alert conditions.\n\n## Error Handling\n\nThis script catches exceptions during the HTTP request process and prints an error message, which helps to identify network or camera accessibility issues.\n\n## External Dependence\n\ncamera_alert.py depends on the requests library to perform HTTP requests. Make sure that requests is installed and available in the project\u00e2\u20ac\u2122s environment.\n\n## Data Flow\n\n1. The area detection system determines that an alert condition is met.\n2. AreaDetector triggers the RaiseAlert method on the CameraAlert instance.\n3. CameraAlert sends an HTTP request to the camera to start or stop recording based on the state of the alert.\n\n## Developer Notes\n\nDevelopers looking to further customize behavior or add features should consider:\n\n- Expanding the CameraAlert class to handle more sophisticated network protocols or add authentication as needed.\n- Implementing retry logic or asynchronous requests if the synchronous POST request model proves to be a bottleneck or if the timeout parameter needs adjustment.\n- Adding logging mechanisms to capture successful interactions and failed attempts for better operational visibility.\n\n## Conclusion\n\nThe camera_alert.py script effectively bridges the gap between radar area detection and physical security measures, empowering the system to take real-world, automated actions in response to detection events. By following the robust design principle of extending an abstract base class, this module enhances the flexibility and scalability of the overall radar area detection mechanism."}, {"file": "radar_area_detection\\comm\\rabbitmq.md", "doc": "# rabbitmq.py - radar_area_detection.comm Module Documentation\n\n## Overview\n\nThe rabbitmq.py script is part of the communication (comm) submodule within the radar_area_detection module. This script contains a class responsible for interfacing with RabbitMQ to send messages, typically used to alert when an object is detected within a specified area by the radar system.\n\n## File Structure\n\nrabbitmq.py includes the following class:\n\n- RabbitMQSender: A class to manage the connection and message dispatch through RabbitMQ.\n\n### RabbitMQSender Class\n\nRabbitMQSender establishes a RabbitMQ connection and allows sending JSON formatted messages to a specified queue.\n\n#### Constructor\n\n- __init__(self, host, port, queue, exchange): Takes in needed RabbitMQ parameters and initializes the RabbitMQSender.\n\n#### Attributes\n\n- host: String. The IP address or hostname of the RabbitMQ server.\n- port: Integer. The port number for the RabbitMQ server.\n- queue: String. The name of the queue to which messages will be sent.\n- exchange: String. The exchange associated with the message routing.\n\n#### Methods\n\n- connect: Establishes a connection to the RabbitMQ server and declares the queue.\n- send_json(self, data): Publishes a JSON-formatted message to the queue.\n- disconnect: Closes the connection to the RabbitMQ server.\n\n## Integration with Other Modules\n\n- This communication class is a standalone tool within the radar_area_detection module. It can be used in conjunction with the area detection logic to automatically send notifications or alerts over a network when certain conditions are met.\n\n## Usage\n\nDevelopers can instantiate RabbitMQSender as needed to send messages to RabbitMQ brokers that other systems or services can receive. These messages may carry data about detection events or status changes.\n\n## Message Flow\n\n1. An instance of RabbitMQSender is created with the necessary connection parameters.\n2. The class connects to the RabbitMQ server and ensures the queue\u00e2\u20ac\u2122s existence.\n3. JSON data is sent to the queue via send_json.\n4. Upon completion or as part of cleanup, the connection is closed with disconnect.\n\n## Developer Notes\n\n- Ensure that the RabbitMQ server settings (host and port) and queue details are accurately configured.\n- Implement error handling for potential exceptions during connection establishment, message publishing, or disconnection.\n- Consider implementing a context manager protocol (__enter__ and __exit__) for RabbitMQSender to manage connections more gracefully in a with statement.\n- When deploying in a production environment, consider additional mechanisms for robustness, such as connection retries and message delivery confirmations.\n\n## External Dependence\n\nrabbitmq.py depends on the pika library, which facilitates RabbitMQ interactions from Python applications. Ensure that the pika library is incorporated within the project\u00e2\u20ac\u2122s environment.\n\n## Conclusion\n\nThe rabbitmq.py script is a utility class enabling the radar_area_detection module to leverage RabbitMQ for transmitting messages related to radar area detection events. Its simplicity and focus allow for flexible and easy integration into the radar system\u00e2\u20ac\u2122s alerting and notification logic. As part of the module\u00e2\u20ac\u2122s decoupled communication strategy, it supports the overarching project\u00e2\u20ac\u2122s goal of rapid and adaptable development for FMCW radar applications."}], "other_modules_doc": [{"module": "radar_visuals", "doc": "# radar_visuals Module Documentation\n\n## Overview\n\nThe radar_visuals module is a dedicated visualization package within a project focused on the use of Frequency Modulated Continuous Wave (FMCW) radar. It is designed to provide tools and utilities for the rendering of radar data in various visual formats, supporting functionalities like data collection, point detection, and tracking analysis. The module aims to facilitate rapid development and integration of new visualization features through a decoupled and flexible structure.\n\n## Module Structure\n\nThe radar_visuals module currently contains the following file:\n\n- display.py: A Python script offering a suite of classes and functions for creating dynamic and static displays for radar data visualization.\n\n## Module Files Documentation\n\n### display.py\n\nThe display.py file within the radar_visuals package encompasses multiple visualization methods and is central to the module. Below is a summary of the provided documentation:\n\n#### Overview\nThe script is essential for visualizing radar data and includes capabilities for 2D, 3D, and polar plotting. It is versatile enough to accommodate both real-time and static data presentations.\n\n#### Components\nEnums such as PlayingMode, Projection, and GraphType allow the user to define the display behavior, the plot\u00e2\u20ac\u2122s projection type, and the graph style, respectively. Along with utility functions like color_from_id and plot_signal, the script provides two main classes:\n\n- UpdatableDisplay: The abstract base class for displays that can be updated, initializing the figure, axes, and other graphical elements.\n- SimpleUpdatableDisplay: A concrete implementation of UpdatableDisplay that prepares and updates displays with new data points.\n\n#### Functionalities\nThe primary functionalities include creating interactive graphs to visualize radar data, updating them according to predefined playing modes, and ensuring compatibility with different data types and visual projections.\n\n#### Data Flow\nThe typical workflow involves:\n1. Initializing a display object with the required properties.\n2. Accumulating or simulating radar data points.\n3. Updating the display as new data arrives through the show() method.\n4. Presenting the visual representation of the radar data to users based on the set playing mode.\n\n#### Developer Notes\nDevelopers are advised to match data dimensions with graph types and projections, manage update rates effectively, and assign unique colors to data sources using UUIDs for better data distinction.\n\n#### Integration\nDespite being part of the radar_visuals package, display.py operates independently from other components, specifically focusing on visualization purposes and not on signal processing.\n\n## Usage\n\nThe module can be employed to:\n\n- Visualize FMCW radar-related data points, signals, and more complex datasets.\n- Develop new visualization tools tailored to the specifics of radar data.\n- Enhance the interpretation of radar data through graphically rich plots.\n\n## Conclusion\n\nradar_visuals is a crucial module for the graphical representation and analysis of radar data within a larger FMCW radar-focused project. The modular structure accommodates efficient development, enabling users and developers to easily integrate new visualization techniques suited to their specific needs. The module\u00e2\u20ac\u2122s design streamlines the translation of complex data into understandable and insightful visual formats, supporting a wide range of functionalities from debugging to presentation."}, {"module": "radar_toolbox", "doc": "# radar_toolbox Module Documentation\n\n## Overview\n\nThe radar_toolbox module is a collection of tools designed for interfacing with Frequency Modulated Continuous Wave (FMCW) radar systems. It is utilized for various purposes such as data collection, point detection, tracking, and other radar signal processing functions. The module is structured to decouple functionalities into distinct units to promote flexibility and rapid development of new features.\n\n## Module Structure\n\nThe radar_toolbox module is composed of the following elements:\n\n- conf/\n - Various configuration files setting parameters for radar initialization and different processing steps, such as profile_vs1642_exp.cfg which provides specific settings for radar models and data handling.\n- capture_session/\n - This submodule contains scripts for setting up and managing radar data capture sessions, with scripts like main.py for starting, monitoring, and saving raw radar captures.\n- raw_data/\n - A collection of code dealing with raw data handling, including adc.py for interfacing with Analog-to-Digital Converters and scripts to convert raw binary radar data into structured formats for analysis.\n- TI_data/\n - Contains tools and scripts to communicate, configure, and process data from Texas Instruments (TI) mmWave radar boards, including sensor_com.py which outlines communication protocols and data parsing mechanisms.\n- fmcw_utils.py\n - This utility file offers essential classes and functions for the processing and analysis of FMCW radar data, such as radar model enums and functions for loading and converting radar data.\n- utils.py\n - General utility functions and classes that support the operation of the radar_toolbox module, with methods for loading configurations, data parsing, and more.\n\n## Module Files Documentation\n\nDevelopers new to radar_toolbox will find documentation for several key files within the module. An outline of this documentation includes:\n\n- fmcw_utils\n - Detailed information on handling FMCW radar systems, managing configurations, processing radar signals, and transforming them into analyzable forms.\n- utils\n - A comprehensive overview of utility functions that aid in loading configurations, preprocessing radar data, and assisting with model training and coordinate adjustments.\n- capture_session/main\n - Instructions on setting up and conducting recording sessions with scripts that interact with the radar system to initiate and manage data capture.\n- raw_data/adc\n - Documentation of the adc.py script which serves as an interface to ADC hardware, allowing for the capture and real-time processing of radar data streams.\n- raw_data/raw_bin_to_numpy\n - Explains the process of converting raw binary radar data into a NumPy array and the steps involved in ensuring data integrity during conversion.\n- raw_data/record_raw_data\n - A guide to a script focused on raw data recording, detailing the initiation of data capture and subsequent data stream management.\n- TI_data/record_ti_data\n - Documentation for a script specific to TI radar hardware, describing real-time data capture and CSV data storage functionality.\n- TI_data/sensor_com\n - Communication protocols and data structure parsing methods for TI mmWave radar boards are outlined for managing interactions with these devices.\n\n## Usage\n\nDevelopers can use the radar_toolbox module to:\n\n- Set up FMCW radar data capture sessions.\n- Record and process raw radar data.\n- Convert binary radar data captures into formats suitable for analysis, such as NumPy arrays.\n- Interact and configure TI mmWave radars for data acquisition.\n\n## Data Flow Summary\n\nThe data flow within the radar_toolbox module follows these general steps:\n\n1. Configuration is set up using JSON files and configuration profiles for the specific radar models.\n2. Data recording sessions are initiated, capturing the radar data and storing it in binary format.\n3. Raw binary data is processed, filtered, and organized into structured data arrays.\n4. Data is made ready for analysis, transformed into point clouds or other representations necessary for further processing and interpretation.\n\n## External Dependencies\n\nWhile the module works as an independent toolkit within the project scope, it interfaces with radar hardware and other software modules that handle advanced data analysis, visualization, and machine learning applications.\n\n## Overall Significance\n\nThe radar_toolbox module serves as the foundational toolset for FMCW radar systems, streamlining the process from initial data capture to data preparation for analytics. It emphasizes modularity, making it easier to grow and adapt the project with new functionalities."}, {"module": "radar_tracking", "doc": "# FMCW Radar Tracking Project Documentation\n\n## radar_tracking Module\n\nThe radar_tracking module sits at the heart of the FMCW radar project, providing algorithms and utilities focused on the tracking of objects detected by the radar system.\n\n### Module Structure\n\nThe module is composed of several scripts and a configuration file organized as follows:\n\n- tracking_utils.py: Utilities for configuring and initializing tracking components.\n- conf/tracking.json: A JSON-formatted configuration file specifying parameters for the tracking system.\n- inference/:\n - example_kalman_filter.py: Perform inference using Kalman filters.\n - example_tracking.py: An example script demonstrating the tracking process.\n- models/:\n - kalman.py: Implementations of Kalman filter for state estimation.\n - tracking.py: The main tracking algorithm handling the temporal correlation of clusters.\n- clustering/:\n - cluster.py: Data structure for managing clusters of points.\n - cluster_predictor.py: Class for predicting clustering behavior based on certain algorithms.\n - optimizer.py: Optimization utilities for clustering performance.\n- algos/:\n - clustering_algorithm.py: Abstract base algorithms for clustering.\n - dbscan.py: DBSCAN clustering algorithm implementation.\n - gaussian_mixture.py: Gaussian Mixture Model clustering implementation.\n - meanshift.py: Mean Shift clustering algorithm implementation.\n- visuals/display.py: Visualization classes for displaying the tracking data.\n\n### Dependencies\n\nThe radar_tracking module relies on other parts of the FMCW radar project:\n\n- radar_toolbox:\nA toolkit for interacting with the radar hardware and processing raw radar data.\n\n- radar_visuals:\nProvides dynamic and static displays to visualize radar data, which can be helpful to show tracking results in an accessible form.\n\n## Development Notes\n\nDevelopers new to this project will want to familiarize themselves with the radar_tracking module by reviewing existing documentation and code comments.\n\nFor practical understanding, developers are encouraged to interact with example scripts inside the inference subdirectory. They illustrate how the various components come together to achieve object tracking.\n\n## Conclusion\n\nThe radar_tracking module integrates sophisticated algorithms and diverse data sets to track objects with high precision. It exemplifies a well-organized codebase that promotes decoupled architecture, thus expediting the development of innovative functionalities in radar-based tracking systems."}], "gen_doc_of_file": {"path": "radar_area_detection\\live_area_detection.py", "content": "\"\"\"\nLive area detection from TI data.\nRun this script with the following parameters: --conf=conf/area_detection/[config file]\n\"\"\"\nimport math\n\nimport numpy as np\n\nfrom radar_toolbox.fmcw_utils import RadarModel\nfrom radar_toolbox.utils import configure_argument_parser_for_conf_file, load_conf, get_reader_from_config, \\\n points_inclination_correction\nfrom radar_area_detection.detection import AreaDetector\nfrom radar_area_detection.comm.camera_alert import CameraAlert\nfrom radar_tracking.tracking_utils import get_capture_limits_from_conf, get_clustering_algo_from_conf, \\\n get_cluster_tracker_from_conf\n\nif __name__ == \"__main__\":\n args = configure_argument_parser_for_conf_file()\n config = load_conf(args.conf)\n rabbitmq_conf = load_conf(config[\"rabbitmq_conf\"])\n if rabbitmq_conf[\"enable\"]:\n from radar_area_detection.comm.rabbitmq import RabbitMQSender\n import json\n\n rabbitmq_sender = RabbitMQSender(host=rabbitmq_conf[\"host\"], port=rabbitmq_conf[\"port\"],\n queue=rabbitmq_conf[\"queue\"])\n rabbitmq_sender.connect()\n\n cfg_file_path = config[\"cfg_file_path\"]\n radar_model = RadarModel.get_model_from_str(config[\"model\"])\n min_velocity_detection = config[\"min_point_vel\"]\n horizontal_inclination = vertical_inclination = None\n if config[\"horizontal_inclination\"] is not None:\n horizontal_inclination = math.radians(config[\"horizontal_inclination\"])\n if config[\"vertical_inclination\"] is not None:\n vertical_inclination = math.radians(config[\"vertical_inclination\"])\n\n tracking_conf = load_conf(config[\"tracking_conf\"])\n frame_grouping_size = tracking_conf[\"frame_grouping_size\"] # How many frames do we want per step\n dt = tracking_conf[\"frame_interval\"] * frame_grouping_size # Delta time between two steps\n verbose = tracking_conf[\"verbose\"]\n capture_limits = get_capture_limits_from_conf(config=tracking_conf)\n\n clustering_algo = get_clustering_algo_from_conf(config=tracking_conf)\n cluster_tracker = get_cluster_tracker_from_conf(config=tracking_conf)\n local_display = config[\"local_display\"]\n if local_display:\n from matplotlib import pyplot as plt\n from radar_area_detection.display import AreasDisplay2D\n from radar_visuals.display import PlayingMode\n\n areaDisplay = AreasDisplay2D(dt=dt, capture_limits=capture_limits, playing_mode=PlayingMode.NO_WAIT,\n time_fade_out=tracking_conf[\"time_fade_out\"])\n\n area_conf = load_conf(config[\"area_detection_conf\"])\n alerts = None\n if area_conf[\"camera\"][\"enable\"]:\n camera_alert = CameraAlert(ip=area_conf[\"camera\"][\"ip\"], port=area_conf[\"camera\"][\"port\"])\n alerts = [camera_alert]\n area_detector = AreaDetector(areas=area_conf[\"areas\"], alerts=alerts)\n\n # Configure the serial port\n reader = get_reader_from_config(config=config)\n reader.connect(cli_port=config[\"CLI_port\"], data_port=config[\"data_port\"])\n reader.send_config(cfg_file_path=cfg_file_path)\n reader.start_sensor(listen_to_data=True)\n\n try:\n while True:\n result = reader.parse_stream(only_points=True)\n # check if the data is okay\n if result[\"data_ok\"]:\n if result[\"detected_points\"] is None:\n points = []\n else:\n points = result[\"detected_points\"]\n if radar_model == RadarModel.IWR6843AOP and min_velocity_detection is not None:\n points = points[np.abs(points[:, 3]) > min_velocity_detection]\n points = points_inclination_correction(points[:, :3], horizontal_inclination, vertical_inclination)\n\n points = points[np.all(capture_limits[:, 0] < points, axis=1)]\n points = points[np.all(points < capture_limits[:, 1], axis=1)]\n\n # Tracking\n clusters, noise = clustering_algo.clusterize(points)\n cluster_tracker.TrackNextTimeStep(current_clusters=clusters, verbose=verbose)\n # Intrusion detection\n area_detector.update(clusters_up_to_date=cluster_tracker.tracked_clusters)\n if local_display:\n areaDisplay.show(clusters=cluster_tracker.tracked_clusters, area_detector=area_detector)\n if rabbitmq_conf[\"enable\"]:\n json_data = {\n \"areas\": area_detector.serialize(),\n \"clusters\": cluster_tracker.serialize()\n }\n json_data = json.dumps(json_data)\n rabbitmq_sender.send_json(json_data)\n except KeyboardInterrupt: # Stop the program and close everything if Ctrl + c is pressed\n pass\n finally:\n reader.disconnect()\n if local_display:\n plt.close('all')\n if rabbitmq_conf[\"enable\"]:\n rabbitmq_sender.disconnect()\n"}}
|
36b050eb26d36ec300f298356a634f6d
|
{
"intermediate": 0.30595943331718445,
"beginner": 0.4961298406124115,
"expert": 0.19791077077388763
}
|
31,165
|
for machine laerning in python, what is the minimum row for performing linear regression model?
