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12,200 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
File systems proxies
This notebook demonstrates file system proxies to folders and directories, which are basically strings (paths) with additional methods for creation, opening moving, dele... | Python Code:
from spectrocrunch.io import fs,localfs,h5fs,nxfs
Explanation: File systems proxies
This notebook demonstrates file system proxies to folders and directories, which are basically strings (paths) with additional methods for creation, opening moving, deleting, renaming, linking and browsing. Three file syste... |
12,201 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Linear classifier on sensor data with plot patterns and filters
Here decoding, a.k.a MVPA or supervised machine learning, is applied to M/EEG
data in sensor space. Fit a linear classifier wi... | Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Romain Trachel <trachelr@gmail.com>
# Jean-Remi King <jeanremi.king@gmail.com>
#
# License: BSD (3-clause)
import mne
from mne import io, EvokedArray
from mne.datasets import sample
from mne.decoding import Vectorizer, get_coef... |
12,202 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ordinary Differential Equations Exercise 1
Imports
Step2: Euler's method
Euler's method is the simplest numerical approach for solving a first order ODE numerically. Given the differential ... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from scipy.integrate import odeint
from IPython.html.widgets import interact, fixed
Explanation: Ordinary Differential Equations Exercise 1
Imports
End of explanation
def solve_euler(derivs, y0, x):
Solve a 1d O... |
12,203 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Land
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify do... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'messy-consortium', 'emac-2-53-vol', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: MESSY-CONSORTIUM
Source ID: EMAC-2-53-VOL
Topic: Land
Sub-Topic... |
12,204 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Insights from Baby Names Data
Author Information
Step1: II- Predictive Analysis
II-1 Most popular name of all time
Step2: Now, let's find the most popular male and female names of all time... | Python Code:
import os
from mpl_toolkits.basemap import Basemap
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
data_folder = os.path.join('data')
file_names = []
for f in os.listdir(data_folder):
file_names.append(os.path.join(data_folder,f))
del file_names[file_names.index(os.path.join(data_... |
12,205 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ardumoto Example
This example shows how to use the
Ardumoto on the board.
Ardumoto supports two DC motor driving.
There are also instructions
on how to hook up the shield.
Motor A and Moto... | Python Code:
from pynq.overlays.base import BaseOverlay
base = BaseOverlay("base.bit")
Explanation: Ardumoto Example
This example shows how to use the
Ardumoto on the board.
Ardumoto supports two DC motor driving.
There are also instructions
on how to hook up the shield.
Motor A and Motor B are connected as below to ... |
12,206 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian deep-learning
Launch in Google Colab
Bayesian deep-learning network using dropout layers to perform Monte Carlo approximations for quantifying model uncertainty.
Overview
This noteb... | Python Code:
%tensorflow_version 2.x
import os
import numpy as np
import tensorflow as tf
from tqdm import tqdm
from matplotlib import pyplot
%matplotlib inline
print("Tensorflow version " + tf.__version__)
Explanation: Bayesian deep-learning
Launch in Google Colab
Bayesian deep-learning network using dropout layers to... |
12,207 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparison of batchflow performance with tf and torch
Models
Firstly, we comapre torch and tf versions of VGG16. Train them on MNIST.
TensorFlow model
Step1: ... then restart kernel to clea... | Python Code:
%%time
%run ./tf_model.py
Explanation: Comparison of batchflow performance with tf and torch
Models
Firstly, we comapre torch and tf versions of VGG16. Train them on MNIST.
TensorFlow model
End of explanation
%%time
%run ./torch_model.py
Explanation: ... then restart kernel to clear GPU
Torch model
End of ... |
12,208 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using Yellow Brick to Explore and Model the Famous Iris Dataset
Exploration Notebook by
Step1: Terminology
150 observations (n=150)
Step2: Import the Good Stuff
Step3: Feature Exploration... | Python Code:
# read the iris data into a DataFrame
import pandas as pd
url = 'http://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
col_names = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
iris = pd.read_csv(url, header=None, names=col_names)
iris.head()
Explanation: Usin... |
12,209 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Perform a 4-terminal calculation with 2 crossed Carbon chains.
Running a two-terminal calculation with TranSiesta is a breeze compared to running $N>2$-electrode calculations. When performin... | Python Code:
chain = sisl.Geometry([[0,0,0]], atoms=sisl.Atom[6], sc=[1.4, 1.4, 11])
elec_x = chain.tile(4, axis=0).add_vacuum(11 - 1.4, 1)
elec_x.write('ELEC_X.fdf')
elec_y = chain.tile(4, axis=1).add_vacuum(11 - 1.4, 0)
elec_y.write('ELEC_Y.fdf')
chain_x = elec_x.tile(4, axis=0)
chain_y = elec_y.tile(4, axis=1)
chain... |
12,210 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Gradient Checking
Welcome to the final assignment for this week! In this assignment you will learn to implement and use gradient checking.
