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## The max value entropy search acquisition function
Max-value entropy search (MES) acquisition function quantifies the information gain about the maximum of a black-box function by observing this black-box function $f$ at the candidate set $\{\textbf{x}\}$ (see [1, 2]). BoTorch provides implementations of the MES acq... | github_jupyter |
# Spreadsheet
Make a spreadsheet using pinkfish. This is useful for developing trading strategies.
It can also be used as a tool for buy and sell signals that you then manually execute.
```
import datetime
import matplotlib.pyplot as plt
import pandas as pd
from talib.abstract import *
import pinkfish as ... | github_jupyter |
Analysis of the Coalescent Simulation
=====================================
```
library(ggplot2)
library(plyr)
library(reshape2)
```
Dataset
-------
This is the summary of Spearman's $\rho$ over 10 replicates of the "coalescent" experiment
```
stats = read.csv("overall.csv")
stats$rep = as.factor(sort(rep(1:10, tim... | github_jupyter |
Example of Receiver Operating Characteristic (ROC) metric to evaluate classifier output quality using cross-validation.
ROC curves typically feature true positive rate on the Y axis, and false positive rate on the X axis. This means that the top left corner of the plot is the “ideal” point - a false positive rate of z... | github_jupyter |
# Overview
* Goal
* simulating emperical SIP data from validation experiments
* SIP validations consisted of one or a few genomes
* Existing datasets
* Lueders et al., 2004 (barkeri vs extorquens)
* Lueders T, Manefield M, Friedrich MW. (2004). Enhanced sensitivity of DNA- and rRNA-based stable isotope pr... | github_jupyter |
# Qurro QIIME 2 "Moving Pictures" Tutorial
In this tutorial, we'll demonstrate the process of using [Qurro](https://github.com/biocore/qurro) to investigate a compositional biplot generated by [DEICODE](https://github.com/biocore/DEICODE/).
## 0. Introduction
### 0.1. What is Qurro?
Lots of tools for analyzing " 'o... | github_jupyter |
# Example queries for Case Counts on COVID-19 Knowledge Graph
[Work in progress]
This notebook demonstrates how to run Cypher queries to retrieve and aggregate COVID-19 case counts.
COVID-19 case numbers are provided by:
Country and US County level data: [JHU](https://github.com/covid-19-net/covid-19-community/blob/... | github_jupyter |
```
import sys
import pandas as pd
import numpy as np
from sklearn import preprocessing
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import plotly.plotly as py
import plotly.graph_objs as go
import plotly.offline as offline
from sklearn.manifold import TSNE
offline.init_notebook_mode(connected=True)... | github_jupyter |
# Continuous Control
---
In this notebook, you will learn how to use the Unity ML-Agents environment for the second project of the [Deep Reinforcement Learning Nanodegree](https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893) program.
### 1. Start the Environment
We begin by importing the ne... | github_jupyter |
```
from random import shuffle
import numpy
from scipy import stats
def truncate(a, b):
n = min(len(a), len(b))
return a[:n], b[:n]
def truncate3(a, b, c):
n = min(len(a), len(b), len(c))
return a[:n], b[:n], c[:n]
def xor(x, y):
# assert len(x) == len(y)
a = int.from_bytes(x, "big")
b =... | github_jupyter |
# Algorithms of graph
```
import sys
import matplotlib.pyplot as plt
#change it to your path
BaseAlgPath = "/home/xuhangkun/Code/BaseAlgorithm"
sys.path.append(BaseAlgPath)
#draw the draph
import random
def DrawGraph(gr,color="blue",directed=False,**kwargs):
"""draw undirected graph
"""
points = []
for... | github_jupyter |
<a href="https://colab.research.google.com/github/AJamal27891/1YBCwVpt3HNYOiYL/blob/main/ConvBert_Matching_entities.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# download dependencies
```
!rm -r test_trainer
!pip install transformers
!pip inst... | github_jupyter |
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import statsmodels.api as sm
from sklearn.linear_model import LinearRegression
import sys
sys.path.insert(0, '../')
from portfolio import *
```
# Load Data
```
rets = pd.read_excel('../data/sp500_fundamentals.xlsx',sheet_name='total returns... | github_jupyter |
<a href="https://colab.research.google.com/github/Tessellate-Imaging/monk_v1/blob/master/study_roadmaps/2_transfer_learning_roadmap/6_freeze_base_network/2.1)%20Understand%20the%20effect%20of%20freezing%20base%20model%20in%20transfer%20learning%20-%202%20-%20mxnet.ipynb" target="_parent"><img src="https://colab.researc... | github_jupyter |
# Pathing
Based on flexible logarithmic spiral
The polar equation of a logarithmic spiral is written as r=e^(a*theta), where r is the distance from the origin, e is Euler's number (about 1.618282), and theta is the angle traveled measured in radians (1 radian is approximately 57 degrees)