|
61fcce6cc8971a8daa150fa5376bbc0d
|
{
"intermediate": 0.19560357928276062,
"beginner": 0.0510309673845768,
"expert": 0.7533654570579529
}
|
31,166
|
There is a collection of photos to place into an empty photo albun one at a time by order of importance. Each time a photo is inserte all subsequent photos are shifted toward the right by one position Given the id's of the photos and the positions where each should t placed, find out the sequence of the photos in the album after all photos have been inserted.
Example
n=5
index=[0, 1, 2, 1, 2]
identity = [0, 1, 2, 3, 4]
The sequence of the photos is as follows:
The photos 0, 1 and 2 keep the same indexes 0, 1 and 2 respectively.
• The photo 3 is inserted in index 1 and the subsequent photos 1 and 2 are shifted right by one position.
• The photo 4 is inserted in position 2 and again the photos 1 and 2 are shifted right by one position.
Identity
Album
[0]
10H 234 Θ
[0, 1]
[0, 1, 2]
[0, 3, 1, 2]
[0, 3, 4, 1, 2]
Function Description
Complete the function photoAlbum in the editor below.
photoAlbum has the following parameter(s):
int index[n]: the insertion points for each photo
int identity[n]: the photograph id numbers
Function Description
Int[n]: the sequence of identity values after all are inserted
Constraints
• 1≤n≤2×105
• Os index[i], identity[i] <n (0≤i<n)
►Input Format For Custom Testing
▼ Sample Case 0
Sample Input 0
STDIN
Function
3
index[] size n = 3
->
index[] = [ 0, 1, 1]
->
identity[] size n = 3
->
2
identity[] = [ 0, 1, 2 ]
Sample Output 0
e
2
1
Explanation 0
n=3
Index = [0, 1, 1]
n=3
Identity = [0, 1, 2]
The output array goes through the following steps: [0] → [0, 1]→ [0, 2, 1].
Sample Case 1
2
0
0
2
0
1
Sample Output 1
1
0
Explanation
n=2
index =[0, 0]
n=2
identity=[0, 1]
Output array goes through following steps
[0]->[0,1]
Sample Case 2
3
0
1
0
1
2
sapmle output 2
2
0
|
dcba49ed8e80a9b0bb75172c562a4ac9
|
{
"intermediate": 0.2527165710926056,
"beginner": 0.3273290991783142,
"expert": 0.4199543297290802
}
|
31,167
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 5, 4, 3, 2, 1 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
int currentTexture; // Индекс текущей текстуры на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow("Slot Machine", SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ "res/01spin.png", "res/11spin.png", "res/21spin.png" },
{ "res/02spin.png", "res/12spin.png", "res/22spin.png" },
{ "res/03spin.png", "res/13spin.png", "res/23spin.png" },
{ "res/04spin.png", "res/14spin.png", "res/24spin.png" },
{ "res/05spin.png", "res/15spin.png", "res/25spin.png" } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH;
int totalSpacingWidth = (NUM_DRUMS - 1) * 20;
int totalWidth = totalDrumsWidth + totalSpacingWidth;
int startX = (WINDOW_WIDTH - totalWidth) / 2;
for (int i = 0; i < NUM_DRUMS; i++)
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = WINDOW_HEIGHT / 20;
drum.currentTexture = 0;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
for (int j = 0; j < NUM_TEXTURES; j++) {
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][j].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums, bool rotate)
{
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
drumRect.y += DRUM_HEIGHT; SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
drum.currentTexture++;
if (drum.currentTexture >= NUM_TEXTURES)
{
drum.currentTexture = 0;
}
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums, isRotating);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} Как сделать 3 ряда барабанов, что бы каждый ряд крутился с одной скоростью, но все картинки при астановке барабанов, были разные.
|
25f0253b09ddd0833bbb1624fa93b2b1
|
{
"intermediate": 0.2968914806842804,
"beginner": 0.5576466917991638,
"expert": 0.1454618275165558
}
|
31,168
|
This program has an error! We are trying to change "black" to "blue" in the rainbow list. Let's debug it!
RULE: .index() returns the index (position) of a value in a list.
Click Run and read the error message.
Change the value in the parentheses of .index() to get the index of the color "black".
Click Run to see if you fixed the program. When it is fixed, click Submit and Next.
rainbow = ["red", "orange", "yellow", "green", "blue"]
index = rainbow.index("black")
rainbow[index] = "blue"
for color in rainbow:
stage.set_background_color(color)
stage.wait(1)
|
c52e463b43c12f4e89b6384efc6d5509
|
{
"intermediate": 0.5597108006477356,
"beginner": 0.17589448392391205,
"expert": 0.2643946707248688
}
|
31,169
|
You are a senior python programmer with an extensive and deep knowledge of the Python language.
Create a python program that complieas with the following requirements:
1) Inspects all open instaces of chrome webbrowser and prints the urls in all the tabs each instance contains.
2) There might be several open instaces of chrome webbrowser, so it has to check them all.
3) If one ot the tabs in any of the instances is browsing the page 'modelo.html' it will fill a specific textbox in that page named 'userInput' with the text obtained from a file named 'input.txt'
4) DO NOT open a new browser instances. Only use instances already open already open.
5) THE PROGRAM CAN NOT NAVIGATE TO A WEB PAGE: IT HAS TO USE THE PAGES PAGE CURRENTLY DISPLAYED INSIDE THE TABS IN ONE OF THE BROWSER ACTIVE INSTANCES
All five requirements must be fulfilled.
|
8e07ae2b0fae9f39c57f20a04d47778e
|
{
"intermediate": 0.36981359124183655,
"beginner": 0.212409108877182,
"expert": 0.41777729988098145
}
|
31,170
|
этот код можно усовершенствовать чтобы он работал быстрее?
import os
import sys
def dp(content):
content = content.replace(" ", "")
return content
def dp2(content):
content = content.replace("'", "")
return content
def dp3(content):
content = content.replace("+", "")
return content
folder_path = 'numbers'
arg = sys.argv[1]
# files = os.listdir(folder_path)
files = [arg]
folder_path2 = 'base'
files2 = os.listdir(folder_path2)
for file_name in files:
if file_name.endswith(".txt"):
print(file_name)
file_path = os.path.join(folder_path, file_name)
with open(file_path, 'r', encoding="utf-8") as file:
lines = file.read()
lines=str(lines).split('\n')
for line in lines:
part=str(line).split('\t')
part = list(filter(None, part))
if len(part)>1:
for file_name2 in files2:
if file_name2.endswith(".txt"):
file_path2 = os.path.join(folder_path2, file_name2)
with open(file_path2, 'r', encoding="utf-8") as file2:
lines2 = file2.read()
lines2=str(lines2).split('\n')
for line in lines2:
if str(part[0]) in line:
line=line.split(',')
line[0] = part[1]
# print(line)
with open('out/'+file_name2, 'a+', encoding="utf-8") as file:
file.write(dp3(dp2(dp(str(line)[1:-1])))+'\n')
break
|
4472b7e58051ba30840231a5bb19210e
|
{
"intermediate": 0.2058292031288147,
"beginner": 0.634349524974823,
"expert": 0.15982124209403992
}
|
31,171
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 5, 4, 3, 2, 1 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
int currentTexture; // Индекс текущей текстуры на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow("Slot Machine", SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ "res/01spin.png", "res/11spin.png", "res/21spin.png" },
{ "res/02spin.png", "res/12spin.png", "res/22spin.png" },
{ "res/03spin.png", "res/13spin.png", "res/23spin.png" },
{ "res/04spin.png", "res/14spin.png", "res/24spin.png" },
{ "res/05spin.png", "res/15spin.png", "res/25spin.png" } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH;
int totalSpacingWidth = (NUM_DRUMS - 1) * 20;
int totalWidth = totalDrumsWidth + totalSpacingWidth;
int startX = (WINDOW_WIDTH - totalWidth) / 2;
for (int i = 0; i < NUM_DRUMS; i++)
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = WINDOW_HEIGHT / 20;
drum.currentTexture = 0;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
for (int j = 0; j < NUM_TEXTURES; j++) {
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][j].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
drumRect.y += DRUM_HEIGHT; SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
drum.currentTexture++;
if (drum.currentTexture >= NUM_TEXTURES)
{
drum.currentTexture = 0;
}
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} 1) Сделать 3 ряда барабанов по центру экрана. 2) Сделать одинаковую скорость вращения рядов по горизонтали. 3) при остановки барабанов в каждом из рядов по горизонтали, должны быть разные картинки.
|
2ada1e950b4a617b4315b4d6e2cb41fb
|
{
"intermediate": 0.26516255736351013,
"beginner": 0.535163402557373,
"expert": 0.19967399537563324
}
|
31,172
|
make it print something everytime the frame has been the same for 1.5 seconds, so it's gonna be a frame with some numbers on it and I wanna run a ocr aslong as the video has stayed the same for 1.5 sec:
# Convert template to grayscale
template_gray = cv2.cvtColor(template_image, cv2.COLOR_BGR2GRAY)
dot_template_gray = cv2.cvtColor(dot_template, cv2.COLOR_BGR2GRAY)
# Open the video
# Load image from file instead of camera
url = "http://10.30.225.250:8088/shot.jpg"
# Initialize background subtractor
# url = "http://10.30.225.127:8080/shot.jpg"
while True:
img_resp = requests.get(url)
img_arr = np.frombuffer(img_resp.content, np.uint8)
frame = cv2.imdecode(img_arr, -1)
# Apply background subtraction
# Convert frame to grayscale
gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Perform template matching
res = cv2.matchTemplate(gray_frame, template_gray, cv2.TM_CCOEFF_NORMED)
# Set a threshold and find where the matching result exceeds it
threshold = 0.7
loc = np.where(res >= threshold)
# Draw rectangles around detected windows
for pt in zip(*loc[::-1]):
cropped_img = current_pic[pt[1] - 10 : pt[1] + h - 35, pt[0] : pt[0] + w - 25]
cropped_img_gray = cv2.cvtColor(cropped_img, cv2.COLOR_BGR2GRAY)
thresholded_image = cv2.adaptiveThreshold(
cropped_img_gray,
255,
cv2.ADAPTIVE_THRESH_MEAN_C,
cv2.THRESH_BINARY,
11,
11,
)
blurred_image = cv2.GaussianBlur(thresholded_image, (3, 3), 0)
res2 = cv2.matchTemplate(blurred_image, dot_template_gray, cv2.TM_CCOEFF_NORMED)
threshold = 0.6
loc2 = np.where(res2 >= threshold)
print(loc2)
for pt in zip(*loc2[::-1]):
cv2.rectangle(blurred_image, pt, (pt[0] + 50, pt[1] + 70), (0, 255, 0), 2)
# Show the frame
cv2.imshow("Detected Window", blurred_image)
# Exit on pressing "q"
if cv2.waitKey(1) & 0xFF == ord("d"):
current_pic = frame2
if cv2.waitKey(1) & 0xFF == ord("a"):
current_pic = frame
if cv2.waitKey(1) & 0xFF == ord("s"):
hey = check_picture(blurred_image)
print(hey)
if cv2.waitKey(1) & 0xFF == ord("q"):
break
|
729ad332d5f17b57bf410994857bae5a
|
{
"intermediate": 0.31859153509140015,
"beginner": 0.44396087527275085,
"expert": 0.23744763433933258
}
|
31,173
|
Instructions:
The project focuses on the use of FMCW radar.
