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11,400 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy Tutorial
Numpy is a computational library for Python that is optimized for operations on multi-dimensional arrays. In this notebook we will use numpy to work with 1-d arrays (often cal... | Python Code:
import numpy as np # importing this way allows us to refer to numpy as np
Explanation: Numpy Tutorial
Numpy is a computational library for Python that is optimized for operations on multi-dimensional arrays. In this notebook we will use numpy to work with 1-d arrays (often called vectors) and 2-d arrays (o... |
11,401 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Response functions
This notebook provides an overview of the response functions that are available in Pastas. Response functions describe the response of the dependent variable (e.g., ground... | Python Code:
import numpy as np
import pandas as pd
import pastas as ps
import matplotlib.pyplot as plt
ps.show_versions()
Explanation: Response functions
This notebook provides an overview of the response functions that are available in Pastas. Response functions describe the response of the dependent variable (e.g., ... |
11,402 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction à l'I/O Asynchrone
Le Socket de Berkeley
Il est difficile d'imaginer le nombre d'instanciations d'objets de type Socket depuis leur introduction en 1983 à l'université Berkeley.... | Python Code:
from IPython.display import Image
from IPython.display import display
import socket
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.connect(("etsmtl.ca" , 80))
Explanation: Introduction à l'I/O Asynchrone
Le Socket de Berkeley
Il est difficile d'imaginer le nombre d'instanciations d'objets de... |
11,403 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
14 - Advanced topics - Cement Pavers albedo example
This journal creates a paver underneath the single-axis trackers, and evaluates the improvement for one day -- June 17th with and without ... | Python Code:
import os
from pathlib import Path
import pandas as pd
testfolder = str(Path().resolve().parent.parent / 'bifacial_radiance' / 'TEMP' / 'Tutorial_14')
if not os.path.exists(testfolder):
os.makedirs(testfolder)
print ("Your simulation will be stored in %s" % testfolder)
from bifacial_radiance impor... |
11,404 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Convolutional Neural Network in TensorFlow
In this notebook, we convert our LeNet-5-inspired, MNIST-classifying, deep convolutional network from Keras to TensorFlow (compare them side b... | Python Code:
import numpy as np
np.random.seed(42)
import tensorflow as tf
tf.set_random_seed(42)
Explanation: Deep Convolutional Neural Network in TensorFlow
In this notebook, we convert our LeNet-5-inspired, MNIST-classifying, deep convolutional network from Keras to TensorFlow (compare them side by side) following A... |
11,405 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Non-Linear Time History Analysis (NLTHA) for Single Degree of Freedom (SDOF) Oscillators
In this method, a single degree of freedom (SDOF) model of each structure is subjected to non-linear ... | Python Code:
import NLTHA_on_SDOF
from rmtk.vulnerability.common import utils
%matplotlib inline
Explanation: Non-Linear Time History Analysis (NLTHA) for Single Degree of Freedom (SDOF) Oscillators
In this method, a single degree of freedom (SDOF) model of each structure is subjected to non-linear time history analysi... |
11,406 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
AutoML for Text Classification
Learning Objectives
Learn how to create a text classification dataset for AutoML using BigQuery
Learn how to train AutoML to build a text classification model
... | Python Code:
import os
from google.cloud import bigquery
import pandas as pd
%load_ext google.cloud.bigquery
Explanation: AutoML for Text Classification
Learning Objectives
Learn how to create a text classification dataset for AutoML using BigQuery
Learn how to train AutoML to build a text classification model
Learn ho... |
11,407 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regression Week 1
Step1: Load house sales data
Dataset is from house sales in King County, the region where the city of Seattle, WA is located.
Step2: Split data into training and testing
... | Python Code:
import graphlab
Explanation: Regression Week 1: Simple Linear Regression
In this notebook we will use data on house sales in King County to predict house prices using simple (one input) linear regression. You will:
* Use graphlab SArray and SFrame functions to compute important summary statistics
* Write a... |
11,408 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Birthday problem simulated
Let's say we can't figure out how to formally calculate the probability that 2 people out of N have the same birthday (ignoring leap years). Not to worry
Step1: T... | Python Code:
import random
from collections import defaultdict
def num_people_same_birthday(n):
bdays = defaultdict(int)
for i in range(n):
bdays[random.randrange(0, 365)] += 1
return len([k for (k, v) in bdays.items() if v > 1])
num_people_same_birthday(60)
Explanation: Birthday problem simulat... |
11,409 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python中常用的高级特性
三目运算符
例如Javascript或者php等大部分编程语言中都会提供三目运算符以达到快捷的判断赋值功能.
但是在Python开发者认为不符合Python简洁, 简单的特点, 所以其实Python中没有常见的?
Step1: 列表生成式
列表生成式是一种生成规律数组的简写形式.
Step2: 字典生成式
字典生成式和列表生成式语法类型. 也是... | Python Code:
# 给一个变量赋值, 取得给定整形变量的绝对值
number1 = -11
value1 = number1
if value1 < 0:
value1 = -value1
print(value1)
# 我们这边可以使用Python中特殊的三目运算符形式
number2 = -22
value2 = number2 if number2 > 0 else -number2
print(value2)
Explanation: Python中常用的高级特性
三目运算符
例如Javascript或者php等大部分编程语言中都会提供三目运算符以达到快捷的判断赋值功能.
但是在Python开发者认为不符合... |
11,410 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1> Preprocessing using Dataflow </h1>
This notebook illustrates
Step1: Run the command again if you are getting oauth2client error.
Note
Step2: You may receive a UserWarning about the Ap... | Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
pip install --user apache-beam[gcp]==2.16.0
Explanation: <h1> Preprocessing using Dataflow </h1>
This notebook illustrates:
<ol>
<li> Creating datasets for Machine Learning using Dataflow
</ol>
<p>
While Pandas is fine for experimenting, fo... |
11,411 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
3/ Exercises solutions
Step1: RREF exercises
E3.1
Step2: Verify the solution geometrically
Step3: E3.2
Step4: E3.3
Step5: Matrix equations
Matrix product
E3.5
Compute the following matr... | Python Code:
# helper code needed for running in colab
if 'google.colab' in str(get_ipython()):
print('Downloading plot_helpers.py to util/ (only neded for colab')
!mkdir util; wget https://raw.githubusercontent.com/minireference/noBSLAnotebooks/master/util/plot_helpers.py -P util
from sympy import *
init_print... |
11,412 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Predict Concentrations of Metabolites
The objective is to see whether continuous vector embedding can help in the prediction of concentrations of metabolites.