The constant a is the... | github_jupyter |
## Illusory contours, intensity/exposure invariance, no need for precision weighting!
Scaling input signal's intensity, not value, e.g. a dim or bright sin wave between 1 and -1.
```
# %%
import torch
from torch import nn
import pdb
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import numpy as np... | github_jupyter |
# Histograms of Oriented Gradients (HOG)
There are several algorithms used to detect objects in a picture. Those algorithms work well for detecting consistent internal features, such as facial detection, because faces have a lot of consistent internal features that don’t get affected by the image background, such as t... | github_jupyter |
---
---
# Born Machine through MPS
## Algorithm
---
#### Legend:
* <font color='blue'>blue</font> means there is still some doubts about the procedure.
* <font color='green'>green</font> means there are some details further discussed about the argument.
***Goal :*** Obtain a wavefunction ${\psi}$ expressed through a ... | github_jupyter |
# Facies classification from well logs with Convolutional Neural Networks (CNN)
## Shiang Yong Looi
Using Keras running on top for Tensorflow, we build two CNNs : first to impute PE on two wells with missing data and then for the main task of classifying facies.
```
import numpy as np
import pandas
import matplotlib... | github_jupyter |
# Master equation
We consider a system made of states $A$, $B$, $C$, ... Each state has a given equilibrium population and the transition rate between any two states can be non-zero and is fixed. The population of any state at any time is stored in the vector $P$. The transition rates are stored in matrix $M$. The evo... | github_jupyter |
# Wrangle OpenStreetMap data
[Cédric Campguilhem](https://github.com/ccampguilhem/Udacity-DataAnalyst), August 2017
<a id="Top"/>
## Table of contents
- [Introduction](#Introduction)
- [Project organisation](#Project organisation)
- [Map area selection](#Area selection)
- [XML data structure](#XML data structure)
- [... | github_jupyter |
```
from google.colab import drive
drive.mount('/content/drive')
!wget http://www.iapr-tc11.org/dataset/4NSigComp2010/Dataset_4NSigComp2010.zip
#maybe play with this later? For submission to ark.
import zipfile
z = zipfile.ZipFile('/content/sigComp2011-trainingSet.zip', 'r')
z.setpassword(b"I hereby accept the SigComp... | github_jupyter |
# __DATA 5600: Introduction to Regression and Machine Learning for Analytics__
## __Notes on the Bayesian Gamma-Poisson Conjugate Model__ <br>
Author: Tyler J. Brough <br>
Last Update: December 6, 2021 <br>
<br>
---
<br>
```
import numpy as np
import pandas as pd
from scipy import stats
import seaborn as sns... | github_jupyter |
# Introduction to MPI
## Overview
### Questions
* What is MPI?
* Why should I run my simulations in parallel?
* How can I execute scripts in parallel?
### Objectives
* Describe **MPI**.
* Explain how **MPI** can provide faster **performance** on **HPC** systems.
* Show how to write a **single program** that can ... | github_jupyter |
# Introduction to Jupyter Notebooks
This lesson will introduce the Jupyter Notebook interface. We will use the interface to run and write, yes, write, some Python code for text data analysis.