It is used for data collection, point detection, tracking and other functions.
The project is broken down into several modules.
The aim of this division is to decouple as much as possible the functionalities present in each module, and make the development of new functionalities more flexible and rapid.
Some information will be presented to you in json format:
- module: the name of the module
- module_structure: the structure of the module (the files making up the module and their hierarchy)
- module_files_already_generated_doc: the documentation of the module's files if already generated
- other_modules_doc: the documentation of the other modules on which the module depends (possibly none at all)
- gen_doc_of_file: the file you will be given to generate the documentation of. If no file is given, the documentation of the entire module must be generated.
Your goal is to create a markdown documentation of the file you will be given, or the entire module if no file is given.
This documentation is intended to guide a developer who is new to the project, you can therefore add whatever you feel is relevant for this task.
Informations:
{"module": "radar_fall_detection", "module_structure": "radar_fall_detection/algo.py;radar_fall_detection/display.py;radar_fall_detection/live_fall_detection.py;radar_fall_detection\\conf/fall_conf.json;radar_fall_detection\\conf/live_fall_detection.json;radar_fall_detection\\conf/ti_conf.json;radar_fall_detection\\conf/tracking.json;", "module_files_already_generated_doc": [], "other_modules_doc": [{"module": "radar_visuals", "doc": "# radar_visuals Module Documentation\n\n## Overview\n\nThe radar_visuals module is a dedicated visualization package within a project focused on the use of Frequency Modulated Continuous Wave (FMCW) radar. It is designed to provide tools and utilities for the rendering of radar data in various visual formats, supporting functionalities like data collection, point detection, and tracking analysis. The module aims to facilitate rapid development and integration of new visualization features through a decoupled and flexible structure.\n\n## Module Structure\n\nThe radar_visuals module currently contains the following file:\n\n- display.py: A Python script offering a suite of classes and functions for creating dynamic and static displays for radar data visualization.\n\n## Module Files Documentation\n\n### display.py\n\nThe display.py file within the radar_visuals package encompasses multiple visualization methods and is central to the module. Below is a summary of the provided documentation:\n\n#### Overview\nThe script is essential for visualizing radar data and includes capabilities for 2D, 3D, and polar plotting. It is versatile enough to accommodate both real-time and static data presentations.\n\n#### Components\nEnums such as PlayingMode, Projection, and GraphType allow the user to define the display behavior, the plot\u00e2\u20ac\u2122s projection type, and the graph style, respectively. Along with utility functions like color_from_id and plot_signal, the script provides two main classes:\n\n- UpdatableDisplay: The abstract base class for displays that can be updated, initializing the figure, axes, and other graphical elements.\n- SimpleUpdatableDisplay: A concrete implementation of UpdatableDisplay that prepares and updates displays with new data points.\n\n#### Functionalities\nThe primary functionalities include creating interactive graphs to visualize radar data, updating them according to predefined playing modes, and ensuring compatibility with different data types and visual projections.\n\n#### Data Flow\nThe typical workflow involves:\n1. Initializing a display object with the required properties.\n2. Accumulating or simulating radar data points.\n3. Updating the display as new data arrives through the show() method.\n4. Presenting the visual representation of the radar data to users based on the set playing mode.\n\n#### Developer Notes\nDevelopers are advised to match data dimensions with graph types and projections, manage update rates effectively, and assign unique colors to data sources using UUIDs for better data distinction.\n\n#### Integration\nDespite being part of the radar_visuals package, display.py operates independently from other components, specifically focusing on visualization purposes and not on signal processing.\n\n## Usage\n\nThe module can be employed to:\n\n- Visualize FMCW radar-related data points, signals, and more complex datasets.\n- Develop new visualization tools tailored to the specifics of radar data.\n- Enhance the interpretation of radar data through graphically rich plots.\n\n## Conclusion\n\nradar_visuals is a crucial module for the graphical representation and analysis of radar data within a larger FMCW radar-focused project. The modular structure accommodates efficient development, enabling users and developers to easily integrate new visualization techniques suited to their specific needs. The module\u00e2\u20ac\u2122s design streamlines the translation of complex data into understandable and insightful visual formats, supporting a wide range of functionalities from debugging to presentation."}, {"module": "radar_toolbox", "doc": "# radar_toolbox Module Documentation\n\n## Overview\n\nThe radar_toolbox module is a collection of tools designed for interfacing with Frequency Modulated Continuous Wave (FMCW) radar systems. It is utilized for various purposes such as data collection, point detection, tracking, and other radar signal processing functions. The module is structured to decouple functionalities into distinct units to promote flexibility and rapid development of new features.\n\n## Module Structure\n\nThe radar_toolbox module is composed of the following elements:\n\n- conf/\n - Various configuration files setting parameters for radar initialization and different processing steps, such as profile_vs1642_exp.cfg which provides specific settings for radar models and data handling.\n- capture_session/\n - This submodule contains scripts for setting up and managing radar data capture sessions, with scripts like main.py for starting, monitoring, and saving raw radar captures.\n- raw_data/\n - A collection of code dealing with raw data handling, including adc.py for interfacing with Analog-to-Digital Converters and scripts to convert raw binary radar data into structured formats for analysis.\n- TI_data/\n - Contains tools and scripts to communicate, configure, and process data from Texas Instruments (TI) mmWave radar boards, including sensor_com.py which outlines communication protocols and data parsing mechanisms.\n- fmcw_utils.py\n - This utility file offers essential classes and functions for the processing and analysis of FMCW radar data, such as radar model enums and functions for loading and converting radar data.\n- utils.py\n - General utility functions and classes that support the operation of the radar_toolbox module, with methods for loading configurations, data parsing, and more.\n\n## Module Files Documentation\n\nDevelopers new to radar_toolbox will find documentation for several key files within the module. An outline of this documentation includes:\n\n- fmcw_utils\n - Detailed information on handling FMCW radar systems, managing configurations, processing radar signals, and transforming them into analyzable forms.\n- utils\n - A comprehensive overview of utility functions that aid in loading configurations, preprocessing radar data, and assisting with model training and coordinate adjustments.\n- capture_session/main\n - Instructions on setting up and conducting recording sessions with scripts that interact with the radar system to initiate and manage data capture.\n- raw_data/adc\n - Documentation of the adc.py script which serves as an interface to ADC hardware, allowing for the capture and real-time processing of radar data streams.\n- raw_data/raw_bin_to_numpy\n - Explains the process of converting raw binary radar data into a NumPy array and the steps involved in ensuring data integrity during conversion.\n- raw_data/record_raw_data\n - A guide to a script focused on raw data recording, detailing the initiation of data capture and subsequent data stream management.\n- TI_data/record_ti_data\n - Documentation for a script specific to TI radar hardware, describing real-time data capture and CSV data storage functionality.\n- TI_data/sensor_com\n - Communication protocols and data structure parsing methods for TI mmWave radar boards are outlined for managing interactions with these devices.\n\n## Usage\n\nDevelopers can use the radar_toolbox module to:\n\n- Set up FMCW radar data capture sessions.\n- Record and process raw radar data.\n- Convert binary radar data captures into formats suitable for analysis, such as NumPy arrays.\n- Interact and configure TI mmWave radars for data acquisition.\n\n## Data Flow Summary\n\nThe data flow within the radar_toolbox module follows these general steps:\n\n1. Configuration is set up using JSON files and configuration profiles for the specific radar models.\n2. Data recording sessions are initiated, capturing the radar data and storing it in binary format.\n3. Raw binary data is processed, filtered, and organized into structured data arrays.\n4. Data is made ready for analysis, transformed into point clouds or other representations necessary for further processing and interpretation.\n\n## External Dependencies\n\nWhile the module works as an independent toolkit within the project scope, it interfaces with radar hardware and other software modules that handle advanced data analysis, visualization, and machine learning applications.\n\n## Overall Significance\n\nThe radar_toolbox module serves as the foundational toolset for FMCW radar systems, streamlining the process from initial data capture to data preparation for analytics. It emphasizes modularity, making it easier to grow and adapt the project with new functionalities."}, {"module": "radar_tracking", "doc": "# FMCW Radar Tracking Project Documentation\n\n## radar_tracking Module\n\nThe radar_tracking module sits at the heart of the FMCW radar project, providing algorithms and utilities focused on the tracking of objects detected by the radar system.\n\n### Module Structure\n\nThe module is composed of several scripts and a configuration file organized as follows:\n\n- tracking_utils.py: Utilities for configuring and initializing tracking components.\n- conf/tracking.json: A JSON-formatted configuration file specifying parameters for the tracking system.\n- inference/:\n - example_kalman_filter.py: Perform inference using Kalman filters.\n - example_tracking.py: An example script demonstrating the tracking process.\n- models/:\n - kalman.py: Implementations of Kalman filter for state estimation.\n - tracking.py: The main tracking algorithm handling the temporal correlation of clusters.\n- clustering/:\n - cluster.py: Data structure for managing clusters of points.\n - cluster_predictor.py: Class for predicting clustering behavior based on certain algorithms.\n - optimizer.py: Optimization utilities for clustering performance.\n- algos/:\n - clustering_algorithm.py: Abstract base algorithms for clustering.\n - dbscan.py: DBSCAN clustering algorithm implementation.\n - gaussian_mixture.py: Gaussian Mixture Model clustering implementation.\n - meanshift.py: Mean Shift clustering algorithm implementation.\n- visuals/display.py: Visualization classes for displaying the tracking data.\n\n### Dependencies\n\nThe radar_tracking module relies on other parts of the FMCW radar project:\n\n- radar_toolbox:\nA toolkit for interacting with the radar hardware and processing raw radar data.\n\n- radar_visuals:\nProvides dynamic and static displays to visualize radar data, which can be helpful to show tracking results in an accessible form.\n\n## Development Notes\n\nDevelopers new to this project will want to familiarize themselves with the radar_tracking module by reviewing existing documentation and code comments.\n\nFor practical understanding, developers are encouraged to interact with example scripts inside the inference subdirectory. They illustrate how the various components come together to achieve object tracking.\n\n## Conclusion\n\nThe radar_tracking module integrates sophisticated algorithms and diverse data sets to track objects with high precision. It exemplifies a well-organized codebase that promotes decoupled architecture, thus expediting the development of innovative functionalities in radar-based tracking systems."}], "gen_doc_of_file": {"path": "radar_fall_detection\\algo.py", "content": "from typing import List\n\nfrom radar_tracking.models.clustering.cluster import Cluster\n\n\nclass FallDetector:\n def __init__(self, minimum_height: float, fall_duration_trigger: float = 1):\n \"\"\"\n The aim of this class is to detect a fall on a given cluster\n :param minimum_height: minimum height of the cluster's center of mass to not consider it as fallen.\n :param fall_duration_trigger: how long a fall needs to be in order to trigger it.\n \"\"\"\n self.minimum_height = minimum_height\n assert fall_duration_trigger > 0, \"fall_duration_trigger must be positive.\"\n self.fall_duration_trigger = fall_duration_trigger\n self.clusters_trigger_t = {}\n\n def update(self, clusters_up_to_date: List[Cluster], dt: float):\n \"\"\"\n To call every step.\n :param clusters_up_to_date: list of tracked clusters.\n :param dt: time elapsed since last update.\n \"\"\"\n # Removing outdated clusters\n to_remove = []\n for cluster in self.clusters_trigger_t:\n if cluster not in clusters_up_to_date:\n to_remove.append(cluster)\n for cluster_to_remove in to_remove:\n del self.clusters_trigger_t[cluster_to_remove]\n # Adding or Updating clusters\n for cluster in clusters_up_to_date:\n fall = cluster.centroid[cluster.height_axis] < self.minimum_height\n if fall:\n if cluster not in self.clusters_trigger_t:\n self.clusters_trigger_t[cluster] = dt\n else:\n self.clusters_trigger_t[cluster] += dt\n else:\n self.clusters_trigger_t[cluster] = 0\n\n\n def detect_fallen_clusters(self):\n \"\"\"\n :return: A dictionary with fallen clusters.\n\n key: \"suspected\"\n values: list of clusters suspected to have fallen\n\n key: \"triggered\"\n values: list of clusters detected as fallen.\n \"\"\"\n fall_dict = {\"suspected\": [], \"confirmed\": []}\n for cluster, t in self.clusters_trigger_t.items():\n if t > 0:\n if t > self.fall_duration_trigger:\n fall_dict[\"confirmed\"].append(cluster)\n else:\n fall_dict[\"suspected\"].append(cluster)\n return fall_dict\n"}}
|
9079ad7125f2b346548cdb0c44ff2c3c
|
{
"intermediate": 0.531252920627594,
"beginner": 0.3211512267589569,
"expert": 0.14759576320648193
}
|
31,174
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 5, 4, 3, 2, 1 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
int currentTexture; // Индекс текущей текстуры на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow("Slot Machine", SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ "res/01spin.png", "res/11spin.png", "res/21spin.png" },
{ "res/02spin.png", "res/12spin.png", "res/22spin.png" },
{ "res/03spin.png", "res/13spin.png", "res/23spin.png" },
{ "res/04spin.png", "res/14spin.png", "res/24spin.png" },
{ "res/05spin.png", "res/15spin.png", "res/25spin.png" } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH;
int totalSpacingWidth = (NUM_DRUMS - 1) * 20;
int totalWidth = totalDrumsWidth + totalSpacingWidth;
int startX = (WINDOW_WIDTH - totalWidth) / 2;
for (int i = 0; i < NUM_DRUMS; i++)
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = WINDOW_HEIGHT / 20;
drum.currentTexture = 0;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
for (int j = 0; j < NUM_TEXTURES; j++) {
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][j].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
drumRect.y += DRUM_HEIGHT; SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
drum.currentTexture++;
if (drum.currentTexture >= NUM_TEXTURES)
{
drum.currentTexture = 0;
}
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} 1) Сделать 3 ряда барабанов по центру экрана. 2) Сделать одинаковую скорость вращения рядов по горизонтали. 3) при остановки барабанов в каждом из рядов по горизонтали, должны быть разные картинки.
|
289035ecd8af6cfe8bbdb2ed20e68de0
|
{
"intermediate": 0.26516255736351013,
"beginner": 0.535163402557373,
"expert": 0.19967399537563324
}
|
31,175
|
Can you draw a basic triangle and present it to the screen in OneAPI, CUDA and ROCm?
|
cde5ee6b0f889364f840f647ef53c419
|
{
"intermediate": 0.6623708605766296,
"beginner": 0.12695525586605072,
"expert": 0.21067392826080322
}
|
31,176
|
этот код можно усовершенствовать чтобы он работал быстрее?
