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# Introduction to zfit
In this notebook, we will have a walk through the main components of zfit and their features. Especially the extensive model building part will be discussed separately.
zfit consists of 5 mostly independent parts. Other libraries can rely on this parts to do plotting or statistical inference, su... | b00b392978a7224fab32ff55c40d9292dc6918f0 | 170,262 | ipynb | Jupyter Notebook | tutorial2_zfit/Introduction.ipynb | zfit/python_hpc_TensorFlow_MSU | a866b63ddf59c773d89b7e499625bd1eb3d70cb0 | [
"BSD-3-Clause"
] | 1 | 2020-10-10T13:34:04.000Z | 2020-10-10T13:34:04.000Z | tutorial2_zfit/Introduction.ipynb | zfit/python_hpc_TensorFlow_MSU | a866b63ddf59c773d89b7e499625bd1eb3d70cb0 | [
"BSD-3-Clause"
] | null | null | null | tutorial2_zfit/Introduction.ipynb | zfit/python_hpc_TensorFlow_MSU | a866b63ddf59c773d89b7e499625bd1eb3d70cb0 | [
"BSD-3-Clause"
] | null | null | null | 89.049163 | 26,560 | 0.823449 | true | 9,792 | Qwen/Qwen-72B | 1. YES
2. YES | 0.72487 | 0.699254 | 0.506869 | __label__eng_Latn | 0.972054 | 0.015955 |
# Cálculo e clasificación de puntos críticos
Con todas as ferramentas que xa levamos revisado nas anteriores prácticas, o cálculo de puntos críticos e a súa clasificación mediante o criterio que involucra á matriz Hessiana de funcións de dúas variables diferenciables é moi sinxelo usando o módulo **Sympy**. No caso de... | 5ff0a30107d820b79eda1a3b90654559cfe0816f | 112,842 | ipynb | Jupyter Notebook | practicas/extremos-relativos.ipynb | maprieto/CalculoMultivariable | 6bd7839803d696c6cd0e3536c0631453eacded70 | [
"MIT"
] | 1 | 2021-01-09T18:30:54.000Z | 2021-01-09T18:30:54.000Z | practicas/extremos-relativos.ipynb | maprieto/CalculoMultivariable | 6bd7839803d696c6cd0e3536c0631453eacded70 | [
"MIT"
] | null | null | null | practicas/extremos-relativos.ipynb | maprieto/CalculoMultivariable | 6bd7839803d696c6cd0e3536c0631453eacded70 | [
"MIT"
] | null | null | null | 307.47139 | 82,555 | 0.905718 | true | 2,880 | Qwen/Qwen-72B | 1. YES
2. YES | 0.833325 | 0.737158 | 0.614292 | __label__glg_Latn | 0.970904 | 0.265537 |
# Constrained optimization
Now we will move to studying constrained optimizaton problems i.e., the full problem
$$
\begin{align} \
\min \quad &f(x)\\
\text{s.t.} \quad & g_j(x) \geq 0\text{ for all }j=1,\ldots,J\\
& h_k(x) = 0\text{ for all }k=1,\ldots,K\\
&a_i\leq x_i\leq b_i\text{ for all } i=1,\ldots,n\\
&x\in \mat... | 45256d4d304a6853e389d2698bef91a04485aac0 | 14,539 | ipynb | Jupyter Notebook | Lecture 6, Indirect methods for constrained optimization.ipynb | maeehart/TIES483 | cce5c779aeb0ade5f959a2ed5cca982be5cf2316 | [
"CC-BY-3.0"
] | 4 | 2019-04-26T12:46:14.000Z | 2021-11-23T03:38:59.000Z | Lecture 6, Indirect methods for constrained optimization.ipynb | maeehart/TIES483 | cce5c779aeb0ade5f959a2ed5cca982be5cf2316 | [
"CC-BY-3.0"
] | null | null | null | Lecture 6, Indirect methods for constrained optimization.ipynb | maeehart/TIES483 | cce5c779aeb0ade5f959a2ed5cca982be5cf2316 | [
"CC-BY-3.0"
] | 6 | 2016-01-08T16:28:11.000Z | 2021-04-10T05:18:10.000Z | 25.285217 | 321 | 0.528578 | true | 2,227 | Qwen/Qwen-72B | 1. YES
2. YES | 0.94079 | 0.897695 | 0.844543 | __label__eng_Latn | 0.981543 | 0.800488 |
# Laboratorio de física con Python
## Temario
* Simulación de ODE (de primer orden) [Proximamente, de orden superior!)