By the end of this lesson, learners should be able to:
1. Explain the difference between markdown and code blocks in Jupyter ... | github_jupyter |
# Introduction
## Goals
By the end of this course, you should be able to
- Do basic data analysis using R or Python/Pandas, with a special emphasis on
- The practical side of things you might not learn in academic courses
- workflows and strategies that work in research
What this course is NOT:
- A basic course in... | github_jupyter |
# Goal
* Primer design for clade of interest
# Var
```
base_dir = '/ebio/abt3_projects/software/dev/ll_pipelines/llprimer/experiments/HMP_most-wanted/v0.3/'
clade = 'Prevotella'
domain = 'Bacteria'
taxid = 838
```
# Init
```
library(dplyr)
library(tidyr)
library(data.table)
library(tidytable)
library(ggplot2)
libr... | github_jupyter |
# Phasing haplotypes of gene 1217 in CAMP
Version of the `Phasing-LJA.ipynb` notebook adapted to just analyze "haplotypes" of gene 1217 in CAMP.
The code for performing read smoothing is derived from that notebook's code; ideally we would consolidate these into a single script to limit code reuse, but for the sake of... | github_jupyter |
# Generate example data
```
%matplotlib inline
import numpy as np
import pandas as pd
from statsmodels.tsa.arima_process import ArmaProcess
from causalimpact import CausalImpact
from typing import Dict
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib
import sys
sys.path.append("../")
import Caus... | github_jupyter |
```
!mkdir folds
import cPickle as pickle
from skmultilearn.dataset import load_from_arff, load_dataset_dump
import copy
import datetime
import numpy as np
from scipy.sparse import lil_matrix
from sklearn.model_selection import KFold, StratifiedKFold
import pandas as pd
import copy
from itertools import chain
from buil... | github_jupyter |
```
import sys
import rics
# Print relevant versions
print(f"{rics.__version__=}")
print(f"{sys.version=}")
!git log --pretty=oneline --abbrev-commit -1
from rics.utility.logs import basic_config, logging
basic_config(level=logging.DEBUG, matplotlib_level=logging.INFO)
```
# In vs between
What's faster at various c... | github_jupyter |
# Exploring und Plotting 2
**Inhalt:** Selbständige Übung in Gruppen
**Nötige Skills:** Time Series
**Lernziele:**
- Selbständig Daten explorieren und Storyideen testen
# Das Beispiel
Börsenkurse aller Bluechips-Firmen an der Schweizer Börse.
Korpus: https://www.six-group.com/exchanges/shares/explorer/swiss_blue_... | github_jupyter |
Original code from https://github.com/eriklindernoren/Keras-GAN/blob/master/dcgan/dcgan.py under the following license:
MIT License
Copyright (c) 2017 Erik Linder-Norén
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), t... | github_jupyter |
# Introduction to cuDF
Now that you have achieved a basic understanding of Python, it's time to introduce you to [cuDF](https://github.com/rapidsai/cudf), a RAPIDS library that enables you to create and manipulate GPU-accelerated dataframes. cuDF implements an interface similar to Pandas so that Python data scientists... | github_jupyter |
##### Copyright 2018 The TensorFlow Authors.
```
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | github_jupyter |
# CH. 7 - TOPIC MODELS
## Activities
#### Activity 7.01
```
# not necessary
# added to suppress warnings coming from pyLDAvis
import warnings
warnings.filterwarnings('ignore')
import langdetect # language detection
import matplotlib.pyplot # plotting
import nltk # natural language processing
import numpy # array... | github_jupyter |
```
#cell-width control
from IPython.core.display import display, HTML
display(HTML("<style>.container { width:80% !important; }</style>"))
%%javascript
IPython.OutputArea.prototype._should_scroll = function(lines) {
return false;
}
#packages
import numpy
import tensorflow as tf
from tensorflow.core.example import ... | github_jupyter |
# T test
---
If calculated t-value is larger than the tabled value at the desired significance level (alpha = .01), we can reject the null hypothesis and accept the alternative hypothesis, namely, that the difference is likely the result of the experimental treatment and not the result of chance variation. <br/>
---... | github_jupyter |
# Getting Started with DaCe
DaCe is a Python library that enables optimizing code with ease, from running on a single core to a full supercomputer. With the power of data-centric transformations, it can automatically map code for CPUs, GPUs, and FPGAs.