import os
import sys
def dp(content):
content = content.replace(" ", "")
return content
def dp2(content):
content = content.replace("'", "")
return content
def dp3(content):
content = content.replace("+", "")
return content
folder_path = 'numbers'
arg = sys.argv[1]
# files = os.listdir(folder_path)
files = [arg]
folder_path2 = 'base'
files2 = os.listdir(folder_path2)
for file_name in files:
if file_name.endswith(".txt"):
print(file_name)
file_path = os.path.join(folder_path, file_name)
with open(file_path, 'r', encoding="utf-8") as file:
lines = file.read()
lines=str(lines).split('\n')
for line in lines:
part=str(line).split('\t')
part = list(filter(None, part))
if len(part)>1:
for file_name2 in files2:
if file_name2.endswith(".txt"):
file_path2 = os.path.join(folder_path2, file_name2)
with open(file_path2, 'r', encoding="utf-8") as file2:
lines2 = file2.read()
lines2=str(lines2).split('\n')
for line in lines2:
if str(part[0]) in line:
line=line.split(',')
line[0] = part[1]
# print(line)
with open('out/'+file_name2, 'a+', encoding="utf-8") as file:
file.write(dp3(dp2(dp(str(line)[1:-1])))+'\n')
break
|
cfec404c63e25493491b4503a45a763a
|
{
"intermediate": 0.2058292031288147,
"beginner": 0.634349524974823,
"expert": 0.15982124209403992
}
|
31,177
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 5, 4, 3, 2, 1 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
int currentTexture; // Индекс текущей текстуры на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow("Slot Machine", SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ "res/01spin.png", "res/11spin.png", "res/21spin.png" },
{ "res/02spin.png", "res/12spin.png", "res/22spin.png" },
{ "res/03spin.png", "res/13spin.png", "res/23spin.png" },
{ "res/04spin.png", "res/14spin.png", "res/24spin.png" },
{ "res/05spin.png", "res/15spin.png", "res/25spin.png" } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH;
int totalSpacingWidth = (NUM_DRUMS - 1) * 20;
int totalWidth = totalDrumsWidth + totalSpacingWidth;
int startX = (WINDOW_WIDTH - totalWidth) / 2;
for (int i = 0; i < NUM_DRUMS; i++)
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = WINDOW_HEIGHT / 20;
drum.currentTexture = 0;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
for (int j = 0; j < NUM_TEXTURES; j++) {
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][j].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
drumRect.y += DRUM_HEIGHT; SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
drum.currentTexture++;
if (drum.currentTexture >= NUM_TEXTURES)
{
drum.currentTexture = 0;
}
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} Этот код представляет собой простую игру “Слот-машина”. Он использует библиотеку SDL для создания окна, отрисовки графики и обработки событий. В игре есть несколько барабанов, каждый из которых вращается со своей скоростью.
На каждом барабане есть несколько текстур, которые отображаются при вращении барабана.
Когда игрок нажимает пробел, начинается вращение барабанов в течение 4 секунд.
После остановки барабанов отображается их текущая текстура.
Как изменить код так, что-бы отображались сразу все текстуры на барабане. После остановки барабана текстуры менялись местами. Нужен пример кода.
|
c3909b693498a3dbcd3a597b91a97108
|
{
"intermediate": 0.26516255736351013,
"beginner": 0.535163402557373,
"expert": 0.19967399537563324
}
|
31,178
|
Instructions:
The project focuses on the use of FMCW radar.
It is used for data collection, point detection, tracking and other functions.
The project is broken down into several modules.
The aim of this division is to decouple as much as possible the functionalities present in each module, and make the development of new functionalities more flexible and rapid.
Some information will be presented to you in json format:
- module: the name of the module
- module_structure: the structure of the module (the files making up the module and their hierarchy)
- module_files_already_generated_doc: the documentation of the module's files if already generated
- other_modules_doc: the documentation of the other modules on which the module depends (possibly none at all)
- gen_doc_of_file: the file you will be given to generate the documentation of. If no file is given, the documentation of the entire module must be generated.
Your goal is to create a markdown documentation of the file you will be given, or the entire module if no file is given.
This documentation is intended to guide a developer who is new to the project, you can therefore add whatever you feel is relevant for this task.
Informations:
{"module": "radar_fall_detection", "module_structure": "radar_fall_detection/algo.py;radar_fall_detection/display.py;radar_fall_detection/live_fall_detection.py;radar_fall_detection\\conf/fall_conf.json;radar_fall_detection\\conf/live_fall_detection.json;radar_fall_detection\\conf/ti_conf.json;radar_fall_detection\\conf/tracking.json;", "module_files_already_generated_doc": [], "other_modules_doc": [{"module": "radar_visuals", "doc": "# radar_visuals Module Documentation\n\n## Overview\n\nThe radar_visuals module is a dedicated visualization package within a project focused on the use of Frequency Modulated Continuous Wave (FMCW) radar. It is designed to provide tools and utilities for the rendering of radar data in various visual formats, supporting functionalities like data collection, point detection, and tracking analysis. The module aims to facilitate rapid development and integration of new visualization features through a decoupled and flexible structure.\n\n## Module Structure\n\nThe radar_visuals module currently contains the following file:\n\n- display.py: A Python script offering a suite of classes and functions for creating dynamic and static displays for radar data visualization.\n\n## Module Files Documentation\n\n### display.py\n\nThe display.py file within the radar_visuals package encompasses multiple visualization methods and is central to the module. Below is a summary of the provided documentation:\n\n#### Overview\nThe script is essential for visualizing radar data and includes capabilities for 2D, 3D, and polar plotting. It is versatile enough to accommodate both real-time and static data presentations.\n\n#### Components\nEnums such as PlayingMode, Projection, and GraphType allow the user to define the display behavior, the plot\u00e2\u20ac\u2122s projection type, and the graph style, respectively. Along with utility functions like color_from_id and plot_signal, the script provides two main classes:\n\n- UpdatableDisplay: The abstract base class for displays that can be updated, initializing the figure, axes, and other graphical elements.\n- SimpleUpdatableDisplay: A concrete implementation of UpdatableDisplay that prepares and updates displays with new data points.\n\n#### Functionalities\nThe primary functionalities include creating interactive graphs to visualize radar data, updating them according to predefined playing modes, and ensuring compatibility with different data types and visual projections.\n\n#### Data Flow\nThe typical workflow involves:\n1. Initializing a display object with the required properties.\n2. Accumulating or simulating radar data points.\n3. Updating the display as new data arrives through the show() method.\n4. Presenting the visual representation of the radar data to users based on the set playing mode.\n\n#### Developer Notes\nDevelopers are advised to match data dimensions with graph types and projections, manage update rates effectively, and assign unique colors to data sources using UUIDs for better data distinction.\n\n#### Integration\nDespite being part of the radar_visuals package, display.py operates independently from other components, specifically focusing on visualization purposes and not on signal processing.\n\n## Usage\n\nThe module can be employed to:\n\n- Visualize FMCW radar-related data points, signals, and more complex datasets.\n- Develop new visualization tools tailored to the specifics of radar data.\n- Enhance the interpretation of radar data through graphically rich plots.\n\n## Conclusion\n\nradar_visuals is a crucial module for the graphical representation and analysis of radar data within a larger FMCW radar-focused project. The modular structure accommodates efficient development, enabling users and developers to easily integrate new visualization techniques suited to their specific needs. The module\u00e2\u20ac\u2122s design streamlines the translation of complex data into understandable and insightful visual formats, supporting a wide range of functionalities from debugging to presentation."}, {"module": "radar_toolbox", "doc": "# radar_toolbox Module Documentation\n\n## Overview\n\nThe radar_toolbox module is a collection of tools designed for interfacing with Frequency Modulated Continuous Wave (FMCW) radar systems. It is utilized for various purposes such as data collection, point detection, tracking, and other radar signal processing functions. The module is structured to decouple functionalities into distinct units to promote flexibility and rapid development of new features.\n\n## Module Structure\n\nThe radar_toolbox module is composed of the following elements:\n\n- conf/\n - Various configuration files setting parameters for radar initialization and different processing steps, such as profile_vs1642_exp.cfg which provides specific settings for radar models and data handling.\n- capture_session/\n - This submodule contains scripts for setting up and managing radar data capture sessions, with scripts like main.py for starting, monitoring, and saving raw radar captures.\n- raw_data/\n - A collection of code dealing with raw data handling, including adc.py for interfacing with Analog-to-Digital Converters and scripts to convert raw binary radar data into structured formats for analysis.\n- TI_data/\n - Contains tools and scripts to communicate, configure, and process data from Texas Instruments (TI) mmWave radar boards, including sensor_com.py which outlines communication protocols and data parsing mechanisms.\n- fmcw_utils.py\n - This utility file offers essential classes and functions for the processing and analysis of FMCW radar data, such as radar model enums and functions for loading and converting radar data.\n- utils.py\n - General utility functions and classes that support the operation of the radar_toolbox module, with methods for loading configurations, data parsing, and more.\n\n## Module Files Documentation\n\nDevelopers new to radar_toolbox will find documentation for several key files within the module. An outline of this documentation includes:\n\n- fmcw_utils\n - Detailed information on handling FMCW radar systems, managing configurations, processing radar signals, and transforming them into analyzable forms.\n- utils\n - A comprehensive overview of utility functions that aid in loading configurations, preprocessing radar data, and assisting with model training and coordinate adjustments.\n- capture_session/main\n - Instructions on setting up and conducting recording sessions with scripts that interact with the radar system to initiate and manage data capture.\n- raw_data/adc\n - Documentation of the adc.py script which serves as an interface to ADC hardware, allowing for the capture and real-time processing of radar data streams.\n- raw_data/raw_bin_to_numpy\n - Explains the process of converting raw binary radar data into a NumPy array and the steps involved in ensuring data integrity during conversion.\n- raw_data/record_raw_data\n - A guide to a script focused on raw data recording, detailing the initiation of data capture and subsequent data stream management.\n- TI_data/record_ti_data\n - Documentation for a script specific to TI radar hardware, describing real-time data capture and CSV data storage functionality.\n- TI_data/sensor_com\n - Communication protocols and data structure parsing methods for TI mmWave radar boards are outlined for managing interactions with these devices.\n\n## Usage\n\nDevelopers can use the radar_toolbox module to:\n\n- Set up FMCW radar data capture sessions.\n- Record and process raw radar data.\n- Convert binary radar data captures into formats suitable for analysis, such as NumPy arrays.\n- Interact and configure TI mmWave radars for data acquisition.\n\n## Data Flow Summary\n\nThe data flow within the radar_toolbox module follows these general steps:\n\n1. Configuration is set up using JSON files and configuration profiles for the specific radar models.\n2. Data recording sessions are initiated, capturing the radar data and storing it in binary format.\n3. Raw binary data is processed, filtered, and organized into structured data arrays.\n4. Data is made ready for analysis, transformed into point clouds or other representations necessary for further processing and interpretation.\n\n## External Dependencies\n\nWhile the module works as an independent toolkit within the project scope, it interfaces with radar hardware and other software modules that handle advanced data analysis, visualization, and machine learning applications.\n\n## Overall Significance\n\nThe radar_toolbox module serves as the foundational toolset for FMCW radar systems, streamlining the process from initial data capture to data preparation for analytics. It emphasizes modularity, making it easier to grow and adapt the project with new functionalities."}, {"module": "radar_tracking", "doc": "# FMCW Radar Tracking Project Documentation\n\n## radar_tracking Module\n\nThe radar_tracking module sits at the heart of the FMCW radar project, providing algorithms and utilities focused on the tracking of objects detected by the radar system.\n\n### Module Structure\n\nThe module is composed of several scripts and a configuration file organized as follows:\n\n- tracking_utils.py: Utilities for configuring and initializing tracking components.\n- conf/tracking.json: A JSON-formatted configuration file specifying parameters for the tracking system.\n- inference/:\n - example_kalman_filter.py: Perform inference using Kalman filters.\n - example_tracking.py: An example script demonstrating the tracking process.\n- models/:\n - kalman.py: Implementations of Kalman filter for state estimation.\n - tracking.py: The main tracking algorithm handling the temporal correlation of clusters.\n- clustering/:\n - cluster.py: Data structure for managing clusters of points.\n - cluster_predictor.py: Class for predicting clustering behavior based on certain algorithms.\n - optimizer.py: Optimization utilities for clustering performance.\n- algos/:\n - clustering_algorithm.py: Abstract base algorithms for clustering.\n - dbscan.py: DBSCAN clustering algorithm implementation.\n - gaussian_mixture.py: Gaussian Mixture Model clustering implementation.\n - meanshift.py: Mean Shift clustering algorithm implementation.\n- visuals/display.py: Visualization classes for displaying the tracking data.\n\n### Dependencies\n\nThe radar_tracking module relies on other parts of the FMCW radar project:\n\n- radar_toolbox:\nA toolkit for interacting with the radar hardware and processing raw radar data.\n\n- radar_visuals:\nProvides dynamic and static displays to visualize radar data, which can be helpful to show tracking results in an accessible form.\n\n## Development Notes\n\nDevelopers new to this project will want to familiarize themselves with the radar_tracking module by reviewing existing documentation and code comments.\n\nFor practical understanding, developers are encouraged to interact with example scripts inside the inference subdirectory. They illustrate how the various components come together to achieve object tracking.\n\n## Conclusion\n\nThe radar_tracking module integrates sophisticated algorithms and diverse data sets to track objects with high precision. It exemplifies a well-organized codebase that promotes decoupled architecture, thus expediting the development of innovative functionalities in radar-based tracking systems."}], "gen_doc_of_file": {"path": "radar_fall_detection\\algo.py", "content": "from typing import List\n\nfrom radar_tracking.models.clustering.cluster import Cluster\n\n\nclass FallDetector:\n def __init__(self, minimum_height: float, fall_duration_trigger: float = 1):\n \"\"\"\n The aim of this class is to detect a fall on a given cluster\n :param minimum_height: minimum height of the cluster's center of mass to not consider it as fallen.\n :param fall_duration_trigger: how long a fall needs to be in order to trigger it.\n \"\"\"\n self.minimum_height = minimum_height\n assert fall_duration_trigger > 0, \"fall_duration_trigger must be positive.\"\n self.fall_duration_trigger = fall_duration_trigger\n self.clusters_trigger_t = {}\n\n def update(self, clusters_up_to_date: List[Cluster], dt: float):\n \"\"\"\n To call every step.\n :param clusters_up_to_date: list of tracked clusters.\n :param dt: time elapsed since last update.\n \"\"\"\n # Removing outdated clusters\n to_remove = []\n for cluster in self.clusters_trigger_t:\n if cluster not in clusters_up_to_date:\n to_remove.append(cluster)\n for cluster_to_remove in to_remove:\n del self.clusters_trigger_t[cluster_to_remove]\n # Adding or Updating clusters\n for cluster in clusters_up_to_date:\n fall = cluster.centroid[cluster.height_axis] < self.minimum_height\n if fall:\n if cluster not in self.clusters_trigger_t:\n self.clusters_trigger_t[cluster] = dt\n else:\n self.clusters_trigger_t[cluster] += dt\n else:\n self.clusters_trigger_t[cluster] = 0\n\n\n def detect_fallen_clusters(self):\n \"\"\"\n :return: A dictionary with fallen clusters.\n\n key: \"suspected\"\n values: list of clusters suspected to have fallen\n\n key: \"triggered\"\n values: list of clusters detected as fallen.\n \"\"\"\n fall_dict = {\"suspected\": [], \"confirmed\": []}\n for cluster, t in self.clusters_trigger_t.items():\n if t > 0:\n if t > self.fall_duration_trigger:\n fall_dict[\"confirmed\"].append(cluster)\n else:\n fall_dict[\"suspected\"].append(cluster)\n return fall_dict\n"}}
|
caf935eda525b7c1603c0f9bd6c9d319
|
{
"intermediate": 0.531252920627594,
"beginner": 0.3211512267589569,
"expert": 0.14759576320648193
}
|
31,179
|
Instructions:
The project focuses on the use of FMCW radar.
