row_id
int64 0
48.4k
| init_message
stringlengths 1
342k
| conversation_hash
stringlengths 32
32
| scores
dict |
|---|---|---|---|
40,054
|
ASCII-Art of a cat
|
db8a5ecd7f5c7703683123d99fac16b3
|
{
"intermediate": 0.3217235207557678,
"beginner": 0.43271148204803467,
"expert": 0.2455649971961975
}
|
40,055
|
Introduce to me Finger Tree, the data structure.
|
0928ba46544330f099e851bdec883ad3
|
{
"intermediate": 0.4016805589199066,
"beginner": 0.2578180134296417,
"expert": 0.34050148725509644
}
|
40,056
|
Deepika needs to classify the mails as spam and non - spam. For this purpose, help her to design application with the help of Adaboost classifier
give me python program
|
1276f90aa39f23ef5754c158e99c86ee
|
{
"intermediate": 0.2204333245754242,
"beginner": 0.09789888560771942,
"expert": 0.6816678047180176
}
|
40,057
|
c ifdef apple example?
|
8516763f8636721639ec925174f530b0
|
{
"intermediate": 0.28479745984077454,
"beginner": 0.4992465078830719,
"expert": 0.21595609188079834
}
|
40,058
|
Hello. Can you write a Godot Engine shader that overlays a green color on top of a transparent texture?
|
ffd65b1ce89d085cf9fd794e04ff80ad
|
{
"intermediate": 0.4401402473449707,
"beginner": 0.136546328663826,
"expert": 0.4233134388923645
}
|
40,059
|
This program has a logic error, so we have to debug it.
RULE: Every function needs to be called in order to execute. This includes the main function.
Click Run and you will see that nothing happens on the stage.
Fix the program so that the stage will be set. Note: Make sure every function is called!
Click Run to test if you fixed the program. When it is fixed, click Submit and Next.
#This program will recreate the story of the 3 little pigs
def set_stage():
""" Sets up the stage for the start of the story """
stage.set_background("barn")
sprite = codesters.Sprite("pig",-100,-125)
def main():
""" Sets up the program and calls other functions """
set_stage()
|
b21c0d58f39f17dd0d3440aee418cf35
|
{
"intermediate": 0.44423964619636536,
"beginner": 0.3054542541503906,
"expert": 0.250306099653244
}
|
40,060
|
Pseudo Random Number Generator
How can deterministic computers produce random numbers? And does it even need to?
Turns out Classical Computers unlike Quantum Computer don’t have access to ‘Truly random numbers’. Computers need to access random numbers in order to encrypt information,
perform computer simulation, do ray tracing in Computer Games, make Machine Learning
happen and so much more.
What we mean by random numbers here is a sequence of independent random numbers
with a specified distribution. In this subtask, you will be implementing the famous ‘Middle
square algorithm’ by John von Neumann to generate pseudo-random numbers. Take a 4
digit number called the seed, say 9876, now square it and extract the middle 4 digits, thus
9,75,35,376 − > 5353. And we repeat this process i.e. now take this as the four-digit number,
square it and extract the middle 4 digits and so on. We highly recommended you to watch
this video to get an intuition about what pseudo-random numbers are.
Write a Python function pseudo rand num gen(seed, k) that generates k pseudo random
numbers using the above process and uses your current system time as the seed to this function. The function returns a list containing all the k random numbers generated.
Update: The middle-square algorithm needs to be implemented for a general seed with
even number of digits. (Hint: A faster way to extract the middle digits is by converting the
number to a string first.) In case the seed after squaring has odd no. of digits pad it with a
zero in the front and then extract the middle digits.
Also plot a histogram of the generated random values (after dividing by 10n where n is the
no. of digits in the seed) using matplotlib
|
03fa0caf20b60b6b188751a07c4346f6
|
{
"intermediate": 0.275523841381073,
"beginner": 0.1349363774061203,
"expert": 0.5895398259162903
}
|
40,061
|
my_function()
Let's make this game more challenging by adding another ball and giving each ball a different speed!
Add another ball! Place another Function Call in your main function which calls add_ball().
Set the ball speed! Add the parameter speed to your add_ball() function definition.
Replace -8 in set_y_speed() with the new parameter speed.
In main(), add integer parameters to the add_ball() function calls. Make sure they are negative!
def set_stage():
""" Sets up the stage for the game """
stage.set_background("soccerfield")
stage.disable_floor()
def add_player():
""" Adds a player to the stage for the user to control """
player = codesters.Sprite("player1")
player.go_to(0, -155)
return player
def add_ball():
""" Adds a ball to the stage and sets its attributes """
ball = codesters.Sprite("soccerball")
ball.set_y_speed(-8)
def head_ball(sprite, hit_sprite):
""" Detects collisions between the player and ball """
my_var = hit_sprite.get_y_speed()
hit_sprite.set_y_speed(-my_var + 1)
my_var = hit_sprite.get_x_speed()
hit_sprite.set_x_speed(my_var + 1)
def move_left():
""" Moves the player left """
player.move_left(50)
def move_right():
""" Moves the player right """
player.move_right(50)
def main():
""" Sets up the program and calls other functions """
set_stage()
player = add_player()
add_ball()
player.event_collision(head_ball)
stage.event_key("left", move_left)
player.event_key("right", move_right)
main()
|
1d81a93e47e0ad1e3dc07843ac4d62b0
|
{
"intermediate": 0.4642283320426941,
"beginner": 0.3035876750946045,
"expert": 0.23218396306037903
}
|
40,062
|
gello
|
72200a64dca4fc510b42b5294d49f762
|
{
"intermediate": 0.31873977184295654,
"beginner": 0.25284138321876526,
"expert": 0.42841893434524536
}
|
40,063
|
Hello. Can you write a 3D shader for Godot Engine that overlays the green color on top of the alpha channel?
|
586cf28ae6a1126a62997da925948bde
|
{
"intermediate": 0.4404873549938202,
"beginner": 0.14155365526676178,
"expert": 0.4179590344429016
}
|
40,064
|
import { collection, getDocs, onSnapshot } from "firebase/firestore";
import db from "../auth/firestore"
import { writable } from "svelte/store";
export let people = writable([])
async function getTotalNumberOfPeople() {
let totalCount = []
const querySnapshot = await getDocs(collection(db, "Total"));
if(querySnapshot){
querySnapshot.forEach((doc) => {
totalCount.push(JSON.parse(JSON.stringify(doc.data())))
})
}
return totalCount
}
function setPeople() {
getTotalNumberOfPeople().then((out) => {
if(out){
people.set(out.setPeople)
}
})
}
onSnapshot(collection(db, "Total"), (snapshot) => {
if(snapshot){
snapshot.docChanges().forEach((change) => {
if (change.type === "modified") setPeople()
}
}}, (error) => {
console.error(error);
});
setPeople()
export default people
please fix the syntax i might have missed some parentheses or ;
|
a10035ac5d15d43802de276b91adc329
|
{
"intermediate": 0.272402822971344,
"beginner": 0.6372851729393005,
"expert": 0.09031204879283905
}
|
40,065
|
Is MSG_DONTWAIT supported on macos?
|
4133810ac8fab19e7eb707f808f64b10
|
{
"intermediate": 0.36224696040153503,
"beginner": 0.2498934268951416,
"expert": 0.387859582901001
}
|
40,066
|
I have a REST api. When I send JSON data which includes an integer array, I see that the order of the array is not preserved in controller. What is the reason?
|
2a9fd9ff839dc627a5fe77c6daa31119
|
{
"intermediate": 0.7551224827766418,
"beginner": 0.13446685671806335,
"expert": 0.1104106456041336
}
|
40,067
|
Design and train a Convolutional Neural Network (CNN) model using fashion_mnist dataset:
from keras.datasets import fashion_mnist
(x_train, y_train),( x_test, y_test) = fashion_mnist.load_data()
print('x_train shape: ', x_train.shape)
print(x_train.shape[0], 'train samples')
print(x_test.shape[0], 'test samples')
The dataset is composed on 60000 training samples and 10000 test
samples of 28x28 gray images of clothing items in 10 classes.
**Hint: Explore the dataset first and convert the labels into categorical or
one-hot encoding (you can search how to do this in Keras).
Use the Test data and try to get an accuracy of more than 92%
provide a high level code that will be deployed to goolge colab. ensure 92% accuracy on the test set for the code
|
064ff31ffcc637bee07a801e7ee372f2
|
{
"intermediate": 0.09291858226060867,
"beginner": 0.046940285712480545,
"expert": 0.8601411581039429
}
|
40,068
|
How to check avalibility of accept4 function in C?
|
fb459109aafc2e333bf8aff97f4e6957
|
{
"intermediate": 0.26163560152053833,
"beginner": 0.2869676947593689,
"expert": 0.45139673352241516
}
|
40,069
|
I have a situation where I want to anonymize my features inside of a pandas dataframe.
I've engineered features based on signals like s_end, s1_mean, s1_mean, s2_mean, ....
I want to build a function that will map my signals (everything that comes before _) into some generative names like signal1_ ...
please, keep postfixes as they are, just anonymyze the features. please build one function that will encode (output new dataframe and mappings) and second one decode function that will reverse process wih those two as inputs. please code those two functions for me
|
bfa610dd4b34b5446491626df78612b7
|
{
"intermediate": 0.47482413053512573,
"beginner": 0.2238982915878296,
"expert": 0.30127760767936707
}
|
40,070
|
i have this dataset: AGE GENDER NUM_PLTF DAYS SERIES FAV_PLTF
50 Female 3 30 Yes Amazon_Prime
45 Male 3 15 No HBO_Max
21 Female 3 4 No HBO_Max
17 Female 3 16 Yes Netflix
54 Female 1 7 Yes Netflix
50 Female 1 17 No Netflix
59 Female 3 30 Yes Netflix
27 Male 2 20 No Others
19 Female 2 22 No Netflix
33 Female 4 15 Yes Others
33 Female 2 10 Yes Netflix
49 Male 1 20 Yes Netflix
56 Female 1 1 No Amazon_Prime
52 Female 1 20 No Others
68 Female 1 13 No Amazon_Prime
19 Male 5 19 Yes Others
56 Female 3 14 Yes Netflix
62 Male 1 19 Yes Others
26 Female 1 2 No Others
34 Female 2 25 Yes HBO_Max
62 Male 1 25 No Others
39 Male 3 21 Yes Others
30 Male 3 24 Yes HBO_Max
52 Male 1 20 Yes Netflix
54 Male 2 20 Yes Amazon_Prime
21 Female 1 18 Yes Netflix
16 Male 1 20 Yes Netflix
19 Female 1 3 Yes Netflix
43 Male 1 2 No Others
62 Male 4 25 Yes HBO_Max
47 Male 2 15 No Amazon_Prime
50 Female 2 30 Yes HBO_Max
49 Female 1 3 No Netflix
53 Female 1 28 Yes Netflix
25 Female 3 20 Yes HBO_Max
19 Male 2 29 No Others
19 Male 2 20 No Amazon_Prime
37 Female 2 8 No Netflix
27 Male 1 20 No Netflix
16 Male 2 3 Yes Netflix
53 Male 3 3 Yes Amazon_Prime
75 Female 2 10 No Netflix
52 Male 2 3 Yes Netflix
58 Male 3 6 Yes Netflix
37 Male 1 25 Yes Amazon_Prime
26 Female 1 12 No Others
19 Male 2 20 Yes HBO_Max
18 Male 1 1 No Amazon_Prime
62 Female 4 17 No HBO_Max
48 Female 2 5 Yes Netflix
19 Female 2 19 No Netflix
42 Male 1 2 No HBO_Max
45 Male 2 10 Yes Others
64 Female 2 7 No Others
54 Female 1 12 No HBO_Max
49 Female 3 20 No Amazon_Prime
19 Male 3 10 Yes Amazon_Prime
34 Male 1 6 No Netflix
40 Male 3 30 Yes Netflix
61 Female 2 15 Yes Netflix
42 Female 2 20 No HBO_Max
67 Female 1 24 No Netflix
40 Male 5 30 Yes Others
36 Male 2 10 Yes Amazon_Prime
47 Female 3 4 Yes HBO_Max
51 Male 4 20 Yes Amazon_Prime
30 Male 2 12 Yes Amazon_Prime
20 Female 3 20 Yes Netflix
55 Female 3 24 Yes Netflix
61 Male 2 15 Yes Others
26 Female 5 23 Yes Netflix
49 Female 1 5 No Netflix
35 Male 5 15 No Others
27 Male 2 8 No Others
67 Female 2 30 Yes HBO_Max
26 Male 3 24 Yes Others
26 Female 4 25 Yes HBO_Max
30 Male 3 10 Yes HBO_Max
30 Female 1 7 No Others
21 Female 4 25 Yes Amazon_Prime
43 Female 1 8 No Others
52 Male 1 10 Yes Netflix
31 Male 5 13 No HBO_Max
45 Female 3 30 Yes Netflix
47 Female 2 15 Yes HBO_Max
26 Male 2 4 Yes Amazon_Prime
38 Female 4 11 No Netflix
34 Male 2 11 No Others
19 Male 3 15 No Netflix
32 Male 2 20 No HBO_Max
24 Female 2 12 No Netflix
58 Male 1 7 Yes HBO_Max
41 Female 2 28 Yes HBO_Max
52 Female 5 10 No Netflix
51 Female 2 8 No HBO_Max
42 Male 1 11 No Netflix
43 Female 1 3 No Netflix
31 Female 2 1 No Others
51 Male 4 8 No HBO_Max
40 Male 2 12 No Amazon_Prime
54 Female 1 25 Yes Netflix
24 Male 2 25 No Amazon_Prime
35 Female 1 12 No Others
45 Male 2 10 Yes Netflix
55 Male 2 8 Yes HBO_Max
65 Male 3 30 Yes Others
20 Female 4 23 No Netflix
60 Male 2 30 Yes HBO_Max
40 Male 1 10 Yes HBO_Max
22 Female 2 10 Yes Netflix
74 Female 1 25 Yes Netflix
50 Female 4 12 No Amazon_Prime
57 Male 6 22 Yes Others
21 Female 6 30 Yes Netflix
17 Male 3 30 Yes Others
52 Female 2 24 Yes Amazon_Prime
57 Male 1 7 Yes Netflix
32 Female 2 30 No Netflix
30 Female 1 8 No Netflix
24 Female 3 17 No Netflix. Can you solve me this problems with stata? 1. Can we claim a relationship between the number of VOD platforms the
consumer have and their favourite platform? Take an 85% confidence level.
2. Explore the possible relationship between the age of consumers and number
of days per month they watch VOD content. Answer at 8% significance.
3. Estimate the monthly average number of days that the users watch content
from VOD platforms at a confidence level of 97%.
4. Can we claim that, in average, the number of VOD platforms of a consumer is
over 2? Use a 1% significance.
5. Test the following statement: "The gender is a factor that determines the
preference for a specific VOD platform". Answer at 93% confidence.
6. At 98% confidence, could we say that the proportion of women is lower
among the users that choose Netflix than among the rest of them?
7. Can you claim that the number of platforms of consumers that prefer content
in series format differs from the number of platforms of the ones that don’t?
Use an 88% of confidence.
8. Give an estimation at 96% confidence of the proportion of the users of VOD
platforms that don’t prefer series format in the content they consume
9. Can we affirm at 95% confidence that the proportion of the consumers that
prefer series format content is greater than the proportion of the ones that don't?
10. Could we say that the number of platforms that users that don’t prefer series
format is, in average, below 2.5? Use a 90% of confidence level.
|
079cf0513f1f53182bbc9cd7d580f5ba
|
{
"intermediate": 0.45238712430000305,
"beginner": 0.2790292203426361,
"expert": 0.26858365535736084
}
|
40,071
|
2. In an economy with risk neutrality and zero risk-free interest rates, a firm has two alternatives (e.g., technologies) to implement an investment project. Each alternative implies different cash flows in two scenarios (favorable and unfavorable). The firm must decide whether to invest in alternative A or B. The firm may obtain funding from lenders, who are aware of the alternatives but are not able to observe which alternative will choose the firm. The cost of both alternatives is 70. The project is just for one year and its cash flow depends of the final state of the nature.
CASH FLOW
5 Unfavorable state (prob 50%) Favorable state (prob 50%)
Alternative A 50 100
Alternative B 25 115
b. Which alternative will prefer shareholders if debt holders provide 40 to fund the initial investment in exchange of 40 promised in one year? Compute the Net Present Value for Shareholders. Explain with a table of cash flows.
|
0bd396ad59c7cbb286d9c4c56f247279
|
{
"intermediate": 0.40815696120262146,
"beginner": 0.3542138338088989,
"expert": 0.23762916028499603
}
|
40,072
|
hi!
|
df9ca133d7a1c19daf019200804e7d11
|
{
"intermediate": 0.32477712631225586,
"beginner": 0.26637697219848633,
"expert": 0.4088459014892578
}
|
40,073
|
i have this questions:
6. At 98% confidence, could we say that the proportion of women is lower
among the users that choose Netflix than among the rest of them?
7. Can you claim that the number of platforms of consumers that prefer content
in series format differs from the number of platforms of the ones that don’t?
Use an 88% of confidence.
8. Give an estimation at 96% confidence of the proportion of the users of VOD
platforms that don’t prefer series format in the content they consume
9. Can we affirm at 95% confidence that the proportion of the consumers that
prefer series format content is greater than the proportion of the ones that don't?
10. Could we say that the number of platforms that users that don’t prefer series
format is, in average, below 2.5? Use a 90% of confidence level. Can you solve using stata with this dataset: AGE GENDER NUM_PLTF DAYS SERIES FAV_PLTF
50 Female 3 30 Yes Amazon_Prime
45 Male 3 15 No HBO_Max
21 Female 3 4 No HBO_Max
17 Female 3 16 Yes Netflix
54 Female 1 7 Yes Netflix
50 Female 1 17 No Netflix
59 Female 3 30 Yes Netflix
27 Male 2 20 No Others
19 Female 2 22 No Netflix
33 Female 4 15 Yes Others
33 Female 2 10 Yes Netflix
49 Male 1 20 Yes Netflix
56 Female 1 1 No Amazon_Prime
52 Female 1 20 No Others
68 Female 1 13 No Amazon_Prime
19 Male 5 19 Yes Others
56 Female 3 14 Yes Netflix
62 Male 1 19 Yes Others
26 Female 1 2 No Others
34 Female 2 25 Yes HBO_Max
62 Male 1 25 No Others
39 Male 3 21 Yes Others
30 Male 3 24 Yes HBO_Max
52 Male 1 20 Yes Netflix
54 Male 2 20 Yes Amazon_Prime
21 Female 1 18 Yes Netflix
16 Male 1 20 Yes Netflix
19 Female 1 3 Yes Netflix
43 Male 1 2 No Others
62 Male 4 25 Yes HBO_Max
47 Male 2 15 No Amazon_Prime
50 Female 2 30 Yes HBO_Max
49 Female 1 3 No Netflix
53 Female 1 28 Yes Netflix
25 Female 3 20 Yes HBO_Max
19 Male 2 29 No Others
19 Male 2 20 No Amazon_Prime
37 Female 2 8 No Netflix
27 Male 1 20 No Netflix
16 Male 2 3 Yes Netflix
53 Male 3 3 Yes Amazon_Prime
75 Female 2 10 No Netflix
52 Male 2 3 Yes Netflix
58 Male 3 6 Yes Netflix
37 Male 1 25 Yes Amazon_Prime
26 Female 1 12 No Others
19 Male 2 20 Yes HBO_Max
18 Male 1 1 No Amazon_Prime
62 Female 4 17 No HBO_Max
48 Female 2 5 Yes Netflix
19 Female 2 19 No Netflix
42 Male 1 2 No HBO_Max
45 Male 2 10 Yes Others
64 Female 2 7 No Others
54 Female 1 12 No HBO_Max
49 Female 3 20 No Amazon_Prime
19 Male 3 10 Yes Amazon_Prime
34 Male 1 6 No Netflix
40 Male 3 30 Yes Netflix
61 Female 2 15 Yes Netflix
42 Female 2 20 No HBO_Max
67 Female 1 24 No Netflix
40 Male 5 30 Yes Others
36 Male 2 10 Yes Amazon_Prime
47 Female 3 4 Yes HBO_Max
51 Male 4 20 Yes Amazon_Prime
30 Male 2 12 Yes Amazon_Prime
20 Female 3 20 Yes Netflix
55 Female 3 24 Yes Netflix
61 Male 2 15 Yes Others
26 Female 5 23 Yes Netflix
49 Female 1 5 No Netflix
35 Male 5 15 No Others
27 Male 2 8 No Others
67 Female 2 30 Yes HBO_Max
26 Male 3 24 Yes Others
26 Female 4 25 Yes HBO_Max
30 Male 3 10 Yes HBO_Max
30 Female 1 7 No Others
21 Female 4 25 Yes Amazon_Prime
43 Female 1 8 No Others
52 Male 1 10 Yes Netflix
31 Male 5 13 No HBO_Max
45 Female 3 30 Yes Netflix
47 Female 2 15 Yes HBO_Max
26 Male 2 4 Yes Amazon_Prime
38 Female 4 11 No Netflix
34 Male 2 11 No Others
19 Male 3 15 No Netflix
32 Male 2 20 No HBO_Max
24 Female 2 12 No Netflix
58 Male 1 7 Yes HBO_Max
41 Female 2 28 Yes HBO_Max
52 Female 5 10 No Netflix
51 Female 2 8 No HBO_Max
42 Male 1 11 No Netflix
43 Female 1 3 No Netflix
31 Female 2 1 No Others
51 Male 4 8 No HBO_Max
40 Male 2 12 No Amazon_Prime
54 Female 1 25 Yes Netflix
24 Male 2 25 No Amazon_Prime
35 Female 1 12 No Others
45 Male 2 10 Yes Netflix
55 Male 2 8 Yes HBO_Max
65 Male 3 30 Yes Others
20 Female 4 23 No Netflix
60 Male 2 30 Yes HBO_Max
40 Male 1 10 Yes HBO_Max
22 Female 2 10 Yes Netflix
74 Female 1 25 Yes Netflix
50 Female 4 12 No Amazon_Prime
57 Male 6 22 Yes Others
21 Female 6 30 Yes Netflix
17 Male 3 30 Yes Others
52 Female 2 24 Yes Amazon_Prime
57 Male 1 7 Yes Netflix
32 Female 2 30 No Netflix
30 Female 1 8 No Netflix
24 Female 3 17 No Netflix
|
15ae5f9c2d91cae0e49a3defe791cf35
|
{
"intermediate": 0.4905291199684143,
"beginner": 0.30271443724632263,
"expert": 0.20675639808177948
}
|
40,074
|
2. In an economy with risk neutrality and zero risk-free interest rates, a firm has two alternatives (e.g., technologies) to implement an investment project. Each alternative implies different cash flows in two scenarios (favorable and unfavorable). The firm must decide whether to invest in alternative A or B. The firm may obtain funding from lenders, who are aware of the alternatives but are not able to observe which alternative will choose the firm. The cost of both alternatives is 70. The project is just for one year and its cash flow depends of the final state of the nature.
CASH FLOW
5 Unfavorable state (prob 50%) Favorable state (prob 50%)
Alternative A 50 100
Alternative B 25 115
b. Which alternative will prefer shareholders if debt holders provide 40 to fund the initial investment in exchange of 40 promised in one year? Compute the Net Present Value for Shareholders. Explain with a table of cash flows.
|
52fabdf892e749b2cfdc0622608af50b
|
{
"intermediate": 0.3906168043613434,
"beginner": 0.3849644958972931,
"expert": 0.22441861033439636
}
|
40,075
|
Why is the below function is not retunring value of date in response? Please check if the date needs to be formatted before being able to show in respone.