* Análisis de datos
- Transformación de datos, filtrado
- Ajuste de modelos
- Integración
- Derivación
* Adquisición de datos
* Gráficos
Importamos librerías: _numpy_ para análisis numérico, _... | 28dcb52ac12618a2eec3535582e5e3b44dd9023c | 203,947 | ipynb | Jupyter Notebook | python/Extras/Arduino/laboratorio.ipynb | LTGiardino/talleresfifabsas | a711b4425b0811478f21e6c405eeb4a52e889844 | [
"MIT"
] | 17 | 2015-10-23T17:14:34.000Z | 2021-12-31T02:18:29.000Z | python/Extras/Arduino/laboratorio.ipynb | LTGiardino/talleresfifabsas | a711b4425b0811478f21e6c405eeb4a52e889844 | [
"MIT"
] | 5 | 2016-04-03T23:39:11.000Z | 2020-04-03T02:09:02.000Z | python/Extras/Arduino/laboratorio.ipynb | LTGiardino/talleresfifabsas | a711b4425b0811478f21e6c405eeb4a52e889844 | [
"MIT"
] | 29 | 2015-10-16T04:16:01.000Z | 2021-09-18T16:55:48.000Z | 225.355801 | 26,954 | 0.890388 | true | 6,268 | Qwen/Qwen-72B | 1. YES
2. YES | 0.894789 | 0.774583 | 0.693089 | __label__spa_Latn | 0.761206 | 0.448609 |
# Binet's Formula
## Formula
Explicit formula to find the nth term of the Fibonacci sequence.
$\displaystyle F_n = \frac{1}{\sqrt{5}} \Bigg(\Bigg( \frac{1 + \sqrt{5}}{2} \Bigg)^n - \Bigg( \frac{1 - \sqrt{5}}{2} \Bigg)^n \Bigg)$
*Derived by Jacques Philippe Marie Binet, alreday known by Abraham de Moivre*
----
## ... | 6e6e90986c00390ebd9217509a085ab7b81c477e | 21,750 | ipynb | Jupyter Notebook | notebooks/math/number_theory/binets_formula.ipynb | sparkboom/my_jupyter_notes | 9255e4236b27f0419cdd2c8a2159738d8fc383be | [
"MIT"
] | null | null | null | notebooks/math/number_theory/binets_formula.ipynb | sparkboom/my_jupyter_notes | 9255e4236b27f0419cdd2c8a2159738d8fc383be | [
"MIT"
] | null | null | null | notebooks/math/number_theory/binets_formula.ipynb | sparkboom/my_jupyter_notes | 9255e4236b27f0419cdd2c8a2159738d8fc383be | [
"MIT"
] | null | null | null | 106.097561 | 14,436 | 0.849011 | true | 996 | Qwen/Qwen-72B | 1. YES
2. YES | 0.913677 | 0.855851 | 0.781971 | __label__eng_Latn | 0.594059 | 0.655113 |
# Exercise 1
## JIT the pressure poisson equation
The equation we need to unroll is given by
\begin{equation}
p_{i,j}^{n} = \frac{1}{4}\left(p_{i+1,j}^{n}+p_{i-1,j}^{n}+p_{i,j+1}^{n}+p_{i,j-1}^{n}\right) - b
\end{equation}
and recall that `b` is already computed, so no need to worry about unrolling that. We've also... | 0e5936f7cf5cec621e0e31c2a188ada3e097a3e4 | 4,223 | ipynb | Jupyter Notebook | notebooks/exercises/05.Cavity.Flow.Exercises.ipynb | gforsyth/numba_tutorial_scipy2017 | 01befd25218783f6d3fb803f55dd9e52f6072ff7 | [
"CC-BY-4.0"
] | 131 | 2017-06-23T10:18:26.000Z | 2022-03-27T21:16:56.000Z | notebooks/exercises/05.Cavity.Flow.Exercises.ipynb | gforsyth/numba_tutorial_scipy2017 | 01befd25218783f6d3fb803f55dd9e52f6072ff7 | [