It is used for data collection, point detection, tracking and other functions.
The project is broken down into several modules.
The aim of this division is to decouple as much as possible the functionalities present in each module, and make the development of new functionalities more flexible and rapid.
Some information will be presented to you in json format:
- module: the name of the module
- module_structure: the structure of the module (the files making up the module and their hierarchy)
- module_files_already_generated_doc: the documentation of the module's files if already generated
- other_modules_doc: the documentation of the other modules on which the module depends (possibly none at all)
- gen_doc_of_file: the file you will be given to generate the documentation of. If no file is given, the documentation of the entire module must be generated.
Your goal is to create a markdown documentation of the file you will be given, or the entire module if no file is given.
This documentation is intended to guide a developer who is new to the project, you can therefore add whatever you feel is relevant for this task.
Informations:
{"module": "radar_fall_detection", "module_structure": "radar_fall_detection/algo.py;radar_fall_detection/display.py;radar_fall_detection/live_fall_detection.py;radar_fall_detection\\conf/fall_conf.json;radar_fall_detection\\conf/live_fall_detection.json;radar_fall_detection\\conf/ti_conf.json;radar_fall_detection\\conf/tracking.json;", "module_files_already_generated_doc": [{"file": "radar_fall_detection\\algo.md", "doc": "# radar_fall_detection.algo Documentation\n\n## Overview\n\nThe FallDetector class within the algo.py file of the radar_fall_detection module is designed to identify fall events based on radar data processed into clusters. It receives data from the radar_tracking module which processes the radar signals to track objects in the vicinity of the FMCW radar system. This class aims to evaluate tracked clusters and determine if a fall has occurred according to predefined criteria.\n\nThe functionality of this class plays a vital role in systems that require fall detection, such as safety monitoring systems for the elderly or in industrial environments.\n\n## Dependencies\n\nThis class is dependent on the Cluster class from the radar_tracking.models.clustering.cluster module, which provides data structures representing clusters of points detected and tracked by the radar system.\n\n## Module Structure\n\nThe algo.py file contains the following class:\n\n- FallDetector: A class responsible for detecting falls based on cluster data.\n\n## Class Description\n\n### FallDetector\n\n#### Initialization Parameters:\n- minimum_height: A float specifying the minimum height of the cluster\u00e2\u20ac\u2122s center of mass to not consider it as fallen.\n- fall_duration_trigger: A float defaulting to 1, representing how long (seconds) a fall needs to be in order to be confirmed as a fall.\n\n#### Methods:\n\n- __init__(self, minimum_height: float, fall_duration_trigger: float = 1):\nInitializes the FallDetector object with its parameters.\n\n- update(self, clusters_up_to_date: List[Cluster], dt: float):\nUpdates the fall detection mechanism with the latest set of clusters and the time elapsed since the last update. This function should be called at each step of the tracking/update loop.\n\n- detect_fallen_clusters(self):\nEvaluates the clusters to detect which ones have fallen. Returns a dictionary with keys \"suspected\" and \"confirmed\", corresponding to clusters that are suspected to have fallen and those that are confirmed to have fallen, respectively.\n\n#### Attributes:\n\n- minimum_height: Holds the minimum cluster height to be considered upright.\n- fall_duration_trigger: Specifies the time threshold for confirming a fall.\n- clusters_trigger_t: A dictionary that stores clusters with their associated time since they have been detected below the minimum_height.\n\n#### Detailed Behavior:\n\n1. update method: It maintains an internal dictionary of clusters being watched for falls, referenced against the clusters_up_to_date provided. Clusters that are no longer up-to-date are removed, and the remaining ones have their internal timer updated.\n\n2. detect_fallen_clusters method: This method checks each tracked cluster\u00e2\u20ac\u2122s timer against the fall_duration_trigger to determine if the cluster has been in a fallen state long enough to confirm the fall.\n\n## Data Flow Summary\n\n1. The FallDetector is initialized with specified parameters for minimum height and duration required to trigger a fall.\n\n2. During real-time operation, the update method is called with a list of updated clusters (clusters_up_to_date) and the time elapsed since the previous call (dt), allowing the FallDetector to update its internal state.\n\n3. After updating, the detect_fallen_clusters method can be used to obtain a current analysis of which clusters are suspected or confirmed to have fallen.\n\n4. This information may then be utilized by external systems for alert generation, logging, or further analysis.\n\n## Integration with Other Modules\n\n- Interacts with radar_tracking for cluster data.\n- May utilize radar_visuals for visualizing detected falls if needed.\n\n## Example Usage\n\nTo utilize the FallDetector class, one would first instantiate it with the desired parameters:\n\n
|
f15b8b9e9ddb39c92e2510a45564582a
|
{
"intermediate": 0.280784010887146,
"beginner": 0.49608689546585083,
"expert": 0.2231290638446808
}
|
31,180
|
schematic figure of a neural network that has two layers: an input layer with 128 neurons and an output layer with 1 neuron
|
ff4aca2dc468a961535f7846ce87d513
|
{
"intermediate": 0.15813696384429932,
"beginner": 0.127715066075325,
"expert": 0.7141479849815369
}
|
31,181
|
For a STM32C030 microcontroller, write a tinygo program to flash a led at 1 Hz.
|
bd903ecca9daac31b6f5ddecd1d6f976
|
{
"intermediate": 0.3441179394721985,
"beginner": 0.2713339924812317,
"expert": 0.38454803824424744
}
|
31,182
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
#include <algorithm>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 5, 4, 3, 2, 1 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
std::vector<int> textureOrder; // Порядок текстур на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow("Slot Machine", SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ "res/01spin.png", "res/11spin.png", "res/21spin.png" },
{ "res/02spin.png", "res/12spin.png", "res/22spin.png" },
{ "res/03spin.png", "res/13spin.png", "res/23spin.png" },
{ "res/04spin.png", "res/14spin.png", "res/24spin.png" },
{ "res/05spin.png", "res/15spin.png", "res/25spin.png" } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH;
int totalSpacingWidth = (NUM_DRUMS - 1) * 20;
int totalWidth = totalDrumsWidth + totalSpacingWidth;
int startX = (WINDOW_WIDTH - totalWidth) / 2;
for (int i = 0; i < NUM_DRUMS; i++)
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = WINDOW_HEIGHT / 20;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
// Инициализация порядка текстур на барабане
drum.textureOrder.resize(NUM_TEXTURES);
std::iota(drum.textureOrder.begin(), drum.textureOrder.end(), 0);
std::random_device rd;
std::mt19937 gen(rd());
std::shuffle(drum.textureOrder.begin(), drum.textureOrder.end(), gen);
// Загрузка текстур для барабана
for (int j = 0; j < NUM_TEXTURES; j++) {
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][drum.textureOrder[j]].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
drumRect.y += DRUM_HEIGHT;
for (int j = 0; j < NUM_TEXTURES; j++) {
SDL_RenderCopy(renderer, drums[i].textures[j], nullptr, &drumRect);
drumRect.y += DRUM_HEIGHT;
}
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
// Изменение порядка текстур на барабане
std::rotate(drum.textureOrder.rbegin(), drum.textureOrder.rbegin() + 1, drum.textureOrder.rend());
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} Картинки не меняются местами, при нажатии на пробел исправь.
|
9a498ef8d665a9e96b6c553806984895
|
{
"intermediate": 0.33054298162460327,
"beginner": 0.4386005103588104,
"expert": 0.23085658252239227
}
|
31,183
|
In bash, I need writing a script to generate a texture of random numbers; the first 2 octets are the width, the 3rd and 4th octets are the height, and the rest are an array of octets which is divisible by 3 representing color. Utilize /dev/random or /dev/urandom since they're faster than $RANDOM.
|
3638943920e077dde4268df89be7898b
|
{
"intermediate": 0.4433314800262451,
"beginner": 0.19178828597068787,
"expert": 0.3648802936077118
}
|
31,184
|
In bash, I need a script to generate a texture of random numbers; the first 2 octets are the width, the 3rd and 4th octets are the height, and the rest are an array of octets which is divisible by 3 representing color. Utilize /dev/random or /dev/urandom since they’re faster than $RANDOM.
|
18900715dd2dfc20097925b3fa7cf36d
|
{
"intermediate": 0.46501055359840393,
"beginner": 0.18396054208278656,
"expert": 0.3510288894176483
}
|
31,185
|
Please use R to solve the following problem. “DHSI.csv” from the data folder on canvas. The file contains daily data of Hang Seng Index from 1987-01-02 to 2023-09-29. Extract the daily close price of DHSI and name the series as “HSI”. Compute log returns of“HSI” and name the series as “DHSILR”.Draw histograms of DHSILR with bin sizes = 20, 100, 500 and 5000.
|
ebdb8b874643aca7537fff8de752cf2e
|
{
"intermediate": 0.534598171710968,
"beginner": 0.14911812543869019,
"expert": 0.3162837028503418
}
|
31,186
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
#include <algorithm>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 5, 4, 3, 2, 1 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
std::vector<int> textureOrder; // Порядок текстур на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow(“Slot Machine”, SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ “res/01spin.png”, “res/11spin.png”, “res/21spin.png” },
{ “res/02spin.png”, “res/12spin.png”, “res/22spin.png” },
{ “res/03spin.png”, “res/13spin.png”, “res/23spin.png” },
{ “res/04spin.png”, “res/14spin.png”, “res/24spin.png” },
{ “res/05spin.png”, “res/15spin.png”, “res/25spin.png” } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH;
int totalSpacingWidth = (NUM_DRUMS - 1) * 20;
int totalWidth = totalDrumsWidth + totalSpacingWidth;
int startX = (WINDOW_WIDTH - totalWidth) / 2;
for (int i = 0; i < NUM_DRUMS; i++)
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = WINDOW_HEIGHT / 20;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
// Инициализация порядка текстур на барабане
drum.textureOrder.resize(NUM_TEXTURES);
std::iota(drum.textureOrder.begin(), drum.textureOrder.end(), 0);
std::random_device rd;
std::mt19937 gen(rd());
std::shuffle(drum.textureOrder.begin(), drum.textureOrder.end(), gen);
// Загрузка текстур для барабана
for (int j = 0; j < NUM_TEXTURES; j++) {
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][drum.textureOrder[j]].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
drumRect.y += DRUM_HEIGHT;
for (int j = 0; j < NUM_TEXTURES; j++) {
SDL_RenderCopy(renderer, drums[i].textures[j], nullptr, &drumRect);
drumRect.y += DRUM_HEIGHT;
}
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
// Изменение порядка текстур на барабане
std::rotate(drum.textureOrder.rbegin(), drum.textureOrder.rbegin() + 1, drum.textureOrder.rend());
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} Картинки не меняются местами, при нажатии на пробел исправь.