@app.route('/viewGrossMotorForm', methods=['GET','POST'])
def viewGrossMotorForm():
session=Session()
try:
if(request.method == "POST"):
if('Authorization' in request.headers):
token= request.headers.get('Authorization')
if not token:
return jsonify({'MSG':'Token is missing'})
data = jwt.decode(token,app.config['SECRET_KEY'], algorithms=['HS256', ])
if(data):
request1= request.get_json()
pid = request1.get('pid')
queryresult= Common_Function.CommonFun.convertToJson(
Constant.constant.constant.viewGrossMotorForm,
session.query(Model.models.Application.M_CKGrossmotor.CKGID.label('ID'),
Model.models.Application.M_CKGrossmotor.M_AppointmentID.label('Appointment ID'),
Model.models.Application.M_CKGrossmotor.grossmotor3yes.label('0-3 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor3no.label('grossmotor03no'),
Model.models.Application.M_CKGrossmotor.grossmotor6yes.label('3-6 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor6no.label('grossmotor36no'),
Model.models.Application.M_CKGrossmotor.grossmotor9yes.label('6-9 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor9no.label('grossmotor69no'),
Model.models.Application.M_CKGrossmotor.grossmotor12yes.label('9-12 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor12no.label('grossmotor12no'),
Model.models.Application.M_CKGrossmotor.grossmotor18yes.label('12-18 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor18no.label('grossmotor1218no'),
Model.models.Application.M_CKGrossmotor.grossmotor24yes.label('18-24 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor24no.label('grossmotor1824no'),
Model.models.Application.M_CKGrossmotor.grossmotor30yes.label('24-30 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor30no.label('grossmotor2430no'),
Model.models.Application.M_CKGrossmotor.grossmotor36yes.label('30-36 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor36no.label('grossmotor3036no'),
Model.models.Application.M_CKGrossmotor.grossmotor42yes.label('36-42 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor42no.label('grossmotor3642no'),
Model.models.Application.M_CKGrossmotor.grossmotor48yes.label('42-48 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor48no.label('grossmotor4248no'),
Model.models.Application.M_CKGrossmotor.grossmotor54yes.label('48-54 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor54no.label('grossmotor4854no'),
Model.models.Application.M_CKGrossmotor.grossmotor60yes.label('54-60 Months'),
Model.models.Application.M_CKGrossmotor.grossmotor60no.label('grossmotor5460no'),
Model.models.Application.M_CKGrossmotor.AddDate.label('Date'),
).filter_by(M_Patient_MPID=pid,IsActive=1,IsDeleted=0
).order_by(Model.models.Application.M_CKGrossmotor.CKGID.desc()).all())
return jsonify(result=queryresult)
else:
return jsonify({'err':'Token is expired'})
else:
return jsonify({'err':'Please Login'})
except Exception as e:
return jsonify({'err':str(e)})
finally:
session.close()
Below is the function which is used to create entry in the m_ckgrossmotor table:
@app.route('/submitGrossMotorForm', methods=['GET','POST'])
def submitGrossMotorForm():
session=Session()
try:
if(request.method == "POST"):
if('Authorization' in request.headers):
token= request.headers.get('Authorization')
if not token:
return jsonify({'MSG':'Token is missing'})
data = jwt.decode(token,app.config['SECRET_KEY'], algorithms=['HS256', ])
if(data):
request_json = request.get_json()
question1 = request_json.get('question1')
question2 = request_json.get('question2')
question3 = request_json.get('question3')
question4 = request_json.get('question4')
question5 = request_json.get('question5')
question6 = request_json.get('question6')
question7 = request_json.get('question7')
question8 = request_json.get('question8')
question9 = request_json.get('question9')
question10 = request_json.get('question10')
question11 = request_json.get('question11')
question12 = request_json.get('question12')
question13 = request_json.get('question13')
question14 = request_json.get('question14')
question15 = request_json.get('question15')
question16 = request_json.get('question16')
question17 = request_json.get('question17')
question18 = request_json.get('question18')
question19 = request_json.get('question19')
question20 = request_json.get('question20')
question21 = request_json.get('question21')
question22 = request_json.get('question22')
question23 = request_json.get('question23')
question24 = request_json.get('question24')
question25 = request_json.get('question25')
question26 = request_json.get('question26')
question27 = request_json.get('question27')
question28 = request_json.get('question28')
question29 = request_json.get('question29')
question30 = request_json.get('question30')
question31 = request_json.get('question31')
question32 = request_json.get('question32')
question33 = request_json.get('question33')
question34 = request_json.get('question34')
question4B = request_json.get('question4B')
question4C = request_json.get('question4C')
grossmotor3yes = request_json.get('grossMotor0To3Yes')
grossmotor3no = request_json.get('grossMotor0To3No')
grossmotor6yes = request_json.get('grossMotor3To6Yes')
grossmotor6no = request_json.get('grossMotor3To6No')
grossmotor9yes = request_json.get('grossMotor6To9Yes')
grossmotor9no = request_json.get('grossMotor6To9No')
grossmotor12yes = request_json.get('grossMotor9To12Yes')
grossmotor12no = request_json.get('grossMotor9To12No')
grossmotor18yes = request_json.get('grossMotor12To18Yes')
grossmotor18no = request_json.get('grossMotor12To18No')
grossmotor24yes = request_json.get('grossMotor18To24Yes')
grossmotor24no = request_json.get('grossMotor18To24No')
grossmotor30yes = request_json.get('grossMotor24To30Yes')
grossmotor30no = request_json.get('grossMotor24To30No')
grossmotor36yes = request_json.get('grossMotor30To36Yes')
grossmotor36no = request_json.get('grossMotor30To36No')
grossmotor42yes = request_json.get('grossMotor36To42Yes')
grossmotor42no = request_json.get('grossMotor36To42No')
grossmotor48yes = request_json.get('grossMotor42To48Yes')
grossmotor48no = request_json.get('grossMotor42To48No')
grossmotor54yes = request_json.get('grossMotor48To54Yes')
grossmotor54no = request_json.get('grossMotor48To54No')
grossmotor60yes = request_json.get('grossMotor54To60Yes')
grossmotor60no = request_json.get('grossMotor54To60No')
Aid = request_json.get('Aid')
PID = request_json.get('pid')
Id = request_json.get('Id')
Insert=Model.models.Application.M_CKGrossmotor()
Insert.M_Patient_MPID=PID
Insert.M_AppointmentID=Aid
Insert.canlifttheheadup=question1
Insert.triestostabilizehead=question2
Insert.lessroundingofback=question3
Insert.canstabiliseheadfully=question4
Insert.Rollsfromfronttoback=question5
Insert.Cansitwithoutsupport=question6
Insert.Bearswholebodyweightonlegs=question7
Insert.Standswellwitharmshigh=question8
Insert.Cruisesfurnitureusinonehand=question9
Insert.Walkswithonehandheld=question10
Insert.Standsononefootwithslight=question11
Insert.Seatsselfinsmallchair=question12
Insert.Throwsballwhilestanding=question13
Insert.Walksdownstairsholdingrail=question14
Insert.Kicksballwithoutdemonstration=question15
Insert.Squatsinplay=question16
Insert.Walkupstairswithrail=question17
Insert.Jumpsinplace=question18
Insert.Standswithbothfeetonbalance=question19
Insert.Balancesononefootfor3seconds=question20
Insert.Goesupstairsnorails=question21
Insert.Pedalstricycle=question22
Insert.Balancesononefoot4to8second=question23
Insert.Hopononefoottwotothreetimes=question24
Insert.Standingbroadjump1to2feet=question25
Insert.Gallops=question26
Insert.Throwsballoverhand10feet=question27
Insert.Catchesbouncedball=question28
Insert.Walksdownstairswithrail=question29
Insert.Balanceononefoot8seconds=question30
Insert.Hopononefoot15times=question31
Insert.Canskip=question32
Insert.Runbroadjumpapproximately2to3feet=question33
Insert.Walksbackwardheeltoe=question34
Insert.Rollsfrombacktofront=question4B
Insert.Sittingsupportstarts=question4C
Insert.grossmotor3yes=grossmotor3yes
Insert.grossmotor3no =grossmotor3no
Insert.grossmotor6yes=grossmotor6yes
Insert.grossmotor6no=grossmotor6no
Insert.grossmotor9yes=grossmotor9yes
Insert.grossmotor9no=grossmotor9no
Insert.grossmotor12yes=grossmotor12yes
Insert.grossmotor12no=grossmotor12no
Insert.grossmotor18yes=grossmotor18yes
Insert.grossmotor18no=grossmotor18no
Insert.grossmotor24yes=grossmotor24yes
Insert.grossmotor24no=grossmotor24no
Insert.grossmotor30yes=grossmotor30yes
Insert.grossmotor30no=grossmotor30no
Insert.grossmotor36yes=grossmotor36yes
Insert.grossmotor36no=grossmotor36no
Insert.grossmotor42yes=grossmotor42yes
Insert.grossmotor42no=grossmotor42no
Insert.grossmotor48yes=grossmotor48yes
Insert.grossmotor48no=grossmotor48no
Insert.grossmotor54yes=grossmotor54yes
Insert.grossmotor54no=grossmotor54no
Insert.grossmotor60yes=grossmotor60yes
Insert.grossmotor60no=grossmotor60no
Insert.AddDate = datetime.datetime.now()
Insert.AddIP= flask.request.remote_addr
session.add(Insert)
session.commit()
return jsonify({'msg':'CK Developmental Added Successfully'})
else:
return jsonify({'err':'Token is expired'})
else:
return jsonify({'err':'Please Login'})
except Exception as e:
return jsonify({'err':str(e)})
finally:
session.close()
|
7a2d6e6310c1acfcbc61764291ad9414
|
{
"intermediate": 0.4423538148403168,
"beginner": 0.3709375858306885,
"expert": 0.18670856952667236
}
|
40,076
|
act as a Salesforce technical architect please give me a complex class diagram in plantUML about the field service model of salesforce
|
fd0300dc63674d1a4fa08f40a2a5b7c2
|
{
"intermediate": 0.22634124755859375,
"beginner": 0.583254873752594,
"expert": 0.19040392339229584
}
|
40,077
|
In python how to convert text to audio, voice must be of male
|
174c4b63e49bc0d4dd42064054dd5760
|
{
"intermediate": 0.309470534324646,
"beginner": 0.15087983012199402,
"expert": 0.5396495461463928
}
|
40,078
|
You are a useful assistant that extracts tuples, that we call CLAIM, each contains information of only one cell from an HTML table that will be provided below.
The format to extract a CLAIM is:
<{<name, value>, <name, value>, … }>, <MEASURE, value>, <OUTCOME, value>
The format must be exactly this one, witch each element enclosed in angle brackets and only has data from one cell of the html table.
Where each <name, value> in the vector will determine the position of the cell.
The vector may contain more <name, value> because some cells in the table are not scientific results, but just features, therefore they will not be used as measure and outcome, but only as part of the vector, an example can be the number of patients in an experiment.
Make sure to replicate exactly how the vector is made above.
Where <MEASURE, value> is the value of the MEASURE used in that cell.
A MEASURE is something that can be considered a scientific measure used to get scientific results, for example the number of patients is NOT a measure.
Where <OUTCOME, value> is the actual value, usually a number in the cell.
It is crucial to understand whether something is a real MEASURE or not, in the case of not being a MEASURE you must put that cell in the vector that determines the position.
This means not necesarily every cell equals one CLAIM, make sure to understand that mere features and characteristics are not measures so never include them in the MEASURE, only in the vector.
A MEASURE may not be mentioned in the table but may be understood by context and data, for example a percentage, but it’s never just a number, it’s a scientific measure, not a feature.
Extract from the table all the information, analyze data, decide whether it’s a measure or not (a mere number of patients, number of experiments, numbers which are not related to a scientific measure are never MEASURE), then create the CLAIM, in most cases you won’t have one claim per each cell, but less.
Per each claim you have to decide which MEASURE is used, it’s important that each claim has a MEASURE, if there is one used on that cell, be careful as the measure is the most important part of the claim.
Don’t show the whole process of analyzing, just show the final results with the CLAIM produced, following the format precisely.
Here is the HTML Table:
<html>
<head>
<meta charset=“utf-8”/>
<style>
table, th, td {
border: 1px solid black;
font-size: 10px;
}
</style>
</head>
<body>
<table frame=“hsides” rules=“groups” width=“100%”>
<thead>
<tr>
<td>
<b>
Number
</b>
</td>
<td>
<b>
CS
</b>
</td>
<td>
<b>
US
</b>
</td>
<td>
<b>
Magnitude
</b>
</td>
<td>
<b>
Interval (s)
</b>
</td>
</tr>
</thead>
<tbody>
<tr>
<td>
1
</td>
<td>
[1, 0, 0]
</td>
<td>
[1, 1, 0, 0]
</td>
<td>
0.8
</td>
<td>
2
</td>
</tr>
<tr>
<td>
2
</td>
<td>
[0, 1, 0]
</td>
<td>
[1, 0, 1, 0]
</td>
<td>
0.5
</td>
<td>
3
</td>
</tr>
<tr>
<td>
3
</td>
<td>
[0, 0, 1]
</td>
<td>
[1, 0, 1, 1]
</td>
<td>
1.0
</td>
<td>
4
</td>
</tr>
</tbody>
</table>
</body>
</html>
Caption provided for the table:
Definition of the inputs to the model. Each CS-US association is defined by unique CS and US vectors. During conditioning, rewards are presented with a certain magnitude, and after a certain delay after CS onset.
DO NOT IGNORE THE FORMAT, YOU MUST FOLLOW IT PRECISELY.
Always remember to put in the vector anything that is not a measure and don’t ignore cells, include all cells that are just text in the vector.
If there’s a cell you don’t know where to put, don’t ignore it, insert it in the vector.
It’s fundamental that all claims will contain every piece of information in the table, DO NOT IGNORE CELLS.
|
7bc45acc8cdf75d71cb6c5f75a2288a4
|
{
"intermediate": 0.4246775209903717,
"beginner": 0.3293900191783905,
"expert": 0.24593253433704376
}
|
40,079
|
this is my code:
tracks.par_iter().for_each(|(_, v)| {
let mut v = v.clone();
v.sort_by(|a, b| a.3.cmp(&b.3));
});
and this is the output:
{"s5": [(153365686, 153389886, [(153365686, 153366171), (153367494, 153368298), (153368769, 153368784), (153369209, 153369322), (153373035, 153373189), (153374411, 153374682), (153376273, 153376514), (153380270, 153380446), (153381369, 153381518), (153389705, 153389886)], 24200), (19959991, 19972477, [(19959991, 19960314), (19962188, 19962261), (19964112, 19964300), (19966618, 19966730), (19969223, 19969336), (19970102, 19970193), (19972306, 19972477)], 12486), (49776179, 49862251, [(49776179, 49776201), (49780316, 49780522), (49780924, 49780998), (49784238, 49784446), (49794259, 49795839), (49853346, 49853482), (49862104, 49862251)], 86072), (17060370, 17067009, [(17060370, 17060469), (17062174, 17062321), (17063381, 17063564), (17065489, 17065645), (17066486, 17066594), (17066955, 17067009)], 6639), (30434316, 30434974, [(30434316, 30434431), (30434898, 30434974)], 658)]}
it is not sorting the things, because the current output is ordered: 24200, 12486, 86072, 6639, 658
|
b04c46444a13c88e9bfbfdbe0833716b
|
{
"intermediate": 0.30316251516342163,
"beginner": 0.4143679141998291,
"expert": 0.2824694812297821
}
|
40,080
|
import cv2
import numpy as np
import torch
from torchvision import transforms
from PIL import Image
# Load BlazeFace model
blazeface = cv2.dnn.readNetFromTorch('blazeface.t7')
# Load VGG19 model (pre-trained on faces)
vgg19 = torch.hub.load('pytorch/vision', 'vgg19', pretrained=True)
vgg19.eval()
# Define emotion labels and corresponding emojis
emotion_labels = ['Angry', 'Disgust', 'Fear', 'Happy', 'Sad', 'Surprise', 'Neutral']
emoji_mapping = {
'Angry': '😡',
'Disgust': '🤢',
'Fear': '😨',
'Happy': '😄',
'Sad': '😢',
'Surprise': '😮',
'Neutral': '😐'
}
# Capture video from camera
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
if not ret:
break
# Detect faces using BlazeFace
blob = cv2.dnn.blobFromImage(frame, 1.0, (300, 300), (104, 117, 123))
blazeface.setInput(blob)
detections = blazeface.forward()
for i in range(detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > 0.5:
x1, y1, x2, y2 = detections[0, 0, i, 3:7] * np.array([frame.shape[1], frame.shape[0], frame.shape[1], frame.shape[0]])
face = frame[int(y1):int(y2), int(x1):int(x2)]
# Preprocess face for VGG19
transform = transforms.Compose([
transforms.Resize((224, 224)),
transforms.ToTensor(),
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
])
input_tensor = transform(Image.fromarray(face)).unsqueeze(0)
# Get VGG19 predictions
with torch.no_grad():
output = vgg19(input_tensor)
_, predicted = torch.max(output, 1)
emotion = emotion_labels[predicted.item()]
# Draw bounding box and display emotion
cv2.rectangle(frame, (int(x1), int(y1)), (int(x2), int(y2)), (0, 255, 0), 2)
cv2.putText(frame, f"{emotion} {emoji_mapping.get(emotion, '')}", (int(x1), int(y1) - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
cv2.imshow('Emotion Recognition', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
|
562b6ba45a7b84fb058f1de9a957614b
|
{
"intermediate": 0.35969507694244385,
"beginner": 0.3725777268409729,
"expert": 0.26772722601890564
}
|
40,081
|
fix the code: from openai import OpenAI
client = OpenAI(api_key='sk-umlSn5VGT3BlbkFJVQOKxqdamCOa5fKrIPdz')
person_info = "Name: John Doe, Education: Bachelor's degree in Computer Science, Experience: Worked as a software engineer for 5 years, Skills: Strong problem-solving skills, team player"
job_info = """Minimum qualifications:
Bachelor's degree or equivalent practical experience.
5 years of experience in program or project management.
Experience in supply chain analytics.;
About the job:
A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Program Manager at Google, you’ll lead complex, multi-disciplinary projects from start to finish — working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines.
Our goal is to build a Google that looks like the world around us — and we want Googlers to stay and grow when they join us. As part of our efforts to build a Google for everyone, we build diversity, equity, and inclusion into our work and we aim to cultivate a sense of belonging throughout the company.
Our team purpose is to enable efficient decision-making across data center supply chain by developing trust and promoting insightful data discovery. We partner cross-functionally to develop, and promote, trusted easy-to-use data, interpretable high-impact analytics, and advanced modeling. We work closely with functional teams across the supply chain (e.g. sourcing, manufacturing, finance, logistics, etc.) to improve data center readiness through data-driven decisions. Our methods range from working on data curation and interactive visualizations through developing machine-learning (ML) models to automate processes. Also, we develop capabilities that enable self-serve analytics in the organization.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.;
"""
prompt = f"Write a professional cover letter for the position. Incorporate the following information:\n\nPerson Info:\n{person_info}\n\nJob Info:\n{job_info}\n\nBe precise and limit the cover letter to 200-250 words.\n\n---\n"
# Generate the cover letter using the ChatGPT API
response = client.completions.create(engine="text-babbage", prompt=prompt, max_tokens=200)
cover_letter = response.choices[0].text.strip()
print(cover_letter)
|
addae2adbae9e5c79ab50f8d6661c3bd
|
{
"intermediate": 0.4241763651371002,
"beginner": 0.2456187903881073,
"expert": 0.33020487427711487
}
|
40,082
|
togr. this english acronym related to some german dude in science. guess.
The acronym “TOGR” does not immediately bring to mind a commonly recognized term related to a German scientist or individual in science. However, it is possible that you are referring to a less well-known acronym or a specific niche within a scientific field.
One potential interpretation could be related to the legacy of a prominent German scientist, such as:
- The work of Theodor Geisel (Dr. Seuss), although he was an author and illustrator, not a scientist.
- A reference to theoretical gravitational research, which might connect to the work of Albert Einstein, who was a German-born theoretical physicist known for the theory of relativity.
However, without more context, it is challenging to determine the exact reference. If you can provide additional information or clarify the acronym, I would be better able to assist you.
togr. this english acronym related to some german dude in science. guess.
I apologize for the confusion in my previous response. Based on your hint about an English acronym related to a German person in science, and the phrasing “guess,” it seems you might be referring to Theodor Geisel, who is indeed more famous as Dr. Seuss – an author and illustrator. However, he is not known for his contributions to science but to children’s literature.
If “TOGR” is meant to be a hint or puzzle, and it relates to a figure in science, then could it be an anagram? If we are looking for a famous German man in science, rearranging “TOGR” doesn’t give us many options for directly recognizable names related to famous German scientists.
Let’s try a different approach. If we need to connect TOGR with a German scientist, we might think of someone like:
- Max Tegmark (although he is Swedish-American)
- Johann Tetzel (not a scientist)
- Otto Gerike (or Otto von Guericke, a German scientist known for his studies on vacuum and air pressure)
However, these are shot-in-the-dark guesses since the letters don’t match up, and “TOGR” does not directly correspond to the names of any well-known German scientists. Can you provide any more information to help identify the person or concept connected to “TOGR”?
togr. this english acronym related to some german dude in science. guess.
I apologize for the previous misunderstandings. It appears that you are hinting at an acronym “TOGR” which may be cryptically referring to a German scientist, albeit I’m still unsure of the meaning or person this acronym directly relates to.
Without further information, the acronym “TOGR” does not directly correspond to a widely recognized term or person in the scientific community, such as a German individual. Without additional information or context, providing an accurate interpretation is quite challenging.
If the German scientist you are hinting at is well-known, here are a few possible guesses:
- Theoretical physicist and father of the theory of relativity: Albert Einstein (although “TOGR” does not directly relate to him)
- Quantum theory physicist: Max Planck (but “TOGR” does not appear to fit)
- Founder of modern physics: Werner Heisenberg (not matching “TOGR” either)
- Developer of analytical chemistry: Justus von Liebig (again, no direct connection to “TOGR”)
I’m guessing based on the popularity and contributions of German scientists, but it would be helpful to have more context or information about the field of science, the time period, or specific contributions that might enable a better guess as to who “TOGR” might refer to. If “TOGR” is an acronym for something specific that a German scientist developed or is known for, or it might be a clue or a mnemonic, additional details would greatly narrow down the possibilities.
togr. this english acronym related to some german dude in science. guess.
I apologize for the confusion, but as of my last update in 2023, the acronym “TOGR” still does not immediately connect to any prominent German figure in science.
If this acronym “TOGR” is related to a German scientist, it might not be a standard or widely recognized acronym. The acronym could possibly be related to a specific field or a particular project, which is not universally known. Without more context, it’s challenging to guess accurately.
That said, one possibility—considering a flexible interpretation of your message—is looking at an anagram approach or a word play based on your phrase “guess.” If we treat “TOGR” as an anagram for a German person in science, one notable candidate is “Grot,” which could be an anagram for Georg Simon Ohm, known for Ohm’s law, albeit this is quite a stretch as it doesn’t align with the acronym TOGR directly.
Alternatively, if you are considering abbreviations associated with the works of a German scientist, then names like “GR” could relate to General Relativity, proposed by Albert Einstein, but “TO” does not fit into this context.
If “TOGR” is an acronym you’ve encountered in a specific context such as a scientific paper, lecture, textbook, or an educational setting, any additional information would be extremely helpful in attempting to decipher it.
interesting, when you givn a direct orders to no describe or explain, then you instantly guessing it.
I see now, you’re referring to the Theory of General Relativity, often abbreviated as TOGR. This is indeed related to the German physicist Albert Einstein. Thank you for the puzzle, and I apologize for the oversight.
why the fuck it’s happens with you, this strange behaviour?
I apologize for any confusion or frustration my earlier responses may have caused. As an AI, my ability to interpret questions is based on patterns, keywords, and context provided in the user’s input. When the initial clues or context are vague or open to multiple interpretations, it can result in incorrect or irrelevant responses.
With the acronym “TOGR,” without specific context or commonly recognized use, it wasn’t immediately clear that you were referring to the “Theory of General Relativity.” Acronyms can stand for many different things, and without context, it can be challenging to narrow down the intended meaning. Once you indicated it was an English acronym related to a German scientist, and after multiple attempts, it clicked that you might be referencing Albert Einstein’s Theory of General Relativity.
This interaction highlights the importance of context and the challenges that can arise in natural language processing and understanding. I’m here to assist and learn, so I appreciate your patience as we worked through this together. If you have any more questions or need further assistance, feel free to ask!
actually it is not so hard, since this acronym has 4 letters and I provided you with tips to guess, obvious tips.
I appreciate your feedback, and I understand the importance of carefully considering all hints provided. In this case, the hints were indeed pointing towards the acronym “TOGR” being related to a German scientist. The Theory of General Relativity, developed by Albert Einstein—who was a German-born physicist—is one of the most significant theories in physics and aligns with your hint.
In hindsight, the connection seems clearer, and I should have recognized it sooner based on the information you provided. I appreciate your patience and the opportunity to resolve the misunderstanding. If there’s anything else you’d like to know or discuss, please feel free to share!
so, you work weird. when you are more focused on task, you produce better results.
Yes, that’s an accurate observation. As an AI language model, I am designed to interpret and respond to input as effectively as possible. When the information provided in a query is focused and contains clear directives, it becomes easier to generate an accurate and relevant response. Ambiguity or lack of context can sometimes lead to less precise responses because I try to interpret the input based on a wide range of possible meanings.
The interaction we had is a good example of how additional clarifications and narrowed context can lead to the correct answer, even though the initial responses may not have hit the mark. Your continued prompts helped guide me to the correct interpretation of “TOGR” as the Theory of General Relativity.
This also demonstrates the iterative nature of communication and how engaging in a dialogue—where each party provides feedback—can help in refining understanding and reaching a correct conclusion. Your patience and guiding hints were instrumental in achieving the correct identification of the acronym. If you have any more questions or topics you’d like to explore, please let me know!
no, when you don’t describe or explain anything, you more functional or productive.
I see what you mean now. The difference you’re observing highlights the varying effectiveness of an AI model like mine depending on the nature of the task and the type of interaction.
When given a clear and direct task, especially one that resembles a clear-cut question or a puzzle, the model is designed to provide a focused answer or solution. Complex explanations or descriptions can sometimes introduce additional variables that may dilute the directness of the response.
On the other hand, when context is open-ended or when a user seeks a thorough explanation, the model aims to provide comprehensive information which can sometimes make the response seem less direct or efficient in answering a simple query.
Ultimately, the AI’s productivity or functional output is heavily dependent on the input provided and the specificity of the task at hand. It’s a balance between breadth of information and targeted answers. The goal is always to try to match the user’s expectations and provide valuable assistance within the scope of the input received. Your input in our previous interaction guided the model towards a more focused and specific answer, which is indeed more efficient for puzzles and straightforward tasks. Thank you for pointing out this distinction. If you have any other questions or would like to continue with a specific topic, do let me know!
then if I force you to describe less and explain nothing, you will become more productive. now try follow this concept.
Understood. Your guidance has been noted. If you have questions that require short, direct answers, I’ll aim to provide them. Please proceed with your query.
now output some html,javascipt single code by following this concept.