You are part of a team working to make mobile paym... | Python Code:
# Packages
import numpy as np
from testCases import *
from gc_utils import sigmoid, relu, dictionary_to_vector, vector_to_dictionary, gradients_to_vector
Explanation: Gradient Checking
Welcome to the final assignment for this week! In this assignment you will learn to implement and use gradient checking.
... |
12,211 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
El vecindario racista
Step1: Supongamos que tenemos un vecindario. Este vecindario es una matriz o casillero, en el que cada vecino puede ocupar una casilla.
Step2: Aquí podemos ver un peq... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import vecindario as vc
Explanation: El vecindario racista: el modelo de segregación de Schelling
La segregación racial es un problema en muchas partes del mundo desde hace mucho tiempo. A pesar de que ciertos colectivos han realizado un... |
12,212 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute seed based time-frequency connectivity in sensor space
Computes the connectivity between a seed-gradiometer close to the visual cortex
and all other gradiometers. The connectivity is... | Python Code:
# Author: Martin Luessi <mluessi@nmr.mgh.harvard.edu>
#
# License: BSD (3-clause)
import numpy as np
import mne
from mne import io
from mne.connectivity import spectral_connectivity, seed_target_indices
from mne.datasets import sample
from mne.time_frequency import AverageTFR
print(__doc__)
Explanation: Co... |
12,213 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Neural Network
Learning Objectives
Step1: Next, we'll load our data set.
Step2: Examine the data
It's a good idea to get to know your data a little bit before you work with it.
We'll print... | Python Code:
import math
import shutil
import numpy as np
import pandas as pd
import tensorflow as tf
tf.logging.set_verbosity(tf.logging.INFO)
pd.options.display.max_rows = 10
pd.options.display.float_format = '{:.1f}'.format
Explanation: Neural Network
Learning Objectives:
* Use the DNNRegressor class in TensorFlow... |
12,214 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
What is NetCDF?
<img src='http
Step1: mode='r' is the default.
mode='a' opens an existing file and allows for appending (does not clobber existing data)
format can be one of
NETCDF3_CLASSIC... | Python Code:
import os
path_to_file = os.path.join(os.pardir, 'data', 'new.nc')
Explanation: What is NetCDF?
<img src='http://www.unidata.ucar.edu/images/logos/netcdf-50x50.png'>
NetCDF (network Common Data Form) is a set of interfaces for array-oriented data access and a freely distributed collection of data access li... |
12,215 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SciPy
Što je SciPy?
SciPy je nadgradnja NumPy paketa, i sadrži veliki broj numeričkih algoritama za cijeli niz područja. Ovdje su pobrojana neka nama zanimljivija
Step1: Narvno, možemo učit... | Python Code:
from scipy import *
Explanation: SciPy
Što je SciPy?
SciPy je nadgradnja NumPy paketa, i sadrži veliki broj numeričkih algoritama za cijeli niz područja. Ovdje su pobrojana neka nama zanimljivija:
Specijalne funkcije (scipy.special)
Integracija (scipy.integrate)
Optimizacija (scipy.optimize)
Interpolacija ... |
12,216 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DAT210x - Programming with Python for DS
Module5- Lab7
Step1: A Convenience Function
This method is for your visualization convenience only. You aren't expected to know how to put this toge... | Python Code:
import random, math
import pandas as pd
import numpy as np
import scipy.io
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot') # Look Pretty
# Leave this alone until indicated:
Test_PCA = False
Explanation: DAT210x - Programming with Python for DS
Module5-... |
12,217 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sveučilište u Zagrebu
Fakultet elektrotehnike i računarstva
Strojno učenje 2018/2019
http
Step1: Zadatci
1. Jednostavna regresija
Zadan je skup primjera $\mathcal{D}={(x^{(i)},y^{(i)})}_{... | Python Code:
# Učitaj osnovne biblioteke...
import numpy as np
import sklearn
import matplotlib.pyplot as plt
import scipy as sp
%pylab inline
Explanation: Sveučilište u Zagrebu
Fakultet elektrotehnike i računarstva
Strojno učenje 2018/2019
http://www.fer.unizg.hr/predmet/su
Laboratorijska vježba 1: Regresija
Verzija... |
12,218 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dataset handling
Scikit-multilearn provides methods to load, save and manipulate multi-label data sets in two formats
Step1: Loading scikit-multilearn data format is easier as it stores mor... | Python Code:
from skmultilearn.dataset import load_dataset_dump, save_dataset_dump
Explanation: Dataset handling
Scikit-multilearn provides methods to load, save and manipulate multi-label data sets in two formats:
a scikit-multilearn pickle of data set in scipy sparse format
the traditional ARFF file format
The functi... |
12,219 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LCS Demo 1
LCS Workshop- Educational LCS - eLCS
Outcome
Step1: Display final population
Step2: Visualise classifiers | Python Code:
import numpy as np
import matplotlib.pyplot as plt
headerList = np.array([])
dataList = []
arraylist = np.array([])
# Open the file for reading.
with open('ExampleRun_eLCS_10000_RulePop.txt', 'r') as infile:
headerList = infile.readline().rstrip('\n').split('\t') #strip off first row
for line in ... |
12,220 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Analysis on "Jallikattu" with Twitter Data Feed <h3 style="color
Step1: We will create a Twitter API handle for fetching data
Inorder to qualify for a Twitter API handle you need ... | Python Code:
# import tweepy for twitter datastream and textblob for processing tweets
import tweepy
import textblob
# wordcloud package is used to produce the cool masked tag cloud above
from wordcloud import WordCloud
# pickle to serialize/deserialize python objects
import pickle
# regex package to extract hasttags f... |
12,221 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
A mass on a spring experiences a force described by Hookes law.
For a displacment $x$, the force is
$$F=-kx,$$
where $k$ is the spring constant with units of N/m.
The equation o... | Python Code:
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.html import widgets
def make_plot(t):
fig, ax = plt.subplots()
x,y = 0,0
plt.plot(x, y, 'k.')
plt.plot(x + 0.3 * t, y, 'bo')
plt.xlim(-1,1)
plt.ylim(-1,1)
widgets.interact(make_plot, t=(-1,1,0.1))
Explanation: Introduct... |
12,222 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Modeling and Simulation in Python
Experiments with different ODE solvers
Copyright 2019 Allen Downey
License
Step1: Glucose minimal model
Read the data.
Step2: Interpolate the insulin data... | 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 functions from the modsim.py module
from modsim import *
init = State(y = 2)
system =... |
12,223 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CrowdTruth vs. MACE vs. Majority Vote for Recognizing Textual Entailment Annotation
This notebook contains a comparative analysis on the task of recognizing textual entailment between three ... | Python Code:
#Read the input file into a pandas DataFrame
import pandas as pd
test_data = pd.read_csv("../data/rte.standardized.csv")
test_data.head()
Explanation: CrowdTruth vs. MACE vs. Majority Vote for Recognizing Textual Entailment Annotation
This notebook contains a comparative analysis on the task of recognizing... |
12,224 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep dive into the Qumulo API python bindings
<span style="background-color
Step1: Inspect all of the Qumulo python bindings and show methods
Step2: Create a new python REST client instanc... | Python Code:
!pip show qumulo_api
import qumulo
import os
import io
import glob
import re
import time
from datetime import datetime
import dateutil.parser as date_parser
from qumulo.rest_client import RestClient
%%javascript
// this will prevent the large output window below from being boxed in.
IPython.OutputArea.auto... |
12,225 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Andrews Curves
D. F. Andrews introduced 'Andrews Curves' in his 1972 paper for plotthing high dimensional data in two dimeion. The underlying principle is simple
Step2: Andrews Curve... | Python Code:
def andrews_curves(data, granularity=1000):
Parameters
-----------
data : array like
ith row is the ith observation
jth column is the jth feature
Size (m, n) => m replicats with n features
granularity : int
linspace granularity for the... |
12,226 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<header class="w3-container w3-teal">
<img src="images/utfsm.png" alt="" height="100px" align="left"/>
<img src="images/mat.png" alt="" height="100px" align="right"/>
</header>
<br/><br/><br... | Python Code:
%%bash
head data/x01.txt -n 60
import numpy as np
from matplotlib import pyplot as plt
# Plot of data
data = np.loadtxt("data/x01.txt", skiprows=33)
x = data[:,1]
y = data[:,2]
plt.figure(figsize=(16,8))
plt.plot(x, y, 'rs')
plt.xlabel("brain weight")
plt.ylabel("body weight")
plt.show()
import numpy as np... |
12,227 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Network Analysis with Python</h1>
<li>Networks are connected bi-directional graphs
<li>Nodes mark the entities in a network
<li>Edges mark the relationships in a network
<h2>Examples of ... | Python Code:
import networkx as nx
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
simple_network = nx.Graph()
nodes = [1,2,3,4,5,6,7,8]
edges = [(1,2),(2,3),(1,3),(4,5),(2,7),(1,9),(3,4),(4,5),(4,9),(5,6),(7,8),(8,9)]
simple_network.add_nodes_from(nodes)
simple_network.add_edges_from(edges)
nx.dr... |
12,228 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mean reversion
By Evgenia "Jenny" Nitishinskaya and Delaney Granizo-Mackenzie
Notebook released under the Creative Commons Attribution 4.0 License.