Let's get started with DaCe by importing it:
```
import dace
```... | github_jupyter |
# README
This notebook is a part of the implementation of ["Adversarial Network Traffic: Towards Evaluating the Robustness of Deep Learning-Based Network Traffic Classification"](https://arxiv.org/abs/2003.01261), including the implementation of flow content classifiers FCC-P, and FCC-HP, and the implementation of Adv... | github_jupyter |
# DE Africa Coastlines raster generation <img align="right" src="https://github.com/digitalearthafrica/deafrica-sandbox-notebooks/raw/main/Supplementary_data/DE_Africa_Logo_Stacked_RGB_small.jpg">
This code conducts raster generation for DE Africa Coastlines:
* Load stack of all available Landsat 5, 7 and 8 satellite... | github_jupyter |
# Flowers Image Classification with TensorFlow on Cloud ML Engine
This notebook demonstrates how to do image classification from scratch on a flowers dataset using the Estimator API.
```
import os
PROJECT = 'cloud-training-demos' # REPLACE WITH YOUR PROJECT ID
BUCKET = 'cloud-training-demos-ml' # REPLACE WITH YOUR BU... | github_jupyter |
```
import math
import random
import gym
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.distributions import Normal
from IPython.display import clear_output
import matplotlib.pyplot as plt
%matplotlib inline
```
<h2>Use CUDA</h2>
```
use_... | github_jupyter |
# Least Angle Regression with RobustScaler and Power Transformer
This Code template is for the regression analysis using LARS Regressor and the feature transformation technique Power Transformer and Robust Scaler rescaling technique in a pipeline.
### **Required Packages**
```
import warnings
import numpy as np
imp... | github_jupyter |
```
import numpy as np
import os
import pandas as pd
import geopandas as gpd #important
import rasterio
import matplotlib.pyplot as plt
import operator
import seaborn as sns
import psycopg2
import shapely
import laspy #las open
from laspy.file import File as read_las #open las
from shapely.geometry import Point #con... | github_jupyter |
# Torch Core
This module contains all the basic functions we need in other modules of the fastai library (split with [`core`](/core.html#core) that contains the ones not requiring pytorch). Its documentation can easily be skipped at a first read, unless you want to know what a given fuction does.
```
from fastai.gen_... | github_jupyter |
```
! pip install psycopg2-binary --user
! pip install --upgrade pip
import pandas as pd
import psycopg2
import numpy as np
from getpass import getpass
# connect to database
connection = psycopg2.connect(
database = "postgres",
user = "postgres",
password = getpass(),
host = "movie-rec-scra... | github_jupyter |
# PyTorch Finetune Example
TextWiser is designed with extensibility and optimizability in mind. As such, it tries to allow fine-tuning for embeddings that are compatible. The detailed list is available in the README, and we will be using the FastText word embeddings for this example.
```
import os
os.chdir('..')
```
... | github_jupyter |
# Hash map
A hash map is a data structure that maps keys to values with amortized O(1) insertion, find, and deletion time. The map is unordered.
Open3D allows parallel hashing on CPU and GPU with keys and values organized as Tensors, where we take a batch of keys and/or values as input.