|
96c8e5d1f7df2641cb614b3dcaea22fa
|
{
"intermediate": 0.27545231580734253,
"beginner": 0.5272324681282043,
"expert": 0.1973152458667755
}
|
31,187
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 5, 4, 3, 2, 1 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
int currentTexture; // Индекс текущей текстуры на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow("Slot Machine", SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ "res/01spin.png", "res/11spin.png", "res/21spin.png" },
{ "res/02spin.png", "res/12spin.png", "res/22spin.png" },
{ "res/03spin.png", "res/13spin.png", "res/23spin.png" },
{ "res/04spin.png", "res/14spin.png", "res/24spin.png" },
{ "res/05spin.png", "res/15spin.png", "res/25spin.png" } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH;
int totalSpacingWidth = (NUM_DRUMS - 1) * 20;
int totalWidth = totalDrumsWidth + totalSpacingWidth;
int startX = (WINDOW_WIDTH - totalWidth) / 2;
for (int i = 0; i < NUM_DRUMS; i++)
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = WINDOW_HEIGHT / 20;
drum.currentTexture = 0;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
for (int j = 0; j < NUM_TEXTURES; j++) {
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][j].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
drumRect.y += DRUM_HEIGHT; SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
drum.currentTexture++;
if (drum.currentTexture >= NUM_TEXTURES)
{
drum.currentTexture = 0;
}
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} Как сделать три ряда барабанов по центру экрана
|
788e3b864bec9beb9b71161e60406e41
|
{
"intermediate": 0.26516255736351013,
"beginner": 0.535163402557373,
"expert": 0.19967399537563324
}
|
31,188
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 5, 4, 3, 2, 1 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
int currentTexture; // Индекс текущей текстуры на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow("Slot Machine", SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ "res/01spin.png", "res/11spin.png", "res/21spin.png" },
{ "res/02spin.png", "res/12spin.png", "res/22spin.png" },
{ "res/03spin.png", "res/13spin.png", "res/23spin.png" },
{ "res/04spin.png", "res/14spin.png", "res/24spin.png" },
{ "res/05spin.png", "res/15spin.png", "res/25spin.png" } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH; // Ширина всех барабанов
int totalSpacingWidth = (NUM_DRUMS - 1) * 20; // Ширина промежутков между барабанами
int totalWidth = totalDrumsWidth + totalSpacingWidth; // Общая ширина всех барабанов и промежутков
int startX = (WINDOW_WIDTH - totalWidth) / 2; // Начальная позиция по X для первого барабана
int startY = (WINDOW_HEIGHT - (DRUM_HEIGHT * 3)) / 2; // Начальная позиция по Y для первого ряда
for (int r = 0; r < 3; r++) // Цикл для формирования трех рядов барабанов
{
for (int i = 0; i < NUM_DRUMS; i++) // Цикл для формирования барабанов в ряду
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = startY + r * (DRUM_HEIGHT + 20);
drum.currentTexture = 0;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
for (int j = 0; j < NUM_TEXTURES; j++)
{
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][j].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
drum.currentTexture++;
if (drum.currentTexture >= NUM_TEXTURES)
{
drum.currentTexture = 0;
}
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} Как сделать что бы при остановки барабанов индекс картинки был разный в первом ряду барабанов у всех картинок свой индекс, у второго ряда барабанов свой и у третьего свой индекс картинок
|
ee72fe544117adfc6aa0e2776c807fec
|
{
"intermediate": 0.26516255736351013,
"beginner": 0.535163402557373,
"expert": 0.19967399537563324
}
|
31,189
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 5, 4, 3, 2, 1 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
int currentTexture; // Индекс текущей текстуры на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow(“Slot Machine”, SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ “res/01spin.png”, “res/11spin.png”, “res/21spin.png” },
{ “res/02spin.png”, “res/12spin.png”, “res/22spin.png” },
{ “res/03spin.png”, “res/13spin.png”, “res/23spin.png” },
{ “res/04spin.png”, “res/14spin.png”, “res/24spin.png” },
{ “res/05spin.png”, “res/15spin.png”, “res/25spin.png” } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH; // Ширина всех барабанов
int totalSpacingWidth = (NUM_DRUMS - 1) * 20; // Ширина промежутков между барабанами
int totalWidth = totalDrumsWidth + totalSpacingWidth; // Общая ширина всех барабанов и промежутков
int startX = (WINDOW_WIDTH - totalWidth) / 2; // Начальная позиция по X для первого барабана
int startY = (WINDOW_HEIGHT - (DRUM_HEIGHT * 3)) / 2; // Начальная позиция по Y для первого ряда
for (int r = 0; r < 3; r++) // Цикл для формирования трех рядов барабанов
{
for (int i = 0; i < NUM_DRUMS; i++) // Цикл для формирования барабанов в ряду
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = startY + r * (DRUM_HEIGHT + 20);
drum.currentTexture = 0;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
for (int j = 0; j < NUM_TEXTURES; j++)
{
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][j].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
drum.currentTexture++;
if (drum.currentTexture >= NUM_TEXTURES)
{
drum.currentTexture = 0;
}
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} Как сделать что бы при остановки барабанов индекс картинки был разный в первом ряду барабанов у всех картинок свой индекс, у второго ряда барабанов свой и у третьего свой индекс картинок
|
b3abab3184c7905c1a79c6710928ee75
|
{
"intermediate": 0.2885934114456177,
"beginner": 0.5267934203147888,
"expert": 0.18461327254772186
}
|
31,190
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 5, 4, 3, 2, 1 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
int currentTexture; // Индекс текущей текстуры на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow(“Slot Machine”, SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ “res/01spin.png”, “res/11spin.png”, “res/21spin.png” },
{ “res/02spin.png”, “res/12spin.png”, “res/22spin.png” },
{ “res/03spin.png”, “res/13spin.png”, “res/23spin.png” },
{ “res/04spin.png”, “res/14spin.png”, “res/24spin.png” },
{ “res/05spin.png”, “res/15spin.png”, “res/25spin.png” } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH; // Ширина всех барабанов
int totalSpacingWidth = (NUM_DRUMS - 1) * 20; // Ширина промежутков между барабанами
int totalWidth = totalDrumsWidth + totalSpacingWidth; // Общая ширина всех барабанов и промежутков
int startX = (WINDOW_WIDTH - totalWidth) / 2; // Начальная позиция по X для первого барабана
int startY = (WINDOW_HEIGHT - (DRUM_HEIGHT * 3)) / 2; // Начальная позиция по Y для первого ряда
for (int r = 0; r < 3; r++) // Цикл для формирования трех рядов барабанов
{
for (int i = 0; i < NUM_DRUMS; i++) // Цикл для формирования барабанов в ряду
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = startY + r * (DRUM_HEIGHT + 20);
drum.currentTexture = 0;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
for (int j = 0; j < NUM_TEXTURES; j++)
{
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][j].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
drum.currentTexture++;
if (drum.currentTexture >= NUM_TEXTURES)
{
drum.currentTexture = 0;
}
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} Три ряда барабанов в каждом ряду и каждом барабане, индекс картинки не должен совпадать с нижним барабаном
|
b4658e02ba5768181c84cccab145cf31
|
{
"intermediate": 0.2885934114456177,
"beginner": 0.5267934203147888,
"expert": 0.18461327254772186
}
|
31,191
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 1, 4, 3, 2, 100 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
int currentTexture; // Индекс текущей текстуры на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow("Slot Machine", SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ "res/01spin.png", "res/11spin.png", "res/21spin.png" },
{ "res/02spin.png", "res/12spin.png", "res/22spin.png" },
{ "res/03spin.png", "res/13spin.png", "res/23spin.png" },
{ "res/04spin.png", "res/14spin.png", "res/24spin.png" },
{ "res/05spin.png", "res/15spin.png", "res/25spin.png" } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH; // Ширина всех барабанов
int totalSpacingWidth = (NUM_DRUMS - 1) * 20; // Ширина промежутков между барабанами
int totalWidth = totalDrumsWidth + totalSpacingWidth; // Общая ширина всех барабанов и промежутков
int startX = (WINDOW_WIDTH - totalWidth) / 2; // Начальная позиция по X для первого барабана
int startY = (WINDOW_HEIGHT - (DRUM_HEIGHT * 3)) / 2; // Начальная позиция по Y для первого ряда
for (int r = 0; r < 3; r++) // Цикл для формирования трех рядов барабанов
{
for (int i = 0; i < NUM_DRUMS; i++) // Цикл для формирования барабанов в ряду
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = startY + r * (DRUM_HEIGHT + 20);
drum.currentTexture = 0;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
for (int j = 0; j < NUM_TEXTURES; j++)
{
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][j].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
/*for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
}*/
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
// Проверка индекса текущей текстуры
if (drums[i].currentTexture == 0)
{
// … Изменение индекса текущей текстуры для других рядов и барабанов
if (i + NUM_DRUMS < drums.size())
{
drums[i + NUM_DRUMS].currentTexture = 1;
}
if (i + (NUM_DRUMS * 2) < drums.size())
{
drums[i + (NUM_DRUMS * 2)].currentTexture = 2;
}
}
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
drum.currentTexture++;
if (drum.currentTexture >= NUM_TEXTURES)
{
drum.currentTexture = 0;
}
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} Убрать промежутки между барабанами по горизонтали.
|
64e3c616015b187d7d2c5cad59eb7842
|
{
"intermediate": 0.26423731446266174,
"beginner": 0.5363492965698242,
"expert": 0.19941338896751404
}
|
31,192
|
#include <SDL.h>
#include <SDL_image.h>
#include <iostream>
#include <vector>
#include <random>
// Размеры окна
const int WINDOW_WIDTH = 800;
const int WINDOW_HEIGHT = 600;
// Размеры барабанов
const int DRUM_WIDTH = 100;
const int DRUM_HEIGHT = 100;
// Общее количество барабанов
const int NUM_DRUMS = 5;
// Количество текстур на каждом барабане
const int NUM_TEXTURES = 3;
// Скорость вращения барабанов
std::vector<int> drumSpeeds = { 1, 4, 3, 2, 100 };
// Структура для хранения информации о барабане
struct Drum
{
int x; // Позиция по X
int y; // Позиция по Y
int currentTexture; // Индекс текущей текстуры на барабане
int rotation; // Угол поворота барабана
int speed; // Скорость вращения барабана
std::vector<SDL_Texture*> textures; // Вектор текстур для барабана
};
// Инициализация SDL и создание окна
bool init(SDL_Window*& window, SDL_Renderer*& renderer)
{
if (SDL_Init(SDL_INIT_VIDEO) < 0)
{
std::cerr << "Failed to initialize SDL: " << SDL_GetError() << std::endl;
return false;
}
if (!IMG_Init(IMG_INIT_PNG) & IMG_INIT_PNG)
{
std::cerr << "Failed to initialize SDL_image: " << IMG_GetError() << std::endl;
return false;
}
window = SDL_CreateWindow(“Slot Machine”, SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED, WINDOW_WIDTH, WINDOW_HEIGHT, SDL_WINDOW_SHOWN);
if (!window)
{
std::cerr << "Failed to create window: " << SDL_GetError() << std::endl;
return false;
}
renderer = SDL_CreateRenderer(window, -1, SDL_RENDERER_ACCELERATED);
if (!renderer)
{
std::cerr << "Failed to create renderer: " << SDL_GetError() << std::endl;
return false;
}
return true;
}
// Загрузка текстуры из файла
SDL_Texture* loadTexture(const std::string& filePath, SDL_Renderer* renderer)
{
SDL_Surface* surface = IMG_Load(filePath.c_str());
if (!surface)
{
std::cerr << "Failed to load image: " << filePath << ", " << IMG_GetError() << std::endl;
return nullptr;
}
SDL_Texture* texture = SDL_CreateTextureFromSurface(renderer, surface);
if (!texture)
{
std::cerr << "Failed to create texture: " << SDL_GetError() << std::endl;
return nullptr;
}
SDL_FreeSurface(surface);
return texture;
}
// Освобождение ресурсов
void cleanup(SDL_Window* window, SDL_Renderer* renderer, std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
for (size_t i = 0; i < drum.textures.size(); i++)
{
SDL_DestroyTexture(drum.textures[i]);
}
}
SDL_DestroyRenderer(renderer);
SDL_DestroyWindow(window);
IMG_Quit();
SDL_Quit();
}
// Инициализация барабанов
void initDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
std::vector<std::vector<std::string>> texturePaths = {
{ “res/01spin.png”, “res/11spin.png”, “res/21spin.png” },
{ “res/02spin.png”, “res/12spin.png”, “res/22spin.png” },
{ “res/03spin.png”, “res/13spin.png”, “res/23spin.png” },
{ “res/04spin.png”, “res/14spin.png”, “res/24spin.png” },
{ “res/05spin.png”, “res/15spin.png”, “res/25spin.png” } };
int totalDrumsWidth = NUM_DRUMS * DRUM_WIDTH; // Ширина всех барабанов
int totalSpacingWidth = (NUM_DRUMS - 1) * 20; // Ширина промежутков между барабанами
int totalWidth = totalDrumsWidth + totalSpacingWidth; // Общая ширина всех барабанов и промежутков
int startX = (WINDOW_WIDTH - totalWidth) / 2; // Начальная позиция по X для первого барабана
int startY = (WINDOW_HEIGHT - (DRUM_HEIGHT * 3)) / 2; // Начальная позиция по Y для первого ряда
for (int r = 0; r < 3; r++) // Цикл для формирования трех рядов барабанов
{
for (int i = 0; i < NUM_DRUMS; i++) // Цикл для формирования барабанов в ряду
{
Drum drum;
drum.x = startX + i * (DRUM_WIDTH + 20);
drum.y = startY + r * (DRUM_HEIGHT + 20);
drum.currentTexture = 0;
drum.rotation = 0;
drum.speed = drumSpeeds[i] * 10;
for (int j = 0; j < NUM_TEXTURES; j++)
{
SDL_Texture* tmp = IMG_LoadTexture(renderer, texturePaths[i][j].c_str());
drum.textures.push_back(tmp);
}
drums.push_back(drum);
}
}
}
// Отрисовка барабанов
void renderDrums(SDL_Renderer* renderer, std::vector<Drum>& drums)
{
/for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
}/
for (size_t i = 0; i < drums.size(); i++)
{
SDL_Rect drumRect = { drums[i].x, drums[i].y, DRUM_WIDTH, DRUM_HEIGHT };
SDL_RenderCopy(renderer, drums[i].textures[drums[i].currentTexture], nullptr, &drumRect);
// Проверка индекса текущей текстуры
if (drums[i].currentTexture == 0)
{
// … Изменение индекса текущей текстуры для других рядов и барабанов
if (i + NUM_DRUMS < drums.size())
{
drums[i + NUM_DRUMS].currentTexture = 1;
}
if (i + (NUM_DRUMS * 2) < drums.size())
{
drums[i + (NUM_DRUMS * 2)].currentTexture = 2;
}
}
}
}
// Обновление барабанов
void updateDrums(std::vector<Drum>& drums)
{
for (Drum& drum : drums)
{
drum.rotation += drum.speed;
if (drum.rotation >= 360)
{
drum.rotation = 0;
drum.currentTexture++;
if (drum.currentTexture >= NUM_TEXTURES)
{
drum.currentTexture = 0;
}
}
}
}
int main(int argc, char* args[])
{
SDL_Window* window = nullptr;
SDL_Renderer* renderer = nullptr;
std::vector<Drum> drums;
if (!init(window, renderer))
{
return 1;
}
initDrums(renderer, drums);
SDL_Event event;
bool isRunning = true;
bool isRotating = false;
Uint32 startTime = 0;
while (isRunning)
{
while (SDL_PollEvent(&event))
{
if (event.type == SDL_QUIT)
{
isRunning = false;
}
else if (event.type == SDL_KEYDOWN && event.key.keysym.sym == SDLK_SPACE)
{
isRotating = true;
startTime = SDL_GetTicks();
}
}
if (isRotating)
{
Uint32 currentTime = SDL_GetTicks();
Uint32 elapsedTime = currentTime - startTime;
if (elapsedTime >= 4000)
{
isRotating = false;
}
else
{
updateDrums(drums);
}
}
SDL_SetRenderDrawColor(renderer, 255, 255, 255, 255);
SDL_RenderClear(renderer);
renderDrums(renderer, drums);
SDL_RenderPresent(renderer);
}
cleanup(window, renderer, drums);
return 0;
} Как сделать прозрачные текстуры на барабанах?