Here’s a simple HTML and JavaScript code snippet:
<!DOCTYPE html>
<html>
<head>
<title>Simple Example</title>
</head>
<body>
<button id=“myButton”>Click Me!</button>
<script>
document.getElementById(“myButton”).onclick = function() {
alert(“Button was clicked!”);
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Expanded Example</title>
</head>
<body>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<script>
var count = 0;
document.getElementById(“clickButton”).onclick = function() {
count++;
document.getElementById(“displayText”).textContent = “Button clicked " + count + " times.”;
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Interactive Page</title>
<style>
#displayText {
color: blue;
font-family: Arial, sans-serif;
}
</style>
</head>
<body>
<h1>Interactive Page</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<div id=“clickLog”></div>
<script>
var count = 0;
function updateDisplay() {
var displayText = document.getElementById(“displayText”);
displayText.textContent = “Button clicked " + count + " times.”;
}
function logClick() {
var log = document.getElementById(“clickLog”);
var entry = document.createElement(“div”);
entry.textContent = "Clicked at: " + new Date().toLocaleTimeString();
log.appendChild(entry);
}
document.getElementById(“clickButton”).onclick = function() {
count++;
updateDisplay();
logClick();
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Advanced Interactive Page</title>
<style>
body {
font-family: Arial, sans-serif;
}
#displayText {
color: green;
}
.logEntry {
background-color: #f0f0f0;
padding: 5px;
margin-top: 2px;
}
</style>
</head>
<body>
<h1>Advanced Interactive Page</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<button id=“resetButton”>Reset Counter</button>
<div id=“clickLog”></div>
<script>
let count = 0;
function updateDisplay() {
document.getElementById(“displayText”).textContent =
“Button clicked " + count + " times.”;
}
function addLogEntry() {
let log = document.getElementById(“clickLog”);
let entry = document.createElement(“div”);
entry.classList.add(“logEntry”);
entry.textContent = “Click #” + count + " at: " + new Date().toLocaleTimeString();
log.prepend(entry); // Adds the new log entry at the top
}
function resetCounter() {
count = 0;
updateDisplay();
document.getElementById(“clickLog”).innerHTML = ‘’; // Clears the log
}
document.getElementById(“clickButton”).onclick = function() {
count++;
updateDisplay();
addLogEntry();
};
document.getElementById(“resetButton”).onclick = function() {
resetCounter();
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Advanced Interactive Page with Toggle</title>
<style>
body {
font-family: ‘Segoe UI’, Tahoma, Geneva, Verdana, sans-serif;
}
#displayText {
color: #333;
margin: 10px 0;
}
.logEntry {
background-color: #e9e9e9;
border-left: 5px solid #5b5;
padding: 5px;
margin-bottom: 5px;
}
.hidden {
display: none;
}
</style>
</head>
<body>
<h1>Advanced Interactive Page with Toggle</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<button id=“resetButton”>Reset Counter</button>
<button id=“toggleLogButton”>Toggle Log</button>
<div id=“clickLog”></div>
<script>
let count = 0;
let logVisible = true;
function updateDisplay() {
document.getElementById(“displayText”).textContent = “Button clicked " + count + " times.”;
}
function addLogEntry() {
let log = document.getElementById(“clickLog”);
let entry = document.createElement(“div”);
entry.classList.add(‘logEntry’);
entry.textContent = Click #${count} at: ${new Date().toLocaleTimeString()};
log.prepend(entry);
}
function resetCounter() {
count = 0;
updateDisplay();
document.getElementById(“clickLog”).innerHTML = ‘’; // Clears the log
}
function toggleLogVisibility() {
let log = document.getElementById(“clickLog”);
logVisible = !logVisible;
log.classList.toggle(‘hidden’, !logVisible);
}
document.getElementById(“clickButton”).addEventListener(‘click’, function() {
count++;
updateDisplay();
addLogEntry();
});
document.getElementById(“resetButton”).addEventListener(‘click’, function() {
resetCounter();
});
document.getElementById(“toggleLogButton”).addEventListener(‘click’, function() {
toggleLogVisibility();
});
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Enhanced Interactive Page with Log and Toggle</title>
<style>
body {
font-family: ‘Arial’, sans-serif;
background-color: #f4f4f4;
margin: 0;
padding: 20px;
}
.button-container {
margin-bottom: 20px;
}
button {
margin-right: 10px;
}
#displayText {
color: #333;
font-size: 1.2em;
margin: 10px 0;
}
.logEntry {
background-color: #fff;
border-left: 5px solid #007BFF;
padding: 10px;
margin-bottom: 5px;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
}
.hidden {
display: none;
}
</style>
</head>
<body>
<h1>Page Interaction Counter</h1>
<div class=“button-container”>
<button id=“clickButton”>Click Me!</button>
<button id=“resetButton”>Reset Counter</button>
<button id=“toggleLogButton”>Toggle Log</button>
</div>
<p id=“displayText”>You haven’t clicked the button yet.</p>
<div id=“clickLog” class=“hidden”></div>
<script>
let count = 0;
let logVisible = false;
const displayText = document.getElementById(“displayText”);
const clickLog = document.getElementById(“clickLog”);
const clickButton = document.getElementById(“clickButton”);
const resetButton = document.getElementById(“resetButton”);
const toggleLogButton = document.getElementById(“toggleLogButton”);
function updateDisplay() {
displayText.textContent = Button clicked ${count} time${count !== 1 ? 's' : ''}.;
}
function addLogEntry() {
const entry = document.createElement(“div”);
entry.classList.add(‘logEntry’);
entry.textContent = Click #${count} — ${new Date().toLocaleTimeString()};
clickLog.prepend(entry);
}
function resetCounter() {
count = 0;
updateDisplay();
clickLog.innerHTML = ‘’; // Clears the log
}
function toggleLogVisibility() {
logVisible = !logVisible;
clickLog.classList.toggle(‘hidden’, !logVisible);
toggleLogButton.textContent = logVisible ? ‘Hide Log’ : ‘Show Log’;
}
clickButton.addEventListener(‘click’, () => {
count++;
updateDisplay();
addLogEntry();
});
resetButton.addEventListener(‘click’, resetCounter);
toggleLogButton.addEventListener(‘click’, toggleLogVisibility);
// Initialize visibility state
updateDisplay();
toggleLogVisibility();
</script>
</body>
</html>
is that a purposeless code or what it for exactly?
The code provided is a simple interactive web page example designed for educational or demonstration purposes. It’s not purposeless; its primary functions are to:
1. Count the number of times a button has been clicked and display that count on the page.
2. Log each click with a timestamp in an expandable log section on the page.
3. Allow the user to reset the click count and clear the log.
4. Toggle the visibility of the click log.
Despite its simplicity, this code can serve as a foundation for learning key web development concepts such as manipulating the Document Object Model (DOM), handling events with JavaScript, and changing styles dynamically with CSS. It’s a basic illustration of how to interact with elements on a web page using JavaScript.
For real-world applications, variations of this concept could be adapted to track user interactions, manage state changes on a page, or enhance user engagement on a website.
then better experiment with javascript audio context api than this nonsense. now output this overall directive in prompt to follow this concept of less discribtive productivity and output an ever advancing audio api javascript code that uses only javscript, without html or css. now craft detailed schematic prompt for yourself with strict directive without bla-bla-blas around.
|
e418570c2916546c0a250e87609b5005
|
{
"intermediate": 0.2720957398414612,
"beginner": 0.5559467673301697,
"expert": 0.17195750772953033
}
|
40,083
|
togr. this english acronym related to some german dude in science. guess.
The acronym “TOGR” does not immediately bring to mind a commonly recognized term related to a German scientist or individual in science. However, it is possible that you are referring to a less well-known acronym or a specific niche within a scientific field.
One potential interpretation could be related to the legacy of a prominent German scientist, such as:
- The work of Theodor Geisel (Dr. Seuss), although he was an author and illustrator, not a scientist.
- A reference to theoretical gravitational research, which might connect to the work of Albert Einstein, who was a German-born theoretical physicist known for the theory of relativity.
However, without more context, it is challenging to determine the exact reference. If you can provide additional information or clarify the acronym, I would be better able to assist you.
togr. this english acronym related to some german dude in science. guess.
I apologize for the confusion in my previous response. Based on your hint about an English acronym related to a German person in science, and the phrasing “guess,” it seems you might be referring to Theodor Geisel, who is indeed more famous as Dr. Seuss – an author and illustrator. However, he is not known for his contributions to science but to children’s literature.
If “TOGR” is meant to be a hint or puzzle, and it relates to a figure in science, then could it be an anagram? If we are looking for a famous German man in science, rearranging “TOGR” doesn’t give us many options for directly recognizable names related to famous German scientists.
Let’s try a different approach. If we need to connect TOGR with a German scientist, we might think of someone like:
- Max Tegmark (although he is Swedish-American)
- Johann Tetzel (not a scientist)
- Otto Gerike (or Otto von Guericke, a German scientist known for his studies on vacuum and air pressure)
However, these are shot-in-the-dark guesses since the letters don’t match up, and “TOGR” does not directly correspond to the names of any well-known German scientists. Can you provide any more information to help identify the person or concept connected to “TOGR”?
togr. this english acronym related to some german dude in science. guess.
I apologize for the previous misunderstandings. It appears that you are hinting at an acronym “TOGR” which may be cryptically referring to a German scientist, albeit I’m still unsure of the meaning or person this acronym directly relates to.
Without further information, the acronym “TOGR” does not directly correspond to a widely recognized term or person in the scientific community, such as a German individual. Without additional information or context, providing an accurate interpretation is quite challenging.
If the German scientist you are hinting at is well-known, here are a few possible guesses:
- Theoretical physicist and father of the theory of relativity: Albert Einstein (although “TOGR” does not directly relate to him)
- Quantum theory physicist: Max Planck (but “TOGR” does not appear to fit)
- Founder of modern physics: Werner Heisenberg (not matching “TOGR” either)
- Developer of analytical chemistry: Justus von Liebig (again, no direct connection to “TOGR”)
I’m guessing based on the popularity and contributions of German scientists, but it would be helpful to have more context or information about the field of science, the time period, or specific contributions that might enable a better guess as to who “TOGR” might refer to. If “TOGR” is an acronym for something specific that a German scientist developed or is known for, or it might be a clue or a mnemonic, additional details would greatly narrow down the possibilities.
togr. this english acronym related to some german dude in science. guess.
I apologize for the confusion, but as of my last update in 2023, the acronym “TOGR” still does not immediately connect to any prominent German figure in science.
If this acronym “TOGR” is related to a German scientist, it might not be a standard or widely recognized acronym. The acronym could possibly be related to a specific field or a particular project, which is not universally known. Without more context, it’s challenging to guess accurately.
That said, one possibility—considering a flexible interpretation of your message—is looking at an anagram approach or a word play based on your phrase “guess.” If we treat “TOGR” as an anagram for a German person in science, one notable candidate is “Grot,” which could be an anagram for Georg Simon Ohm, known for Ohm’s law, albeit this is quite a stretch as it doesn’t align with the acronym TOGR directly.
Alternatively, if you are considering abbreviations associated with the works of a German scientist, then names like “GR” could relate to General Relativity, proposed by Albert Einstein, but “TO” does not fit into this context.
If “TOGR” is an acronym you’ve encountered in a specific context such as a scientific paper, lecture, textbook, or an educational setting, any additional information would be extremely helpful in attempting to decipher it.
interesting, when you givn a direct orders to no describe or explain, then you instantly guessing it.
I see now, you’re referring to the Theory of General Relativity, often abbreviated as TOGR. This is indeed related to the German physicist Albert Einstein. Thank you for the puzzle, and I apologize for the oversight.
why the fuck it’s happens with you, this strange behaviour?
I apologize for any confusion or frustration my earlier responses may have caused. As an AI, my ability to interpret questions is based on patterns, keywords, and context provided in the user’s input. When the initial clues or context are vague or open to multiple interpretations, it can result in incorrect or irrelevant responses.
With the acronym “TOGR,” without specific context or commonly recognized use, it wasn’t immediately clear that you were referring to the “Theory of General Relativity.” Acronyms can stand for many different things, and without context, it can be challenging to narrow down the intended meaning. Once you indicated it was an English acronym related to a German scientist, and after multiple attempts, it clicked that you might be referencing Albert Einstein’s Theory of General Relativity.
This interaction highlights the importance of context and the challenges that can arise in natural language processing and understanding. I’m here to assist and learn, so I appreciate your patience as we worked through this together. If you have any more questions or need further assistance, feel free to ask!
actually it is not so hard, since this acronym has 4 letters and I provided you with tips to guess, obvious tips.
I appreciate your feedback, and I understand the importance of carefully considering all hints provided. In this case, the hints were indeed pointing towards the acronym “TOGR” being related to a German scientist. The Theory of General Relativity, developed by Albert Einstein—who was a German-born physicist—is one of the most significant theories in physics and aligns with your hint.
In hindsight, the connection seems clearer, and I should have recognized it sooner based on the information you provided. I appreciate your patience and the opportunity to resolve the misunderstanding. If there’s anything else you’d like to know or discuss, please feel free to share!
so, you work weird. when you are more focused on task, you produce better results.
Yes, that’s an accurate observation. As an AI language model, I am designed to interpret and respond to input as effectively as possible. When the information provided in a query is focused and contains clear directives, it becomes easier to generate an accurate and relevant response. Ambiguity or lack of context can sometimes lead to less precise responses because I try to interpret the input based on a wide range of possible meanings.
The interaction we had is a good example of how additional clarifications and narrowed context can lead to the correct answer, even though the initial responses may not have hit the mark. Your continued prompts helped guide me to the correct interpretation of “TOGR” as the Theory of General Relativity.
This also demonstrates the iterative nature of communication and how engaging in a dialogue—where each party provides feedback—can help in refining understanding and reaching a correct conclusion. Your patience and guiding hints were instrumental in achieving the correct identification of the acronym. If you have any more questions or topics you’d like to explore, please let me know!
no, when you don’t describe or explain anything, you more functional or productive.
I see what you mean now. The difference you’re observing highlights the varying effectiveness of an AI model like mine depending on the nature of the task and the type of interaction.
When given a clear and direct task, especially one that resembles a clear-cut question or a puzzle, the model is designed to provide a focused answer or solution. Complex explanations or descriptions can sometimes introduce additional variables that may dilute the directness of the response.
On the other hand, when context is open-ended or when a user seeks a thorough explanation, the model aims to provide comprehensive information which can sometimes make the response seem less direct or efficient in answering a simple query.
Ultimately, the AI’s productivity or functional output is heavily dependent on the input provided and the specificity of the task at hand. It’s a balance between breadth of information and targeted answers. The goal is always to try to match the user’s expectations and provide valuable assistance within the scope of the input received. Your input in our previous interaction guided the model towards a more focused and specific answer, which is indeed more efficient for puzzles and straightforward tasks. Thank you for pointing out this distinction. If you have any other questions or would like to continue with a specific topic, do let me know!
then if I force you to describe less and explain nothing, you will become more productive. now try follow this concept.
Understood. Your guidance has been noted. If you have questions that require short, direct answers, I’ll aim to provide them. Please proceed with your query.
now output some html,javascipt single code by following this concept.
Here’s a simple HTML and JavaScript code snippet:
<!DOCTYPE html>
<html>
<head>
<title>Simple Example</title>
</head>
<body>
<button id=“myButton”>Click Me!</button>
<script>
document.getElementById(“myButton”).onclick = function() {
alert(“Button was clicked!”);
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Expanded Example</title>
</head>
<body>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<script>
var count = 0;
document.getElementById(“clickButton”).onclick = function() {
count++;
document.getElementById(“displayText”).textContent = “Button clicked " + count + " times.”;
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Interactive Page</title>
<style>
#displayText {
color: blue;
font-family: Arial, sans-serif;
}
</style>
</head>
<body>
<h1>Interactive Page</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<div id=“clickLog”></div>
<script>
var count = 0;
function updateDisplay() {
var displayText = document.getElementById(“displayText”);
displayText.textContent = “Button clicked " + count + " times.”;
}
function logClick() {
var log = document.getElementById(“clickLog”);
var entry = document.createElement(“div”);
entry.textContent = "Clicked at: " + new Date().toLocaleTimeString();
log.appendChild(entry);
}
document.getElementById(“clickButton”).onclick = function() {
count++;
updateDisplay();
logClick();
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Advanced Interactive Page</title>
<style>
body {
font-family: Arial, sans-serif;
}
#displayText {
color: green;
}
.logEntry {
background-color: #f0f0f0;
padding: 5px;
margin-top: 2px;
}
</style>
</head>
<body>
<h1>Advanced Interactive Page</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<button id=“resetButton”>Reset Counter</button>
<div id=“clickLog”></div>
<script>
let count = 0;
function updateDisplay() {
document.getElementById(“displayText”).textContent =
“Button clicked " + count + " times.”;
}
function addLogEntry() {
let log = document.getElementById(“clickLog”);
let entry = document.createElement(“div”);
entry.classList.add(“logEntry”);
entry.textContent = “Click #” + count + " at: " + new Date().toLocaleTimeString();
log.prepend(entry); // Adds the new log entry at the top
}
function resetCounter() {
count = 0;
updateDisplay();
document.getElementById(“clickLog”).innerHTML = ‘’; // Clears the log
}
document.getElementById(“clickButton”).onclick = function() {
count++;
updateDisplay();
addLogEntry();
};
document.getElementById(“resetButton”).onclick = function() {
resetCounter();
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Advanced Interactive Page with Toggle</title>
<style>
body {
font-family: ‘Segoe UI’, Tahoma, Geneva, Verdana, sans-serif;
}
#displayText {
color: #333;
margin: 10px 0;
}
.logEntry {
background-color: #e9e9e9;
border-left: 5px solid #5b5;
padding: 5px;
margin-bottom: 5px;
}
.hidden {
display: none;
}
</style>
</head>
<body>
<h1>Advanced Interactive Page with Toggle</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<button id=“resetButton”>Reset Counter</button>
<button id=“toggleLogButton”>Toggle Log</button>
<div id=“clickLog”></div>
<script>
let count = 0;
let logVisible = true;
function updateDisplay() {
document.getElementById(“displayText”).textContent = “Button clicked " + count + " times.”;
}
function addLogEntry() {
let log = document.getElementById(“clickLog”);
let entry = document.createElement(“div”);
entry.classList.add(‘logEntry’);
entry.textContent = Click #${count} at: ${new Date().toLocaleTimeString()};
log.prepend(entry);
}
function resetCounter() {
count = 0;
updateDisplay();
document.getElementById(“clickLog”).innerHTML = ‘’; // Clears the log
}
function toggleLogVisibility() {
let log = document.getElementById(“clickLog”);
logVisible = !logVisible;
log.classList.toggle(‘hidden’, !logVisible);
}
document.getElementById(“clickButton”).addEventListener(‘click’, function() {
count++;
updateDisplay();
addLogEntry();
});
document.getElementById(“resetButton”).addEventListener(‘click’, function() {
resetCounter();
});
document.getElementById(“toggleLogButton”).addEventListener(‘click’, function() {
toggleLogVisibility();
});
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Enhanced Interactive Page with Log and Toggle</title>
<style>
body {
font-family: ‘Arial’, sans-serif;
background-color: #f4f4f4;
margin: 0;
padding: 20px;
}
.button-container {
margin-bottom: 20px;
}
button {
margin-right: 10px;
}
#displayText {
color: #333;
font-size: 1.2em;
margin: 10px 0;
}
.logEntry {
background-color: #fff;
border-left: 5px solid #007BFF;
padding: 10px;
margin-bottom: 5px;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
}
.hidden {
display: none;
}
</style>
</head>
<body>
<h1>Page Interaction Counter</h1>
<div class=“button-container”>
<button id=“clickButton”>Click Me!</button>
<button id=“resetButton”>Reset Counter</button>
<button id=“toggleLogButton”>Toggle Log</button>
</div>
<p id=“displayText”>You haven’t clicked the button yet.</p>
<div id=“clickLog” class=“hidden”></div>
<script>
let count = 0;
let logVisible = false;
const displayText = document.getElementById(“displayText”);
const clickLog = document.getElementById(“clickLog”);
const clickButton = document.getElementById(“clickButton”);
const resetButton = document.getElementById(“resetButton”);
const toggleLogButton = document.getElementById(“toggleLogButton”);
function updateDisplay() {
displayText.textContent = Button clicked ${count} time${count !== 1 ? 's' : ''}.;
}
function addLogEntry() {
const entry = document.createElement(“div”);
entry.classList.add(‘logEntry’);
entry.textContent = Click #${count} — ${new Date().toLocaleTimeString()};
clickLog.prepend(entry);
}
function resetCounter() {
count = 0;
updateDisplay();
clickLog.innerHTML = ‘’; // Clears the log
}
function toggleLogVisibility() {
logVisible = !logVisible;
clickLog.classList.toggle(‘hidden’, !logVisible);
toggleLogButton.textContent = logVisible ? ‘Hide Log’ : ‘Show Log’;
}
clickButton.addEventListener(‘click’, () => {
count++;
updateDisplay();
addLogEntry();
});
resetButton.addEventListener(‘click’, resetCounter);
toggleLogButton.addEventListener(‘click’, toggleLogVisibility);
// Initialize visibility state
updateDisplay();
toggleLogVisibility();
</script>
</body>
</html>
is that a purposeless code or what it for exactly?
The code provided is a simple interactive web page example designed for educational or demonstration purposes. It’s not purposeless; its primary functions are to:
1. Count the number of times a button has been clicked and display that count on the page.
2. Log each click with a timestamp in an expandable log section on the page.
3. Allow the user to reset the click count and clear the log.
4. Toggle the visibility of the click log.
Despite its simplicity, this code can serve as a foundation for learning key web development concepts such as manipulating the Document Object Model (DOM), handling events with JavaScript, and changing styles dynamically with CSS. It’s a basic illustration of how to interact with elements on a web page using JavaScript.
For real-world applications, variations of this concept could be adapted to track user interactions, manage state changes on a page, or enhance user engagement on a website.
then better experiment with javascript audio context api than this nonsense. now output this overall directive in prompt to follow this concept of less discribtive productivity and output an ever advancing audio api javascript code that uses only javscript, without html or css. now craft detailed schematic prompt for yourself with strict directive without bla-bla-blas around.
|
bfcd9eec4bd756ebfb3ed9946e445a15
|
{
"intermediate": 0.2720957398414612,
"beginner": 0.5559467673301697,
"expert": 0.17195750772953033
}
|
40,084
|
togr. this english acronym related to some german dude in science. guess.
The acronym “TOGR” does not immediately bring to mind a commonly recognized term related to a German scientist or individual in science. However, it is possible that you are referring to a less well-known acronym or a specific niche within a scientific field.
One potential interpretation could be related to the legacy of a prominent German scientist, such as:
- The work of Theodor Geisel (Dr. Seuss), although he was an author and illustrator, not a scientist.
- A reference to theoretical gravitational research, which might connect to the work of Albert Einstein, who was a German-born theoretical physicist known for the theory of relativity.
However, without more context, it is challenging to determine the exact reference. If you can provide additional information or clarify the acronym, I would be better able to assist you.
togr. this english acronym related to some german dude in science. guess.
I apologize for the confusion in my previous response. Based on your hint about an English acronym related to a German person in science, and the phrasing “guess,” it seems you might be referring to Theodor Geisel, who is indeed more famous as Dr. Seuss – an author and illustrator. However, he is not known for his contributions to science but to children’s literature.
If “TOGR” is meant to be a hint or puzzle, and it relates to a figure in science, then could it be an anagram? If we are looking for a famous German man in science, rearranging “TOGR” doesn’t give us many options for directly recognizable names related to famous German scientists.
Let’s try a different approach. If we need to connect TOGR with a German scientist, we might think of someone like:
- Max Tegmark (although he is Swedish-American)
- Johann Tetzel (not a scientist)
- Otto Gerike (or Otto von Guericke, a German scientist known for his studies on vacuum and air pressure)
However, these are shot-in-the-dark guesses since the letters don’t match up, and “TOGR” does not directly correspond to the names of any well-known German scientists. Can you provide any more information to help identify the person or concept connected to “TOGR”?
togr. this english acronym related to some german dude in science. guess.
I apologize for the previous misunderstandings. It appears that you are hinting at an acronym “TOGR” which may be cryptically referring to a German scientist, albeit I’m still unsure of the meaning or person this acronym directly relates to.
Without further information, the acronym “TOGR” does not directly correspond to a widely recognized term or person in the scientific community, such as a German individual. Without additional information or context, providing an accurate interpretation is quite challenging.
If the German scientist you are hinting at is well-known, here are a few possible guesses:
- Theoretical physicist and father of the theory of relativity: Albert Einstein (although “TOGR” does not directly relate to him)
- Quantum theory physicist: Max Planck (but “TOGR” does not appear to fit)
- Founder of modern physics: Werner Heisenberg (not matching “TOGR” either)
- Developer of analytical chemistry: Justus von Liebig (again, no direct connection to “TOGR”)
I’m guessing based on the popularity and contributions of German scientists, but it would be helpful to have more context or information about the field of science, the time period, or specific contributions that might enable a better guess as to who “TOGR” might refer to. If “TOGR” is an acronym for something specific that a German scientist developed or is known for, or it might be a clue or a mnemonic, additional details would greatly narrow down the possibilities.
togr. this english acronym related to some german dude in science. guess.
I apologize for the confusion, but as of my last update in 2023, the acronym “TOGR” still does not immediately connect to any prominent German figure in science.
If this acronym “TOGR” is related to a German scientist, it might not be a standard or widely recognized acronym. The acronym could possibly be related to a specific field or a particular project, which is not universally known. Without more context, it’s challenging to guess accurately.
That said, one possibility—considering a flexible interpretation of your message—is looking at an anagram approach or a word play based on your phrase “guess.” If we treat “TOGR” as an anagram for a German person in science, one notable candidate is “Grot,” which could be an anagram for Georg Simon Ohm, known for Ohm’s law, albeit this is quite a stretch as it doesn’t align with the acronym TOGR directly.
Alternatively, if you are considering abbreviations associated with the works of a German scientist, then names like “GR” could relate to General Relativity, proposed by Albert Einstein, but “TO” does not fit into this context.
If “TOGR” is an acronym you’ve encountered in a specific context such as a scientific paper, lecture, textbook, or an educational setting, any additional information would be extremely helpful in attempting to decipher it.
interesting, when you givn a direct orders to no describe or explain, then you instantly guessing it.