Step1: Load Standards Data
Ste... | Python Code:
%matplotlib inline
%load_ext autoreload
%autoreload 2
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
from IPython.display import display, HTML
from scipy import stats
from sklearn import linear_model
from sklearn.linear_model import LinearRegression
from sklearn.gaussian_process impor... |
11,413 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Biblioteca Shapely e Objetos geométricos
Fonte
Step1: Vamos ver como a variável do tipo Point é mostrada no jupyter
Step2: Também podemos imprimir os pontos para ver a sua definição
Step3:... | Python Code:
# Import necessary geometric objects from shapely module
from shapely.geometry import Point, LineString, Polygon
# Create Point geometric object(s) with coordinates
point1 = Point(2.2, 4.2)
point2 = Point(7.2, -25.1)
point3 = Point(9.26, -2.456)
point3D = Point(9.26, -2.456, 0.57)
Explanation: Biblioteca S... |
11,414 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Analyse
If you want to do your own analyse of the data on db.sqlite3 and are going to use Python you can take advantage of some Django code. This Jupyter Notebook will help you to enabl... | Python Code:
import lowfat.models as models
Explanation: Data Analyse
If you want to do your own analyse of the data on db.sqlite3 and are going to use Python you can take advantage of some Django code. This Jupyter Notebook will help you to enable the Django code.
Setup and run
To setup your environment to run this Ju... |
11,415 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<table align="left">
<td>
<a href="https
Step1: Restart the Kernel
Once you've installed the {packages}, you need to restart the notebook kernel so it can find the packages.
Step2: B... | Python Code:
%pip install -U missing_or_updating_package --user
Explanation: <table align="left">
<td>
<a href="https://colab.research.google.com/github/GoogleCloudPlatform/ai-platform-samples/blob/main/notebooks/templates/ai_platform_notebooks_template_hybrid.ipynb"">
<img src="https://cloud.google.com/ml-... |
11,416 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: TensorFlow Addons 优化器：ConditionalGradient
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: 构建模型
S... | Python Code:
#@title Licensed under the Apache License, Version 2.0
# 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 writing, software
# distributed under the... |
11,417 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
STA 208
Step1: Load the following medical dataset with 750 patients. The response variable is survival dates (Y), the predictors are 104 measurements measured at a specific time (numerical ... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.linear_model import Ridge, RidgeCV, Lasso, LassoCV, lars_path, LogisticRegression
from sklearn.preprocessing import scale
from sklearn.metrics import confusion_matrix
import matplotlib.pyplot as plt
plt.style.use('ggplot')
... |
11,418 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Examples of Stacking BOSS Spectra using Speclite
Examples of using the speclite package to perform basic operations on spectral data accessed with the bossdata package. To keep the examples... | Python Code:
%pylab inline
import speclite
print(speclite.version.version)
import bossdata
print(bossdata.__version__)
finder = bossdata.path.Finder()
mirror = bossdata.remote.Manager()
Explanation: Examples of Stacking BOSS Spectra using Speclite
Examples of using the speclite package to perform basic operations on sp... |
11,419 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Clase 5
Step1: 1. Uso de Pandas para descargar datos de precios de cierre
Ahora, en forma de función
Step2: Una vez cargados los paquetes, es necesario definir los tickers de las acciones ... | Python Code:
#importar los paquetes que se van a usar
import pandas as pd
import pandas_datareader.data as web
import numpy as np
from sklearn.cluster import KMeans
import datetime
from datetime import datetime
import scipy.stats as stats
import scipy as sp
import scipy.optimize as optimize
import scipy.cluster.hierarc... |
11,420 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chem 30324, Spring 2019, Homework 5
Due Febrary 25, 2020
Real-world particle-in-a-box.
A one-dimensional particle-in-a-box is a simple but plausible model for the π electrons of a conjugated... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
E = []
l = 1.4e-10 #m
hbar = 1.05457e-34 #J*s
m = 9.109e-31 #kg
N = [1,3,5,7,9] #N = number of C-C bonds
for n in range (1,7):
for i in N:
e = (n**2*np.pi**2*hbar**2*6.2415e18)/(2*m*(i*l)**2)
E.append(e)
plt.scatter(N,E[0:5], label = "n=1")
plt.... |
11,421 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial 2 of 3
Step1: Let's generate a cubic network again, but with a different connectivity
Step2: This Network has pores distributed in a cubic lattice, but connected to diagonal neigh... | Python Code:
import numpy as np
import scipy as sp
import openpnm as op
np.random.seed(10)
ws = op.Workspace()
ws.settings["loglevel"] = 40
Explanation: Tutorial 2 of 3: Digging Deeper into OpenPNM
This tutorial will follow the same outline as Getting Started, but will dig a little bit deeper at each step to reveal the... |
11,422 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Sentiment analysis model using deep learning
| Python Code::
import tensorflow as tf
model = tf.keras.model.Sequential()
model.add(tf.keras.layers.Embedding(n_most_words,n_dim,input_length = X_train.shape[1]))
model.add(tf.keras.layers.Dropout(0.25))
model.add(tf.keras.layers.Conv1D(64, 3, padding = 'same', activation = 'relu'))
model.add(tf.keras.layers.LSTM(64,dr... |
11,423 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 DeepMind Technologies Limited.
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 ... | Python Code:
!pip install dm-acme
!pip install dm-acme[reverb]
!pip install dm-acme[tf]
!pip install dm-sonnet
!git clone https://github.com/deepmind/deepmind-research.git
%cd deepmind-research
Explanation: Copyright 2020 DeepMind Technologies Limited.
Licensed under the Apache License, Version 2.0 (the "License"); you... |
11,424 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regression Week 2
Step1: Load in house sales data
Dataset is from house sales in King County, the region where the city of Seattle, WA is located.