- Keys: The Open3D hash map su... | github_jupyter |
# Xarray-spatial
### User Guide: Remote Sensing tools
-----
Xarray-spatial's Remote Sensing tools provide a range of functions pertaining to remote sensing data such as satellite imagery. A range of functions are available to calculate various vegetation and environmental parameters from the range of band data availab... | github_jupyter |
```
# import mne
import pywt
import numpy as np
import pandas as pd
import antropy as ant
from os import listdir
# from entropy import *
from tqdm import tqdm
from scipy.stats import entropy
from sklearn.decomposition import PCA
from sklearn.utils import shuffle
from scipy.stats import entropy
from multiprocessing im... | github_jupyter |
# Re-creating [Capillary Hysteresis in Neutrally Wettable Fibrous Media: A Pore Network Study of a Fuel Cell Electrode](http://link.springer.com/10.1007/s11242-017-0973-2)
# Part A: Percolation
## Introduction
In this tutorial, we will use the ```MixedInvasionPercolation``` algorithm to examine capillary hysteresis i... | github_jupyter |
# Building an ARIMA Model for a Financial Dataset
In this notebook, you will build an ARIMA model for AAPL stock closing prices. The lab objectives are:
* Pull data from Google Cloud Storage into a Pandas dataframe
* Learn how to prepare raw stock closing data for an ARIMA model
* Apply the Dickey-Fuller test
* Buil... | github_jupyter |
<a href="https://colab.research.google.com/github/Sonochy/UoA_school_mission-12/blob/master/LPE_U_Net.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
## [惑星探査育英会 第十二回実習会](https://www.cps-jp.org/~tansaku/wiki/top/?school_mission-12)
U-Netを用いたsemantic... | github_jupyter |
```
%matplotlib notebook
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
#plt.style.use('ggplot')
import ipywidgets as widgets
import sys, os, io, string, shutil, math
from hublib.ui import Submit
from hublib.ui import RunCommand
import hublib.use
%use boost-1.62.0-mpich2-1.3-gnu-4.7.2
%use lamm... | github_jupyter |
# Web scraping: Senate press accrediations
In this notebook, we're going to scrape [a table of journalists in the Senate press gallery](https://www.dailypress.senate.gov/?page_id=67).
The data are paginated, but what do we see when we inspect the source? Boom: All of the table rows are there on the page when it loads... | github_jupyter |
## <p style="text-align: center; font-size: 4em;"> Python tutorial 2 </p>
# 1. random number generators: numpy.random
[https://docs.scipy.org/doc/numpy/reference/routines.random.html](https://docs.scipy.org/doc/numpy/reference/routines.random.html)
```
import numpy as np
pr... | github_jupyter |
# Finding Similar Movies
We'll start by loading up the MovieLens dataset. Using Pandas, we can very quickly load the rows of the u.data and u.item files that we care about, and merge them together so we can work with movie names instead of ID's. (In a real production job, you'd stick with ID's and worry about the name... | github_jupyter |
# Neural networks simulation (Synchronization Problem)
This file is going to study any neural netwrok class which is defined in the `<network_reference.py>` file.
```
import numpy as np
from tqdm import tqdm
import matplotlib.pyplot as plt
import os
%%capture
from tqdm import tqdm_notebook as tqdm
tqdm().pandas() #Th... | github_jupyter |
<h1 dir="rtl"><a href="https://koichiyasuoka.github.io/deplacy/">deplacy</a> برای تحلیل نحو</h1>
<h2 dir="rtl">با <a href="https://stanfordnlp.github.io/stanza">Stanza</a></h2>
```
!pip install deplacy stanza
import stanza
stanza.download("fa")
nlp=stanza.Pipeline("fa")
doc=nlp("به اعتقاد من موسيقي هنر نيست، بلكه متا... | github_jupyter |
# End-to-End Example #1
1. [Introduction](#Introduction)
2. [Prerequisites and Preprocessing](#Prequisites-and-Preprocessing)
1. [Permissions and environment variables](#Permissions-and-environment-variables)
2. [Data ingestion](#Data-ingestion)
3. [Data inspection](#Data-inspection)
4. [Data conversion](#Data... | github_jupyter |
## Tutorial 4. Network Modularity: Quantitative History
Created by Emanuel Flores-Bautista 2018. All code contained in this notebook is licensed under the [Creative Commons License 4.0](https://creativecommons.org/licenses/by/4.0/).
This tutorial can be accesed here: https://programminghistorian.org/lessons/explorin... | github_jupyter |
## Введение
Сегодня познакомимся с инструментами работы с данными.
Библиотеки **numpy, pandas, matplotlib**.