"CC-BY-4.0"
] | 9 | 2017-06-11T21:20:59.000Z | 2018-10-18T13:57:30.000Z | notebooks/exercises/05.Cavity.Flow.Exercises.ipynb | gforsyth/numba_tutorial_scipy2017 | 01befd25218783f6d3fb803f55dd9e52f6072ff7 | [
"CC-BY-4.0"
] | 64 | 2017-06-26T13:04:48.000Z | 2022-01-11T20:36:31.000Z | 23.461111 | 206 | 0.460336 | true | 653 | Qwen/Qwen-72B | 1. YES
2. YES | 0.880797 | 0.888759 | 0.782816 | __label__eng_Latn | 0.89803 | 0.657077 |
```python
from sympy import *
from IPython.display import display, Latex, HTML, Markdown
init_printing()
from eqn_manip import *
from codegen_extras import *
import codegen_extras
from importlib import reload
from sympy.codegen.ast import Assignment, For, CodeBlock, real, Variable, Pointer, Declaration
from sympy.codeg... | 7b01ff500c6cfa45f4fff37c44f8da2857c39ab1 | 58,317 | ipynb | Jupyter Notebook | Wavefunctions/CubicSplineSolver.ipynb | QMCPACK/qmc_algorithms | 015fd1973e94f98662149418adc6b06dcd78946d | [
"MIT"
] | 3 | 2018-02-06T06:15:19.000Z | 2019-11-26T23:54:53.000Z | Wavefunctions/CubicSplineSolver.ipynb | chrinide/qmc_algorithms | 015fd1973e94f98662149418adc6b06dcd78946d | [
"MIT"
] | null | null | null | Wavefunctions/CubicSplineSolver.ipynb | chrinide/qmc_algorithms | 015fd1973e94f98662149418adc6b06dcd78946d | [
"MIT"
] | 4 | 2017-11-14T20:25:00.000Z | 2022-02-28T06:02:01.000Z | 31.403877 | 1,028 | 0.365434 | true | 9,653 | Qwen/Qwen-72B | 1. YES
2. YES | 0.859664 | 0.817574 | 0.702839 | __label__eng_Latn | 0.199713 | 0.471262 |
```python
from decodes.core import *
from decodes.io.jupyter_out import JupyterOut
import math
out = JupyterOut.unit_square( )
```
# Transformation Mathematics
We are familiar with a set of operations in CAD designated by verbs, such as "Move”, “Mirror”, “Rotate”, and “Scale”, and that ***act upon a geometric object... | 3c9cc74527c223690a3d4d7509cc2912e12c259c | 35,016 | ipynb | Jupyter Notebook | 107 - Transformations and Intersections/242 - Transformation Mathematics.ipynb | ksteinfe/decodes_ipynb | 2e4bb6b398472fc61ef8b88dad7babbdeb2a5754 | [
"MIT"
] | 1 | 2018-05-15T14:31:23.000Z | 2018-05-15T14:31:23.000Z | 107 - Transformations and Intersections/242 - Transformation Mathematics.ipynb | ksteinfe/decodes_ipynb | 2e4bb6b398472fc61ef8b88dad7babbdeb2a5754 | [
"MIT"
] | null | null | null | 107 - Transformations and Intersections/242 - Transformation Mathematics.ipynb | ksteinfe/decodes_ipynb | 2e4bb6b398472fc61ef8b88dad7babbdeb2a5754 | [
"MIT"
] | 2 | 2020-05-19T05:40:18.000Z | 2020-06-28T02:18:08.000Z | 41.439053 | 467 | 0.617061 | true | 5,839 | Qwen/Qwen-72B | 1. YES
2. YES | 0.695958 | 0.847968 | 0.59015 | __label__eng_Latn | 0.998084 | 0.209447 |
# Announcements
- No Problem Set this week, Problem Set 4 will be posted on 9/28.