Step2: Split data into training and testi... | Python Code:
import graphlab
graphlab.product_key.set_product_key("C0C2-04B4-D94B-70F6-8771-86F9-C6E1-E122")
Explanation: Regression Week 2: Multiple Regression (Interpretation)
The goal of this first notebook is to explore multiple regression and feature engineering with existing graphlab functions.
In this notebook y... |
11,425 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I have two input arrays x and y of the same shape. I need to run each of their elements with matching indices through a function, then store the result at those indices in a third a... | Problem:
import numpy as np
x = [[2, 2, 2],
[2, 2, 2],
[2, 2, 2]]
y = [[3, 3, 3],
[3, 3, 3],
[3, 3, 1]]
x_new = np.array(x)
y_new = np.array(y)
z = x_new + y_new |
11,426 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocean
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify d... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'fio-ronm', 'sandbox-3', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: FIO-RONM
Source ID: SANDBOX-3
Topic: Ocean
Sub-Topics: Timestepping Frame... |
11,427 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Summary
scikit-learn API
X
Step1: Model complexity, overfitting, underfitting
Pipelines
Step2: Scoring metrics
Step3: Data Wrangling | Python Code:
from sklearn.datasets import load_digits
from sklearn.linear_model import LogisticRegression
from sklearn.cross_validation import cross_val_score
digits = load_digits()
X, y = digits.data / 16., digits.target
cross_val_score(LogisticRegression(), X, y, cv=5)
from sklearn.grid_search import GridSearchCV
fro... |
11,428 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Atmoschem
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Speci... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mri', 'sandbox-1', 'atmoschem')
Explanation: ES-DOC CMIP6 Model Properties - Atmoschem
MIP Era: CMIP6
Institute: MRI
Source ID: SANDBOX-1
Topic: Atmoschem
Sub-Topics: Transport, Emiss... |
11,429 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Network Traffic Forecasting (using time series data)
In telco, accurate forecast of KPIs (e.g. network traffic, utilizations, user experience, etc.) for communication networks ( 2G/3G... | Python Code:
def plot_predict_actual_values(date, y_pred, y_test, ylabel):
plot the predicted values and actual values (for the test data)
fig, axs = plt.subplots(figsize=(16,6))
axs.plot(date, y_pred, color='red', label='predicted values')
axs.plot(date, y_test, color='blue', label='actual va... |
11,430 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How rider usage varies with temperature when binning months
Setting up the data
Step1: Getting the data into groupby objects and getting a correlation table
Step2: Comments on above
As we ... | Python Code:
import numpy as np
import pandas as pd
import datetime
from pandas import Series, DataFrame
stations = pd.read_table('stations.tsv')
usage = pd.read_table('usage_2012.tsv')
weather = pd.read_table('daily_weather.tsv')
def change_seasons():
weather.loc[weather["season_code"] == 1, "season_desc"] = 'Wint... |
11,431 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Probabilistic Programming in Python using PyMC
Authors
Step1: Here is what the simulated data look like. We use the pylab module from the plotting library matplotlib.
Step2: Model Specific... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
# Initialize random number generator
np.random.seed(123)
# True parameter values
alpha, sigma = 1, 1
beta = [1, 2.5]
# Size of dataset
size = 100
# Predictor variable
X1 = np.random.randn(size)
X2 = np.random.randn(size) * 0.2
# Simulate outcome variable
Y... |
11,432 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h2> Plot a horizontal map of gridded radar data</h2>
<h4>This script loads in a binary file of gridded tail Doppler radar from the NOAA P-3 produced by the windsyn program (NOAA NSSL) - a s... | Python Code:
# Load the needed packages
from glob import glob
import os
import matplotlib.pyplot as plt
from awot.io import read_p3_radar
from awot.graph.common import create_basemap
from awot.graph import RadarHorizontalPlot
from awot.graph import FlightLevel
%matplotlib inline
Explanation: <h2> Plot a horizontal map ... |
11,433 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Loss Functions
Custom fastai loss functions
Step1: Wrapping a general loss function inside of BaseLoss provides extra functionalities to your loss functions
Step3: Focal Loss is the same a... | Python Code:
#|export
class BaseLoss():
"Same as `loss_cls`, but flattens input and target."
activation=decodes=noops
def __init__(self,
loss_cls, # Uninitialized PyTorch-compatible loss
*args,
axis:int=-1, # Class axis
flatten:bool=True, # Flatten `inp` and `targ` before ca... |
11,434 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ApJdataFrames McClure
Title
Step1: Table 1 - Target Information for Ophiuchus Sources
Step2: Table 2 - Spectral Type Information for the Entire Sample
Step3: Merge the two catalogs
Step4:... | Python Code:
import warnings
warnings.filterwarnings("ignore")
from astropy.io import ascii
import pandas as pd
Explanation: ApJdataFrames McClure
Title: THE EVOLUTIONARY STATE OF THE PRE-MAIN SEQUENCE POPULATION IN OPHIUCHUS: A LARGE INFRARED SPECTROGRAPH SURVEY
Authors: McClure et al.
Data is from this paper:
http://... |
11,435 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interact Exercise 01
Import
Step2: Interact basics
Write a print_sum function that prints the sum of its arguments a and b.
Step3: Use the interact function to interact with the print_sum ... | Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display
Explanation: Interact Exercise 01
Import
End of explanation
def print_sum(a, b):
Print the sum of the arguments a and b.
retur... |
11,436 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CH82 Model
The following tries to reproduce Fig 8 from Hawkes, Jalali, Colquhoun (1992).
First we create the $Q$-matrix for this particular model. Please note that the units are different fr... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from dcprogs.likelihood import QMatrix
tau = 1e-4
qmatrix = QMatrix([[ -3050, 50, 3000, 0, 0 ],
[ 2./3., -1502./3., 0, 500, 0 ],
[ 15, 0, -2065, 50, 2000 ]... |
11,437 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Spam detection
The main aim of this project is to build a machine learning classifier that is able to automatically detect
spammy articles, based on their content.