```
import numpy as np # для работы с числами, векторами и матрицами
import pandas as pd # для работы с датасетом (это умное слово для "набора данных" или "таблицы")
import matplotlib.pyplot as plt # для пос... | github_jupyter |
# Calibrating a qubit
```
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from qiskit import IBMQ
import qiskit.pulse as pulse
import qiskit.pulse.pulse_lib as pulse_lib
from qiskit.compiler import assemble
from qiskit.qobj.ut... | github_jupyter |
# 02 - Reverse Time Migration
This notebook is the second in a series of tutorial highlighting various aspects of seismic inversion based on Devito operators. In this second example we aim to highlight the core ideas behind seismic inversion, where we create an image of the subsurface from field recorded data. This tu... | github_jupyter |
```
#@title ## Download Kaggle Dataset
#@markdown Dataset: Annotated Corpus for Named Entity Recognition <br>
#@markdown [https://www.kaggle.com/therohk/million-headlines](https://www.kaggle.com/therohk/million-headlines)
#@markdown <br><br>
#@markdown News headlines published over a period of seventeen years.
#@m... | github_jupyter |
```
!pip install catboost
import io
import os
import gc
import re
import random
import pickle
from pathlib import Path
import pandas as pd
import numpy as np
from tqdm.auto import tqdm
from sklearn.model_selection import StratifiedKFold
from sklearn.metrics import accuracy_score
from sklearn.metrics import accuracy... | github_jupyter |
# NumPy
NumPy ist ein Erweiterungsmodul für numerische Berechnungen mit Python. Es beinhaltet grundlegende Datenstrukturen, sprich Matrizen und mehrdimensionale Arrays. Selbst ist NumPy in C umgesetzt worden und bietet mithilfe der Python-Schnittstelle die Möglichkeit Berechnungen schnell durchzuführen. Die Module Sci... | github_jupyter |
```
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import difflib
df = pd.read_json('Fix1.json')
df.sort_index(inplace=True)
# دانشگاههای پذیرفته شده: accUni
# دانشگاه انتخاب شده:apUni
# Renaming : Cause it is not clear
# + Make them a same style!
df.rename(columns={"apUni": 'uniSelected', 'acc... | github_jupyter |
# ETL Pipeline Preparation
Follow the instructions below to help you create your ETL pipeline.
### 1. Import libraries and load datasets.
- Import Python libraries
- Load `messages.csv` into a dataframe and inspect the first few lines.
- Load `categories.csv` into a dataframe and inspect the first few lines.
```
# imp... | github_jupyter |
# Map your IBM Cloud data
- last modified: July, 2016
- author: [Raj Singh](https://developer.ibm.com/clouddataservices/author/rrsingh/)
- original: https://github.com/ibm-cds-labs/open-data/blob/master/samples/cartodb.ipynb
- blog post: [Map your IBM Cloud data](https://developer.ibm.com/clouddataservices/)
## Overv... | github_jupyter |
# Monitoring Data Drift
Over time, models can become less effective at predicting accurately due to changing trends in feature data. This phenomenon is known as *data drift*, and it's important to monitor your machine learning solution to detect it so you can retrain your models if necessary.
In this lab, you'll conf... | github_jupyter |
<h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a href="#Testando-Lógica" data-toc-modified-id="Testando-Lógica-1"><span class="toc-item-num">1 </span>Testando Lógica</a></span></li></ul></div>
Ideias:
* Criar um diretório específico na pasta do proj... | github_jupyter |
# Analysis of Charles Murray's Basic Income Plan
Details from http://www.fljs.org/files/publications/Murray.pdf, based on *In Our Hands* (2006).
Key elements summarized in [Ghenis (2017)](https://medium.com/@MaxGhenis/the-case-for-a-person-centric-basic-income-plan-55e90010fc9e) include:
* Annual amount: \\$10,000, ... | github_jupyter |
```
from google.colab import drive
drive.mount('/content/drive')
```
# **Introducing the Keras Sequential API**
**Learning Objectives**
1. Build a DNN model using the Keras Sequential API
1. Learn how to use feature columns in a Keras model
1. Learn how to train a model with Keras
1. Learn how to save/load, a... | github_jupyter |
<style>div.container { width: 100% }</style>
<img style="float:left; vertical-align:text-bottom;" height="65" width="172" src="../assets/PyViz_logo_wm_line.png" />
<div style="float:right; vertical-align:text-bottom;"><h2>Tutorial A1. Exploration with Containers</h2></div>
In the first two sections of this tutorial w... | github_jupyter |
```
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
from pylab import *
length=40
for it in range(0,80,20):
f,axarr = plt.subplots(4,5,figsize=(50,40))
f.subplots_adjust(hspace=0.1)
for ii in range(0,5):
for iii in range (0,4):
i = it+iii+4*ii
maxtime=0
... | github_jupyter |
```
# Copyright 2021 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writi... | github_jupyter |
## Stress Determinator
### Bi-directional Long-Short-Term-Memory
#### Implemented by Pytorch
This is the tutorial notebook for how to use the stress determinator, prepared by **DMaS** and **Douglas Research Center**.