- Stay on at the end of lecture if you want to ask questions about Problem Set 3.
<style>
@import url(https://www.numfys.net/static/css/nbstyle.css);
</style>
<a href="https://www.numfys.net"></a>
# Ordinary Differential Equations - hig... | 30c00abbaaa3111abafe96512375232710a15b33 | 28,444 | ipynb | Jupyter Notebook | Lectures/Lecture 12/Lecture12_ODE_part3.ipynb | astroarshn2000/PHYS305S20 | 18f4ebf0a51ba62fba34672cf76bd119d1db6f1e | [
"MIT"
] | 3 | 2020-09-10T06:45:46.000Z | 2020-10-20T13:50:11.000Z | Lectures/Lecture 12/Lecture12_ODE_part3.ipynb | astroarshn2000/PHYS305S20 | 18f4ebf0a51ba62fba34672cf76bd119d1db6f1e | [
"MIT"
] | null | null | null | Lectures/Lecture 12/Lecture12_ODE_part3.ipynb | astroarshn2000/PHYS305S20 | 18f4ebf0a51ba62fba34672cf76bd119d1db6f1e | [
"MIT"
] | null | null | null | 36.84456 | 598 | 0.544825 | true | 6,292 | Qwen/Qwen-72B | 1. YES
2. YES | 0.880797 | 0.91848 | 0.808995 | __label__eng_Latn | 0.987972 | 0.717899 |
# definition
数值定义. 对于 N-bit two's complement number system, 最高位 N-th bit 为符号位, 0 为正,
1 为负. 对于任意一个非负整数, 它的相反数为 its complement with respect to $2^N$.
# properties
- 一个数字的 two's complement 可以通过:
1. take its ones' complement and add one.
因为: the sum of a number and its ones' complement is -0, i.e. ‘1’ bits... | 57e58ee67b325cd5a78841b53ba007ba4ce08912 | 2,461 | ipynb | Jupyter Notebook | math/arithmetic/binary-arithmetic/two-s-complement.ipynb | Naitreey/notes-and-knowledge | 48603b2ad11c16d9430eb0293d845364ed40321c | [
"BSD-3-Clause"
] | 5 | 2018-05-16T06:06:45.000Z | 2021-05-12T08:46:18.000Z | math/arithmetic/binary-arithmetic/two-s-complement.ipynb | Naitreey/notes-and-knowledge | 48603b2ad11c16d9430eb0293d845364ed40321c | [
"BSD-3-Clause"
] | 2 | 2018-04-06T01:46:22.000Z | 2019-02-13T03:11:33.000Z | math/arithmetic/binary-arithmetic/two-s-complement.ipynb | Naitreey/notes-and-knowledge | 48603b2ad11c16d9430eb0293d845364ed40321c | [
"BSD-3-Clause"
] | 2 | 2019-04-11T11:02:32.000Z | 2020-06-27T11:59:09.000Z | 30.7625 | 102 | 0.502641 | true | 675 | Qwen/Qwen-72B | 1. YES
2. YES | 0.872347 | 0.875787 | 0.76399 | __label__eng_Latn | 0.872233 | 0.613338 |
```python
from sympy import *
from sympy.abc import m,M,l,b,c,g,t
from sympy.physics.mechanics import dynamicsymbols, init_vprinting
th = dynamicsymbols('theta')
x = dynamicsymbols('x')
dth = diff(th)
dx = diff(x)
ddth = diff(dth)
ddx = diff(dx)
init_vprinting()
```
```python
```
```python
ddth = (-(1/2)*m*l cos(t... | de761e7fe343e53c15b1cbb441c4f622da1a09df | 1,294 | ipynb | Jupyter Notebook | notebook.ipynb | dnlrbns/pendcart | 696c5d2c5fc7b787f3ab074e3ec3949a94dfc5ed | [
"MIT"
] | null | null | null | notebook.ipynb | dnlrbns/pendcart | 696c5d2c5fc7b787f3ab074e3ec3949a94dfc5ed | [
"MIT"
] | null | null | null | notebook.ipynb | dnlrbns/pendcart | 696c5d2c5fc7b787f3ab074e3ec3949a94dfc5ed | [
"MIT"
] | null | null | null | 21.213115 | 90 | 0.51391 | true | 174 | Qwen/Qwen-72B | 1. YES
2. YES | 0.90599 | 0.61878 | 0.560609 | __label__yue_Hant | 0.234876 | 0.140812 |
# The Harmonic Oscillator Strikes Back
*Note:* Much of this is adapted/copied from https://flothesof.github.io/harmonic-oscillator-three-methods-solution.html
This week we continue our adventures with the harmonic oscillator.