Step1: Modeling
We tried... | Python Code:
! sh bootstrap.sh
from sklearn.cluster import KMeans
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import random
from sklearn.utils import shuffle
from sklearn.metrics import f1_score
from sklearn.cross_validation import KFold
from sklearn.metrics import recall_score
from sklearn.e... |
11,438 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Missionaries and Infidels
We illustrate the notion of a search problem with the following example, which is also known as the
<a href="https
Step1: $\texttt{no_problem}(m, i)$ is true if th... | Python Code:
problem = lambda m, i: 0 < m < i
Explanation: Missionaries and Infidels
We illustrate the notion of a search problem with the following example, which is also known as the
<a href="https://en.wikipedia.org/wiki/Missionaries_and_cannibals_problem">missionaries and cannibals problem</a>:
Three missionaries a... |
11,439 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic Optimization
In this example, we'll be performing a simple optimization of single-objective functions using the global-best optimizer in pyswarms.single.GBestPSO and the local-best opt... | Python Code:
# Import modules
import numpy as np
# Import PySwarms
import pyswarms as ps
from pyswarms.utils.functions import single_obj as fx
# Some more magic so that the notebook will reload external python modules;
# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython
%load_ext autoreloa... |
11,440 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
L'objectif de ce script est d'illustrer graphiquement l'évolution du taux implicite de la TICPE depuis 1993. On étudie ce taux pour le diesel, et pour les carburants sans plombs.
Import de m... | Python Code:
from pandas import concat
%matplotlib inline
Explanation: L'objectif de ce script est d'illustrer graphiquement l'évolution du taux implicite de la TICPE depuis 1993. On étudie ce taux pour le diesel, et pour les carburants sans plombs.
Import de modules généraux
End of explanation
from openfisca_france_in... |
11,441 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Recommender Systems
In this project, we build a movie recommender system. We read a dataset of movie ratings by users, then we select other movies that a specific user would be interesting i... | Python Code:
import numpy as np
import pandas as pd
Explanation: Recommender Systems
In this project, we build a movie recommender system. We read a dataset of movie ratings by users, then we select other movies that a specific user would be interesting in based on his previous choice.
End of explanation
column_names =... |
11,442 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Clustering the subsampled 1.3 M cells
The data consists in 20K Neurons, downsampled from 1.3 Million Brain Cells from E18 Mice and is freely available from 10x Genomics (here).
Step1: Run s... | Python Code:
import numpy as np
import pandas as pd
import scanpy.api as sc
sc.settings.verbosity = 3 # verbosity: errors (0), warnings (1), info (2), hints (3)
sc.settings.set_figure_params(dpi=70) # dots (pixels) per inch determine size of inline figures
sc.logging.print_versions()
adata = sc.read_10x_h5('./data/1M... |
11,443 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Minimos Cuadrados
Por
Step1: 2- Aplique paso a paso el método de mínimos cuadrados de tal forma que le permita obtener la mejor curva lineal de ajuste de los datos anteriores, y determine l... | Python Code:
########################################################
## Librerias para el trabajo
########################################################
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
data1= np.loadtxt('datos.csv',delimiter=',') #datos para regresion lineal
X1=data1[:,0]
Y1=dat... |
11,444 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ordinal Regression
Step1: Loading a stata data file from the UCLA website.This notebook is inspired by https
Step2: This dataset is about the probability for undergraduate students to appl... | Python Code:
import numpy as np
import pandas as pd
import scipy.stats as stats
from statsmodels.miscmodels.ordinal_model import OrderedModel
Explanation: Ordinal Regression
End of explanation
url = "https://stats.idre.ucla.edu/stat/data/ologit.dta"
data_student = pd.read_stata(url)
data_student.head(5)
data_student.dt... |
11,445 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Think Bayes
This notebook presents example code and exercise solutions for Think Bayes.
Copyright 2018 Allen B. Downey
MIT License
Step1: The dinner party
Suppose you are having a dinner pa... | Python Code:
# Configure Jupyter so figures appear in the notebook
%matplotlib inline
# Configure Jupyter to display the assigned value after an assignment
%config InteractiveShell.ast_node_interactivity='last_expr_or_assign'
# import classes from thinkbayes2
from thinkbayes2 import Hist, Pmf, Suite, Beta
import thinkp... |
11,446 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example 1
Step1: This dataset is a debug dump from a Lustre filesystem. Typically these events occur due to code bugs (LBUG), heavy load, hardware problems, or misbehaving user application... | Python Code:
from pyspark import SparkConf, SparkContext
import re
Explanation: Example 1: Parallel Log Parsing with Map and Filter
Step 1: Data ingest and parsing
End of explanation
sc
partitions = 18
parlog = sc.textFile("/lustre/janus_scratch/dami9546/lustre_debug.out", partitions)
Explanation: This dataset is a deb... |
11,447 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Q1. Let's practice the seq2seq framework with a simple example. In this example, we will take the last state of the encoder as the initial state of the decoder. Complete the code.
Step1: Q2... | Python Code:
# Inputs and outputs: ten digits
x = tf.placeholder(tf.int32, shape=(32, 10))
y = tf.placeholder(tf.int32, shape=(32, 10))
# One-hot encoding
enc_inputs = tf.one_hot(x, 10)
dec_inputs = tf.concat((tf.zeros_like(y[:, :1]), y[:, :-1]), -1)
dec_inputs = tf.one_hot(dec_inputs, 10)
# encoder
encoder_cell = tf.c... |
11,448 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interact Exercise 5
Imports
Put the standard imports for Matplotlib, Numpy and the IPython widgets in the following cell.
Step2: Interact with SVG display
SVG is a simple way of drawing vec... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from IPython.html.widgets import interact, interactive, fixed
from IPython.html import widgets
from IPython.display import SVG
Explanation: Interact Exercise 5
Imports
Put the standard imports for Matplotlib, Numpy and the IPython widget... |
11,449 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Eaton & Ree (2013) single-end RAD data set
Here we demonstrate a denovo assembly for an empirical RAD data set using the ipyrad Python API. This example was run on a workstation with 20 core... | Python Code:
## conda install ipyrad -c ipyrad
## conda install toytree -c eaton-lab
## conda install sra-tools -c bioconda
## conda install entrez-direct -c bioconda
## imports
import ipyrad as ip
import ipyrad.analysis as ipa
import ipyparallel as ipp
Explanation: Eaton & Ree (2013) single-end RAD data set
Here we de... |
11,450 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Assigning particles unique IDs and removing particles from the simulation
For some applications, it is useful to keep track of which particle is which, and this can get jumbled up when parti... | Python Code:
import rebound
import numpy as np
def setupSimulation(Nplanets):
sim = rebound.Simulation()
sim.integrator = "ias15" # IAS15 is the default integrator, so we don't need this line
sim.add(m=1.,id=0)
for i in range(1,Nbodies):
sim.add(m=1e-5,x=i,vy=i**(-0.5),id=i)
sim.move_to_com(... |
11,451 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Function ptrans
Synopse
Perform periodic translation in 1-D, 2-D or 3-D space.
g = ptrans(f, t)
OUTPUT
g
Step1: Examples
Step2: Example 1
Numeric examples in 2D and 3D.