**Data used:**
All the data sourced from Dr. Wong's mouse neuron experiments in Douglas Research ... | github_jupyter |
```
import os
import json
import numpy as np
dataLists = []
dataSource = 'participant' #'pilot'
path = './data/interaction_ros_logs'
for f in os.listdir(os.path.join(path,dataSource,'session1')):
filepath = os.path.join(path,dataSource,'session1',f)
if os.path.isfile(filepath):
# Read in ... | github_jupyter |
# Osher solution to a scalar Riemann problem
Implementation of the general solution to the scalar Riemann problem that is valid also for non-convex fluxes.
$$
Q(\xi) = \begin{cases}
\text{argmin}_{q_l \leq q \leq q_r} [f(q) - \xi q]& \text{if} ~q_l\leq q_r,\\
\text{argmax}_{q_r \leq q \leq q_l} [f(q) - \xi q... | github_jupyter |
```
import tensorflow as tf
import random
import numpy as np
import time
import sys, getopt
from tensorflow.contrib import rnn
def stdout(s):
sys.stdout.write(str(s)+'\n')
nrod = 400
nlabel = 6
batchsize = 200
seq_len = 3
nEpoch = 2
eta = 1e-2
nInput = nrod
nHidden = 32
nDense = 32
subnlayer = 1
seqnlayer = 1
bThe... | github_jupyter |
```
%matplotlib inline
```
# Comparing anomaly detection algorithms for outlier detection on toy datasets
This example shows characteristics of different anomaly detection algorithms
on 2D datasets. Datasets contain one or two modes (regions of high density)
to illustrate the ability of algorithms to cope with mult... | github_jupyter |
___
<a href='https://www.udemy.com/user/joseportilla/'><img src='../Pierian_Data_Logo.png'/></a>
___
<center><em>Content Copyright by Pierian Data</em></center>
# Nested Statements and Scope
Now that we have gone over writing our own functions, it's important to understand how Python deals with the variable names y... | github_jupyter |
# TCSS503 - Week 2 Balanced Trees
In this simple interactive tutorial, we will create a **Red-Black Tree**. A Red-Black Tree is an implementation of a Binary Search Tree that grows from bottom to top, maintaining its balance to guarante a $O(\log{n})$ time complexity for Inserts and Searches.
## Red-Black Tree
A R... | github_jupyter |
# Função Softmax
A função softmax é um dos blocos básicos de redes neurais. Ela é usualmente utilizada em classificação multiclasses. Ela transforma valores ("scores", "logits") em probabilidades.
Nesse tutorial, iremos:
1. Ver a definição da função softmax,
2. Implementá-la via programação matricial e
3. Explorar ... | github_jupyter |
# Lambda Functions (Funções Anônimas)
https://realpython.com/python-lambda/
Identity function. Returns its argument:
```
def identity(x):
return x
```
In contrast, if you use a Python Lambda Construction, you get the following:
```
lambda x: x
```
In the example above, the expression is composed of:
- The ke... | github_jupyter |
# UCS Manager Python SDK Examples
Used with the UCS Platform Emulator with the IP address `192.168.72.4`.
- Update the `ip`, `username`, and `password` constant values below, as necessary.