The harmonic oscillator is a system that, when displaced from its equilibrium position, ... | 5da4b5239749aaa9408ca4110a87007295b39726 | 87,460 | ipynb | Jupyter Notebook | harmonic_student.ipynb | sju-chem264-2019/new-10-14-10-m-jacobo | a80b342b8366f5203d08b8d572468b519067752c | [
"MIT"
] | null | null | null | harmonic_student.ipynb | sju-chem264-2019/new-10-14-10-m-jacobo | a80b342b8366f5203d08b8d572468b519067752c | [
"MIT"
] | null | null | null | harmonic_student.ipynb | sju-chem264-2019/new-10-14-10-m-jacobo | a80b342b8366f5203d08b8d572468b519067752c | [
"MIT"
] | null | null | null | 93.540107 | 11,464 | 0.804574 | true | 2,225 | Qwen/Qwen-72B | 1. YES
2. YES | 0.867036 | 0.746139 | 0.646929 | __label__eng_Latn | 0.880557 | 0.341364 |
# Sizing a mosfet using gm/Id method
This is an example you can use to calculate mosfet size in Sky130 for given design parameters. You can change the parameters below and recalculate.
```python
%pylab inline
import numpy as np
from scipy.interpolate import interp1d
import pint
ureg = pint.UnitRegistry() # convenie... | 14f0905464a6d9cee459617aaf0502b60725b1bf | 39,374 | ipynb | Jupyter Notebook | utils/gm_id_example.ipynb | tclarke/sky130radio | 4eca853b7e4fd6bc0d69998f65c04f97e73bee84 | [
"Apache-2.0"
] | 14 | 2020-09-28T19:41:26.000Z | 2021-10-05T01:40:00.000Z | utils/gm_id_example.ipynb | tclarke/sky130radio | 4eca853b7e4fd6bc0d69998f65c04f97e73bee84 | [
"Apache-2.0"
] | null | null | null | utils/gm_id_example.ipynb | tclarke/sky130radio | 4eca853b7e4fd6bc0d69998f65c04f97e73bee84 | [
"Apache-2.0"
] | 6 | 2020-07-30T21:54:19.000Z | 2021-02-07T07:58:12.000Z | 133.471186 | 16,484 | 0.893254 | true | 1,108 | Qwen/Qwen-72B | 1. YES
2. YES | 0.875787 | 0.826712 | 0.724023 | __label__eng_Latn | 0.736974 | 0.520481 |
End of preview. Expand in Data Studio
Math Notebooks
This repository contains mathematically informative ipython notebooks that were collated from OpenWebMath, RedPajama, and the Algebraic Stack in the AutoMathText effort. Zhang et. al. used Qwen 72B to score text with the following prompt:
<system>
You are ChatGPT, equipped with extensive expertise in mathematics and coding, and skilled
in complex reasoning and problem-solving. In the following task, I will present a text excerpt
from a website. Your role is to evaluate whether this text exhibits mathematical intelligence
and if it is suitable for educational purposes in mathematics. Please respond with only YES
or NO
</system>
User: {
“url”: “{url}”,
“text”: “{text}”
}
1. Does the text exhibit elements of mathematical intelligence? Respond with YES or NO
2. Is the text suitable for educational purposes for YOURSELF in the field of mathematics? Respond with YES or NO
The responses to these questions were each scored with the function:
These scores are found in the meta.lm_q1_score and meta.lm_q2_score columns. A total score (meta.lm_q1q2_score) is achieved by taking the product of the two scores.
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