Mean-reversion strategies are those relyin... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Load the pricing data for a stock
start = '2012-01-01'
end = '2015-01-01'
pricing = get_pricing('MCD', fields='price', start_date=start, end_date=end)
# Compute the cumulative moving average of the price
mu = [pricing[:i].mean() for i... |
12,229 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Landice
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', 'hammoz-consortium', 'sandbox-1', 'landice')
Explanation: ES-DOC CMIP6 Model Properties - Landice
MIP Era: CMIP6
Institute: HAMMOZ-CONSORTIUM
Source ID: SANDBOX-1
Topic: Landice
Sub-To... |
12,230 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Input and output
Currently, the only supported approach for loading and saving ensembles in medusa is via pickle. pickle is the Python module that serializes and de-serializes Python objects... | Python Code:
import medusa
from pickle import load
with open("../medusa/test/data/Staphylococcus_aureus_ensemble.pickle", 'rb') as infile:
ensemble = load(infile)
Explanation: Input and output
Currently, the only supported approach for loading and saving ensembles in medusa is via pickle. pickle is the Python modul... |
12,231 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting a config parser
The pypmj-module uses a configuration file in which all information about the JCMsuite-installation, data storage, servers and so on are set. This makes pypmj very fl... | Python Code:
import config_tools as ct
Explanation: Getting a config parser
The pypmj-module uses a configuration file in which all information about the JCMsuite-installation, data storage, servers and so on are set. This makes pypmj very flexible, as you can generate as many configuration files as you like. Here, we ... |
12,232 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example
Step1: First start by seeing that there does exist a SparkContext object in the sc variable
Step2: Now let's load an RDD with some interesting data. We have the GDELT event data se... | Python Code:
import findspark
import os
findspark.init('/home/ubuntu/shortcourse/spark-1.5.1-bin-hadoop2.6')
from pyspark import SparkContext, SparkConf
conf = SparkConf().setAppName("pyspark-example").setMaster("local[2]")
sc = SparkContext(conf=conf)
Explanation: Example: Use pyspark to process GDELT event data
GDELT... |
12,233 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
There is a lot of room for feature engineering the 8 qualitative features, but we'll reserve it for later
Step1: From now we try a range of estimators and use GridSearch to iteratively tune... | Python Code:
#Drop quantitative features for which most samples take 0 or 1
for cols in quan:
if train_c[cols].mean() < 0.01 or train_c[cols].mean() > 0.99:
train_c.drop(cols, inplace=True, axis=1)
test_c.drop(cols, inplace=True, axis=1)
#For now we only use the quantitative features left to make pr... |
12,234 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simple Dendritic Gated Networks in numpy
This colab implements a Dendritic Gated Network (DGN) solving a regression (using quadratic loss) or a binary classification problem (using Bernoulli... | Python Code:
# Copyright 2021 DeepMind Technologies Limited. All rights reserved.
#
#
# 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 ... |
12,235 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
EfficientNetV2 Tutorial
Step1: 0.2 View graph in TensorBoard
Step2: 1. inference
Step3: 2. Finetune EfficientNetV2 on CIFAR10. | Python Code:
%%capture
#@title
!pip install tensorflow_addons
import os
import sys
import tensorflow.compat.v1 as tf
# Download source code.
if "efficientnetv2" not in os.getcwd():
!git clone --depth 1 https://github.com/google/automl
os.chdir('automl/efficientnetv2')
sys.path.append('.')
else:
!git pull
def do... |
12,236 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<div align="right">Python [conda env
Step1: <a id="globals" name="globals"></a>
Using globals() and .items() to get Names
Step2: <a id="__name__" name="__name__"></a>
name of Methods
Step3... | Python Code:
from dill.source import getname # run this cell first before any cells below
peg1 = [1,2]
peg2 = [3]
peg3 = [5,4]
# this example shows what at first would appear to be unexpected behavior
# it illustrates some concepts though later cells of this notebook show how to effectively use dill.getname
def move... |
12,237 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
IRIS Dataset
Processes selected samples from the iris dataset to fit the specifications of the sliding windows used in images from the FLIR thermal camera.