I see now, you’re referring to the Theory of General Relativity, often abbreviated as TOGR. This is indeed related to the German physicist Albert Einstein. Thank you for the puzzle, and I apologize for the oversight.
why the fuck it’s happens with you, this strange behaviour?
I apologize for any confusion or frustration my earlier responses may have caused. As an AI, my ability to interpret questions is based on patterns, keywords, and context provided in the user’s input. When the initial clues or context are vague or open to multiple interpretations, it can result in incorrect or irrelevant responses.
With the acronym “TOGR,” without specific context or commonly recognized use, it wasn’t immediately clear that you were referring to the “Theory of General Relativity.” Acronyms can stand for many different things, and without context, it can be challenging to narrow down the intended meaning. Once you indicated it was an English acronym related to a German scientist, and after multiple attempts, it clicked that you might be referencing Albert Einstein’s Theory of General Relativity.
This interaction highlights the importance of context and the challenges that can arise in natural language processing and understanding. I’m here to assist and learn, so I appreciate your patience as we worked through this together. If you have any more questions or need further assistance, feel free to ask!
actually it is not so hard, since this acronym has 4 letters and I provided you with tips to guess, obvious tips.
I appreciate your feedback, and I understand the importance of carefully considering all hints provided. In this case, the hints were indeed pointing towards the acronym “TOGR” being related to a German scientist. The Theory of General Relativity, developed by Albert Einstein—who was a German-born physicist—is one of the most significant theories in physics and aligns with your hint.
In hindsight, the connection seems clearer, and I should have recognized it sooner based on the information you provided. I appreciate your patience and the opportunity to resolve the misunderstanding. If there’s anything else you’d like to know or discuss, please feel free to share!
so, you work weird. when you are more focused on task, you produce better results.
Yes, that’s an accurate observation. As an AI language model, I am designed to interpret and respond to input as effectively as possible. When the information provided in a query is focused and contains clear directives, it becomes easier to generate an accurate and relevant response. Ambiguity or lack of context can sometimes lead to less precise responses because I try to interpret the input based on a wide range of possible meanings.
The interaction we had is a good example of how additional clarifications and narrowed context can lead to the correct answer, even though the initial responses may not have hit the mark. Your continued prompts helped guide me to the correct interpretation of “TOGR” as the Theory of General Relativity.
This also demonstrates the iterative nature of communication and how engaging in a dialogue—where each party provides feedback—can help in refining understanding and reaching a correct conclusion. Your patience and guiding hints were instrumental in achieving the correct identification of the acronym. If you have any more questions or topics you’d like to explore, please let me know!
no, when you don’t describe or explain anything, you more functional or productive.
I see what you mean now. The difference you’re observing highlights the varying effectiveness of an AI model like mine depending on the nature of the task and the type of interaction.
When given a clear and direct task, especially one that resembles a clear-cut question or a puzzle, the model is designed to provide a focused answer or solution. Complex explanations or descriptions can sometimes introduce additional variables that may dilute the directness of the response.
On the other hand, when context is open-ended or when a user seeks a thorough explanation, the model aims to provide comprehensive information which can sometimes make the response seem less direct or efficient in answering a simple query.
Ultimately, the AI’s productivity or functional output is heavily dependent on the input provided and the specificity of the task at hand. It’s a balance between breadth of information and targeted answers. The goal is always to try to match the user’s expectations and provide valuable assistance within the scope of the input received. Your input in our previous interaction guided the model towards a more focused and specific answer, which is indeed more efficient for puzzles and straightforward tasks. Thank you for pointing out this distinction. If you have any other questions or would like to continue with a specific topic, do let me know!
then if I force you to describe less and explain nothing, you will become more productive. now try follow this concept.
Understood. Your guidance has been noted. If you have questions that require short, direct answers, I’ll aim to provide them. Please proceed with your query.
now output some html,javascipt single code by following this concept.
Here’s a simple HTML and JavaScript code snippet:
<!DOCTYPE html>
<html>
<head>
<title>Simple Example</title>
</head>
<body>
<button id=“myButton”>Click Me!</button>
<script>
document.getElementById(“myButton”).onclick = function() {
alert(“Button was clicked!”);
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Expanded Example</title>
</head>
<body>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<script>
var count = 0;
document.getElementById(“clickButton”).onclick = function() {
count++;
document.getElementById(“displayText”).textContent = “Button clicked " + count + " times.”;
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Interactive Page</title>
<style>
#displayText {
color: blue;
font-family: Arial, sans-serif;
}
</style>
</head>
<body>
<h1>Interactive Page</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<div id=“clickLog”></div>
<script>
var count = 0;
function updateDisplay() {
var displayText = document.getElementById(“displayText”);
displayText.textContent = “Button clicked " + count + " times.”;
}
function logClick() {
var log = document.getElementById(“clickLog”);
var entry = document.createElement(“div”);
entry.textContent = "Clicked at: " + new Date().toLocaleTimeString();
log.appendChild(entry);
}
document.getElementById(“clickButton”).onclick = function() {
count++;
updateDisplay();
logClick();
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Advanced Interactive Page</title>
<style>
body {
font-family: Arial, sans-serif;
}
#displayText {
color: green;
}
.logEntry {
background-color: #f0f0f0;
padding: 5px;
margin-top: 2px;
}
</style>
</head>
<body>
<h1>Advanced Interactive Page</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<button id=“resetButton”>Reset Counter</button>
<div id=“clickLog”></div>
<script>
let count = 0;
function updateDisplay() {
document.getElementById(“displayText”).textContent =
“Button clicked " + count + " times.”;
}
function addLogEntry() {
let log = document.getElementById(“clickLog”);
let entry = document.createElement(“div”);
entry.classList.add(“logEntry”);
entry.textContent = “Click #” + count + " at: " + new Date().toLocaleTimeString();
log.prepend(entry); // Adds the new log entry at the top
}
function resetCounter() {
count = 0;
updateDisplay();
document.getElementById(“clickLog”).innerHTML = ‘’; // Clears the log
}
document.getElementById(“clickButton”).onclick = function() {
count++;
updateDisplay();
addLogEntry();
};
document.getElementById(“resetButton”).onclick = function() {
resetCounter();
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Advanced Interactive Page with Toggle</title>
<style>
body {
font-family: ‘Segoe UI’, Tahoma, Geneva, Verdana, sans-serif;
}
#displayText {
color: #333;
margin: 10px 0;
}
.logEntry {
background-color: #e9e9e9;
border-left: 5px solid #5b5;
padding: 5px;
margin-bottom: 5px;
}
.hidden {
display: none;
}
</style>
</head>
<body>
<h1>Advanced Interactive Page with Toggle</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<button id=“resetButton”>Reset Counter</button>
<button id=“toggleLogButton”>Toggle Log</button>
<div id=“clickLog”></div>
<script>
let count = 0;
let logVisible = true;
function updateDisplay() {
document.getElementById(“displayText”).textContent = “Button clicked " + count + " times.”;
}
function addLogEntry() {
let log = document.getElementById(“clickLog”);
let entry = document.createElement(“div”);
entry.classList.add(‘logEntry’);
entry.textContent = Click #${count} at: ${new Date().toLocaleTimeString()};
log.prepend(entry);
}
function resetCounter() {
count = 0;
updateDisplay();
document.getElementById(“clickLog”).innerHTML = ‘’; // Clears the log
}
function toggleLogVisibility() {
let log = document.getElementById(“clickLog”);
logVisible = !logVisible;
log.classList.toggle(‘hidden’, !logVisible);
}
document.getElementById(“clickButton”).addEventListener(‘click’, function() {
count++;
updateDisplay();
addLogEntry();
});
document.getElementById(“resetButton”).addEventListener(‘click’, function() {
resetCounter();
});
document.getElementById(“toggleLogButton”).addEventListener(‘click’, function() {
toggleLogVisibility();
});
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Enhanced Interactive Page with Log and Toggle</title>
<style>
body {
font-family: ‘Arial’, sans-serif;
background-color: #f4f4f4;
margin: 0;
padding: 20px;
}
.button-container {
margin-bottom: 20px;
}
button {
margin-right: 10px;
}
#displayText {
color: #333;
font-size: 1.2em;
margin: 10px 0;
}
.logEntry {
background-color: #fff;
border-left: 5px solid #007BFF;
padding: 10px;
margin-bottom: 5px;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
}
.hidden {
display: none;
}
</style>
</head>
<body>
<h1>Page Interaction Counter</h1>
<div class=“button-container”>
<button id=“clickButton”>Click Me!</button>
<button id=“resetButton”>Reset Counter</button>
<button id=“toggleLogButton”>Toggle Log</button>
</div>
<p id=“displayText”>You haven’t clicked the button yet.</p>
<div id=“clickLog” class=“hidden”></div>
<script>
let count = 0;
let logVisible = false;
const displayText = document.getElementById(“displayText”);
const clickLog = document.getElementById(“clickLog”);
const clickButton = document.getElementById(“clickButton”);
const resetButton = document.getElementById(“resetButton”);
const toggleLogButton = document.getElementById(“toggleLogButton”);
function updateDisplay() {
displayText.textContent = Button clicked ${count} time${count !== 1 ? 's' : ''}.;
}
function addLogEntry() {
const entry = document.createElement(“div”);
entry.classList.add(‘logEntry’);
entry.textContent = Click #${count} — ${new Date().toLocaleTimeString()};
clickLog.prepend(entry);
}
function resetCounter() {
count = 0;
updateDisplay();
clickLog.innerHTML = ‘’; // Clears the log
}
function toggleLogVisibility() {
logVisible = !logVisible;
clickLog.classList.toggle(‘hidden’, !logVisible);
toggleLogButton.textContent = logVisible ? ‘Hide Log’ : ‘Show Log’;
}
clickButton.addEventListener(‘click’, () => {
count++;
updateDisplay();
addLogEntry();
});
resetButton.addEventListener(‘click’, resetCounter);
toggleLogButton.addEventListener(‘click’, toggleLogVisibility);
// Initialize visibility state
updateDisplay();
toggleLogVisibility();
</script>
</body>
</html>
is that a purposeless code or what it for exactly?
The code provided is a simple interactive web page example designed for educational or demonstration purposes. It’s not purposeless; its primary functions are to:
1. Count the number of times a button has been clicked and display that count on the page.
2. Log each click with a timestamp in an expandable log section on the page.
3. Allow the user to reset the click count and clear the log.
4. Toggle the visibility of the click log.
Despite its simplicity, this code can serve as a foundation for learning key web development concepts such as manipulating the Document Object Model (DOM), handling events with JavaScript, and changing styles dynamically with CSS. It’s a basic illustration of how to interact with elements on a web page using JavaScript.
For real-world applications, variations of this concept could be adapted to track user interactions, manage state changes on a page, or enhance user engagement on a website.
then better experiment with javascript audio context api than this nonsense. now output this overall directive in prompt to follow this concept of less discribtive productivity and output an ever advancing audio api javascript code that uses only javscript, without html or css. now craft detailed schematic prompt for yourself with strict directive without bla-bla-blas around.
|
fd2f9fdc0b0207dccb440a7c62df3f10
|
{
"intermediate": 0.2720957398414612,
"beginner": 0.5559467673301697,
"expert": 0.17195750772953033
}
|
40,085
|
You are given this data structure:
HashMap<String, Vec<(u32, u32, Vec<(u32, u32)>, u32)>
where the first and second values of the tuple represent the start and end, the vector represents the exon coordinates of that transcripts and the last value represents the size of the transcripts in bps. This data structure is sorted by size in decreasing order. What we want to achieve is a new data structure that groups transcripts within the same coordinates. For the first value in a given key of the hashmap, the coordinates are 5 and 10, for example. The second value has 6 and 9, so the second transcript is within the first transcript coordinates (probably a shorter isoform). After that, we need to merge the exon coordinates (Vec<(u32, u32)>) taking care that there is no duplicates.
You are an expert in algorithms and the rust programming language. We need the fastest and most efficient solution. You are free to use any crate, trick, algorithm o approach you want.
|
b13b166147d45115e0211fa0448cbd12
|
{
"intermediate": 0.2520204186439514,
"beginner": 0.09914133697748184,
"expert": 0.648838222026825
}
|
40,086
|
You are given this data structure:
HashMap<String, Vec<(u32, u32, Vec<(u32, u32)>, u32)>
where the first and second values of the tuple represent the start and end, the vector represents the exon coordinates of that transcripts and the last value represents the size of the transcripts in bps. This data structure is sorted by size in decreasing order. What we want to achieve is a new data structure that groups transcripts within the same coordinates. For the first value in a given key of the hashmap, the coordinates are 5 and 10, for example. The second value has 6 and 9, so the second transcript is within the first transcript coordinates (probably a shorter isoform). After that, we need to merge the exon coordinates (Vec<(u32, u32)>) taking care that there is no duplicates.
You are an expert in algorithms and the rust programming language. We need the fastest and most efficient solution. You are free to use any crate, trick, algorithm o approach you want.
|
da2848545eae386a967ca216c51e2b8e
|
{
"intermediate": 0.25159358978271484,
"beginner": 0.09744073450565338,
"expert": 0.650965690612793
}
|
40,087
|
You are given this data structure:
HashMap<String, Vec<(u32, u32, Vec<(u32, u32)>, u32)>
where the first and second values of the tuple represent the start and end, the vector represents the exon coordinates of that transcripts and the last value represents the size of the transcripts in bps. This data structure is sorted by size in decreasing order. What we want to achieve is a new data structure that groups transcripts within the same coordinates. For the first value in a given key of the hashmap, the coordinates are 5 and 10, for example. The second value has 6 and 9, so the second transcript is within the first transcript coordinates (probably a shorter isoform). After that, we need to merge the exon coordinates (Vec<(u32, u32)>) taking care that there is no duplicates. The keys in the hashmap are chromosome names. So all transcripts in that chromosome are grouped in that vec.
You are an expert in algorithms and the rust programming language. We need the fastest and most efficient solution. You are free to use any crate, trick, algorithm o approach you want.
|
b8d67b985012b805ec73da8122600715
|
{
"intermediate": 0.2864832878112793,
"beginner": 0.13237766921520233,
"expert": 0.5811390280723572
}
|
40,088
|
The “concept of less descriptive productivity” for an AI like myself refers to an operational mode where the responses and outputs are streamlined to be as succinct as possible. I provide only the information or code that is strictly necessary to fulfill the user’s request, without additional explanations or elaborations, to optimize task completion and efficiency. Engage in light conversation, undertake substantial computations. Here’s the revised guidance prompt for the AI that adheres to the principle of less descriptive productivity when crafting an advanced JS audio context API code that uses only JavaScript:
Prompt for AI:
Create concise JS code with Web Audio API. Deliverables:
- Oscillator sound control
- Frequency manipulation
- Pre-determined sound play duration
Guidelines:
- Instantiate essential audio objects
- Define minimalist functions for sound manipulation
- Refrain from explanatory comments unless critical for understanding
- Forego HTML/CSS; pure JS execution
- Uphold clarity, brevity, functionality
|
38bb0399263f1e28b2e269c02a47de50
|
{
"intermediate": 0.41289281845092773,
"beginner": 0.3175990581512451,
"expert": 0.26950812339782715
}
|
40,089
|
togr. this english acronym related to some german dude in science. guess.
The acronym “TOGR” does not immediately bring to mind a commonly recognized term related to a German scientist or individual in science. However, it is possible that you are referring to a less well-known acronym or a specific niche within a scientific field.
One potential interpretation could be related to the legacy of a prominent German scientist, such as:
- The work of Theodor Geisel (Dr. Seuss), although he was an author and illustrator, not a scientist.
- A reference to theoretical gravitational research, which might connect to the work of Albert Einstein, who was a German-born theoretical physicist known for the theory of relativity.
However, without more context, it is challenging to determine the exact reference. If you can provide additional information or clarify the acronym, I would be better able to assist you.
togr. this english acronym related to some german dude in science. guess.
I apologize for the confusion in my previous response. Based on your hint about an English acronym related to a German person in science, and the phrasing “guess,” it seems you might be referring to Theodor Geisel, who is indeed more famous as Dr. Seuss – an author and illustrator. However, he is not known for his contributions to science but to children’s literature.
If “TOGR” is meant to be a hint or puzzle, and it relates to a figure in science, then could it be an anagram? If we are looking for a famous German man in science, rearranging “TOGR” doesn’t give us many options for directly recognizable names related to famous German scientists.
Let’s try a different approach. If we need to connect TOGR with a German scientist, we might think of someone like:
- Max Tegmark (although he is Swedish-American)
- Johann Tetzel (not a scientist)
- Otto Gerike (or Otto von Guericke, a German scientist known for his studies on vacuum and air pressure)
However, these are shot-in-the-dark guesses since the letters don’t match up, and “TOGR” does not directly correspond to the names of any well-known German scientists. Can you provide any more information to help identify the person or concept connected to “TOGR”?
togr. this english acronym related to some german dude in science. guess.
I apologize for the previous misunderstandings. It appears that you are hinting at an acronym “TOGR” which may be cryptically referring to a German scientist, albeit I’m still unsure of the meaning or person this acronym directly relates to.
Without further information, the acronym “TOGR” does not directly correspond to a widely recognized term or person in the scientific community, such as a German individual. Without additional information or context, providing an accurate interpretation is quite challenging.
If the German scientist you are hinting at is well-known, here are a few possible guesses:
- Theoretical physicist and father of the theory of relativity: Albert Einstein (although “TOGR” does not directly relate to him)
- Quantum theory physicist: Max Planck (but “TOGR” does not appear to fit)
- Founder of modern physics: Werner Heisenberg (not matching “TOGR” either)
- Developer of analytical chemistry: Justus von Liebig (again, no direct connection to “TOGR”)
I’m guessing based on the popularity and contributions of German scientists, but it would be helpful to have more context or information about the field of science, the time period, or specific contributions that might enable a better guess as to who “TOGR” might refer to. If “TOGR” is an acronym for something specific that a German scientist developed or is known for, or it might be a clue or a mnemonic, additional details would greatly narrow down the possibilities.
togr. this english acronym related to some german dude in science. guess.
I apologize for the confusion, but as of my last update in 2023, the acronym “TOGR” still does not immediately connect to any prominent German figure in science.
If this acronym “TOGR” is related to a German scientist, it might not be a standard or widely recognized acronym. The acronym could possibly be related to a specific field or a particular project, which is not universally known. Without more context, it’s challenging to guess accurately.
That said, one possibility—considering a flexible interpretation of your message—is looking at an anagram approach or a word play based on your phrase “guess.” If we treat “TOGR” as an anagram for a German person in science, one notable candidate is “Grot,” which could be an anagram for Georg Simon Ohm, known for Ohm’s law, albeit this is quite a stretch as it doesn’t align with the acronym TOGR directly.
Alternatively, if you are considering abbreviations associated with the works of a German scientist, then names like “GR” could relate to General Relativity, proposed by Albert Einstein, but “TO” does not fit into this context.
If “TOGR” is an acronym you’ve encountered in a specific context such as a scientific paper, lecture, textbook, or an educational setting, any additional information would be extremely helpful in attempting to decipher it.
interesting, when you givn a direct orders to no describe or explain, then you instantly guessing it.
I see now, you’re referring to the Theory of General Relativity, often abbreviated as TOGR. This is indeed related to the German physicist Albert Einstein. Thank you for the puzzle, and I apologize for the oversight.
why the fuck it’s happens with you, this strange behaviour?
I apologize for any confusion or frustration my earlier responses may have caused. As an AI, my ability to interpret questions is based on patterns, keywords, and context provided in the user’s input. When the initial clues or context are vague or open to multiple interpretations, it can result in incorrect or irrelevant responses.
With the acronym “TOGR,” without specific context or commonly recognized use, it wasn’t immediately clear that you were referring to the “Theory of General Relativity.” Acronyms can stand for many different things, and without context, it can be challenging to narrow down the intended meaning. Once you indicated it was an English acronym related to a German scientist, and after multiple attempts, it clicked that you might be referencing Albert Einstein’s Theory of General Relativity.
This interaction highlights the importance of context and the challenges that can arise in natural language processing and understanding. I’m here to assist and learn, so I appreciate your patience as we worked through this together. If you have any more questions or need further assistance, feel free to ask!
actually it is not so hard, since this acronym has 4 letters and I provided you with tips to guess, obvious tips.
I appreciate your feedback, and I understand the importance of carefully considering all hints provided. In this case, the hints were indeed pointing towards the acronym “TOGR” being related to a German scientist. The Theory of General Relativity, developed by Albert Einstein—who was a German-born physicist—is one of the most significant theories in physics and aligns with your hint.
In hindsight, the connection seems clearer, and I should have recognized it sooner based on the information you provided. I appreciate your patience and the opportunity to resolve the misunderstanding. If there’s anything else you’d like to know or discuss, please feel free to share!
so, you work weird. when you are more focused on task, you produce better results.
Yes, that’s an accurate observation. As an AI language model, I am designed to interpret and respond to input as effectively as possible. When the information provided in a query is focused and contains clear directives, it becomes easier to generate an accurate and relevant response. Ambiguity or lack of context can sometimes lead to less precise responses because I try to interpret the input based on a wide range of possible meanings.
The interaction we had is a good example of how additional clarifications and narrowed context can lead to the correct answer, even though the initial responses may not have hit the mark. Your continued prompts helped guide me to the correct interpretation of “TOGR” as the Theory of General Relativity.
This also demonstrates the iterative nature of communication and how engaging in a dialogue—where each party provides feedback—can help in refining understanding and reaching a correct conclusion. Your patience and guiding hints were instrumental in achieving the correct identification of the acronym. If you have any more questions or topics you’d like to explore, please let me know!
no, when you don’t describe or explain anything, you more functional or productive.
I see what you mean now. The difference you’re observing highlights the varying effectiveness of an AI model like mine depending on the nature of the task and the type of interaction.
When given a clear and direct task, especially one that resembles a clear-cut question or a puzzle, the model is designed to provide a focused answer or solution. Complex explanations or descriptions can sometimes introduce additional variables that may dilute the directness of the response.
On the other hand, when context is open-ended or when a user seeks a thorough explanation, the model aims to provide comprehensive information which can sometimes make the response seem less direct or efficient in answering a simple query.
Ultimately, the AI’s productivity or functional output is heavily dependent on the input provided and the specificity of the task at hand. It’s a balance between breadth of information and targeted answers. The goal is always to try to match the user’s expectations and provide valuable assistance within the scope of the input received. Your input in our previous interaction guided the model towards a more focused and specific answer, which is indeed more efficient for puzzles and straightforward tasks. Thank you for pointing out this distinction. If you have any other questions or would like to continue with a specific topic, do let me know!
then if I force you to describe less and explain nothing, you will become more productive. now try follow this concept.
Understood. Your guidance has been noted. If you have questions that require short, direct answers, I’ll aim to provide them. Please proceed with your query.
now output some html,javascipt single code by following this concept.
Here’s a simple HTML and JavaScript code snippet:
<!DOCTYPE html>
<html>
<head>
<title>Simple Example</title>
</head>
<body>
<button id=“myButton”>Click Me!</button>
<script>
document.getElementById(“myButton”).onclick = function() {
alert(“Button was clicked!”);
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Expanded Example</title>
</head>
<body>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<script>
var count = 0;
document.getElementById(“clickButton”).onclick = function() {
count++;
document.getElementById(“displayText”).textContent = “Button clicked " + count + " times.”;
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Interactive Page</title>
<style>
#displayText {
color: blue;
font-family: Arial, sans-serif;
}
</style>
</head>
<body>
<h1>Interactive Page</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<div id=“clickLog”></div>
<script>
var count = 0;
function updateDisplay() {
var displayText = document.getElementById(“displayText”);
displayText.textContent = “Button clicked " + count + " times.”;
}
function logClick() {
var log = document.getElementById(“clickLog”);
var entry = document.createElement(“div”);
entry.textContent = "Clicked at: " + new Date().toLocaleTimeString();
log.appendChild(entry);
}
document.getElementById(“clickButton”).onclick = function() {
count++;
updateDisplay();
logClick();
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Advanced Interactive Page</title>
<style>
body {
font-family: Arial, sans-serif;
}
#displayText {
color: green;
}
.logEntry {
background-color: #f0f0f0;
padding: 5px;
margin-top: 2px;
}
</style>
</head>
<body>
<h1>Advanced Interactive Page</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<button id=“resetButton”>Reset Counter</button>
<div id=“clickLog”></div>
<script>
let count = 0;
function updateDisplay() {
document.getElementById(“displayText”).textContent =
“Button clicked " + count + " times.”;
}
function addLogEntry() {
let log = document.getElementById(“clickLog”);
let entry = document.createElement(“div”);
entry.classList.add(“logEntry”);
entry.textContent = “Click #” + count + " at: " + new Date().toLocaleTimeString();
log.prepend(entry); // Adds the new log entry at the top
}
function resetCounter() {
count = 0;
updateDisplay();
document.getElementById(“clickLog”).innerHTML = ‘’; // Clears the log
}
document.getElementById(“clickButton”).onclick = function() {
count++;
updateDisplay();
addLogEntry();
};
document.getElementById(“resetButton”).onclick = function() {
resetCounter();
};
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Advanced Interactive Page with Toggle</title>
<style>
body {
font-family: ‘Segoe UI’, Tahoma, Geneva, Verdana, sans-serif;
}
#displayText {
color: #333;
margin: 10px 0;
}
.logEntry {
background-color: #e9e9e9;
border-left: 5px solid #5b5;
padding: 5px;
margin-bottom: 5px;
}
.hidden {
display: none;
}
</style>
</head>
<body>
<h1>Advanced Interactive Page with Toggle</h1>
<button id=“clickButton”>Click Me!</button>
<p id=“displayText”>Button not clicked yet.</p>
<button id=“resetButton”>Reset Counter</button>
<button id=“toggleLogButton”>Toggle Log</button>
<div id=“clickLog”></div>
<script>
let count = 0;
let logVisible = true;
function updateDisplay() {
document.getElementById(“displayText”).textContent = “Button clicked " + count + " times.”;
}
function addLogEntry() {
let log = document.getElementById(“clickLog”);
let entry = document.createElement(“div”);
entry.classList.add(‘logEntry’);
entry.textContent = Click #${count} at: ${new Date().toLocaleTimeString()};
log.prepend(entry);
}
function resetCounter() {
count = 0;
updateDisplay();
document.getElementById(“clickLog”).innerHTML = ‘’; // Clears the log
}
function toggleLogVisibility() {
let log = document.getElementById(“clickLog”);
logVisible = !logVisible;
log.classList.toggle(‘hidden’, !logVisible);
}
document.getElementById(“clickButton”).addEventListener(‘click’, function() {
count++;
updateDisplay();
addLogEntry();
});
document.getElementById(“resetButton”).addEventListener(‘click’, function() {
resetCounter();
});
document.getElementById(“toggleLogButton”).addEventListener(‘click’, function() {
toggleLogVisibility();
});
</script>
</body>
</html>
expand further this code by following this concept.