Step3: Example 2
I... | Python Code:
def ptrans(f,t):
import numpy as np
g = np.empty_like(f)
if f.ndim == 1:
W = f.shape[0]
col = np.arange(W)
g = f[(col-t)%W]
elif f.ndim == 2:
H,W = f.shape
rr,cc = t
row,col = np.indices(f.shape)
g = f[(row-rr)%H, (col-cc)%W]
elif f.ndim == 3:
... |
11,452 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Morphological Transformations Morphological Transformations are some simple operation based on the image shape. Morphological Transformations are normally performed on binary image... | Python Code::
import cv2
%matplotlib notebook
%matplotlib inline
from matplotlib import pyplot as plt
img = cv2.imread("hsv_ball.jpg",cv2.IMREAD_GRAYSCALE)
_,mask = cv2.threshold(img, 220,255,cv2.THRESH_BINARY_INV)
titles = ['images',"mask"]
images = [img,mask]
for i in range(2):
plt.subplot(1,2,i+1)
plt.imshow... |
11,453 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ported to Python (by Ilan Fridman Rojas) from original R implementation by Rasmus Bååth
Step2: The standard bootstrap method
Step5: The Bayesian bootstrap (with a Dirichlet prior)
(See
Ste... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
plt.style.use('ggplot')
%matplotlib inline
data = pd.read_csv('american_presidents.csv', header=0, index_col=None)
data
data.describe()
data.plot(x='order',y='height_cm', color='blue')
data.plot('order', kind='hist', color='blue')
impor... |
11,454 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Aerosol
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mri', 'sandbox-3', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: MRI
Source ID: SANDBOX-3
Topic: Aerosol
Sub-Topics: Transport, Emissions, ... |
11,455 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example of how to find peaks in a synthetic image
Create a set of 2D Gaussians
Find the center of the Guassian to integer accuracy
Optimize the position using Gaussian fitting for each peak
... | Python Code:
%matplotlib notebook
import numpy as np
import matplotlib.pyplot as plt
# Import these from ncempy.algo
from ncempy.algo import gaussND
from ncempy.algo import peakFind
Explanation: Example of how to find peaks in a synthetic image
Create a set of 2D Gaussians
Find the center of the Guassian to integer acc... |
11,456 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Aerosol
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'snu', 'sandbox-1', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: SNU
Source ID: SANDBOX-1
Topic: Aerosol
Sub-Topics: Transport, Emissions, ... |
11,457 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Steady-state simulation of organic light emitting cell
This is an example of steady-state simulation of the light emitting electrochemical cell.
It attempts to reproduce reference. Exact agr... | Python Code:
from oedes.fvm import mesh1d
from oedes import progressbar, testing, init_notebook, models, context
init_notebook()
%matplotlib inline
import matplotlib.pylab as plt
import numpy as np
Explanation: Steady-state simulation of organic light emitting cell
This is an example of steady-state simulation of the l... |
11,458 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy Exercise 3
Imports
Step2: Geometric Brownian motion
Here is a function that produces standard Brownian motion using NumPy. This is also known as a Wiener Process.
Step3: Call the bro... | Python Code:
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import antipackage
import github.ellisonbg.misc.vizarray as va
Explanation: Numpy Exercise 3
Imports
End of explanation
def brownian(maxt, n):
Return one realization of a Brownian (Wiener) process with n steps a... |
11,459 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Note
Step1: Suppose we want to get from A to B. Where can we go from the start state, A?
Step2: We see that from A we can get to any of the three cities ['Z', 'T', 'S']. Which should we ch... | Python Code:
romania = {
'A': ['Z', 'T', 'S'],
'B': ['F', 'P', 'G', 'U'],
'C': ['D', 'R', 'P'],
'D': ['M', 'C'],
'E': ['H'],
'F': ['S', 'B'],
'G': ['B'],
'H': ['U', 'E'],
'I': ['N', 'V'],
'L': ['T', 'M'],
'M': ['L', 'D'],
'N': ['I'],
'O': ['Z', 'S'],
'P': ['R', 'C', 'B'],
'R': ['S', 'C', 'P'],
'S': ['A'... |
11,460 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center>
<a href="http
Step1: 2.2 Données "Titanic"
Les données sur le naufrage du Titanic sont décrites dans le calepin consacré à la librairie pandas. Reconstruire la table des données en... | Python Code:
# Importations
import matplotlib.pyplot as plt
from sklearn import datasets
%matplotlib inline
# les données
digits = datasets.load_digits()
# Contenu et mode d'obtention
print(digits)
images_and_labels = list(zip(digits.images,
digits.target))
for index, (image, label) in enumerate(images_and_labels... |
11,461 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: 5T_데이터 분석을 위한 SQL 실습 (4) - SQL Advanced
특정 카테고리에 포함된 영화들의 렌탈 횟수
rental, inventory, film, film_category, category
"Comedy", "Sports", "Family" 카테고리에 포함되는 영화들의 렌탈 횟수
Step3: Store 1의 등급... | Python Code:
import pymysql
db = pymysql.connect(
"db.fastcamp.us",
"root",
"dkstncks",
"sakila",
charset='utf8',
)
rental_df = pd.read_sql("SELECT * FROM rental;", db)
inventory_df = pd.read_sql("SELECT * FROM inventory;", db)
film_df = pd.read_sql("SELECT * FROM film;", db)
film_category_df = pd.r... |
11,462 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multi-Class Classifier on Particle Track Data
Step1: Get angle values and cast to boolean
Step2: Create our simple classification target
Step3: Create an image generator from this datafra... | Python Code:
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import os
import sys
import numpy as np
import math
Explanation: Multi-Class Classifier on Particle Track Data
End of explanation
track_params = pd.read_csv('../TRAIN/track_parms.csv')
track_params.tail()
Explanation: Get angle values a... |
11,463 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: Create an Estimator from a Keras model
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Crea... | Python Code:
#@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 agreed to in writing, software
# dist... |
11,464 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
练习 1：仿照求$ \sum_{i=1}^mi + \sum_{i=1}^ni + \sum_{i=1}^ki$的完整代码，写程序，可求m!+n!+k!