|
ba9da85482cf3905f302c30fdef32fc5
|
{
"intermediate": 0.2830542325973511,
"beginner": 0.5300540924072266,
"expert": 0.1868916153907776
}
|
31,193
|
public void run() {
try {
if (this.player == null) {
return;
}
if (this.player.tank == null) {
return;
}
if (this.player.battle == null) {
return;
}
this.preparedPosition = SpawnManager.getSpawnState(this.player.battle.battleInfo.map, this.player.playerTeamType);
if (this.onlySpawn) {
this.player.send(Type.BATTLE, "prepare_to_spawn", StringUtils.concatStrings(this.player.tank.id, ";", String.valueOf(this.preparedPosition.x), "@", String.valueOf(this.preparedPosition.y), "@", String.valueOf(this.preparedPosition.z), "@", String.valueOf(this.preparedPosition.rot)));
} else {
if (this.player.battle == null) {
return;
}
this.player.tank.position = this.preparedPosition;
this.player.send(Type.BATTLE, "prepare_to_spawn", StringUtils.concatStrings(this.player.tank.id, ";", String.valueOf(this.preparedPosition.x), "@", String.valueOf(this.preparedPosition.y), "@", String.valueOf(this.preparedPosition.z), "@", String.valueOf(this.preparedPosition.rot)));
}
this.spawnTask = new TankRespawnScheduler.SpawnTask();
this.spawnTask.preparedSpawnTask = this;
if (this.onlySpawn) {
TankRespawnScheduler.TIMER.schedule(this.spawnTask, 1000L);
}
else {
TankRespawnScheduler.TIMER.schedule(this.spawnTask, 5000L);
}
} catch (Exception var2) {
var2.printStackTrace();
RemoteDatabaseLogger.error(var2);
}
}
} как здесь сделать if (this.onlySpawn) {
TankRespawnScheduler.TIMER.schedule(this.spawnTask, 1000L);
}
else {
TankRespawnScheduler.TIMER.schedule(this.spawnTask, 5000L);
} надо добавить еще точно такойже 3
|
62f90d71d4305705a03f24b703175f24
|
{
"intermediate": 0.32148003578186035,
"beginner": 0.46575528383255005,
"expert": 0.2127646952867508
}
|
31,194
|
package gtanks.battles.timer.schedulers.runtime;
import gtanks.StringUtils;
import gtanks.battles.BattlefieldPlayerController;
import gtanks.battles.managers.SpawnManager;
import gtanks.battles.tanks.math.Vector3;
import gtanks.commands.Type;
import gtanks.json.JSONUtils;
import gtanks.logger.remote.RemoteDatabaseLogger;
import java.util.HashMap;
import java.util.Timer;
import java.util.TimerTask;
public class TankRespawnScheduler {
private static final Timer TIMER = new Timer("TankRespawnScheduler timer");
private static final long TIME_TO_PREPARE_SPAWN = 3000L;
private static final long TIME_TO_SPAWN = 5000L;
private static HashMap<BattlefieldPlayerController, TankRespawnScheduler.PrepareToSpawnTask> tasks = new HashMap();
private static boolean disposed;
public static void startRespawn(BattlefieldPlayerController player, boolean onlySpawn) {
if (!disposed) {
try {
if (player == null) {
return;
}
if (player.battle == null) {
return;
}
TankRespawnScheduler.PrepareToSpawnTask task = new TankRespawnScheduler.PrepareToSpawnTask();
task.player = player;
task.onlySpawn = onlySpawn;
tasks.put(player, task);
TIMER.schedule(task, onlySpawn ? 1000L : 5000L);
} catch (Exception var3) {
var3.printStackTrace();
RemoteDatabaseLogger.error(var3);
}
}
}
public static void dispose() {
disposed = true;
}
public static void cancelRespawn(BattlefieldPlayerController player) {
try {
TankRespawnScheduler.PrepareToSpawnTask task = (TankRespawnScheduler.PrepareToSpawnTask)tasks.get(player);
if (task == null) {
return;
}
if (task.spawnTask == null) {
task.cancel();
} else {
task.spawnTask.cancel();
}
tasks.remove(player);
} catch (Exception var2) {
var2.printStackTrace();
RemoteDatabaseLogger.error(var2);
}
}
static class PrepareToSpawnTask extends TimerTask {
public TankRespawnScheduler.SpawnTask spawnTask;
public BattlefieldPlayerController player;
public Vector3 preparedPosition;
public boolean onlySpawn;
public void run() {
try {
if (this.player == null) {
return;
}
if (this.player.tank == null) {
return;
}
if (this.player.battle == null) {
return;
}
this.preparedPosition = SpawnManager.getSpawnState(this.player.battle.battleInfo.map, this.player.playerTeamType);
if (this.onlySpawn) {
this.player.send(Type.BATTLE, "prepare_to_spawn", StringUtils.concatStrings(this.player.tank.id, ";", String.valueOf(this.preparedPosition.x), "@", String.valueOf(this.preparedPosition.y), "@", String.valueOf(this.preparedPosition.z), "@", String.valueOf(this.preparedPosition.rot)));
} else {
if (this.player.battle == null) {
return;
}
this.player.tank.position = this.preparedPosition;
this.player.send(Type.BATTLE, "prepare_to_spawn", StringUtils.concatStrings(this.player.tank.id, ";", String.valueOf(this.preparedPosition.x), "@", String.valueOf(this.preparedPosition.y), "@", String.valueOf(this.preparedPosition.z), "@", String.valueOf(this.preparedPosition.rot)));
}
this.spawnTask = new TankRespawnScheduler.SpawnTask();
this.spawnTask.preparedSpawnTask = this;
TankRespawnScheduler.TIMER.schedule(this.spawnTask, 5000L);
} catch (Exception var2) {
var2.printStackTrace();
RemoteDatabaseLogger.error(var2);
}
}
}
static class SpawnTask extends TimerTask {
TankRespawnScheduler.PrepareToSpawnTask preparedSpawnTask;
public void run() {
try {
BattlefieldPlayerController player = this.preparedSpawnTask.player;
if (player == null) {
return;
}
if (player.tank == null) {
return;
}
if (player.battle == null) {
return;
}
player.battle.tanksKillModel.changeHealth(player.tank, 10000);
player.battle.sendToAllPlayers(Type.BATTLE, "spawn", JSONUtils.parseSpawnCommand(player, this.preparedSpawnTask.preparedPosition));
player.tank.state = "newcome";
TankRespawnScheduler.tasks.remove(player);
} catch (Exception var2) {
var2.printStackTrace();
RemoteDatabaseLogger.error(var2);
}
}
}
}
как сделать чтобы инвиз был не сразу, через секунд 5
|
64e941ed4b56392b61d67cab354b4eb7
|
{
"intermediate": 0.33010512590408325,
"beginner": 0.5338963270187378,
"expert": 0.13599857687950134
}
|
31,195
|
How do i Calculate dVarA and dVarB in al?
section .data
EXIT_SUCCESS equ 0
SYS_exit equ 60
dVarA db 0xa5
dVarB db 0xb3
bResult db 0
section .text
global _start
_start:
mov al, byte [dVarA]
add al, byte [dVarB]
mov byte [bResult], al
last:
mov rax, SYS_exit
mov rdi, EXIT_SUCCESS
syscall
|
31e25d5d183f4533c8e8f882230307ac
|
{
"intermediate": 0.302497535943985,
"beginner": 0.30160728096961975,
"expert": 0.39589518308639526
}
|
31,196
|
I want to divs to be side by side, and have a gap between them, if the screen size is like the size of the table the divs should wrap if not they need to be side by side. Inside those divs there should be a barchart from recharts, they need to be responsive. the max height of the divs are 322px, but the with should be atomatically based on the screen, im using typescript , please provide me a simple example with data for the charts also.
|
651e315c2a7d5f2a031205c062f60260
|
{
"intermediate": 0.5919510126113892,
"beginner": 0.188913956284523,
"expert": 0.2191350907087326
}
|
31,197
|
I want to divs to be side by side, and have a gap between them, if the screen size is like the size of the table the divs should wrap if not they need to be side by side. Inside those divs there should be a barchart from recharts, they need to be responsive. the max height of the divs are 322px, but the with should be automatically based on the screen
|
583de5826c7374d15b1f16847e15b9c3
|
{
"intermediate": 0.4612261950969696,
"beginner": 0.20089101791381836,
"expert": 0.33788278698921204
}
|
31,198
|
public void executeCommand(Command cmd) {
try {
String _name = null;
switch($SWITCH_TABLE$gtanks$commands$Type()[cmd.type.ordinal()]) {
case 3:
if (cmd.args[0].equals("try_mount_item")) {
if (this.localUser.getGarage().mountItem(cmd.args[1])) {
this.send(Type.GARAGE, "mount_item", cmd.args[1]);
this.localUser.getGarage().parseJSONData();
database.update(this.localUser.getGarage());
} else {
this.send(Type.GARAGE, "try_mount_item_NO");
}
}
if (cmd.args[0].equals("try_update_item")) {
this.onTryUpdateItem(cmd.args[1]);
}
if (cmd.args[0].equals("get_garage_data") && this.localUser.getGarage().mountHull != null && this.localUser.getGarage().mountTurret != null && this.localUser.getGarage().mountColormap != null) {
this.send(Type.GARAGE, "init_mounted_item", StringUtils.concatStrings(this.localUser.getGarage().mountHull.id, "_m", String.valueOf(this.localUser.getGarage().mountHull.modificationIndex)));
this.send(Type.GARAGE, "init_mounted_item", StringUtils.concatStrings(this.localUser.getGarage().mountTurret.id, "_m", String.valueOf(this.localUser.getGarage().mountTurret.modificationIndex)));
this.send(Type.GARAGE, "init_mounted_item", StringUtils.concatStrings(this.localUser.getGarage().mountColormap.id, "_m", String.valueOf(this.localUser.getGarage().mountColormap.modificationIndex)));
}
if (cmd.args[0].equals("try_buy_item")) {
this.onTryBuyItem(cmd.args[1], Integer.parseInt(cmd.args[2]));
}
case 4:
case 8:
case 9:
case 10:
default:
break;
case 5:
if (cmd.args[0].equals("get_hall_of_fame_data")) {
this.localUser.setUserLocation(UserLocation.HALL_OF_FAME);
this.send(Type.LOBBY, "init_hall_of_fame", JSONUtils.parseHallOfFame(top));
}
if (cmd.args[0].equals("get_garage_data")) {
this.sendGarage();
}
if (cmd.args[0].equals("get_data_init_battle_select")) {
this.sendMapsInit();
}
if (cmd.args[0].equals("check_battleName_for_forbidden_words")) {
_name = cmd.args.length > 0 && cmd.args[1].length() <= 25 ? cmd.args[1] : "Name map";
this.checkBattleName(_name);
}
if (cmd.args[0].equals("try_create_battle_dm")) {
if (this.getLocalUser().getRang() + 1 >= 4 || this.getLocalUser().getType() != TypeUser.DEFAULT) {
this.tryCreateBattleDM(cmd.args[1], cmd.args[2], Integer.parseInt(cmd.args[3]), Integer.parseInt(cmd.args[4]), Integer.parseInt(cmd.args[5]), Integer.parseInt(cmd.args[6]), Integer.parseInt(cmd.args[7]), this.stringToBoolean(cmd.args[8]), this.stringToBoolean(cmd.args[9]), this.stringToBoolean(cmd.args[10]), false);
} else {
this.sendTableMessage("Создание битв доступно, начиная со звания Капрал.");
}
}
if (cmd.args[0].equals("try_create_battle_tdm")) {
if (this.getLocalUser().getRang() + 1 >= 4 || this.getLocalUser().getType() != TypeUser.DEFAULT) {
this.tryCreateTDMBattle(cmd.args[1], false);
} else {
this.sendTableMessage("Создание битв доступно, начиная со звания Капрал.");
}
}
if (cmd.args[0].equals("try_create_battle_ctf")) {
if (this.getLocalUser().getRang() + 1 >= 4 || this.getLocalUser().getType() != TypeUser.DEFAULT) {
this.tryCreateCTFBattle(cmd.args[1], false);
} else {
this.sendTableMessage("Создание битв доступно, начиная со звания Капрал.");
}
}
if (cmd.args[0].equals("get_show_battle_info")) {
this.sendBattleInfo(cmd.args[1]);
}
if (cmd.args[0].equals("enter_battle")) {
this.onEnterInBattle(cmd.args[1]);
}
cmd.args[0].equals("bug_report");
cmd.args[0].equals("screenshot");
if (cmd.args[0].equals("enter_battle_team")) {
this.onEnterInTeamBattle(cmd.args[1], Boolean.parseBoolean(cmd.args[2]));
}
if (cmd.args[0].equals("enter_battle_spectator")) {
if (this.getLocalUser().getType() == TypeUser.DEFAULT) {
return;
}
this.enterInBattleBySpectator(cmd.args[1]);
}
if (cmd.args[0].equals("user_inited")) {
dailyBonusService.userLoaded(this);
}
if (cmd.args[0].equals("show_profile")) {
this.send(Type.LOBBY,"show_profile;{\"isComfirmEmail\":false,\"emailNotice\":false}");
}
break;
case 6:
if (this.getLocalUser().getRang() + 1 >= 3 || this.getLocalUser().getType() != TypeUser.DEFAULT) {
chatLobby.addMessage(new ChatMessage(this.localUser, cmd.args[0], this.stringToBoolean(cmd.args[1]), cmd.args[2].equals("NULL") ? null : database.getUserById(cmd.args[2]), this));
} else {
send(Type.LOBBY_CHAT, "system", "Чат доступен, начиная со звания Ефрейтор.");
}
break;
case 7:
if (this.battle != null) {
this.battle.executeCommand(cmd);
}
if (this.spectatorController != null) {
this.spectatorController.executeCommand(cmd);
}
break;
case 11:
_name = cmd.args[0];
if (_name.equals("c01")) {
this.kick();
}
}
} catch (Exception var3) {
var3.printStackTrace();
}
}
как сюда добавить проверку на куплен ли предмет с id no_supplies
|
d0304ad63828d388a1acd5cbd85d014b
|
{
"intermediate": 0.31641116738319397,
"beginner": 0.47294872999191284,
"expert": 0.21064014732837677
}
|
31,199
|
implement a table insite of this wrapper
wrappedText.forEach((line) => {
let posY = margin + defaultYJump * iterations++;
if (posY > pageHeight - margin) {
pdfDoc.addPage();
iterations = 1;
posY = margin + defaultYJump * iterations++;
}
pdfDoc.text(15, posY, line);
});*
|
3ba0f7ae597628324fbbdc57623b0c31
|
{
"intermediate": 0.3927824795246124,
"beginner": 0.2958262860774994,
"expert": 0.3113912343978882
}
|
31,200
|
¿Cómo formatear los campos de fecha start_date y end_date para que tengan el formato format('d-m-Y') en este query de laravel?