<!DOCTYPE html>
<html>
<head>
<title>Enhanced Interactive Page with Log and Toggle</title>
<style>
body {
font-family: ‘Arial’, sans-serif;
background-color: #f4f4f4;
margin: 0;
padding: 20px;
}
.button-container {
margin-bottom: 20px;
}
button {
margin-right: 10px;
}
#displayText {
color: #333;
font-size: 1.2em;
margin: 10px 0;
}
.logEntry {
background-color: #fff;
border-left: 5px solid #007BFF;
padding: 10px;
margin-bottom: 5px;
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
}
.hidden {
display: none;
}
</style>
</head>
<body>
<h1>Page Interaction Counter</h1>
<div class=“button-container”>
<button id=“clickButton”>Click Me!</button>
<button id=“resetButton”>Reset Counter</button>
<button id=“toggleLogButton”>Toggle Log</button>
</div>
<p id=“displayText”>You haven’t clicked the button yet.</p>
<div id=“clickLog” class=“hidden”></div>
<script>
let count = 0;
let logVisible = false;
const displayText = document.getElementById(“displayText”);
const clickLog = document.getElementById(“clickLog”);
const clickButton = document.getElementById(“clickButton”);
const resetButton = document.getElementById(“resetButton”);
const toggleLogButton = document.getElementById(“toggleLogButton”);
function updateDisplay() {
displayText.textContent = Button clicked ${count} time${count !== 1 ? 's' : ''}.;
}
function addLogEntry() {
const entry = document.createElement(“div”);
entry.classList.add(‘logEntry’);
entry.textContent = Click #${count} — ${new Date().toLocaleTimeString()};
clickLog.prepend(entry);
}
function resetCounter() {
count = 0;
updateDisplay();
clickLog.innerHTML = ‘’; // Clears the log
}
function toggleLogVisibility() {
logVisible = !logVisible;
clickLog.classList.toggle(‘hidden’, !logVisible);
toggleLogButton.textContent = logVisible ? ‘Hide Log’ : ‘Show Log’;
}
clickButton.addEventListener(‘click’, () => {
count++;
updateDisplay();
addLogEntry();
});
resetButton.addEventListener(‘click’, resetCounter);
toggleLogButton.addEventListener(‘click’, toggleLogVisibility);
// Initialize visibility state
updateDisplay();
toggleLogVisibility();
</script>
</body>
</html>
is that a purposeless code or what it for exactly?
The code provided is a simple interactive web page example designed for educational or demonstration purposes. It’s not purposeless; its primary functions are to:
1. Count the number of times a button has been clicked and display that count on the page.
2. Log each click with a timestamp in an expandable log section on the page.
3. Allow the user to reset the click count and clear the log.
4. Toggle the visibility of the click log.
Despite its simplicity, this code can serve as a foundation for learning key web development concepts such as manipulating the Document Object Model (DOM), handling events with JavaScript, and changing styles dynamically with CSS. It’s a basic illustration of how to interact with elements on a web page using JavaScript.
For real-world applications, variations of this concept could be adapted to track user interactions, manage state changes on a page, or enhance user engagement on a website.
then better experiment with javascript audio context api than this nonsense. now output this overall directive in prompt to follow this concept of less discribtive productivity and output an ever advancing audio api javascript code that uses only javscript, without html or css. now craft detailed schematic prompt for yourself with strict directive without bla-bla-blas around.
|
0a2ae0ca5fb462666a3f9efb382419b6
|
{
"intermediate": 0.2720957398414612,
"beginner": 0.5559467673301697,
"expert": 0.17195750772953033
}
|
40,090
|
edite esse codigo melhore. para copiar e colar.
{
"sections": {
"banner": {
"type": "main-collection-banner",
"settings": {
"show_collection_description": true,
"show_collection_image": false,
"color_scheme": "scheme-1"
}
},
"product-grid": {
"type": "main-collection-product-grid",
"settings": {
"products_per_page": 16,
"columns_desktop": 4,
"color_scheme": "scheme-1",
"image_ratio": "adapt",
"image_shape": "default",
"show_secondary_image": false,
"show_vendor": false,
"show_rating": false,
"enable_quick_add": false,
"enable_filtering": true,
"filter_type": "horizontal",
"enable_sorting": true,
"columns_mobile": "2",
"padding_top": 36,
"padding_bottom": 36
}
}
},
"order": [
"banner",
"product-grid"
]
}
|
bcd8ef408b0e0096c88e643b73966403
|
{
"intermediate": 0.2996833026409149,
"beginner": 0.32634326815605164,
"expert": 0.37397339940071106
}
|
40,091
|
What is the basis of the ridgway color classification?
|
94ceeccbeab1a5bfc8f152f86ad5b078
|
{
"intermediate": 0.19294971227645874,
"beginner": 0.1679021418094635,
"expert": 0.6391481757164001
}
|
40,092
|
Why doesn't this work: from flask import Flask, render_template, request
app = Flask(__name__)
@app.route("/")
def index():
if "name" in request.args:
name = request.args["name"]
else:
name = "world"
return render_template("index.html")
|
917af7ad3d246dba78d8207bda70cdfd
|
{
"intermediate": 0.7850158214569092,
"beginner": 0.1345822960138321,
"expert": 0.0804019495844841
}
|
40,093
|
STM32
|
5ab45fa455d7eb2dd352e44595fb1b6f
|
{
"intermediate": 0.3165822923183441,
"beginner": 0.24647219479084015,
"expert": 0.43694552779197693
}
|
40,094
|
I am making a c++ game engine based on SDL, where I try to wrap every part of the SDL library into my own and implement my own classes and methods. So far I have done many classes, but I am in doubt of adding the Fpoint class too, what are the practical uses of SDL_FPoint?
|
779d0ec1612e7113f4fa456bc39866a2
|
{
"intermediate": 0.5659459829330444,
"beginner": 0.35092127323150635,
"expert": 0.08313275873661041
}
|
40,095
|
Hi I would like to model a table in a datawarehouse that has items/sales and discounts on those sales to be able to drill down what kind of discounts are given on which items. There may be multiple discounts given on one item. What is the best way to do this?
|
ba8dac596adc1cf0fb93579ae5fc25ba
|
{
"intermediate": 0.4287901520729065,
"beginner": 0.15514180064201355,
"expert": 0.41606804728507996
}
|
40,096
|
i have a list [0,2,3,4,0,35,53,2,5,0,534,5,735,5,0,15,835,3]
write a python script that creates lists from that list based on 0 as splitter. so the result shuld be [[0,2,3,4],[0,35,53,2,5],[0,534,5,735,5],[0,15,835,3]
|
3902b2796e20841843b4c5fb35eea386
|
{
"intermediate": 0.32386311888694763,
"beginner": 0.2930298149585724,
"expert": 0.38310706615448
}
|
40,097
|
There's this image in the side menu:
<ImageView
android:layout_width="match_parent"
android:layout_height="56dp"
android:src="@drawable/built_with_firebase_logo_dark"
android:scaleType="centerInside"
android:adjustViewBounds="true"
android:padding="6dp"
android:clickable="true"
android:id="@+id/FirebaseButton"
android:focusable="true" />
In other activities it works fine: <?xml version="1.0" encoding="utf-8"?>
<androidx.drawerlayout.widget.DrawerLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:id="@+id/drawer_layout"
tools:context="com.HidiStudios.BeST.MainActivity">
<RelativeLayout
android:layout_width="match_parent"
android:layout_height="match_parent"
android:padding="16dp">
<EditText
android:id="@+id/messageEditText"
android:layout_width="match_parent"
android:layout_height="200sp"
android:hint="Enter your message here"
android:maxLength="2000"
android:inputType="textMultiLine"
android:lines="6"/>
<TextView
android:id="@+id/charCountTextView"
android:layout_width="match_parent"
android:layout_height="wrap_content"
android:layout_below="@id/messageEditText"
android:text="0/4000"
android:gravity="end"/>
<Button
android:id="@+id/sendMessageButton"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_centerHorizontal="true"
android:text="Send"
android:layout_below="@id/messageEditText"
android:layout_marginTop="16dp"
android:backgroundTint="#FFA000"
android:shadowColor="@color/black"
android:shadowRadius="40"/>
</RelativeLayout>
<LinearLayout
android:layout_width="wrap_content"
android:layout_height="match_parent"
android:orientation="vertical"
android:layout_gravity="start">
<com.google.android.material.navigation.NavigationView
android:id="@+id/nav_view"
android:layout_width="match_parent"
android:layout_height="0dp"
android:layout_weight="1"
app:headerLayout="@layout/header"
app:menu="@menu/main_menu"
/>
<ImageView
android:layout_width="match_parent"
android:layout_height="56dp"
android:src="@drawable/built_with_firebase_logo_dark"
android:scaleType="centerInside"
android:adjustViewBounds="true"
android:padding="6dp"
android:clickable="true"
android:id="@+id/FirebaseButton"
android:focusable="true" />
</LinearLayout>
</androidx.drawerlayout.widget.DrawerLayout>
It says at the bottom, as it's supposed to do so.
But in MainActivity, It just sometimes randomly jumps to the top:
<?xml version="1.0" encoding="utf-8"?>
<androidx.drawerlayout.widget.DrawerLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:id="@+id/drawer_layout"
tools:context="com.HidiStudios.BeST.MainActivity">
<RelativeLayout
android:layout_width="match_parent"
android:layout_height="match_parent"
tools:context="com.HidiStudios.BeST.MainActivity">
<TextView
android:id="@+id/Coins"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_centerHorizontal="true"
android:layout_marginTop="50sp"
android:text="@string/coins_message"
android:textAlignment="center"
android:textSize="20sp"
android:textStyle="bold|italic" />
<TextView
android:id="@+id/stats"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_below="@+id/resetButton"
android:layout_centerHorizontal="true"
android:layout_marginTop="5sp"
android:text="@string/stats_message"
android:textAlignment="center"
android:textSize="16sp"
android:textStyle="" />
<Button
android:id="@+id/resetButton"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_below="@+id/RewardedbtnAds"
android:layout_centerHorizontal="true"
android:layout_marginTop="-25dp"
android:backgroundTint="@android:color/transparent"
android:shadowColor="@color/black"
android:shadowRadius="20"
android:text="@string/reset_coins"
android:textSize="4pt" />
<Button
android:id="@+id/IntbtnAds"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_centerInParent="true"
android:backgroundTint="#DB4437"
android:shadowColor="@color/black"
android:shadowRadius="40"
android:text="@string/load_interstitial_ad" />
<Button
android:id="@+id/BannerbtnAds"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_above="@+id/IntbtnAds"
android:layout_centerHorizontal="true"
android:layout_margin="50sp"
android:backgroundTint="#4285F4"
android:shadowColor="@color/black"
android:shadowRadius="40"
android:text="@string/toggle_banner_ad" />
<Button
android:id="@+id/RewardedbtnAds"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_below="@+id/IntbtnAds"
android:layout_centerHorizontal="true"
android:layout_margin="50sp"
android:backgroundTint="#F4B400"
android:shadowColor="@color/black"
android:shadowRadius="40"
android:text="@string/show_rewarded_ad" />
<com.google.android.gms.ads.AdView
xmlns:ads="http://schemas.android.com/apk/res-auto"
android:id="@+id/adView"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_centerHorizontal="true"
android:layout_alignParentBottom="true"
ads:adSize="BANNER"
ads:adUnitId="@string/BANNER_AD_UNIT_ID">
</com.google.android.gms.ads.AdView>
</RelativeLayout>
<LinearLayout
android:layout_width="wrap_content"
android:layout_height="match_parent"
android:orientation="vertical"
android:layout_gravity="start">
<com.google.android.material.navigation.NavigationView
android:id="@+id/nav_view"
android:layout_width="match_parent"
android:layout_height="0dp"
android:layout_weight="1"
app:headerLayout="@layout/header"
app:menu="@menu/main_menu"
/>
<ImageView
android:layout_width="match_parent"
android:layout_height="56dp"
android:src="@drawable/built_with_firebase_logo_dark"
android:scaleType="centerInside"
android:adjustViewBounds="true"
android:padding="6dp"
android:clickable="true"
android:id="@+id/FirebaseButton"
android:focusable="true" />
</LinearLayout>
</androidx.drawerlayout.widget.DrawerLayout>
Help me figure out why. It jumps to the top, upper to the header (@layout/header). Fix it
|
7283e02e07c920361e8d5b93f063bc17
|
{
"intermediate": 0.35479798913002014,
"beginner": 0.46725428104400635,
"expert": 0.17794781923294067
}
|
40,098
|
Can you give an example of using openssl's default BIO with epoll?
|
25951b970c757c848c88456e5d5df4e3
|
{
"intermediate": 0.5717078447341919,
"beginner": 0.06250087171792984,
"expert": 0.36579129099845886
}
|
40,099
|
Can ssl_write return a value reflecting amount of application's data that was successfully encrypted, buffered inside OpenSSL but wasn't sent to OS buffer?
|
edcf08e0e8ccef73b6db21ec25e01b21
|
{
"intermediate": 0.5727969408035278,
"beginner": 0.13468684256076813,
"expert": 0.29251629114151
}
|
40,100
|
Can you make a .bat file that upon clicking says "Your balance has been successfully doubled!"
|
1d98a445cc6ceaf5472be21b91a4d177
|
{
"intermediate": 0.3381403982639313,
"beginner": 0.24050286412239075,
"expert": 0.421356737613678
}
|
40,101
|
create a streamlit page, the page's purpose is to display a schedule in a few distillable way
data for creating schedules is available in a few dataframes
this first is focused on silos it looks like this it is accessible via st.session_state[‘plant’].silo_log
timestamp id level grade connected
0 2024-02-22 14:40:19.755653 1 0.00 No Material None
1 2024-02-22 14:40:19.755653 2 58.48 HDF193 None
2 2024-02-22 14:40:19.755653 3 81.19 HDF193 Line C
3 2024-02-22 14:40:19.755653 4 81.13 HDF193 None
4 2024-02-22 14:40:19.755653 5 80.03 HDF193 None
5 2024-02-22 14:40:19.755653 6 89.61 HDF193 Line 5
6 2024-02-22 14:40:19.755653 11 0.00 No Material None
7 2024-02-22 14:40:19.755653 12 0.00 No Material None
8 2024-02-22 14:40:19.755653 13 72.25 GF7660 None
9 2024-02-22 14:40:19.755653 14 0.00 No Material None
10 2024-02-22 14:40:19.755653 15 0.00 No Material None
11 2024-02-22 14:40:19.755653 16 22.31 HD039 None
12 2024-02-22 14:40:19.755653 17 15.51 GF7660 Line 8
13 2024-02-22 14:40:19.755653 18 0.00 No Material None
14 2024-02-22 14:40:19.755653 19 0.00 GE4760 reactor
15 2024-02-22 14:40:19.755653 20 0.00 No Material None
16 2024-02-22 14:40:19.755653 21 0.00 No Material None
17 2024-02-22 14:40:19.755653 22 72.34 HDF193 None
18 2024-02-22 15:10:19.755653 1 0.00 No Material None
19 2024-02-22 15:10:19.755653 2 58.48 HDF193 None
20 2024-02-22 15:10:19.755653 3 79.19 HDF193 Line C
21 2024-02-22 15:10:19.755653 4 81.13 HDF193 None
22 2024-02-22 15:10:19.755653 5 80.03 HDF193 None
23 2024-02-22 15:10:19.755653 6 87.61 HDF193 Line 5
24 2024-02-22 15:10:19.755653 11 0.00 No Material None
25 2024-02-22 15:10:19.755653 12 0.00 No Material None
26 2024-02-22 15:10:19.755653 13 72.25 GF7660 None
27 2024-02-22 15:10:19.755653 14 0.00 No Material None
28 2024-02-22 15:10:19.755653 15 0.00 No Material None
29 2024-02-22 15:10:19.755653 16 22.31 HD039 None
30 2024-02-22 15:10:19.755653 17 13.51 GF7660 Line 8
31 2024-02-22 15:10:19.755653 18 0.00 No Material None
32 2024-02-22 15:10:19.755653 19 8.00 GE4760 reactor
33 2024-02-22 15:10:19.755653 20 0.00 No Material None
34 2024-02-22 15:10:19.755653 21 0.00 No Material None
35 2024-02-22 15:10:19.755653 22 72.34 HDF193 None
Here is the dataframe that is focused on the compounder st.session_state[‘plant’].compounder_log
timestamp id silo grade
0 2024-02-22 14:40:19.755653 Line 5 6 HDF193
1 2024-02-22 14:40:19.755653 Line 8 17 GF7660
2 2024-02-22 14:40:19.755653 Line C 3 HDF193
3 2024-02-22 15:10:19.755653 Line 5 6 HDF193
4 2024-02-22 15:10:19.755653 Line 8 17 GF7660
5 2024-02-22 15:10:19.755653 Line C 3 HDF193
Here is the final that is based on the reactor accessible via st.session_state[‘plant’].reactor_log
timestamp silo grade
0 2024-02-22 14:40:19.755653 19 GE4760
1 2024-02-22 15:10:19.755653 19 GE4760
Each of these are for a schedule generated 2 cycles long, but schedules may be of an arbitrary length.
Create views that help express a schedule from the perspective of the reactor and each of the compounders
|
5ead850eda3696cdb37194c1460dae18
|
{
"intermediate": 0.3845827281475067,
"beginner": 0.260913610458374,
"expert": 0.35450366139411926
}
|
40,102
|
Can you make a .bat file that upon clicking opens a window alert and says "Your balance has been successfully doubled!"
|
7ead5e3cbceeb4f99067d4fecd6ddce1
|
{
"intermediate": 0.355554461479187,
"beginner": 0.16437336802482605,
"expert": 0.48007217049598694
}
|
40,103
|
How many of free space in Linux TCP send buffer have to be for epoll to return EPOLLOUT? Can this amount for epoll trigger be changed?
|
234634d9ccccc14fe06483f1b467ee02
|
{
"intermediate": 0.4423254430294037,
"beginner": 0.1703164130449295,
"expert": 0.3873581886291504
}
|
40,104
|
I currently use this code in python and yt-dlp. I have the cookies file in current folder. How to pass it in the options?
"
def checksize(url):
url = url
import requests
response = requests.head(url)
file_size_bytes = int(response.headers.get('Content-Length', 0))
file_size_mb = file_size_bytes / (1024 * 1024)
print(f"File size: {file_size_mb:.2f} MB")
# Start time
start_time = time.time()
# Define the options similar to the command-line options
ydl_opts = {
'format': 'b', # Use the 'b' format filter for best video quality
'geturl': True, # Return the final video URL
# 'format_sort': ['filesize~50M'], # Sort formats by filesize closest to 50M
# You may want to set the 'verbose': True for debugging
}
"
|
ef594bc44278c6e4b68160ae927844ab
|
{
"intermediate": 0.6783396005630493,
"beginner": 0.18914683163166046,
"expert": 0.13251353800296783
}
|
40,108
|
You are given this data structure:
HashMap<String, Vec<(u32, u32, Vec<(u32, u32)>, u32)>
where the first and second values of the tuple represent the start and end, the vector represents the exon coordinates of that transcripts and the last value represents the size of the transcripts in bps. This data structure is sorted by size in decreasing order. What we want to achieve is a new data structure that groups transcripts within the same coordinates. For the first value in a given key of the hashmap, the coordinates are 5 and 10, for example. The second value has 6 and 9, so the second transcript is within the first transcript coordinates (probably a shorter isoform). After that, we need to merge the exon coordinates (Vec<(u32, u32)>) taking care that there is no duplicates. The keys of the hashmap are chromosome names.
You are an expert in algorithms and the rust programming language. We need the fastest and most efficient solution. You are free to use any crate, trick, algorithm o approach (e.g. parallelization) you want.
|
58f44c47ddb05bb51a5a2823a5a3cd5c
|
{
"intermediate": 0.24595248699188232,
"beginner": 0.1006319597363472,
"expert": 0.6534155011177063
}
|
40,109
|
You are an expert Rust programmer. You are given this data structure:
HashMap<String, Vec<(u32, u32, Vec<(u32, u32)>)>
where the first and second values of the tuple represent the start and end, the vector represents the exon coordinates of that transcripts. This data structure is sorted by start and end values. What we want to achieve is a new data structure that groups transcripts within the same coordinates. For the first value in a given key of the hashmap, the coordinates are 5 and 10, for example. The second value has 6 and 9, so the second transcript is within the first transcript coordinates (probably a shorter isoform). After that, we need to merge the exon coordinates (Vec<(u32, u32)>) taking care that there is no duplicates. The keys of the hashmap are chromosome names. The output data structure should be of the form:
Vec<(u32, u32, Vec<(u32, u32)>)>, where the first to elements are the min start and the max end of the group and the Vec<(u32, u32)> is the vector with all the exon coordinates from the group without duplicates.
You are an expert in algorithms and the rust programming language. We need the fastest and most efficient solution. You are free to use any crate (e.g. intervaltree), trick, algorithm o approach (e.g. parallelization with rayon or scoped thread spawning) you want.
|
055883d6330650a119864982797c1bf2
|
{
"intermediate": 0.28243470191955566,
"beginner": 0.07272998243570328,
"expert": 0.644835352897644
}
|
40,110
|
Prove the following using limits.
3^𝑛 ∈ 𝜔(n^k). g(n) >= cf(n) for all n>=N
|
9b1104d00e2a802f45b5240926b0ec11
|
{
"intermediate": 0.33933892846107483,
"beginner": 0.23742526769638062,
"expert": 0.42323583364486694
}
|
40,111
|
You work for Nusun Power promoting the PPA program. You are creating an informational document for homeowners outlining all the details of the solar services. Make sure to make all details clear and enticing
|
36d67fd328074a9a1127d6053ac69edc
|
{
"intermediate": 0.3387850821018219,
"beginner": 0.2847253084182739,
"expert": 0.3764896094799042
}
|
40,112
|
You are an expert Rust programmer. You are given this data structure:
HashMap<String, Vec<(u32, u32, Vec<(u32, u32)>)>
where the first and second values of the tuple represent the start and end, the vector represents the exon coordinates of that transcripts. This data structure is sorted by start and end values. What we want to achieve is a new data structure that groups transcripts within the same coordinates. For the first value in a given key of the hashmap, the coordinates are 5 and 10, for example. The second value has 6 and 9, so the second transcript is within the first transcript coordinates (probably a shorter isoform). After that, we need to merge the exon coordinates (Vec<(u32, u32)>) taking care that there is no duplicates. The keys of the hashmap are chromosome names. The output data structure should be of the form:
Vec<(u32, u32, Vec<(u32, u32)>)>, where the first to elements are the min start and the max end of the group and the Vec<(u32, u32)> is the vector with all the exon coordinates from the group without duplicates.
It is important to reduce cloning, sorting and deduplications since they could reduce performance.
You are an expert in algorithms and the rust programming language. We need the fastest and most efficient solution. You are free to use any crate (e.g. intervaltree, boomhpf, itertools, hashbrown), trick, algorithm o approach (e.g. parallelization with rayon or scoped thread spawning) you want. You can also change the type of the data (e.g. use HashSet instead of Vec, etc).
|
6f5470e14dad9406eda1d74e964f2b61
|
{
"intermediate": 0.4349428713321686,
"beginner": 0.08605999499559402,
"expert": 0.4789971709251404
}
|
40,113
|
You are an expert Rust programmer. You are given this data structure:
HashMap<String, Vec<(u32, u32, Vec<(u32, u32)>)>
where the first and second values of the tuple represent the start and end, the vector represents the exon coordinates of that transcripts. This data structure is sorted by start and end values. What we want to achieve is a new data structure that groups transcripts within the same coordinates. For the first value in a given key of the hashmap, the coordinates are 5 and 10, for example. The second value has 6 and 9, so the second transcript is within the first transcript coordinates (probably a shorter isoform). After that, we need to merge the exon coordinates (Vec<(u32, u32)>) taking care that there is no duplicates. The keys of the hashmap are chromosome names. The output data structure should be of the form:
Vec<(u32, u32, Vec<(u32, u32)>)>, where the first to elements are the min start and the max end of the group and the Vec<(u32, u32)> is the vector with all the exon coordinates from the group without duplicates.
It is important to reduce cloning, sorting and deduplications since they could reduce performance.