Step1: 练习 2：写函数可返回1 - 1/3 + 1/5 - 1/7...的前n项的和。在主程序中，分别令n=1000及100000，打印4倍该函数的和。
Step2: 练习 3：将task3中的练习1及练习4改写... | Python Code:
def compute_multi(end):
i = 0
multi = 1
while i < end:
i = i + 1
multi = multi * i
return multi
n = int(input('请输入第1个整数，以回车结束。'))
m = int(input('请输入第2个整数，以回车结束。'))
k = int(input('请输入第3个整数，以回车结束。'))
print('最终的和是：', compute_multi(m) + compute_multi(n) + compute_multi(k))
Expla... |
11,465 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Keypoint Detection with Transfer Learning
Author
Step1: Data collection
The StanfordExtra dataset contains 12,000 images of dogs together with keypoints and
segmentation maps. It is develop... | Python Code:
!pip install -q -U imgaug
Explanation: Keypoint Detection with Transfer Learning
Author: Sayak Paul<br>
Date created: 2021/05/02<br>
Last modified: 2021/05/02<br>
Description: Training a keypoint detector with data augmentation and transfer learning.
Keypoint detection consists of locating key object parts... |
11,466 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Census Data Correlation
Correlate another table with US Census data. Expands a data set dimensions by finding population segments that correlate with the master table.
License
Copyright 202... | Python Code:
!pip install git+https://github.com/google/starthinker
Explanation: Census Data Correlation
Correlate another table with US Census data. Expands a data set dimensions by finding population segments that correlate with the master table.
License
Copyright 2020 Google LLC,
Licensed under the Apache License, ... |
11,467 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
tsam - 1. Example
Example usage of the time series aggregation module (tsam)
Date
Step1: Input data
Read in time series from testdata.csv with pandas
Step2: Show a slice of the dataset
Ste... | Python Code:
%load_ext autoreload
%autoreload 2
import copy
import os
import pandas as pd
import matplotlib.pyplot as plt
import tsam.timeseriesaggregation as tsam
%matplotlib inline
Explanation: tsam - 1. Example
Example usage of the time series aggregation module (tsam)
Date: 08.05.2017
Author: Leander Kotzur
Import ... |
11,468 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: JFreeChart Versions - Diving into Differences and Similarities
This notebook reports code and results of the analysis conducted on the two versions of the JfreeChart software system i... | Python Code:
# %load preamble_directives.py
Some imports and path settings to make notebook code
running smoothly.
# Author: Valerio Maggio <valeriomaggio@gmail.com>
# Copyright (c) 2015 Valerio Maggio <valeriomaggio@gmail.com>
# License: BSD 3 clause
import sys, os
# Extending PYTHONPATH to allow relative import!
sys.... |
11,469 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
XGBoost-Ray with Dask
This notebook includes an example workflow using
XGBoost-Ray and
Dask for distributed model training,
hyperparameter optimization, and prediction.
Cluster Setup
First, ... | Python Code:
import argparse
import time
import dask
import dask.dataframe as dd
from xgboost_ray import RayDMatrix, RayParams, train, predict
import ray
from ray import tune
from ray.util.dask import ray_dask_get
Explanation: XGBoost-Ray with Dask
This notebook includes an example workflow using
XGBoost-Ray and
Dask f... |
11,470 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Preprocessing
Joeri R. Hermans
Departement of Data Science & Knowledge Engineering
Maastricht University, The Netherlands
In this notebook we mainly... | Python Code:
%matplotlib inline
import numpy as np
import os
from pyspark import SparkContext
from pyspark import SparkConf
from pyspark.storagelevel import StorageLevel
from pyspark.sql import Row
from pyspark.sql.types import *
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
# Use the DataBricks AVRO r... |
11,471 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Excercises Electric Machinery Fundamentals
Chapter 9
Problem 9-1
Step1: Description
A 120-V 1/4-hp 60-Hz four-pole split-phase induction motor has the following impedances
Step2: If the sl... | Python Code:
%pylab notebook
%precision %.4g
Explanation: Excercises Electric Machinery Fundamentals
Chapter 9
Problem 9-1
End of explanation
V = 120 # [V]
p = 4
R1 = 2.0 # [Ohm]
R2 = 2.8 # [Ohm]
X1 = 2.56 # [Ohm]
X2 = 2.56 # [Ohm]
Xm = 60.5 # [Ohm]
s = 0.05
Prot = 51 # [W]
Explanation: Descript... |
11,472 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example Usage for Drop-in List Replacements
Step1: BList
The underlying data structure can be any drop-in replacement for list, in this example blist is used.
Step2: All the standard funct... | Python Code:
# remove comment to use latest development version
import sys; sys.path.insert(0, '../')
# import libraries
import raccoon as rc
Explanation: Example Usage for Drop-in List Replacements
End of explanation
from blist import blist
# Construct with blist
df_blist = rc.DataFrame({'a': [1, 2, 3]}, index=[5, 6, ... |
11,473 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step5: tsfresh returns a great number of features. Depending on the dynamics of the inspected time series, some of them maybe highly correlated.
A common technique to deal with such highly ... | Python Code:
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler
import pandas as pd
class PCAForPandas(PCA):
This class is just a small wrapper around the PCA estimator of sklearn including normalization to make it
compatible with pandas DataFrames.
def __init__(sel... |
11,474 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Posterior Predictive Checks in PyMC3
PPCs are a great way to validate a model. The idea is to generate data sets from the model using parameter settings from draws from the posterior.