---
## Constants
```
# UCSM credentials
IP = '192.168.72.4'
USERNAME = 'admin'
PASSWORD = 'admin'
SECURE = False
# NTP server... | github_jupyter |
### Independent Component Analysis
Independent Component Analysis is an algorithm to obtain a linear combination of the original data source. So does Principal Component Analysis! Well, ICA attempts to decompose the original data into independent subsets yet PCA attempts to maximize the variance in the new lin... | github_jupyter |
# MNIST distributed training and batch transform
The SageMaker Python SDK helps you deploy your models for training and hosting in optimized, production-ready containers in SageMaker. The SageMaker Python SDK is easy to use, modular, extensible and compatible with TensorFlow and MXNet. This tutorial focuses on how to ... | github_jupyter |
```
from urllib.request import urlopen
data_set_url = 'https://static-content.springer.com/esm/art%3A10.1038%2Fncomms5212/MediaObjects/41467_2014_BFncomms5212_MOESM1045_ESM.txt'
data = urlopen(data_set_url)
my_data = []
for line in data:
data_row = line.decode().rstrip()
my_data.append([term for term in data_r... | github_jupyter |
<a href="https://colab.research.google.com/github/AnilZen/centpy/blob/master/notebooks/Scalar_2d.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
# Quasilinear scalar equation with CentPy in 2d
### Import packages
```
# Install the centpy package
!... | github_jupyter |
# Pendulum visualization using ipywidgets
v2 adds driving force curve
* Created 12-Dec-2018 by Dick Furnstahl (furnstahl.1@osu.edu)
* Last revised 19-Jan-2019 by Dick Furnstahl (furnstahl.1@osu.edu).
```
%matplotlib inline
import numpy as np
from scipy.integrate import ode, odeint
import matplotlib.pyplot as plt
``... | github_jupyter |
## Kaggle Dogbreeds
```
%reload_ext autoreload
%autoreload 2
%matplotlib inline
from fastai.imports import *
from fastai.conv_learner import *
from fastai.model import *
from fastai.dataset import *
from fastai.sgdr import *
from fastai.plots import *
PATH = "data/dogbreeds/"
TRAIN = "train/"; VALID = "valid/"; TEST ... | github_jupyter |
# Learning a cosine with keras
```
import os
os.environ['THEANO_FLAGS']='mode=FAST_COMPILE,optimizer=None,device=cpu,floatX=float32'
import numpy as np
import sklearn.cross_validation as skcv
#x = np.linspace(0, 5*np.pi, num=10000, dtype=np.float32)
x = np.linspace(0, 4*np.pi, num=10000, dtype=np.float32)
y = np.cos(x... | github_jupyter |
Adapted from: https://github.com/explosion/spacy-transformers/blob/master/examples/Spacy_Transformers_Demo.ipynb
# Spacy PyTorch Transformers Demo
[](https://colab.research.google.com/drive/1lG3ReZc9ESyVPsstjuu5ek73u6vVsi3X)
# License: MIT
# Email: matthew.dixon@iit.edu
# Notes: tested on Mac OS X with Python 3.6 and Tensorflow 1.3.0
# Citation: Please cite the following reference if this notebook is used for research purposes:
# Dixon M.F., I. Halperin and P.... | github_jupyter |
```
import numpy as np
import matplotlib.pyplot as plt
from tsmoothie.utils_func import sim_seasonal_data
from tsmoothie.smoother import *
```
# SINGLE SEASONALITY
```
# generate sinusoidal timeseries
np.random.seed(33)
data = sim_seasonal_data(n_series=10, timesteps=300,
freq=24, measure_... | github_jupyter |
# Lab 2: Indexing and Slicing
For this lab, we'll get a bit of hands on practice creating data structures, practicing how to apply some common methods, and we'll learn about how to access elements inside the data structures using indexing and slicing.
## Strings
Let's create a bit a chunk of text so that we can practi... | github_jupyter |
```
import numpy as np
import matplotlib.pyplot as plt
from computerrefractored import Computer
import re
%load_ext autoreload
%autoreload 2
noun, verb = 0,0
f=open('input.txt').read()
memory = tuple(int(i) for i in f.split(',')) # let's make it immutable as a tuple
memsize = 100000
memory = tuple(list(memory)+[0]*mems... | github_jupyter |
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