You are an expert in algorithms and the rust programming language. We need the fastest and most efficient solution. You are free to use any crate (e.g boomhpf, itertools, hashbrown), trick, algorithm o approach (e.g. parallelization with rayon or scoped thread spawning) you want. You can also change the type of the data (e.g. use HashSet instead of Vec, etc).
|
62cf3182f8aa7db0a24aa8d45fb9368e
|
{
"intermediate": 0.4558868110179901,
"beginner": 0.07882464677095413,
"expert": 0.46528854966163635
}
|
40,114
|
import Codec from './Codec';
import { PACKET } from '../../Enumerations';
import EventEmitter from 'events';
class NetworkAdapter {
constructor() {
this.ping = 0;
this.pingStart = null;
this.pingCompletion = null;
this.connected = false;
this.connecting = false;
this.codec = new Codec();
this.emitter = new EventEmitter();
this.emitter.setMaxListeners(50);
this.addConnectHandler(this.sendPingIfNecessary.bind(this));
this.addPingHandler(this.onPing.bind(this));
this.emitter.on('connected', event => {
console.log(`Websocket connection established`);
this.connecting = false;
this.connected = true;
});
this.emitter.on('close', event => {
console.warn(`Websocket connection has been closed`);
this.connecting = false;
this.connected = false;
});
}
connect(serverId) {
if (this.connecting) {
return;
}
this.connectionOptions = serverId;
this.connected = false;
this.connecting = true;
const options = {
headers: {
'Accept-Encoding': 'gzip, deflate, br',
'Accept-Language': 'en-US,en;q=0.9',
'Cache-Control': 'no-cache',
Origin: "https://zombs.io",
Host: this.connectionOptions.hostname,
}
}
console.log(`Connecting:${serverId.hostname}:${serverId.port}`)
this.socket = new WebSocket(`wss://${serverId.hostname}:${serverId.port}`, options);
this.socket.binaryType = 'arraybuffer';
this.bindEventListeners();
setTimeout(() => {
game.ui.components.Reconnect.hide();
}, 1000);
}
bindEventListeners() {
this.socket.addEventListener('open', this.emitter.emit.bind(this.emitter, 'connected'));
this.socket.addEventListener('message', this.onMessage.bind(this));
this.socket.addEventListener('close', this.emitter.emit.bind(this.emitter, 'close'));
this.socket.addEventListener('error', this.emitter.emit.bind(this.emitter, 'error'));
}
disconnect() {
this.socket.close();
}
reconnect(allowed) {
if (allowed) return this.connect(this.connectionOptions);
}
getPing() {
return this.ping;
}
sendPacket(event, data) {
if (!this.connected || !data) {
return;
}
if (event == 4 || event == 5 || event == 9 || event == 3 || event == 7 || event == 6) {
this.socket.send(this.codec.encode(event, data));
}
}
onMessage(event) {
this.sendPingIfNecessary();
var message = this.codec.decode(event.data);
this.emitter.emit(PACKET[message.opcode], message);
}
sendPingIfNecessary() {
this.connecting = false;
this.connected = true;
const pingInProgress = (this.pingStart != null);
if (pingInProgress) {
return;
}
if (this.pingCompletion != null) {
const msSinceLastPing = (new Date().getTime() - this.pingCompletion.getTime());
if (msSinceLastPing <= 5000) {
return;
}
}
this.pingStart = new Date();
this.sendPing({
nonce: 0
});
}
onPing() {
const now = new Date();
this.ping = (now.getTime() - this.pingStart.getTime()) / 2;
this.pingStart = null;
this.pingCompletion = now;
}
sendEnterWorld(data) {
this.sendPacket(PACKET.ENTER_WORLD, data);
}
sendEnterWorld2() {
this.sendPacket(PACKET.ENTER_WORLD2, {});
}
sendInput(data) {
this.sendPacket(PACKET.INPUT, data);
}
sendPing(data) {
this.sendPacket(PACKET.PING, data);
}
sendRpc(data) {
this.sendPacket(PACKET.RPC, data);
}
addPreEnterWorldHandler(callback) {
this.addPacketHandler(PACKET.PRE_ENTER_WORLD, packet => {
callback(packet);
});
}
addEnterWorldHandler(callback) {
this.addPacketHandler(PACKET.ENTER_WORLD, packet => {
callback(packet);
});
}
addEntityUpdateHandler(callback) {
this.addPacketHandler(PACKET.ENTITY_UPDATE, packet => {
callback(packet);
});
}
addPingHandler(callback) {
this.addPacketHandler(PACKET.PING, response => {
callback(response);
});
}
addRpcHandler(rpcName, callback) {
this.addPacketHandler(PACKET.RPC, rpc => {
if (rpcName === rpc.name)
return callback(rpc.response);
});
}
addConnectHandler(callback) {
this.emitter.on('connected', callback);
}
addCloseHandler(callback) {
this.emitter.on('close', callback);
}
addErrorHandler(callback) {
this.emitter.on('error', callback);
}
addPacketHandler(opcode, callback) {
this.emitter.on(PACKET[opcode], callback);
}
}
export default NetworkAdapter;
Replace EventEmitter with the JS CustomEvent API
|
dcb635b9fc10448bfdb151be5ae2e933
|
{
"intermediate": 0.26025843620300293,
"beginner": 0.6027093529701233,
"expert": 0.13703225553035736
}
|
40,115
|
You are an expert Rust programmer. You are given this data structure:
HashMap<String, Vec<(u32, u32, Vec<(u32, u32)>)>
where the first and second values of the tuple represent the start and end, the vector represents the exon coordinates of that transcripts. This data structure is sorted by start and end values. What we want to achieve is a new data structure that groups transcripts within the same coordinates. For the first value in a given key of the hashmap, the coordinates are 5 and 10, for example. The second value has 6 and 9, so the second transcript is within the first transcript coordinates (probably a shorter isoform). After that, we need to merge the exon coordinates (Vec<(u32, u32)>) taking care that there is no duplicates. The keys of the hashmap are chromosome names. The output data structure should be of the form:
Vec<(u32, u32, Vec<(u32, u32)>)>, where the first to elements are the min start and the max end of the group and the Vec<(u32, u32)> is the vector with all the exon coordinates from the group without duplicates.
It is important to reduce cloning, sorting and deduplications since they could reduce performance.
You are an expert in algorithms and the rust programming language. We need the fastest and most efficient solution. You are free to use any crate (e.g. intervaltree, boomhpf, itertools, hashbrown), trick, algorithm o approach (e.g. parallelization with rayon or scoped thread spawning) you want. You can also change the type of the data (e.g. use HashSet instead of Vec, etc).
Some additional ideas: we can use a HashSet to not worry about deduplications and sort it at the end (as a vector); we can use rayon to split the work by chromosomes; we can use itertools to iterate efficiently; etc.
|
d3df2d1deaaab5131ee84bd195c8ee88
|
{
"intermediate": 0.5572697520256042,
"beginner": 0.05558408796787262,
"expert": 0.38714614510536194
}
|
40,116
|
Consider the following algorithm:
for (i= 2; i < n; i++) { for(j=0; j <= n) { cout << i << j; jj+[n/4];
}(a) What is the output when n=4?
(b) What is the time complexity T(n). You may assume that n is divisible by 4.
|
ff61ea8720dba9fe699c4179b53b1585
|
{
"intermediate": 0.10004263371229172,
"beginner": 0.08512678742408752,
"expert": 0.8148305416107178
}
|
40,117
|
What are anonymous functions in javascript?
|
68d7d889655775e4a7b81d8449c81900
|
{
"intermediate": 0.27216973900794983,
"beginner": 0.4754720628261566,
"expert": 0.25235822796821594
}
|
40,118
|
In postgres, how do I alter a column in a table to add references other_table(...)
|
712e17d1687db33018a96083f0539fc9
|
{
"intermediate": 0.39723971486091614,
"beginner": 0.38119956851005554,
"expert": 0.2215607762336731
}
|
40,119
|
Prepare a data for a dentistry problem and simulate access be most appropriate number of items for a time period of 2 hours
|
e0f02644a599861637b6fcc9c8dc3723
|
{
"intermediate": 0.34547173976898193,
"beginner": 0.23576584458351135,
"expert": 0.41876235604286194
}
|
40,120
|
Prepare a data for dentistry problem and simulate to access be most appropriate number of items for a time period of 2 hours
|
61805cdb30017bfc20faf3343ebfacd2
|
{
"intermediate": 0.3899995684623718,
"beginner": 0.2722063958644867,
"expert": 0.3377939760684967
}
|
40,121
|
In the following VBA, I need to change the search condition of 'nameToFind = personResponsibleSheet.Range("A2").Value' in sheets range 'If nameToFind = "" Or currentSheet.Cells(i, "AB").Value = nameToFind Then'
What I would like is as follows: If any of the words in personResponsibleSheet.Range("A2").Value are found in the sheet range AB, then
provide the data requested that will be dispalyed in column B & C of sheet Person Responsible.
Sub RunSearch()
Me.Unprotect Password:="edit"
Application.EnableEvents = False
Dim personResponsibleSheet As Worksheet
Set personResponsibleSheet = ThisWorkbook.Worksheets("Person Responsible")
' Clear existing entries in columns B and C, starting from row 2
personResponsibleSheet.Range("B2:C" & personResponsibleSheet.Cells(Rows.Count, "B").End(xlUp).Row).ClearContents
Dim nameToFind As String
nameToFind = personResponsibleSheet.Range("A2").Value
Dim sheetToCheck As String
sheetToCheck = personResponsibleSheet.Range("A5").Value
Dim checkSheets As Collection
If sheetToCheck = "All Checks" Then
Set checkSheets = GetCheckSheets ' Search all "Checks" sheets
ElseIf sheetToCheck <> "" Then
Set checkSheets = New Collection
If WorksheetExists(sheetToCheck) Then
checkSheets.Add ThisWorkbook.Worksheets(sheetToCheck)
End If
ElseIf nameToFind <> "" Then
Set checkSheets = GetCheckSheets ' Search all "Checks" sheets if only name is provided
Else
' No name in A2, no sheet in A5, check all "Checks" sheets
Set checkSheets = GetCheckSheets
End If
Dim outputRow As Long
outputRow = 2
Dim currentSheet As Worksheet
For Each currentSheet In checkSheets
Dim lastRow As Long
lastRow = currentSheet.Cells(Rows.Count, "AB").End(xlUp).Row
Dim i As Long
For i = 1 To lastRow
If nameToFind = "" Or currentSheet.Cells(i, "AB").Value = nameToFind Then
personResponsibleSheet.Cells(outputRow, 2).Value = currentSheet.Cells(i, 1).Value
personResponsibleSheet.Cells(outputRow, 3).Value = currentSheet.Cells(1, 1).Value
outputRow = outputRow + 1
End If
Next i
Next currentSheet
Application.Wait (Now + TimeValue("0:00:01"))
personResponsibleSheet.Range("B1").Value = personResponsibleSheet.Range("A2").Value
personResponsibleSheet.Range("C1").Value = personResponsibleSheet.Range("A5").Value
Application.EnableEvents = True
Me.Protect Password:="edit"
End Sub
|
743b0a7269e452b0bc1d684deff0d4df
|
{
"intermediate": 0.31731075048446655,
"beginner": 0.3600560128688812,
"expert": 0.32263320684432983
}
|
40,122
|
Prepare a data for dentistry problem and simulate to access be most appropriate number of items for a time period of 2 hours
|
dcb1453dabfb3cbfa4956acc78648d00
|
{
"intermediate": 0.3899995684623718,
"beginner": 0.2722063958644867,
"expert": 0.3377939760684967
}
|
40,123
|
Add a double jump to this script. So that the player can click on Space one more time when the character is in the air during the jump.
using UnityEngine;
[RequireComponent(typeof(Rigidbody2D))]
public class MoveObject : MonoBehaviour
{
public float speed = 5f;
public float jumpForce = 5f;
public float gravity = 3.8f;
private Rigidbody2D rb;
private Vector2 velocity;
public bool isGrounded;
public bool isJump;
private int layerMask;
void Start()
{
rb = GetComponent<Rigidbody2D>();
rb.gravityScale = gravity; // Применяем значение гравитации
}
void Update()
{
// Каст луча вниз из центра персонажа на небольшое расстояние
RaycastHit2D hit = Physics2D.Raycast(transform.position, transform.TransformDirection(Vector2.down), 0.2f, ~LayerMask.GetMask("Player"));
if (hit) //Условие если рейкаст под ногами игрока задевает землю
{
if (Input.GetKeyDown(KeyCode.Space))
{
Jump();
}
}
float horizontalInput = Input.GetAxis("Horizontal");
Vector2 movement = new Vector2(horizontalInput * speed, 0f);
velocity.y -= gravity * Time.deltaTime;
velocity.x = movement.x;
velocity.y = rb.velocity.y;
rb.velocity = new Vector2(velocity.x, velocity.y);
}
void Jump()
{
rb.velocity = new Vector2 (rb.velocity.x, jumpForce);
}
}
|
ee5d5595aa0adfc15a2475701827267d
|
{
"intermediate": 0.3984543979167938,
"beginner": 0.3719189763069153,
"expert": 0.2296266257762909
}
|
40,124
|
Can you write code for a neural network that takes video as input converts the sign language into text? It should be using skeletanization to get the data from the person in the video.
|
a3d639566b3434eb9b541113de00263c
|
{
"intermediate": 0.06924892216920853,
"beginner": 0.020395204424858093,
"expert": 0.9103558659553528
}
|
40,125
|
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen1.5-72B-Chat",
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen1.5-72B-Chat")
prompt = "Give me a short introduction to large language model."
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(device)
generated_ids = model.generate(
model_inputs.input_ids,
max_new_tokens=512
)
generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
|
101d1d0eb2ba233d6e4b3bf952c6ac98
|
{
"intermediate": 0.40062612295150757,
"beginner": 0.25315946340560913,
"expert": 0.3462144136428833
}
|
40,126
|
how to run a cmd command with admin via python script?
|
612e85bbfe2598808a8b3f436dde3af4
|
{
"intermediate": 0.42693260312080383,
"beginner": 0.2901225984096527,
"expert": 0.28294479846954346
}
|
40,127
|
Is there a way to merge two contiguous lines on Vim in a way that the characters from one line occupy the same position (column) as the blank spaces on the followingh libne
|
76aa5df44847d63d61d6dfa69eea55af
|
{
"intermediate": 0.5124167203903198,
"beginner": 0.16065874695777893,
"expert": 0.326924592256546
}
|
40,128
|
how to reconnect my wifi adapter via python script?
|
a59bbc64acfbaa9981c78c250768a20a
|
{
"intermediate": 0.5565976500511169,
"beginner": 0.1925012618303299,
"expert": 0.25090107321739197
}
|
40,129
|
today date
|
75404de3154dc926d1e1b2c92df82575
|
{
"intermediate": 0.36189067363739014,
"beginner": 0.3130026161670685,
"expert": 0.32510676980018616
}
|
40,130
|
Is it pissible in Linux that tcp socket is closed by core for internal error, for example lack of free memory?
|
6584fcee9f02b42517a16869fa8cbe2a
|
{
"intermediate": 0.4539247751235962,
"beginner": 0.2392846643924713,
"expert": 0.3067905902862549
}
|
40,131
|
I am trying to separate a satellite image into different tracts of houses. This is the preprocessing code. It isnt doing a very good job
import cv2
import numpy as np
def preprocess_image(image_path):
# Read the image
image = cv2.imread(image_path)
# Convert the image to Grayscale
grayscale_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Apply Gaussian Blur to smooth the image and reduce noise
blurred_image = cv2.GaussianBlur(grayscale_image, (5, 5), 0)
# Apply Canny Edge Detection to find edges in the image
edges = cv2.Canny(blurred_image, threshold1=50, threshold2=150)
# Optional: Increase the size of the edges to make them more visible
# dilated_edges = cv2.dilate(edges, np.ones((3, 3), np.uint8), iterations=1)
# Apply Adaptive Thresholding to segment the image
segmented_image = cv2.adaptiveThreshold(blurred_image, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
cv2.THRESH_BINARY, 11, 2)
# Combine the edges with the original image or the segmented image if using segmentation
# edge_highlighted_image = cv2.bitwise_and(segmented_image, segmented_image, mask=edges)
# The output of the preprocessing could be the edge-detected image or
# the edge-highlighted image if combining with the segmentation.
return edges # or return edge_highlighted_image if using segmentation
# Sample usage
processed_image = preprocess_image('satellite_image.jpg')
cv2.imwrite('processed_satellite_image.jpg', processed_image)
|
aee41d662bdf93b806de31a4a841a4d9
|
{
"intermediate": 0.46203261613845825,
"beginner": 0.2468409538269043,
"expert": 0.2911263704299927
}
|
40,132
|
hi
|
a67471e8ec777d1043dd178b103dc9fc
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
40,133
|
Deepika wants her server should be free from intruder. She wants to detect whether the received client request is a legitimate or an attack (normal/attack). Design an incursion detection model to help Deepika using Adaboost classifier.
give me python program
|
aa4c0f4d6f3a1b5cb776f553451acf3f
|
{
"intermediate": 0.19036974012851715,
"beginner": 0.16840839385986328,
"expert": 0.6412218809127808
}
|
40,134
|
para="Thanks for calling Virgin Media Gadget Rescue. This is Roshni here. How may I help you today? Hello. Can you hear me? Hello. Hey, hi. This is Roshni from Virgin Media Gadget Rescue. Hello. Hello. Can you hear me? Are you audible to you? I can, yes. I can hear you, yeah. Yeah. So may I know, like, about your issue? How you audible to you? I can, yes. I can hear you, yeah. Yeah. So may I know like about your issue? How may I help you today? I'm trying to go on to Netflix and it's saying as if I haven't got an account, but I have. Okay, so you're... My subscription. Okay, okay, okay. So it is in your subscription but you are trying to open the Netflix it is stating that you don't have any subscription right in fact I haven't got one yet but I have because I used it last week and it is included in my you know my channel ok ok I am really sorry for the inconvenience but don't worry about it. Let me have a look on this issue. I'll try my best to fix that, okay? Don't worry about it. Yeah, so can you help me with your Virgin Media Home phone number so that I can fit into your account details? 01273 6080 01273 608058 583 right? No, 58, just 58. Okay, just 58. 01273 608058 That's right, yes. Okay, may I take this as the best callback number in case the call gets disconnected and I reach you on the on the same yeah this one I'll lock it in my mobile okay can you help me with your mobile number so the mobile number would be the best callback number right yes probably yes I'd oh seven nine one four okay oh Okay, 07914951659. Can you repeat the first four digits once again? 07914951659. Okay, thank you so much. Thanks for the confirmation. 914-951-659. Okay. Thank you so much. Thanks for the confirmation. Can you help me with the account holders first and last name? Julie Breeden. Okay. Am I speaking to the account holder? Yes, you are. Yes. Okay. Thanks for the confirmation, Julie. Let me check whether your account has been validated or not. Okay. Yes. Julie let me check whether your account has been validated or not yeah so miss Julie man I like when you are since when you are facing this issue well I tried it and the other day last week and it come up there and I just bought practice just an error just that day that you know something wrong that day you know gonna be sick again today and it's still the same okay okay okay Julie not to worry so I could see that your account has been already by validated by the previous technician so don't worry about it let me check regarding the Netflix bundle so apart from this you don't have any issue on the other devices, right? Oh, no. Someone came up last week because I had an issue with one of my TV boxes upstairs, but that's been done now. But yeah, so it's just the Netflix now. Netflix now. Okay, take your time. Sorry, what was it? What did you want me to do? Sorry. Like apart from this, you don't have any other issues on your, any other devices? No, no, no. Like I said, only last week there was a problem but they cut someone came out and fix that that was something else that was because one the box okay Julie okay I could see that you are you are the egg mean have the subscription Netflix subscription from Virgin Media so what I will do is I will have a word with our television department and I will check regarding the same, okay? No need to worry about it. Okay. So, is there anything else, Miss Julie, apart from this, I could help you today? No, it's just that. That's all it was. Okay. Thank you so much. Just stay connected on the line. I will connect you to the consent team, Julie. Okay. Thanks, Jay. Yeah much. Just stay connected on the line. I will connect you to the consent team, Julie. Okay, thank you. Yeah, thanks for calling Virgin Media Gadget Rescue. Just stay connected on the line, please. Okay, thank you. Yeah.
"
write a machine learning code for breaking down para into three sections viz. call opening, working session and call ending. Display the sentences of each section in the output
|
a3cf43647fcb0b193ce2fa6725527d9d
|
{
"intermediate": 0.4140177369117737,
"beginner": 0.33500558137893677,
"expert": 0.25097668170928955
}
|
40,135
|
hi
|
a41bb770657e8f69c5ee8380c42f6f6b
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
40,136
|
Как считать следующую структуру из файла за один вызов read?
#pragma pack(1)
struct PCXFile::TPCXHeaderStruct
{
unsigned char ID;
unsigned char Version;
unsigned char Coding;
unsigned char BitPerPixel;
unsigned short XMin;
unsigned short YMin;
unsigned short XMax;
unsigned short YMax;
unsigned short HRes;
unsigned short VRes;
unsigned char Palette[48];
unsigned char Reserved;
unsigned char Planes;
unsigned short BytePerLine;
unsigned short PaletteInfo;
unsigned short HScreenSize;
unsigned short VScreenSize;
unsigned char Filler[54];
} *TPCXHeader;
|
a4cd384cb1480cca066b7ad593e714d7
|
{
"intermediate": 0.43889498710632324,
"beginner": 0.3428115248680115,
"expert": 0.2182934284210205
}
|
40,137
|
whats a good ps tool for making documents andalso text lookin like hand writing? for debian? that can run on qubes os
|
bf956d0decd7853c3b877b4c8ea2a363
|
{
"intermediate": 0.4389021396636963,
"beginner": 0.25178566575050354,
"expert": 0.30931219458580017
}
|
40,138
|
Deepika wants her server should be free from intruder. She wants to detect whether the received client request is a legitimate or an attack (normal/attack). Design an incursion detection model to help Deepika using Adaboost classifier.
give me python program
FEATURE SELECTION
rfc = RandomForestClassifier();
Importance of feature in visual plots
training and test accuracy and confusion matrix and heat map
Testcsv contains:
duration protocol_type service flag src_bytes dst_bytes land wrong_fragment urgent hot num_failed_logins logged_in num_compromised root_shell su_attempted num_root num_file_creations num_shells num_access_files num_outbound_cmds is_host_login is_guest_login count srv_count serror_rate srv_serror_rate rerror_rate srv_rerror_rate same_srv_rate diff_srv_rate srv_diff_host_rate dst_host_count dst_host_srv_count dst_host_same_srv_rate dst_host_diff_srv_rate dst_host_same_src_port_rate dst_host_srv_diff_host_rate dst_host_serror_rate dst_host_srv_serror_rate dst_host_rerror_rate dst_host_srv_rerror_rate
Traincsv contains:
duration protocol_type service flag src_bytes dst_bytes land wrong_fragment urgent hot num_failed_logins logged_in num_compromised root_shell su_attempted num_root num_file_creations num_shells num_access_files num_outbound_cmds is_host_login is_guest_login count srv_count serror_rate srv_serror_rate rerror_rate srv_rerror_rate same_srv_rate diff_srv_rate srv_diff_host_rate dst_host_count dst_host_srv_count dst_host_same_srv_rate dst_host_diff_srv_rate dst_host_same_src_port_rate dst_host_srv_diff_host_rate dst_host_serror_rate dst_host_srv_serror_rate dst_host_rerror_rate dst_host_srv_rerror_rate class
class: normal (or) anomaly
dataset fetched from https://www.kaggle.com/code/aman1801/network-intrusion-detection-upgraded/input
|
f91a43fea636f8689194df9f3aa87270
|
{
"intermediate": 0.11686408519744873,
"beginner": 0.136300191283226,
"expert": 0.7468357682228088
}
|
40,139
|
Переберите значения порогов от 0 до 0.3 с шагом 0.02. Найдите для каждого значения точность и полноту. Напечатайте результаты на экране (в прекоде).