PyMC3 ... | Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
import numpy as np
import pymc3 as pm
import seaborn as sns
import matplotlib.pyplot as plt
from collections import defaultdict
Explanation: Posterior Predictive Checks in PyMC3
PPCs are a great way to validate a model. The idea is to generate data sets... |
11,475 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Сценарий
Step1: Группируем по миллисекундам и усредняем
Step2: Интересные нам всплески потребления кончаются где-то на 10000-ной миллисекунде.
Step3: Синхронизируемся по 3-му всплеску, ка... | Python Code:
df = pd.DataFrame(np.fromfile(
"./browser_download_lte_wf.bin",
dtype=np.uint16).astype(np.float32) * (3300 / 2**12))
Explanation: Сценарий:
- заранее выдвигаем шторку с фонариком и запускаем браузер
- включаем мониторинг
- мигаем фонариком пять раз
- задвигаем шторку, ждем чуть больше мину... |
11,476 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
← Back to Index
Exercise
Step1: Load 120 seconds of an audio file
Step2: Plot the time-domain waveform of the audio signal
Step3: Play the audio file
Step4: Step 2
Step5: We transp... | Python Code:
filename_brahms = 'brahms_hungarian_dance_5.mp3'
url = "http://audio.musicinformationretrieval.com/" + filename_brahms
if not os.path.exists(filename_brahms):
urllib.urlretrieve(url, filename=filename_brahms)
Explanation: ← Back to Index
Exercise: Genre Recognition
Goals
Extract features from an a... |
11,477 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Biology with Python
By Fatih Enes Kemal Ergin
In this small tutorial I will talk about biological concepts with theory and implementation in Python
Before we go into the implementatio... | Python Code:
# Here is the genetic code of the amino acids defined as dictionaries
STANDARD_GENETIC_CODE = {'UUU':'Phe', 'UUC':'Phe', 'UCU':'Ser', 'UCC':'Ser',
'UAU':'Tyr', 'UAC':'Tyr', 'UGU':'Cys', 'UGC':'Cys',
'UUA':'Leu', 'UCA':'Ser', 'UAA':None, 'UGA':None,
... |
11,478 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
new_data['residuals1'] = results.resid
Step1: Subseting the data
Three different methods for subsetting the data.
1. Using a systematic selection by index modulus
2. Using a random uniform ... | Python Code:
#new_data = prepareDataFrame("/RawDataCSV/idiv_share/plotsClimateData_11092017.csv")
## En Hec
#new_data = prepareDataFrame("/home/hpc/28/escamill/csv_data/idiv/plotsClimateData_11092017.csv")
## New "official" dataset
new_data = prepareDataFrame("/RawDataCSV/idiv_share/FIA_Plots_Biomass_11092017.csv")
#IN... |
11,479 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Adding a discharge point source to a LEM
(Greg Tucker, CSDMS / CU Boulder, fall 2020)
This notebook shows how to add one or more discharge point sources to a Landlab-built landscape evolutio... | Python Code:
from landlab import RasterModelGrid, imshow_grid
from landlab.components import FlowAccumulator
import numpy as np
Explanation: Adding a discharge point source to a LEM
(Greg Tucker, CSDMS / CU Boulder, fall 2020)
This notebook shows how to add one or more discharge point sources to a Landlab-built landsca... |
11,480 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Toplevel
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specif... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cas', 'sandbox-2', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: CAS
Source ID: SANDBOX-2
Sub-Topics: Radiative Forcings.
Properties: 85... |
11,481 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Programming Assignment
Step1: Составление корпуса
Step2: Наша коллекция небольшая, и целиком помещается в оперативную память. Gensim может работать с такими данными и не требует их сохране... | Python Code:
import json
with open("recipes.json") as f:
recipes = json.load(f)
print(recipes[0])
Explanation: Programming Assignment:
Готовим LDA по рецептам
Как вы уже знаете, в тематическом моделировании делается предположение о том, что для определения тематики порядок слов в документе не важен; об этом гласит ... |
11,482 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href='http
Step1: Crear una serie
Se pueden crear series desde listas, arreglos de numpy y diccionarios
Step2: Usando listas
Step3: Arreglos Numpy
Step4: Diccionarios
Step5: Informac... | Python Code:
# librerias
import numpy as np
import pandas as pd
Explanation: <a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>
Series
El primer tipo de dato que vamos a aprender en pandas es Series
Una series es muy similar a un arreglo de Numpy, la diferencia es que una serie tiene etiqu... |
11,483 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Assembling detector data into images
The X-ray detectors at XFEL are made up of a number of small pieces. To get an image from the data, or analyse it spatially, we need to know where each p... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import h5py
from karabo_data import RunDirectory, stack_detector_data
from karabo_data.geometry2 import LPD_1MGeometry
run = RunDirectory('/gpfs/exfel/exp/FXE/201830/p900020/proc/r0221/')
run.info()
# Find a train with some data in
empty... |
11,484 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Linear regresion - part 2
Many variables
Step1: For many variables we will use vectorized implementation
$$X=\left[\begin{array}{cc}
1 & (\vec x^{(1)})^T \
1 & (\vec x^{(2)})^T \
\vdots & \... | Python Code:
# imports
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import seaborn as sns
from IPython.display import (
display,
Math,
Latex
)
%matplotlib inline
Explanation: Linear regresion - part 2
Many variables
End of explanation
df = ... |
11,485 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The problem with perfect phylogenies
Previously, I wrote a blog post, exploring the Gusfield algorithm for building phylogenetic trees from binary traits. While the algorithm works well if y... | Python Code:
from mgraph import MGraph
Explanation: The problem with perfect phylogenies
Previously, I wrote a blog post, exploring the Gusfield algorithm for building phylogenetic trees from binary traits. While the algorithm works well if you have a clean matrix that just-so happes to form a perfect phylogeny, if you... |
11,486 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this notebook, we mainly utilize extreme gradient boost to improve the prediction model originially proposed in TLE 2016 November machine learning tuotrial. Extreme gradient boost can be ... | Python Code:
%matplotlib inline
import pandas as pd
from pandas.tools.plotting import scatter_matrix
import matplotlib.pyplot as plt
import matplotlib as mpl
import seaborn as sns
import matplotlib.colors as colors
import xgboost as xgb
import numpy as np
from sklearn.metrics import confusion_matrix, f1_score, accuracy... |
11,487 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generate a left cerebellum volume source space
Generate a volume source space of the left cerebellum and plot its vertices
relative to the left cortical surface source space and the freesurf... | Python Code:
# Author: Alan Leggitt <alan.leggitt@ucsf.edu>
#
# License: BSD (3-clause)
import numpy as np
from scipy.spatial import ConvexHull
from mayavi import mlab
from mne import setup_source_space, setup_volume_source_space
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
subjects_dir... |
11,488 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2017 Google LLC.