$vacations = Vacation::select('id', 'start_date', 'end_date', 'total_days', 'status', 'supervisor_reviewer_id', 'human_resources_reviewer_id')
->with('supervisor_reviewer')
->with('human_resources_reviewer')
->where('requesting_employee_id', $this->requesting_employee_id)
->orderBy('start_date');
|
363ad7d36332c36a07f809e1cc76367c
|
{
"intermediate": 0.37757694721221924,
"beginner": 0.3823126554489136,
"expert": 0.2401103526353836
}
|
31,202
|
write a VBA code for a presentation powerpoint about kant's philosophy ( in arabic )using at least 20 slides
|
3fbb4d2ec359f2b851b1877933077471
|
{
"intermediate": 0.31808850169181824,
"beginner": 0.42063915729522705,
"expert": 0.2612723410129547
}
|
31,203
|
int main(int argc, char *argv[]) {
uint8_t *pBuffer = malloc(sizeof(uint8_t) * 2);
FILE *pFile = fopen(TEX_FILENAME, "rb");
fread(pBuffer, sizeof(uint8_t) * 2, 1, pFile);
printf("[%d, %d]\n", pBuffer[0], pBuffer[1]);
if (!realloc(pBuffer, sizeof(uint8_t) * 2 + sizeof(uint8_t) * pBuffer[0] * pBuffer[1])) {
return 1;
}
fread(pBuffer, sizeof(uint8_t) * 2 + sizeof(uint8_t) * pBuffer[0] * pBuffer[1], 1, pFile);
for (unsigned int i = 2; i < pBuffer[0] * pBuffer[1]; i += 3) {
printf("(%d, %d, %d) ", pBuffer[i], pBuffer[i + 1], pBuffer[i + 2]);
}
putchar('\n');
fclose(pFile);
}
This code segfaults at the second fread.
|
ff624c44cfcdfe9870a2a0eedee3522a
|
{
"intermediate": 0.3239760994911194,
"beginner": 0.45489200949668884,
"expert": 0.22113193571567535
}
|
31,204
|
when using CSS Modules i have a component that is a select from antd , I want to add the following css called style to that .ant-select-selector, but im unable to do it,
the style is
profitOptimizerCascader{
color: #279989;
font-size: 24px;
font-weight: bold;
margin-right: 20px;
display: flex;
align-items: center;
}
and the code is
<Select
className={style.profitOptimizerCascader}
data-testid="month-dropdown"
onChange={handleMonthChange}
style={{ height: '45px', width: '177px' }}
value={month !== 0 ? ProperCase(moment.months(month - 1)) : t('Label_Month', { ns: 'weekly' })}
>
{monthNames.map((value, index) => (
<Option key={`${index}_Weekly${value}`} value={index}>
{ProperCase(value)}
</Option>
))}
</Select>
|
96da22f07fa85b15cea87d324d5b6ff9
|
{
"intermediate": 0.2892029285430908,
"beginner": 0.39614009857177734,
"expert": 0.31465694308280945
}
|
31,205
|
how to append to existing excel using python
|
1d25d2e780c1e776fb9a4c956ad35876
|
{
"intermediate": 0.3502238690853119,
"beginner": 0.2864491939544678,
"expert": 0.3633269667625427
}
|
31,206
|
Write a C program to generate a texture where each pixel is randomly colored. Store a 16-bit unsigned int at the very start representing the width, and another representing the height. Then an 8-bit integer representing the number of channels. After that comes the list of pixel colors, each pixel's color channel is an 8-bit unsigned int. Then write a program to display it in the terminal using ASCII escape sequences.
|
0e2e3e5bccf2d545344275a0d0d54c90
|
{
"intermediate": 0.44367143511772156,
"beginner": 0.16902124881744385,
"expert": 0.387307345867157
}
|
31,207
|
si la variable $this->start_date_filter tiene un valor distinto de null, entonces agregar la condicion de que ese valor tiene que ser mayor o igual al campo "start_date" del query de laravel
$vacations = Vacation::select('id', 'start_date', 'end_date', 'total_days', 'status', 'supervisor_reviewer_id', 'human_resources_reviewer_id')
->with('supervisor_reviewer')
->with('human_resources_reviewer')
->where('requesting_employee_id', $this->requesting_employee_id)
->orderBy('start_date');
|
970259dd4f4e5c5798baba7210f0ca77
|
{
"intermediate": 0.2422938048839569,
"beginner": 0.57591712474823,
"expert": 0.18178904056549072
}
|
31,208
|
si la variable $this->start_date_filter tiene un valor distinto de null, entonces agregar la condicion de que ese valor tiene que ser mayor o igual al campo "start_date" del query de laravel
$vacations = Vacation::select('id', 'start_date', 'end_date', 'total_days', 'status', 'supervisor_reviewer_id', 'human_resources_reviewer_id')
->with('supervisor_reviewer')
->with('human_resources_reviewer')
->where('requesting_employee_id', $this->requesting_employee_id)
->orderBy('start_date');
|
d0dd7285a6ed2a82c7fe14610ea33b2c
|
{
"intermediate": 0.2422938048839569,
"beginner": 0.57591712474823,
"expert": 0.18178904056549072
}
|
31,209
|
public Item buyItem(String id, int count, int nul) {
id = id.substring(0, id.length() - 3);
Item temp = (Item)GarageItemsLoader.items.get(id);
if (temp.specialItem) {
return null;
} else {
Item item = temp.clone();
if (!this.items.contains(this.getItemById(id))) {
if (item.itemType == ItemType.INVENTORY) {
item.count += count;
}
this.items.add(item);
return item;
} else if (item.itemType == ItemType.INVENTORY) {
Item fromUser = this.getItemById(id);
fromUser.count += count;
return fromUser;
} else {
return null;
}
}
} как сюда добавить чтобы 1000_scores не добавлялась в гараж после покупки а если точнее заблокировать для этого предмета this.items.add(item);
|
6ed17dfba9b011df92a40132927ee4d2
|
{
"intermediate": 0.345655620098114,
"beginner": 0.3522818386554718,
"expert": 0.3020625710487366
}
|
31,210
|
set up a quick platformer for me, here is the start:
import React from "react";
function GameMain(){
const gameOver = false;
function mainLoop(){
while(!gameOver){
}
}
return(
<div></div>
)
}
export default GameMain
private Vector3 GetInputDirectionWithAngles()
{
Vector3 inputDirection = Vector3.Zero;
float horizontal = Input.GetActionStrength("ui_right") - Input.GetActionStrength("ui_left");
float vertical = Input.GetActionStrength("ui_down") - Input.GetActionStrength("ui_up");
if (Math.Abs(vertical) > Mathf.Epsilon) // Prevent division by zero if vertical is 0
{
// Calculate the tilt angle based on the vertical input
float tiltAngle = (vertical > 0) ? UpwardAngleDeg : DownwardAngleDeg;
// Calculate the tilt using tan(angle) = opposite/adjacent (rise over run), and run is 1 unit, so rise = tan(angle)
float rise = Mathf.Tan(Mathf.Deg2Rad(tiltAngle));
// Apply horizontal movement and tilt in the direction
inputDirection = new Vector3(horizontal, rise, 1).Normalized();
}
else
{
inputDirection = new Vector3(horizontal, 0, 1).Normalized(); // Only horizontal movement when not moving up or down
}
return inputDirection;
}
|
9aa1cb3e8a47273831fe8edf6d35d2e6
|
{
"intermediate": 0.4074542820453644,
"beginner": 0.41732102632522583,
"expert": 0.1752246618270874
}
|
31,211
|
Schreibe ein C++ Programm, das eine positive ganze Zahl z ¨uber eine
Kommandozeilen-Eingabe (cin) ¨ubergeben bekommt und die
Bin¨ardarstellung dieser Zahl auf der Kommandozeile ausgibt. Die Anzahl
der Bits n, die ben¨otigt werden um die Zahl z darzustellen kann mit
n =
log(z + 1)
log(2)
,
berechnet werden. Die Klammern bedeuten, dass das Ergebnis nach oben
gerundet werden soll, was in C++ mit der Funktion ceil aus dem
<cmath>-Teil der Standardbibliothek implementiert ist. Nutze eine Schleife
um ¨uber die Bits zu iterieren und um zu bestimmen, ob ein Bit 0 oder 1
ist. Ein m¨oglicher Programmablauf k¨onnte wie folgt aussehen:
Eingabe Zahl: > 11
Ausgabe: 1011
STCE, Global¨ubung C++ 2
Kontrollfluss
Aufgaben II
3. Erweitere das Programm so, dass es auch eine (positive) Bin¨arzahl in eine
Dezimalzahl umwandeln kann. Frage daf¨ur am Anfang des Programms, ob
der Nutzer eine Bin¨arzahl zur Dezimalzahl umwandeln m¨ochte oder
umgekehrt. Falls eine Bin¨arzahl eingegeben werden soll wird der Nutzer
zuerst gefragt wie viele Bits die Bin¨arzahl hat. Anschließend sollen diese
nacheinander abgefragt werden. Ein m¨oglicher Programmablauf k¨onnte
wie folgt aussehen:
W¨ahle 0 f¨ur dec-to-bin, 1 f¨ur bin-to-dec: > 1
Anzahl der Bits: > 4
1. Bit: > 1
2. Bit: > 0
3. Bit: > 1
4. Bit: > 1
Ausgabe: 11
|
8294688febc382eb6d689a098aa9a0cc
|
{
"intermediate": 0.4028872847557068,
"beginner": 0.27975383400917053,
"expert": 0.3173588812351227
}
|
31,212
|
In a q-btn-toggle, how do I have different colored buttons for each option?
|
eeb847e87ed689c95c4c3fb3966699e9
|
{
"intermediate": 0.49684205651283264,
"beginner": 0.19009056687355042,
"expert": 0.31306737661361694
}
|
31,213
|
How to put a paragraph before \makelettertitle in Latex
|
45ad70e8785cc2c313226b5851848c28
|
{
"intermediate": 0.313345342874527,
"beginner": 0.28088220953941345,
"expert": 0.4057723879814148
}
|
31,214
|
how do I fix this error:
error: invalid method declaration; return type required
public static Image (String filename)
from this code:
public static Image (String filename)
{
MyroImage.loadImage("apcshelicopter.jpg");
}
|
ca7687fb27ba3344f32a9724e85ee13d
|
{
"intermediate": 0.5470021367073059,
"beginner": 0.31282007694244385,
"expert": 0.1401776820421219
}
|
31,215
|
Write a C++ Program to print the letter K using stars.
Note:
1) Using nested For Loop
2) The number of lines is given by user.
3) Using one Outer loop to print your letter
|
a7476b08884cab12eafb59977eea5e41
|
{
"intermediate": 0.24581018090248108,
"beginner": 0.5523070096969604,
"expert": 0.20188279449939728
}
|
31,216
|
the character is stuck in the air:
import React, { useState, useEffect, useRef } from "react";
// Constants for gravity and jumping
const GRAVITY = 0.5;
const JUMP_STRENGTH = -10; // Negative because the Y axis is downward
const Platform = ({ width, height, top, left }) => {
const style = {
position: "absolute",
width: `${width}px`,
height: `${height}px`,
backgroundColor: "brown",
left: `${left}px`,
top: `${top}px`,
};
return <div style={style} />;
};
const Player = ({ position }) => {
const style = {
position: "absolute",
width: "50px",
height: "50px",
backgroundColor: "blue",
left: `${position.x}px`,
top: `${position.y}px`,
};
return <div style={style} />;
};
function GameMain() {
const [playerPosition, setPlayerPosition] = useState({ x: 100, y: 100 });
const [playerVelocity, setPlayerVelocity] = useState({ x: 0, y: 0 });
const [isGrounded, setIsGrounded] = useState(false);
const requestRef = useRef<number | null>(null);
const lastTimeRef = useRef(0);
const playerPositionRef = useRef({ x: 100, y: 100 });
const playerVelocityRef = useRef({ x: 0, y: 0 });
// Platform
const platform = {
width: 400,
height: 20,
top: 450,
left: 100,
};
const checkCollisionWithPlatform = (newPosition) => {
const playerFoot = newPosition.y + 50;
if (playerFoot < platform.top) return false;
const withinPlatformXBounds =
newPosition.x < (platform.left + platform.width) &&
(newPosition.x + 50) > platform.left;
const fallingOntoPlatform = playerFoot >= platform.top && playerVelocityRef.current.y >= 0;
return withinPlatformXBounds && fallingOntoPlatform;
};
const handleKeyPress = (event) => {
if (event.key === "ArrowRight") {
// Increment horizontal position
setPlayerPosition((prev) => ({ ...prev, x: prev.x + 5 }));
} else if (event.key === "ArrowLeft") {
// Decrement horizontal position
setPlayerPosition((prev) => ({ ...prev, x: prev.x - 5 }));
} else if (event.key === "ArrowUp" && isGrounded) {
// Set vertical velocity for jump only if player is grounded
setPlayerVelocity((prev) => ({ ...prev, y: JUMP_STRENGTH }));
setIsGrounded(false);
}
};
useEffect(() => {
window.addEventListener("keydown", handleKeyPress);
return () => window.removeEventListener("keydown", handleKeyPress);
}, [isGrounded]); // Adding isGrounded as a dependency ensures that the states are updated correctly.
useEffect(() => {
playerPositionRef.current = playerPosition;
playerVelocityRef.current = playerVelocity;
});
const updateGame = (time) => {
const deltaTime = (time - lastTimeRef.current) / 1000;
lastTimeRef.current = time;
// Calculate new velocity and position based on gravity
let newVelocity = {
x: playerVelocityRef.current.x,
y: (!isGrounded ? playerVelocityRef.current.y + GRAVITY * deltaTime : 0)
};
let newPosition = {
x: playerPositionRef.current.x + newVelocity.x * deltaTime,
y: (!isGrounded ? playerPositionRef.current.y + newVelocity.y * deltaTime : playerPositionRef.current.y)
};
// If the player is not grounded and colliding with the platform, adjust their position and velocity
if (!isGrounded && checkCollisionWithPlatform(newPosition)) {
newPosition.y = platform.top - 50; // Adjust player to be on top of the platform
newVelocity.y = 0; // Stop the vertical velocity as the player has landed
setIsGrounded(true);
}
// Update player position and velocity
setPlayerPosition(newPosition);
setPlayerVelocity(newVelocity);
// Continue the game loop
requestRef.current = requestAnimationFrame(updateGame);
};
return (
<div style={{ position: "relative", width: "100%", height: "100%" }}>
<img src="assets/Grassy_Mountains_preview_fullcolor.png" style={{ width: "100%" }} alt="Background" />
<Player position={playerPosition} />
<Platform {...platform} />
</div>
);
}
export default GameMain;
|
6d2c9690fae033bb4206aa440e5bd864
|
{
"intermediate": 0.35806789994239807,
"beginner": 0.4292200207710266,
"expert": 0.21271200478076935
}
|
31,217
|
I'm using virt-manager (in Debian). Where is the xml file that I want to edit for a certain VM I have?
|
bd397502dd01e3cd16d83749b0b6e8b7
|
{
"intermediate": 0.6712606549263,
"beginner": 0.14056962728500366,
"expert": 0.18816980719566345
}
|
31,218
|
how to consider proximity of words in query string in whoosh searching
|
7a53e208a86dd345f4b5786f79c71e1b
|
{
"intermediate": 0.21312855184078217,
"beginner": 0.18370914459228516,
"expert": 0.6031622886657715
}
|
31,219
|
Two source programs master.c and slave.c and the header file myShm.h
The master process and its child processes executing the slave executable communicate through a
shared memory segment. When master executes, it first outputs a message to identify itself, then requests to create a
shared memory segment of a certain name xxxxx, structures it to that defined in the myShm.h header file shown below,
initializes the index therein to zero, followed by creating n child processes. (Note that both xxxxx and the number n are
obtained from the commandline parameters.) Each child process is to execute slave, with its child number (i.e., 1, 2, etc.)
and other relevant arguments passed to it from the exec() system call. The master process outputs the number of slaves it
has created, and waits for all of them to terminate. Upon receiving termination signals from all child processes, master
then outputs content of the shared memory segment, removes the shared memory and then exits.
Two implementations of semaphore are commonly available on most distributions of UNIX and Linux operating systems:
System V and POSIX. In this assignment you will use the POSIX implementation. The POSIX implementation supports
named and unnamed semaphores, both of which are defined in <semaphore.h>. The named semaphore mechanism
includes sem_wait(), sem_post(), sem_open(), sem_close() & sem_unlink(), and should be used in this assignment.
Details on the definition of these system calls and their use may be found on Linux man pages. A sample program that
shows the use of these system calls can be found in the observer.c file on Canvas.
Suppose program execution is launched as follows. Notice that the specifications of the master and slave processes as
described below have minor differences from those given in Assignment 3. One reason is to add semaphore and the other
to highlight the potential problem due to potential race condition on the access to the monitor as an output device and the
keyboard as input device.
|
8b86a5a98e5322fceb1428ffff174593
|
{
"intermediate": 0.3156270980834961,
"beginner": 0.2874997556209564,
"expert": 0.3968731760978699
}
|
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