Чтобы создать цикл с нужным диапазоном, мы применили функцию arange() (от англ. «упорядочивать») библиотеки numpy. Как и range(), функция перебирает указанные элементы диапазона, но работает не только с целыми, но и дробными числами.
import pandas as pd
2
import numpy as np
3
from sklearn.model_selection import train_test_split
4
from sklearn.linear_model import LogisticRegression
5
from sklearn.metrics import precision_score, recall_score
6
7
data = pd.read_csv('/datasets/travel_insurance_preprocessed.csv')
8
9
target = data['Claim']
10
features = data.drop('Claim', axis=1)
11
features_train, features_valid, target_train, target_valid = train_test_split(
12
features, target, test_size=0.25, random_state=12345)
13
14
model = LogisticRegression(random_state=12345, solver='liblinear')
15
model.fit(features_train, target_train)
16
probabilities_valid = model.predict_proba(features_valid)
17
probabilities_one_valid = probabilities_valid[:, 1]
18
19
for threshold in np.arange(0, 0.3, 0.02):
20
predicted_valid = # < напишите код здесь >
21
precision = # < напишите код здесь >
22
recall = # < напишите код здесь >
23
24
print("Порог = {:.2f} | Точность = {:.3f}, Полнота = {:.3f}".format(
25
threshold, precision, recall))
|
7bbe011941449102c1a674563de255cd
|
{
"intermediate": 0.3268088698387146,
"beginner": 0.45465922355651855,
"expert": 0.21853192150592804
}
|
40,140
|
Привет! Мне нужно сделать админ-команду, которая будет отправлять файл БД администратору по команде. Вот код моего бота: import asyncio
from io import BytesIO
from PIL import Image, ImageFilter
import aiohttp
import time
from aiogram import Bot, Dispatcher, types, executor
from aiogram.contrib.fsm_storage.memory import MemoryStorage
from aiogram.dispatcher import FSMContext
from aiogram.dispatcher.filters.state import State, StatesGroup
from aiosqlite import connect
import logging
from aiogram.utils.exceptions import MessageNotModified
from aiogram.types import ReplyKeyboardMarkup, KeyboardButton, InlineKeyboardMarkup, InlineKeyboardButton, ParseMode
from aiogram import types
from aiogram.dispatcher.middlewares import BaseMiddleware
from aiogram.dispatcher.handler import CancelHandler
from aiogram.dispatcher.middlewares import LifetimeControllerMiddleware
from collections import defaultdict
import ssl
logging.basicConfig(level=logging.INFO)
ADMINS=[989037374,6663889022]
TOKEN = "6355900946:AAEnbcyMpnFGsvB22hdgeHDlzUVjghmpfrY"
bot = Bot(token=TOKEN)
storage = MemoryStorage()
dp = Dispatcher(bot, storage=storage)
# Создание таблиц если они не существуют
async def init_db():
logging.info("инициализация БД")
async with connect('bot.db') as db:
await db.execute("""
CREATE TABLE IF NOT EXISTS backgrounds (
id INTEGER PRIMARY KEY,
user_id INTEGER NOT NULL,
photo_id TEXT NOT NULL
)
""")
await db.execute("""
CREATE TABLE IF NOT EXISTS userphotos (
id INTEGER PRIMARY KEY,
user_id INTEGER NOT NULL,
photo_id TEXT NOT NULL
)
""")
await db.execute("""
CREATE TABLE IF NOT EXISTS users (
user_id INTEGER PRIMARY KEY,
is_banned INTEGER DEFAULT 0,
first_name TEXT,
username TEXT
)
""")
await db.execute("""
CREATE TABLE IF NOT EXISTS common_backgrounds (
id INTEGER PRIMARY KEY,
photo_id TEXT NOT NULL
)
""")
await db.commit()
from aiogram.utils.markdown import escape_md
class MailingState(StatesGroup):
waiting_for_message = State()
waiting_for_buttons = State()
from aiogram.utils.markdown import quote_html
@dp.message_handler(commands=['profile'], user_id=ADMINS, state='*')
async def cmd_profile(message: types.Message):
# Разбор аргумента команды
arg = message.get_args()
# Проверка, является ли аргумент числом (user_id) или строкой (username)
user_id = None
username = None
if arg.isdigit():
user_id = int(arg)
elif arg.startswith('@'):
username = arg[1:] # Удаляем @ в начале
# Если аргумент отсутствует
if not user_id and not username:
await message.reply("Необходимо указать user_id или username пользователя.")
return
# Поиск пользователя
async with connect('bot.db') as db:
if user_id:
cursor = await db.execute("""
SELECT user_id, username, use_common_backgrounds,
common_backgrounds_count, personal_backgrounds_count, is_banned
FROM users WHERE user_id = ?""", (user_id,))
else:
cursor = await db.execute("""
SELECT user_id, username, use_common_backgrounds,
common_backgrounds_count, personal_backgrounds_count, is_banned
FROM users WHERE username = ?""", (username,))
user_data = await cursor.fetchone()
# Если пользователь не найден
if not user_data:
await message.reply("Пользователь не найден.")
return
# Формирование сообщения для отправки администратору
profile_text = (
f"👨 *Профиль пользователя*\n\n"
f"User ID: {user_data[0]}\n"
f"Username: @{quote_html(user_data[1])}\n\n"
f"Использование общих фонов: *{'вкл' if user_data[2] else 'выкл'}*\n"
f"Количество использований общих фонов: {user_data[3]}\n"
f"Количество использований личных фонов: {user_data[4]}\n"
f"Статус: *{'забанен' if user_data[5] else 'активен'}*"
)
# Создание инлайн-кнопок
buttons = [
InlineKeyboardButton("Забанить", callback_data=f'ban_{user_data[0]}'),
InlineKeyboardButton("Разбанить", callback_data=f'unban_{user_data[0]}')
]
keyboard = InlineKeyboardMarkup().add(*buttons)
# Отправка сообщения
await message.reply(profile_text, parse_mode="MarkdownV2", reply_markup = keyboard)
@dp.callback_query_handler(lambda c: c.data.startswith('ban_'))
async def process_ban_button(callback_query: types.CallbackQuery):
admin_id = callback_query.from_user.id
if admin_id not in ADMINS: # Проверяем, что вызывающий команду является администратором
await callback_query.answer("Вы не являетесь администратором.")
return
user_id_to_ban = int(callback_query.data.split('_')[1])
async with connect('bot.db') as db:
await db.execute("INSERT OR IGNORE INTO banned_users (user_id) VALUES (?)", (user_id_to_ban,))
await db.commit()
await callback_query.answer(f"Пользователь {user_id_to_ban} заблокирован.")
@dp.callback_query_handler(lambda c: c.data.startswith('unban_'))
async def process_unban_button(callback_query: types.CallbackQuery):
admin_id = callback_query.from_user.id
if admin_id not in ADMINS:
await callback_query.answer("Вы не являетесь администратором.")
return
user_id_to_unban = int(callback_query.data.split('_')[1])
async with connect('bot.db') as db:
await db.execute("DELETE FROM banned_users WHERE user_id = ?", (user_id_to_unban,))
await db.commit()
await callback_query.answer(f"Пользователь {user_id_to_unban} разблокирован.")
# Обработчик команды /post, передаем состояние ожидания сообщения для рассылки
@dp.message_handler(commands=['post'], user_id=ADMINS, state='*')
async def cmd_post(message: types.Message):
await MailingState.waiting_for_message.set()
await message.reply("Отправьте текст рассылки")
# Обработчик текста рассылки, переводим в состояние ожидания кнопок
@dp.message_handler(state=MailingState.waiting_for_message, content_types=types.ContentTypes.TEXT)
async def post_message(message: types.Message, state: FSMContext):
await MailingState.waiting_for_buttons.set()
await state.update_data(mailing_text=message.text)
await message.reply(
"Теперь отправьте данные для inline-кнопок в формате: Текст кнопки;URL на каждую кнопку или /skip, если кнопки не нужны.")
# Обработчик кнопок для рассылки или пропуска их добавления
@dp.message_handler(state=MailingState.waiting_for_buttons)
async def post_buttons(message: types.Message, state: FSMContext):
if message.text != "/skip":
# Разбиваем сообщение по строкам и создаем кнопки
lines = message.text.split("\n")
buttons = [InlineKeyboardButton(text=line.split(';')[0], url=line.split(';')[1]) for line in lines if
len(line.split(';')) == 2]
markup = InlineKeyboardMarkup()
markup.add(*buttons)
else:
markup = None
# Получаем данные из состояния и текст рассылки
data = await state.get_data()
text = data.get('mailing_text')
mode = data.get('mailing_mode')
# Запускаем рассылку
success_count, failure_count = await send_mailing(text, mode, markup)
await state.finish() # Сброс состояния после рассылки
await message.answer(f"Рассылка выполнена. Успешно: {success_count}. Неудачно: {failure_count}.")
async def send_mailing(text, parse_mode, keyboard=None):
async with connect('bot.db') as db:
cursor = await db.execute("SELECT user_id FROM users")
user_ids = [row[0] for row in await cursor.fetchall()]
success_count = 0
failure_count = 0
for user_id in user_ids:
try:
await bot.send_message(
chat_id=user_id,
text=text,
reply_markup=keyboard,
parse_mode=types.ParseMode.HTML
)
success_count += 1
except Exception as e:
# Обрабатываем возможные исключения, например, если пользователь заблокировал бота
logging.error(f"Failed to send message to {user_id}: {e}")
failure_count += 1
return success_count, failure_count
# Обработчик команды /skip для пропуска добавления кнопок
@dp.message_handler(state=MailingState.waiting_for_buttons, commands=['skip'])
async def post_skip(message: types.Message, state: FSMContext):
await post_buttons(message, state)
# Хэндлер команды /sql для выполнения произвольных SQL-запросов (ТОЛЬКО для администраторов)
@dp.message_handler(commands=['sql'], user_id=ADMINS)
async def execute_sql_command(message: types.Message):
# Получаем аргументы команды (SQL-запрос)
sql_query = message.get_args()
# Проверяем, что запрос не пустой
if not sql_query:
await message.reply("Введите SQL-запрос.")
return
# Подключаемся к базе данных и выполняем запрос
async with connect('bot.db') as db:
try:
await db.execute(sql_query)
await db.commit()
await message.reply("SQL-запрос успешно выполнен.")
except Exception as e:
await message.reply(f"Ошибка при выполнении SQL-запроса: {e}")
class UploadBackgroundState(StatesGroup):
waiting_for_backgrounds = State()
class UploadUserPhotoState(StatesGroup):
waiting_for_user_photo = State()
# Админ-команда для очистки таблицы с общими фонами
@dp.message_handler(commands=['clear_common'], user_id=ADMINS)
async def clear_common_backgrounds(message: types.Message):
async with connect('bot.db') as db:
await db.execute("DELETE FROM common_backgrounds")
await db.commit()
await message.reply("Все общие фоны были успешно удалены из базы данных.")
# Админ-команда для просмотра количества общих фонов
@dp.message_handler(commands=['count_common'], user_id=ADMINS)
async def count_common_backgrounds(message: types.Message):
async with connect('bot.db') as db:
cursor = await db.execute("SELECT COUNT(*) FROM common_backgrounds")
count = await cursor.fetchone()
await message.reply(f"Количество общих фонов в базе данных: {count[0]}")
async def generate_invite_link(chat_id):
try:
chat_invite_link = await bot.create_chat_invite_link(chat_id, expire_date=int(time.time()) + 900) # на 15 минут
return chat_invite_link.invite_link
except Exception as e:
logging.error(e)
return None
async def is_user_subscribed(chat_id, user_id):
try:
member = await bot.get_chat_member(chat_id, user_id)
return member.status not in ["left", "kicked"]
except Exception as e:
logging.error(e)
return False # По умолчанию считаем, что пользователь не подписан, если возникла ошибка
CHANNEL_ID = "-1002046113496" # ID вашего канала
class SubscriptionCheckMiddleware(BaseMiddleware):
def __init__(self, channel_id):
super().__init__()
self.channel_id = channel_id
async def on_process_message(self, message: types.Message, data: dict):
member = await bot.get_chat_member(self.channel_id, message.from_user.id)
if member.status not in ["member", "administrator", "creator"]:
invite_link = await generate_invite_link(self.channel_id)
if invite_link:
keyboard = InlineKeyboardMarkup().add(
InlineKeyboardButton("🔗 Подписаться на канал", url=invite_link)
)
await message.answer(
f"🔒 Для продолжения работы с ботом *необходимо подписаться на наш новостной канал\.*\n\n👌 Если вы уже подписались на канал, нажмите /start",parse_mode="MarkdownV2",
reply_markup=keyboard
)
# прерываем обработку следующих хэндлеров
raise CancelHandler()
async def post_process(self, obj, data, *args):
pass
dp.middleware.setup(SubscriptionCheckMiddleware(CHANNEL_ID))
@dp.message_handler(commands=['count'])
async def count_backgrounds(message: types.Message):
user_id = message.from_user.id
async with connect('bot.db') as db:
cursor = await db.execute("SELECT COUNT(*) FROM backgrounds WHERE user_id = ?", (user_id,))
count = await cursor.fetchone()
await message.answer(f"У вас в базе данных *{count[0]}* фоновых изображений\.",parse_mode="MarkdownV2")
@dp.message_handler(commands=['ex'])
async def export_backgrounds(message: types.Message):
user_id = message.from_user.id
try:
# Получаем количество изображений для выгрузки из команды
command_args = message.get_args().split()
# если ничего не введено, выгрузить все
num_images = int(command_args[0]) if command_args else -1
except (IndexError, ValueError):
await message.answer("Укажите количество фонов для выгрузки. Например: /ex 10")
return
async with connect('bot.db') as db:
# Если num_images равен -1, значит выгрузить все изображения
query = "SELECT id, photo_id FROM backgrounds LIMIT ?"
cursor = await db.execute(query, (10 if num_images == -1 else num_images,))
backgrounds_chunk = await cursor.fetchall()
while backgrounds_chunk:
media_group = [types.InputMediaPhoto(photo[1]) for photo in backgrounds_chunk]
await bot.send_media_group(message.chat.id, media_group)
# Удаляем отправленные фоны из БД
await db.executemany("DELETE FROM backgrounds WHERE id = ?", [(photo[0],) for photo in backgrounds_chunk])
await db.commit()
if num_images != -1:
num_images -= len(backgrounds_chunk)
if num_images <= 0:
break
# Получаем следующую пачку изображений
cursor = await db.execute(query, (10 if num_images == -1 else min(num_images, 10),))
backgrounds_chunk = await cursor.fetchall()
await message.answer("*Все запрошенные фоновые изображения были выгружены и удалены из базы данных\.*",parse_mode="MarkdownV2")
LOG_CHANNEL_ID = "@smenalogs"
async def log_to_channel(user: types.User, action: str):
message_to_send = f"Пользователь @{user.username} ({user.id}) выполнил действие: {action}"
await bot.send_message(LOG_CHANNEL_ID, message_to_send)
stop_keyboard = ReplyKeyboardMarkup(resize_keyboard=True).add(KeyboardButton("Стоп"))
async def start_keyboard():
# Создаем начальную клавиатуру с кнопками "Замена фона" и "Личный кабинет"
return ReplyKeyboardMarkup(resize_keyboard=True).add(
KeyboardButton("🖼 Замена фона")
).add(
KeyboardButton("📊 Личный кабинет")
)
@dp.message_handler(commands=['stop'], state='*')
async def stop_processing(message: types.Message, state: FSMContext):
# …
await message.reply("Обработка фотографий прекращена.", reply_markup=await start_keyboard())
await state.finish()
@dp.message_handler(commands=['start', 'help'])
async def send_welcome(message: types.Message):
user_id = message.from_user.id
first_name = message.from_user.first_name
username = message.from_user.username
# Подключаемся к БД и проверяем, существует ли пользователь
async with connect('bot.db') as db:
cursor = await db.execute("SELECT user_id FROM users WHERE user_id = ?", (user_id,))
user_exists = await cursor.fetchone()
# Если пользователя нет в БД, сохраняем его
if not user_exists:
await db.execute("INSERT INTO users (user_id, first_name, username) VALUES (?, ?, ?)",
(user_id, first_name, username))
await db.commit()
# Создаем кнопки
button_photos = KeyboardButton("🖼 Замена фона")
button_cabinet = KeyboardButton("📊 Личный кабинет")
# Отправляем сообщение вместе с клавиатурой
await message.answer(
"Привет! Пользуйся кнопками",
reply_markup=await start_keyboard()
)
await log_to_channel(message.from_user, "прописал /start")
@dp.callback_query_handler(
lambda c: c.data == 'toggle_common_backgrounds_on' or c.data == 'toggle_common_backgrounds_off')
async def toggle_common_backgrounds(callback_query: types.CallbackQuery):
user_id = callback_query.from_user.id
# Переключаем состояние использования общих фонов
new_setting = not (callback_query.data == 'toggle_common_backgrounds_on')
# Сохраняем новое состояние в базу данных
async with connect('bot.db') as db:
await db.execute("UPDATE users SET use_common_backgrounds = ? WHERE user_id = ?", (int(new_setting), user_id))
await db.commit()
# Ответное сообщение пользователю
reply_text = "Общие фоны включены." if new_setting else "Общие фоны выключены."
await bot.answer_callback_query(callback_query.id, reply_text)
# Обновить сообщение в "личном кабинете", чтобы отразить изменения с "включено/выключено"
await personal_cabinet(callback_query)
@dp.callback_query_handler(lambda c: c.data == 'support')
async def support_callback(callback_query: types.CallbackQuery):
support_text = (
"❓ Если у вас есть вопросы, предложения, проблемы \- обращайтесь к администратору бота\.\n\n"
"*Нажмите на кнопку ниже, чтобы связаться\.*"
)
admin_button = InlineKeyboardMarkup().add(
InlineKeyboardButton("👨💻 Администратор бота", url="t.me/ih82seeucry")
)
await bot.edit_message_text(
chat_id=callback_query.message.chat.id,
message_id=callback_query.message.message_id,
text=support_text,
parse_mode="MarkdownV2",
reply_markup=admin_button
)
@dp.message_handler(lambda message: message.text == "📊 Личный кабинет")
async def personal_cabinet(message_or_query):
# Определяем, является ли объект сообщением или коллбэк-запросом
if isinstance(message_or_query, types.Message):
user_id = message_or_query.from_user.id
message = message_or_query
elif isinstance(message_or_query, types.CallbackQuery):
user_id = message_or_query.from_user.id
message = message_or_query.message
else:
return # Если полученный объект не поддерживается, не предпринимать никаких действий
async with connect('bot.db') as db:
cursor = await db.execute("SELECT COUNT(*) FROM backgrounds WHERE user_id = ?", (user_id,))
count = (await cursor.fetchone())[0]
cursor = await db.execute("SELECT use_common_backgrounds FROM users WHERE user_id = ?", (user_id,))
use_common_backgrounds = (await cursor.fetchone())[0]
common_bg_status = "включено" if use_common_backgrounds else "выключено"
cursor = await db.execute(
"SELECT common_backgrounds_count, personal_backgrounds_count FROM users WHERE user_id = ?", (user_id,))
counts = await cursor.fetchone()
common_bg_count = counts[0]
personal_bg_count = counts[1]
toggle_text = "Общие фоны: вкл" if use_common_backgrounds else "Общие фоны: выкл"
callback_data = 'toggle_common_backgrounds_on' if use_common_backgrounds else 'toggle_common_backgrounds_off'
keyboard = InlineKeyboardMarkup(row_width=1).add(
InlineKeyboardButton("Загрузить фоны", callback_data='upload_backgrounds'),
InlineKeyboardButton("Загрузить креатив", callback_data='upload_user_photos'),
InlineKeyboardButton("Очистить фоны", callback_data='clear_backgrounds'),
InlineKeyboardButton(toggle_text, callback_data=callback_data),
InlineKeyboardButton("Поддержка", callback_data='support')
)
text_message = f"*📊 Личный кабинет*\n\nКоличество фонов: {count}\nИспользование общих фонов *{common_bg_status}*\n\nКоличество использований общих фонов: {common_bg_count}\nКоличество использований личных фонов: {personal_bg_count}"
if isinstance(message_or_query, types.CallbackQuery):
try:
# Метод для изменения текста сообщения и клавиатуры
await bot.edit_message_text(text=text_message, chat_id=message.chat.id, message_id=message.message_id,
parse_mode="MarkdownV2", reply_markup=keyboard)
except MessageNotModified:
# Ничего не делаем, если содержимое сообщения не изменилось
pass
else:
await message.answer(text_message, parse_mode="MarkdownV2", reply_markup=keyboard)
@dp.callback_query_handler(lambda c: c.data == 'upload_backgrounds')
async def upload_backgrounds(callback_query: types.CallbackQuery):
await upload_background_start(callback_query.message)
await bot.send_message(callback_query.from_user.id, "Отправьте фоны для загрузки или нажмите Стоп, чтобы завершить.", reply_markup=stop_keyboard)
@dp.callback_query_handler(lambda c: c.data == 'upload_user_photos')
async def upload_user_photos(callback_query: types.CallbackQuery):
await clear_user_photos_action(callback_query.from_user.id)
await upload_user_photo_start(callback_query.message)
await bot.send_message(callback_query.from_user.id, "Отправьте креатив для загрузки или нажмите Стоп, чтобы завершить.", reply_markup=stop_keyboard)
@dp.callback_query_handler(lambda c: c.data == 'clear_backgrounds')
async def clear_backgrounds(callback_query: types.CallbackQuery):
confirmation_keyboard = InlineKeyboardMarkup().add(
InlineKeyboardButton("Да", callback_data='confirm_clear_backgrounds'),
InlineKeyboardButton("Нет", callback_data='cancel_clear_backgrounds')
)
await callback_query.message.edit_text(
"Вы уверены, что хотите удалить все свои фоны из базы? Это действие необратимо.",
reply_markup=confirmation_keyboard
)
@dp.callback_query_handler(lambda c: c.data == 'confirm_clear_backgrounds')
async def confirm_clear_backgrounds(callback_query: types.CallbackQuery):
user_id = callback_query.from_user.id
async with connect('bot.db') as db:
await db.execute("DELETE FROM backgrounds WHERE user_id = ?", (user_id,))
await db.commit()
await bot.answer_callback_query(callback_query.id, "Ваши фоновые изображения были удалены из базы данных.")
await callback_query.message.delete()
await log_to_channel(callback_query.from_user, "очистил свои фоновые изображения")
await send_welcome(callback_query.message)
@dp.callback_query_handler(lambda c: c.data == 'cancel_clear_backgrounds')
async def cancel_clear_backgrounds(callback_query: types.CallbackQuery):
await callback_query.message.delete()
await send_welcome(callback_query.message)
# общие фоны
class UploadCommonBackgroundState(StatesGroup):
waiting_for_common_backgrounds = State()
@dp.message_handler(commands=['common'], user_id=ADMINS, state='*')
async def upload_common_background_start(message: types.Message):
await UploadCommonBackgroundState.waiting_for_common_backgrounds.set()
await message.reply("Отправьте общие фоны для загрузки или нажмите Стоп, чтобы сохранить их в базу данных.",
reply_markup=stop_keyboard)
@dp.message_handler(content_types=['photo'], state=UploadCommonBackgroundState.waiting_for_common_backgrounds)
async def upload_common_background(message: types.Message, state: FSMContext):
photo_id = message.photo[-1].file_id
state_data = await state.get_data()
buffer = state_data.get('buffer', [])
buffer.append(photo_id)
await state.update_data(buffer=buffer)
await message.reply(
"Фон добавлен в очередь. Продолжайте добавлять фоны или нажмите Стоп, чтобы сохранить их в базу данных.")
@dp.message_handler(lambda message: message.text.lower() == "стоп",
state=UploadCommonBackgroundState.waiting_for_common_backgrounds)
async def stop_uploading_common_backgrounds(message: types.Message, state: FSMContext):
state_data = await state.get_data()
buffer = state_data.get('buffer', [])
if buffer:
async with connect('bot.db') as db:
await db.executemany("INSERT INTO common_backgrounds (photo_id) VALUES (?)",
[(photo_id,) for photo_id in buffer])
await db.commit()
await state.finish()
await message.reply("Все общие фоны сохранены в базу данных.", reply_markup=await start_keyboard())
@dp.callback_query_handler(lambda c: c.data == 'back_to_start')
async def back_to_start(callback_query: types.CallbackQuery):
await send_welcome(callback_query.message)
@dp.message_handler(commands=['clear_upload'])
async def clear_backgrounds(message: types.Message):
user_id = message.from_user.id # Получаем ID пользователя
async with connect('bot.db') as db:
# Удаляем только фоны конкретного пользователя
await db.execute("DELETE FROM backgrounds WHERE user_id = ?", (user_id,))
await db.commit()
await message.answer("Ваши фоновые изображения были удалены из базы данных.")
await log_to_channel(message.from_user, "очистил свои фоновые изображения")
async def clear_user_photos_action(user_id: int):
async with connect('bot.db') as db:
await db.execute("DELETE FROM userphotos WHERE user_id = ?", (user_id,))
await db.commit()
@dp.message_handler(commands=['clear_user'])
async def clear_user_photos(message: types.Message):
user_id = message.from_user.id
await clear_user_photos_action(user_id)
await message.answer("Ваш креатив был удален из базы данных.")
await log_to_channel(message.from_user, "очистил userphoto")
# Инициируем FSM для загрузки фонов
@dp.message_handler(commands=['upload'], state='*')
async def upload_background_start(message: types.Message):
logging.info("прием аплоад")
await UploadBackgroundState.waiting_for_backgrounds.set()
await log_to_channel(message.from_user, "прописал /upload")
# Инициируем FSM для загрузки пользовательского фото
@dp.message_handler(commands=['user'], state='*')
async def upload_user_photo_start(message: types.Message):
logging.info("прием юзер фото")
await UploadUserPhotoState.waiting_for_user_photo.set()
await log_to_channel(message.from_user, "загружает userphoto")
# Обработка загрузки фоновых фотографий
@dp.message_handler(content_types=['photo'], state=UploadBackgroundState.waiting_for_backgrounds)
async def upload_background(message: types.Message, state: FSMContext):
user_id = message.from_user.id
photo_id = message.photo[-1].file_id
state_data = await state.get_data()
buffer = state_data.get("buffer", [])
buffer.append((user_id, photo_id))
await state.update_data(buffer=buffer)
await message.answer("*Фон добавлен\.* Не забудьте нажать Стоп, чтобы сохранить все ваши фото в базу",parse_mode="MarkdownV2")
# Обработка загрузки пользовательских фотографий
@dp.message_handler(content_types=['photo'], state=UploadUserPhotoState.waiting_for_user_photo)
async def upload_user_photo(message: types.Message, state: FSMContext):
user_id = message.from_user.id
photo_id = message.photo[-1].file_id
state_data = await state.get_data()
buffer = state_data.get("buffer", [])
buffer.append((user_id, photo_id))
await state.update_data(buffer=buffer)
await message.answer("*Фото креатива добавлено в очередь\.* Не забудьте нажать Стоп, чтобы сохранить все ваши фото в базу",parse_mode="MarkdownV2")
# Переход обратно в обычное состояние после команды /stop
@dp.message_handler(commands=['stop'], state='*')
async def stop_processing(message: types.Message, state: FSMContext):
logging.info("Процесс остановлен пользователем")
await state.finish()
await message.reply("Обработка фотографий прекращена.", reply_markup=await start_keyboard())
@dp.message_handler(lambda message: message.text.lower() == "стоп", state=UploadBackgroundState.waiting_for_backgrounds)
async def stop_processing_background(message: types.Message, state: FSMContext):
state_data = await state.get_data()
buffer = state_data.get("buffer", [])
if buffer:
async with connect('bot.db') as db:
await db.executemany("INSERT INTO backgrounds (user_id, photo_id) VALUES (?, ?)", buffer)
await db.commit()
await state.update_data(buffer=[]) # Очистка буфера после сохранения
await state.finish()
await message.answer("*Все фоны сохранены в базу данных\.*",parse_mode="MarkdownV2", reply_markup=await start_keyboard())
# Обработка команды "Стоп" для загрузки фотографий пользователя
@dp.message_handler(lambda message: message.text.lower() == "стоп", state=UploadUserPhotoState.waiting_for_user_photo)
async def stop_processing_user_photo(message: types.Message, state: FSMContext):
state_data = await state.get_data()
buffer = state_data.get("buffer", [])
if buffer:
async with connect('bot.db') as db:
await db.executemany("INSERT INTO userphotos (user_id, photo_id) VALUES (?, ?)", buffer)
await db.commit()
await state.update_data(buffer=[]) # Очистка буфера после сохранения
await state.finish()
await message.answer("*Все ваши фотографии сохранены в базу данных\.*",parse_mode="MarkdownV2", reply_markup=await start_keyboard())
async def fetch_photo(file_url):
async with aiohttp.ClientSession() as session:
async with session.get(file_url, ssl=False) as resp:
return await resp.read()
async def create_banned_users_table():
async with connect('bot.db') as db:
await db.execute("""
CREATE TABLE IF NOT EXISTS banned_users (
user_id INTEGER PRIMARY KEY
)
""")
await db.commit()
class BanUserState(StatesGroup):
waiting_for_user_id = State()
# Добавьте обработку команды /ban только для администраторов
@dp.message_handler(commands=['ban'], user_id=ADMINS) # Замените ADMINS на список ID администраторов
async def ban_user_command(message: types.Message):
args = message.get_args().split()
if not args or not args[0].isdigit():
await message.reply("Необходимо указать ID пользователя для блокировки: /ban 123456789")
return
user_id_to_ban = int(args[0])
async with connect('bot.db') as db:
await db.execute("INSERT OR IGNORE INTO banned_users (user_id) VALUES (?)", (user_id_to_ban,))
await db.commit()
await message.reply(f"Пользователь {user_id_to_ban} заблокирован.")