Step1: Creating and Manipulating Tensors
Learning Objectives
Step2: Vector Addition
You can perform many typical mathematical operations on tensors (TF API). The... | Python Code:
# 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 writing, software
# distribute... |
11,489 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example 3
Step1: Note
Step2: Now, let's start with the ANTs normalization workflow!
Imports (ANTs)
First, we need to import all the modules we later want to use.
Step3: Experiment paramet... | Python Code:
%%bash
datalad get -J 4 -d /data/ds000114 /data/ds000114/derivatives/fmriprep/sub-0[2345789]/anat/*h5
Explanation: Example 3: Normalize data to MNI template
This example covers the normalization of data. Some people prefer to normalize the data during the preprocessing, just before smoothing. I prefer to d... |
11,490 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Outline
Glossary
5. Imaging
Previous
Step1: Import section specific modules
Step2: 5.3 Gridding and Degridding for using the FFT <a id='imaging
Step3: Figure
Step4: Figure
Step5: Figure... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import HTML
from IPython.display import Image, display, clear_output
from ipywidgets import HBox, Label, FloatSlider, Layout
HTML('../style/course.css') #apply general CSS
Explanation: Outline
Glossary
5. Imaging
Pr... |
11,491 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Original Voce-Chaboche Model Fitting Example 1
An example of fitting the original Voce-Chaboche model to a set of test data is provided.
Documentation for all the functions used in this exam... | Python Code:
import RESSPyLab as rpl
import numpy as np
Explanation: Original Voce-Chaboche Model Fitting Example 1
An example of fitting the original Voce-Chaboche model to a set of test data is provided.
Documentation for all the functions used in this example can be found by either looking at docstrings for any of t... |
11,492 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Global Ocean Waves Analysis
As a part of the continuous Marine Data support, this time Planet OS Team releases a Meteo France Global Ocean Waves Analysis and and Meteo France WAve Model (MF... | Python Code:
import os
from dh_py_access import package_api
import dh_py_access.lib.datahub as datahub
import xarray as xr
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
import imageio
import shutil
import datetime
import matplotlib as mpl
mpl.rcParams['font.family'] = 'Aven... |
11,493 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Face verification
Goals
train a network for face similarity using triplet loss
work data augmentation, generators and hard negative mining
Dataset
We will be using Labeled Faces in the Wild ... | Python Code:
import tensorflow as tf
# If you have a GPU, execute the following lines to restrict the amount of VRAM used:
gpus = tf.config.experimental.list_physical_devices('GPU')
if len(gpus) > 1:
print("Using GPU {}".format(gpus[0]))
tf.config.experimental.set_visible_devices(gpus[0], 'GPU')
else:
print... |
11,494 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>2b. Machine Learning using tf.estimator </h1>
In this notebook, we will create a machine learning model using tf.estimator and evaluate its performance. The dataset is rather small (770... | Python Code:
import tensorflow as tf
import pandas as pd
import numpy as np
import shutil
print(tf.__version__)
Explanation: <h1>2b. Machine Learning using tf.estimator </h1>
In this notebook, we will create a machine learning model using tf.estimator and evaluate its performance. The dataset is rather small (7700 sam... |
11,495 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
IPython Widgets
IPython widgets are tools that give us interactivity within our analysis. This is most useful when looking at a complication plot and trying to figure out how it depends on a... | Python Code:
import IPython.html.widgets as widg
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
%matplotlib inline
Explanation: IPython Widgets
IPython widgets are tools that give us interactivity within our analysis. This is most useful when looking at a complication plot and try... |
11,496 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Fibonacci Numbers
The Fibonacci numbers $F_n$ are defined by induction for all $n\in\mathbb{N}$
Step1: It seems that the Fibonacci numbers grow pretty fast. Let us plot these numbers to... | Python Code:
def fibonacci(n):
if n <= 1:
return n
return fibonacci(n-1) + fibonacci(n-2)
[ (n,fibonacci(n)) for n in range(19) ]
Explanation: The Fibonacci Numbers
The Fibonacci numbers $F_n$ are defined by induction for all $n\in\mathbb{N}$:
- $F_0 := 0$,
- $F_1 := 1$,
- $F_{n+2} = F_{n+1} + F_... |
11,497 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The big reset
So I went ahead and cleared the memory.
Step1: The mystery section remains the same.
Step2: All the blocks are empty.
Step3: The 'PresetStyle' settings are empty, too.
Step4... | Python Code:
import sys
sys.path.append('..')
import collections
import mido
from commons import dgxdump
from commons.dumpdata import messages, songdata, regdata, regvalues
old_syx_messages = mido.read_syx_file('../data/syxout5.syx')
clear_syx_messages = mido.read_syx_file('../data/clear_bulk.txt')
o_dump = dgxdump.Dgx... |
11,498 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GEE nested covariance structure simulation study
This notebook is a simulation study that illustrates and evaluates the performance of the GEE nested covariance structure.
A nested covarianc... | Python Code:
import numpy as np
import pandas as pd
import statsmodels.api as sm
Explanation: GEE nested covariance structure simulation study
This notebook is a simulation study that illustrates and evaluates the performance of the GEE nested covariance structure.
A nested covariance structure is based on a nested seq... |
11,499 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fast Sign Adversary Generation Example
This notebook demos find adversary example by using symbolic API and integration with Numpy
Reference
Step1: Build Network
note
Step2: Prepare useful... | Python Code:
%matplotlib inline
import mxnet as mx
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from mxnet.test_utils import get_mnist_iterator
Explanation: Fast Sign Adversary Generation Example
This notebook demos find adversary example by using symbolic API and integration with Numpy... |
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