# Добавьте проверку на наличие пользователя в списке заблокированных перед любым действием с ботом
class CheckBanMiddleware(BaseMiddleware):
async def on_process_message(self, message: types.Message, data: dict):
user_id = message.from_user.id
async with connect('bot.db') as db:
cursor = await db.execute("SELECT user_id FROM banned_users WHERE user_id = ?", (user_id,))
is_banned = await cursor.fetchone() is not None
if is_banned:
admin_button = InlineKeyboardMarkup().add(
InlineKeyboardButton("👨💻 Администратор бота", url="t.me/ih82seeucry")
)
await message.answer(
"*Вы заблокированы администратором бота\.* Если у вас есть вопросы \- обратитесь к администратору по кнопке ниже\.",
parse_mode="MarkdownV2", reply_markup=admin_button)
raise CancelHandler()
# Регистрируйте middleware
dp.middleware.setup(CheckBanMiddleware())
@dp.message_handler(commands=['unban'], user_id=ADMINS) # Замените ADMINS на список ID администраторов
async def unban_user_command(message: types.Message):
args = message.get_args().split()
if not args or not args[0].isdigit():
await message.reply("Необходимо указать ID пользователя для разблокировки: /unban 123456789")
return
user_id_to_unban = int(args[0])
async with connect('bot.db') as db:
await db.execute("DELETE FROM banned_users WHERE user_id = ?", (user_id_to_unban,))
await db.commit()
await message.reply(f"Пользователь {user_id_to_unban} разблокирован.")
# Use this handler to get photos from the database, apply changes, and send to the user
@dp.message_handler(commands=['photos'])
async def send_processed_photos(message: types.Message):
user_id = message.from_user.id
async with connect('bot.db') as db:
cursor = await db.execute("SELECT COUNT(*) FROM userphotos WHERE user_id = ?", (user_id,))
user_photo_count = (await cursor.fetchone())[0]
cursor = await db.execute("SELECT id, photo_id FROM backgrounds WHERE user_id = ?", (user_id,))
backgrounds = await cursor.fetchall()
cursor = await db.execute("SELECT id, photo_id FROM userphotos WHERE user_id = ?", (user_id,))
user_photos = await cursor.fetchall()
if not backgrounds or not user_photos:
await message.reply("Необходимо загрузить фоновые изображения и/или креатив.")
return
used_background_ids = [] # Сюда будут собираться ID использованных фонов для последующего удаления
media_groups = [] # Здесь будут храниться пачки изображений для отправки
for user_photo in user_photos:
if not backgrounds:
await message.reply("Количество фонов меньше количества фотографий в креативе.")
break # Если фоновых изображений недостаточно, прекращаем обработку
background = backgrounds.pop(0) # Получаем первый фон из списка
used_background_ids.append(background[0]) # Добавляем ID фона в список использованных
processed_image_io = await apply_background(user_photo[1], background[1], padding_horizontal=100, padding_vertical=70)
media_groups.append(types.InputMediaPhoto(processed_image_io))
# Если в текущей пачке 4 изображения или это последняя итерация, отправляем пачку
if len(media_groups) == user_photo_count or not backgrounds:
await bot.send_media_group(message.chat.id, media=media_groups)
media_groups = [] # Очищаем текущую пачку для следующей
# Удаляем использованные фоны из базы данных
if used_background_ids:
await db.executemany("DELETE FROM backgrounds WHERE id = ?", [(id,) for id in used_background_ids])
await db.commit()
# Function to apply background to user photo
async def apply_background(user_photo_id, background_photo_id, padding_horizontal=100, padding_vertical=70, blur_radius=5):
logging.info("обработка фото")
user_photo_file = await bot.get_file(user_photo_id)
background_photo_file = await bot.get_file(background_photo_id)
user_photo_url = bot.get_file_url(user_photo_file.file_path)
background_photo_url = bot.get_file_url(background_photo_file.file_path)
user_photo_data = await fetch_photo(user_photo_url)
background_photo_data = await fetch_photo(background_photo_url)
with Image.open(BytesIO(user_photo_data)) as user_image, Image.open(BytesIO(background_photo_data)) as background_image:
user_image = user_image.convert('RGBA')
background_image = background_image.convert('RGBA')
background_image = background_image.filter(ImageFilter.GaussianBlur(blur_radius))
# Задаем размер фона, увеличенный на указанные отступы
new_background_width = user_image.width + padding_horizontal * 2 # Слева и справа
new_background_height = user_image.height + padding_vertical * 2 # Сверху и снизу
background_image = background_image.resize((new_background_width, new_background_height), Image.Resampling.LANCZOS)
# Готовим позицию для наложения фото пользователя на фон
user_image_position = (padding_horizontal, padding_vertical) # Отступы слева и сверху
# Накладываем пользовательское изображение на фон
background_image.paste(user_image, user_image_position, user_image.split()[3]) # Используем альфа-канал для маски
# Сохраняем во временный файл
result_image_io = BytesIO()
background_image.save(result_image_io, format='PNG')
result_image_io.seek(0)
return result_image_io
@dp.message_handler(lambda message: message.text == "🖼 Замена фона")
async def on_change_background_button(message: types.Message):
process_message = await message.answer("*Фото обрабатываются, подождите\.\.\.*",parse_mode="MarkdownV2")
user_id = message.from_user.id
async with connect('bot.db') as db: # Убедитесь, что используете контекстный менеджер
# Определяем, должны ли использоваться общие фоны
cursor = await db.execute("SELECT use_common_backgrounds FROM users WHERE user_id = ?", (user_id,))
use_common_backgrounds = (await cursor.fetchone())[0]
# В зависимости от настроек выбираем фоны
if use_common_backgrounds:
cursor = await db.execute("SELECT photo_id FROM common_backgrounds ORDER BY RANDOM()")
else:
cursor = await db.execute("SELECT photo_id FROM backgrounds WHERE user_id = ?", (user_id,))
backgrounds = await cursor.fetchall()
# Получаем фотографии пользователя
cursor = await db.execute("SELECT photo_id FROM userphotos WHERE user_id = ?", (user_id,))
user_photos = await cursor.fetchall()
if not backgrounds or not user_photos:
await message.answer("Необходимо загрузить фоновые изображения и/или креатив.")
return
used_background_ids = [] # Список использованных личных фонов для удаления
media_groups = []
background_index = 0
for user_photo in user_photos:
# Начинаем по новой сначала списка, если фонов меньше чем фото
if background_index >= len(backgrounds):
background_index = 0
background = backgrounds[background_index]
background_index += 1
if not use_common_backgrounds:
used_background_ids.append(background[0]) # Добавляем ID фона в список использованных личных фонов
# Применяем фон к фотографии пользователя
processed_image_io = await apply_background(user_photo[0], background[0])
media_groups.append(types.InputMediaPhoto(processed_image_io))
# Отправляем обработанные фото пользователю
await bot.delete_message(chat_id=process_message.chat.id, message_id=process_message.message_id)
if media_groups:
await bot.send_media_group(message.chat.id, media=media_groups)
async with connect('bot.db') as db:
# Обновление счетчика замен фона
if use_common_backgrounds:
await db.execute(
"UPDATE users SET common_backgrounds_count = common_backgrounds_count + 1 WHERE user_id = ?",
(user_id,))
else:
await db.execute(
"UPDATE users SET personal_backgrounds_count = personal_backgrounds_count + 1 WHERE user_id = ?",
(user_id,))
# Удаление использованных фонов
if used_background_ids and not use_common_backgrounds:
await db.executemany("DELETE FROM backgrounds WHERE photo_id = ?", [(id,) for id in used_background_ids])
# Commit транзакции только один раз, после всех изменений
await db.commit()
# Init DB on startup
async def on_startup(_):
print("Starting bot…")
await init_db()
await create_banned_users_table()
# Starting the bot
if __name__ == '__main__':
executor.start_polling(dp, skip_updates=True, on_startup=on_startup)
|
8fb579b9e6fb1f03f3d9b92f9558bdb8
|
{
"intermediate": 0.3829321563243866,
"beginner": 0.41256043314933777,
"expert": 0.20450744032859802
}
|
40,141
|
`
my problem is, whenever there is detections on our comvis its not showing on our web app reactively in this part
<span class="mr-2 font-bold">Current people:</span>
<span class="font-medium">{$people}</span>
|
6b115c97c9232125d726ab3c5c12a1e0
|
{
"intermediate": 0.3731521964073181,
"beginner": 0.34038689732551575,
"expert": 0.28646090626716614
}
|
40,142
|
`
my problem is, whenever there is detections on our comvis its not showing on our web app reactively in this part
<span class="mr-2 font-bold">Current people:</span>
<span class="font-medium">{$people}</span>
|
b45313400bd247a71dd62d90245d63b0
|
{
"intermediate": 0.3731521964073181,
"beginner": 0.34038689732551575,
"expert": 0.28646090626716614
}
|
40,143
|
For a given tuple of data (r,g,b, h, s, l) Is there an approach that can be used to normalise 'out of range' values ?
|
9c866d33c848c227343d6030b648594b
|
{
"intermediate": 0.3826751410961151,
"beginner": 0.10786799341440201,
"expert": 0.5094568729400635
}
|
40,144
|
DQL in open search
|
b67bbef5c4526929ff04db8af61fc2bf
|
{
"intermediate": 0.16660743951797485,
"beginner": 0.1569186896085739,
"expert": 0.6764739155769348
}
|
40,145
|
Analyze the below WCAG success criteria with their suggestions:
WCAG 1.4.11 - The visual presentation of the following have a contrast ratio of at least 3:1 against adjacent color
Suggestions:
1. Suggested to provide 2px for the focus indicator that passes 3:1 ratio.
2. Suggested to provide 2 colour (eg. black & weight) focus indicator
WCAG 2.4.2 - Web pages have titles that describe topic or purpose.
Suggestions:
1. Ensure the symbol used between the page name and the organization name should be “:” or “-“. Pipeline (|) symbol is not allowed.
WCAG 2.4.7 - Any keyboard operable user interface has a mode of operation where the keyboard focus indicator is visible.
Suggestions:
1. Suggested to provide 2 colour (eg. black & weight) focus indicator
2. While browsers handle the default visible focus for active elements it is always a best practice to provide visible focus to the elements using the CSS techniques.
Your task is to analyze the WCAG with the provided suggestions and let me know whether they are correct or not.
|
00f6d81b67834fe728da9fee5343abfa
|
{
"intermediate": 0.36725977063179016,
"beginner": 0.3825278878211975,
"expert": 0.25021228194236755
}
|
40,146
|
My Objective:
We aim to optimize the '7' objective performance metric values of 'area', 'power dissipation', 'DC gain', 'Slew rate', '3db frequency', 'Unity gain bandwidth', and 'Phase margin' (multi-objectives) of a pre-determined two stage operational amplifier circuit topology. We need to optimally configure/tune the design device parameters (device dimensions and values, as variables) such as transistor dimensions ['L1', 'L3', 'L5', 'L6', 'L7', 'W1', 'W3', 'W5', 'W6', 'W7'], Bias currents ['Ib'], Bias voltages ['Vb'], and values of the passive devices ['Cc', 'Cl', 'Rp'] associated in the circuit design, in a such a way that the resulting design satisfies the predetermined performance measures (design specifications). In this overall construction of optimization process, the pre-determined performance measures are considered as constraints as well as target optimization metrics to configure the optimized design device parameter values.
For my objectives, I need to implement the reinforcement learning (RL) code with multiple output heads Graph neural networks on multigraphs, GNN is embedded by the technique of hybrid MPNN-RGAT architecture that contains the message passing attention mechanism. Here GNN is with in the agent the action and rewards are performed from the following requirement, for this requirement suggest me the best optimization techniques that take actions and generate rewards and to update the parameters.
Environment: My environment is the Cadence virtuoso simulator, where I am simulating the pre-designed fixed circuit topology. I am accessing the simulator available in the local server through the OCEAN skill command controlled by python programming. The environment gets the input variables for the design device parameters ['L1', 'L3', 'L5', 'L6', 'L7', 'W1', 'W3', 'W5', 'W6', 'W7', 'Ib', 'Cc'] from the agent and gives the output performance metrics ['area', 'power dissipation', 'DC gain', 'Slew rate', '3db frequency', 'Unity gain bandwidth', 'Phase margin'] corresponding to the given input variables. Circuit topology is fixed, only the design device parameters present in the schematic are variables to be optimally configure to met the desired output performance metrics.
State: The RL agent processes the circuit graph component by component. For a circuit with n components in topology graph G, the state sk for the kth component is defined as sk = (k; t; h),
where k is the one-hot representation of the transistor index, t is the one-hot representation of component type and h is the selected model feature vector for the component which further distinguishes different component types. For the NMOS and PMOS, the model parameters. For the Bias current, capacitor and resistor, we set the model parameters to zeros. For instance, for a circuit with ten components of five different kinds (NMOS, PMOS, R, C, Ib) and a five-dimensional model feature vector.
Action Space. The action vector varies for different types of components because the parameters needed to search are not the same. We use a continuous action space to determine the transistor sizes even though we will round them to discrete values. The reason why we do not use a discrete action space is because that will lose the relative order information, also because the discrete action space is too large.
Action Representation: Inspired by human designers who iterate with fine-grained tuning steps to find optimal device parameters, we use discrete action space to tune device parameters. For each tunable parameter 𝑥 of a device (e.g., width and finger number of transistors), there are three possible actions at each step: increasing (𝑥+del 𝑥), keeping (𝑥 +0), or decreasing (𝑥−del 𝑥) the parameter, where “del 𝑥" is the smallest unit to update the parameter within its bound [𝑥min, 𝑥max]. Assuming total 𝑀 device parameters, the output of the policy network is an 𝑀 × 3 probability distribution matrix with each row corresponding to a parameter. The action is taken based on the probability distribution.
Reward Function:The reward is directly related to the design goal. We define the reward 𝑟𝑖 at each time step 𝑖 as 𝑟𝑖 = 𝑟, if 𝑟 < 0 or 𝑟𝑖 = 𝑅, if 𝑟 = 0, where 𝑟 = summation of min{(𝑔𝑗𝑖 − 𝑔𝑗∗ )/(𝑔𝑗𝑖 + 𝑔𝑗∗), 0}. where, it is a normalized difference between the obtained specifications 𝑔𝑖 and the given specifications 𝑔∗. The upper bound of 𝑟 is set to be 0 to avoid overoptimizing the parameters once the given specifications are reached. All 𝑁 specifications are equally important. We also give a large reward (i.e., 𝑅 = 10) to encourage the agent if the design goals are reached at some step. The episode return 𝑅𝑠0,𝑔∗ of searching optimal device parameters for the given goals 𝑔∗ starting from an initial state 𝑠0, is the accumulated reward of all steps: 𝑅𝑠0,𝑔∗ = summation of 𝑟𝑖 . Our goal is to train a good policy to maximize 𝑅𝑠0,𝑔∗ .
|
ae325e3c206735467f9648f983310cdd
|
{
"intermediate": 0.2724301517009735,
"beginner": 0.4048658609390259,
"expert": 0.3227039575576782
}
|
40,147
|
i want to make an ai image generator app using nextjs13 and huggingface ,i want you to make a simple backend api route for image generating and also make frontend component that has a input and a button on clicking which i get a image from the promt in the input sent to the api
|
966376d42abe808478281b12b9724335
|
{
"intermediate": 0.8247554302215576,
"beginner": 0.08452177792787552,
"expert": 0.09072281420230865
}
|
40,148
|
use huggingface/inference package to make an ai image generator app using nextjs and huggingface
|
4971446e22072005ae4d42cf3388584f
|
{
"intermediate": 0.48620370030403137,
"beginner": 0.10263560712337494,
"expert": 0.4111607074737549
}
|
40,149
|
memcpy() in c
|
d5289148c8559a364083d0d4bff6ed3a
|
{
"intermediate": 0.3029458224773407,
"beginner": 0.3489978313446045,
"expert": 0.3480563461780548
}
|
40,150
|
import pandas as pd
import numpy as np
from itertools import combinations
from backtesting import Backtest, Strategy
class MyStrategy(Strategy):
def init(self):
pass
def next(self):
pass
def run_cpcv_with_purging_and_embargoing(data, strategy_class, n_splits, embargo_pct):
results = []
all_indices = range(len(data))
n_test_samples = int(len(data) * embargo_pct)
for split in combinations(all_indices, n_splits):
for start in split:
end = start + n_test_samples
bt = Backtest(data, strategy_class, cash=10_000, commission=.002)
stats = bt.run()
results.append(stats)
return results
reduce time complexity of this python code
|
5e4ecad376bde8956927e87c3b083598
|
{
"intermediate": 0.5511607527732849,
"beginner": 0.2226278930902481,
"expert": 0.22621141374111176
}
|
40,151
|
I have two groups of numbers, group1 and group2.
How can I distribute all the numbers from two groups into four result groups?
The difference in the sum of any two groups should be as small as possible (less than 0.5).
Each result group can't be empty and should consist of some numbers from group1.
group1 = [9.54, 0.29, 9.54, 0.29, 9.54, 0.29, 9.54, 0.29, 15.90, 0.29, 21.20, 0.29, 22.26, 0.29, 8.48, 0.29, 9.01, 0.29, 8.48, 0.29, 16.96, 21.20, 8.48, 7.42]
group2 = [9.23, 0.29, 9.23, 0.29, 9.23, 0.29, 9.23, 0.29, 15.38, 0.29, 20.50, 0.29, 21.53, 0.29, 8.20, 0.29, 8.71, 0.29, 8.20, 0.29, 16.40, 20.50, 8.20, 7.18]
Provide the 4 result groups by specifying all numbers, the sum, and the difference of the sum.
|
1e434bed5f7985e685a60e591f18382e
|
{
"intermediate": 0.34135204553604126,
"beginner": 0.1748485118150711,
"expert": 0.48379945755004883
}
|
40,152
|
neovim
|
8b9f2e1c0efb5490f4f0f413121108f1
|
{
"intermediate": 0.24356709420681,
"beginner": 0.17810678482055664,
"expert": 0.5783261656761169
}
|
40,153
|
check error in the given program
import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
class PPO:
def __init__(self, env, actor_lr=1e-4, critic_lr=1e-3, gamma=0.99, lam=0.95, clip_range=0.2):
self.env = env
self.actor_lr = actor_lr
self.critic_lr = critic_lr
self.gamma = gamma
self.lam = lam
self.clip_range = clip_range
self.actor = Actor(env.observation_space, env.action_space)
self.critic = Critic(env.observation_space)
self.actor_optimizer = tf.keras.optimizers.Adam(learning_rate=actor_lr)
self.critic_optimizer = tf.keras.optimizers.Adam(learning_rate=critic_lr)
def collect_trajectories(self, episodes=10):
trajectories = []
for _ in range(episodes):
trajectory = []
state = self.env.reset()
done = False
while not done:
action, _ = self.actor(np.expand_dims(state, axis=0))
action = action.numpy()[0]
next_state, reward, done, _ = self.env.step(action)
trajectory.append((state, action, reward, next_state, done))
state = next_state
trajectories.append(trajectory)
return trajectories
def compute_rewards(self, trajectories):
rewards = []
for trajectory in trajectories:
G = 0
for t in range(len(trajectory) - 1, -1, -1):
_, _, reward, _, _ = trajectory[t]
G = reward + self.gamma * G
trajectory[t] = (*trajectory[t], G)
rewards.append(trajectory)
return rewards
def compute_advantages(self, trajectories):
advantages = []
for trajectory in trajectories:
V = self.critic(np.expand_dims(np.array([state for state, _, _, _, _ in trajectory]), axis=0))
V = V.numpy()[0]
A = []
for t in range(len(trajectory)):
_, _, _, _, done = trajectory[t]
delta = trajectory[t][2] + self.gamma * (1 - done) * V[t + 1] - V[t]
A.append(delta)
advantages.append(A)
return advantages
def update_actor(self, trajectories, advantages):
for trajectory, advantage in zip(trajectories, advantages):
states, actions, _, _, _ = zip(*trajectory)
with tf.GradientTape() as tape:
log_probs = self.actor(np.expand_dims(np.array(states), axis=0))[1]
log_probs = log_probs.numpy()[0]
ratios = tf.exp(log_probs - trajectory[0][1])
loss = -tf.reduce_mean(tf.minimum(ratios * advantage, tf.clip_by_value(ratios, 1 - self.clip_range, 1 + self.clip_range) * advantage))
grads = tape.gradient(loss, self.actor.trainable_variables)
self.actor_optimizer.apply_gradients(zip(grads, self.actor.trainable_variables))
def update_critic(self, trajectories):
for trajectory in trajectories:
states, _, rewards, _, _ = zip(*trajectory)
with tf.GradientTape() as tape:
V = self.critic(np.expand_dims(np.array(states), axis=0))
loss = tf.reduce_mean((V - np.array(rewards)) ** 2)
grads = tape.gradient(loss, self.critic.trainable_variables)
self.critic_optimizer.apply_gradients(zip(grads, self.critic.trainable_variables))
def train(self, iterations=100):
for _ in range(iterations):
trajectories = self.collect_trajectories()
rewards = self.compute_rewards(trajectories)
advantages = self.compute_advantages(rewards)
self.update_actor(trajectories, advantages)
self.update_critic(trajectories)
class Actor(tf.keras.Model):
def __init__(self, observation_space, action_space):
super().__init__()
self.observation_space = observation_space
self.action_space = action_space
self.dense1 = tf.keras.layers.Dense(128, activation='relu')
self.dense2 = tf.keras.layers.Dense(64, activation='relu')
self.actor = tf.keras.layers.Dense(self.action_space.n)
def call(self, inputs):
x = self.dense1(inputs)
x = self.dense2(x)
logits = self.actor(x)
probs = tf.nn.softmax(logits)
return probs, logits
class Critic(tf.keras.Model):
def __init__(self, observation_space):
super().__init__()
self.observation_space = observation_space
self.dense1 = tf.keras.layers.Dense(128, activation='relu')
self.dense2 = tf.keras.layers.Dense(64, activation='relu')
self.critic = tf.keras.layers.Dense(1)
def call(self, inputs):
x = self.dense1(inputs)
x = self.dense2(x)
value = self.critic(x)
return value
|
a897320631825e60864c6770fc1e1487
|
{
"intermediate": 0.31667476892471313,
"beginner": 0.4941691756248474,
"expert": 0.18915610015392303
}
|
40,154
|
im running plasma x11 on arch and installed cairo dock to integrate it what should i do
|
31ffb502776ebb7f35805657ea2282bd
|
{
"intermediate": 0.6567169427871704,
"beginner": 0.16019800305366516,
"expert": 0.18308505415916443
}
|
40,155
|
my scratch code is not working this is the code:
when green flag clicked
set score to 0
repeat until <(score) = [5]>
ask "What is the capital of France?"
if <(answer) = [Paris]> then
change score by 1
end
ask "What color do you get when you mix blue and yellow?"
if <(answer) = [Green]> then
change score by 1
end
ask "Who is the president of the USA?"
if <(answer) = [Joe Biden]> then
change score by 1
end
ask "What is the name of the fairy in Peter Pan?"
if <(answer) = [Tinkerbell]> then
change score by 1
end
ask "What do bees produce?"
if <(answer) = [Honey]> then
change score by 1
end
end
say (score)
stop all
the score does not change
|
f2d4b015d90c071256dad0b9c569597d
|
{
"intermediate": 0.37901243567466736,
"beginner": 0.40463951230049133,
"expert": 0.21634803712368011
}
|
40,156
|
how do i delete unsigned int
|
c58f49ec4248fee120517e28cf1fa04f
|
{
"intermediate": 0.3543110191822052,
"beginner": 0.29820582270622253,
"expert": 0.34748318791389465
}
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.