Step1: A reference image we gathe... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import os
from skimage import data
from skimage import io
from skimage.transform import resize
from skimage.color import rgb2gray
from scipy.misc import bytescale
%matplotlib inline
WINDOW_WIDTH = 18
WINDOW_HEIGHT = 26
sample_iris_frame = data.imread('exte... |
12,238 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1A.1 - Intégrale et la méthode des rectangles - correction
Approximation du calcul d'une intégrale par la méthode des rectangles.
Step1: Calcul de l'intégrale
Step2: Il faut écrire la fonc... | Python Code:
%matplotlib inline
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 1A.1 - Intégrale et la méthode des rectangles - correction
Approximation du calcul d'une intégrale par la méthode des rectangles.
End of explanation
a = -2
b = 3
n = 20
import math
f = lambda x: x * math.cos (x)... |
12,239 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Parameter space coverage 3D graphs
See the parameter-space-coverage notebook for more information.
Step1: Set the sample size
Step2: Uniform
Step3: Stepped
Set the step size. I'm using a ... | Python Code:
import random
import numpy as np
import plotly.plotly as py
import plotly.graph_objs as go
import plotly.offline as offline
offline.init_notebook_mode(connected=True)
Explanation: Parameter space coverage 3D graphs
See the parameter-space-coverage notebook for more information.
End of explanation
sample_si... |
12,240 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A jupyter notebook is a browser-based environment that integrates
Step1: Create a variable
Step2: Print out the value of the variable
Step3: or even easier
Step4: Datatypes
In computer p... | Python Code:
print("Hello World!")
# lines that begin with a # are treated as comment lines and not executed
# print("This line is not printed")
print("This line is printed")
Explanation: A jupyter notebook is a browser-based environment that integrates:
A Kernel (python)
Text
Executable code
Plots and images
Rendered ... |
12,241 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
build your model
| Python Code::
from tensorflow.keras import Sequential
from tensorflow.keras.layers import Dense, Input, Flatten
model = Sequential([
Input(shape=(28,28,1,)),
Flatten(),
Dense(units=84, activation="relu"),
Dense(units=10, activation="softmax"),
])
print (model.summary())
|
12,242 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hands-on LH1
Step1: Scattering parameters measurement
The following figure illustrates the measurement setup, and the adopted port indexing convention.
<img src="./LH1_Mode-Converter_data/... | Python Code:
# This line configures matplotlib to show figures embedded in the notebook,
# and also import the numpy library
%pylab
%matplotlib inline
Explanation: Hands-on LH1: the $\mathrm{TE}{10}$-$\mathrm{TE}{30}$ Mode Converter
Introduction
The Tore Supra Lower Hybrid Launchers are equiped by $\mathrm{TE}{10}$... |
12,243 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Spring 2017 Data Bootcamp Final Project by Colleen Jin dj928, Yingying Chen yc1875
Analysis On Relation Between News Sentiment And Market Portfolio
In this project, we use two sets of data t... | Python Code:
%matplotlib inline
# import necessary packages
import pandas as pd
import matplotlib.pyplot as plt
from pandas_datareader import data
from datetime import datetime
import numpy as np
from textblob import TextBlob
import csv
from wordcloud import WordCloud,Im... |
12,244 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simulation Progress
Christian Kongsgaard
RIBuild Meeting 19-09-2019
Simulated Projects
Step1: Simulation Time Stats
Step2: Compute Resources
500 - 1000 cores available
250 - 500 Delphin Jo... | Python Code:
current_projects = get_simulated_projects_count()
print(f'There are currently {current_projects} simulated Delphin projects in the database')
Explanation: Simulation Progress
Christian Kongsgaard
RIBuild Meeting 19-09-2019
Simulated Projects
End of explanation
times = get_simulation_time()
for key in times... |
12,245 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mass Maps From Mass-Luminosity Inference Posterior
In this notebook we start to explore the potential of using a mass-luminosity relation posterior to refine mass maps.
Content
Step2: Prob... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from matplotlib import rc
rc('text', usetex=True)
from bigmali.grid import Grid
from bigmali.prior import TinkerPrior
from bigmali.hyperparameter import get
import numpy as np
from scipy.stats import lognorm
from numpy.random import normal
#globals that fu... |
12,246 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Float $Y_i$ & Float $\alpha_{MLT}$
First, we load the appropriate libraries and data file. MCMC trials where all quantities are permitted to float happened during Run 05. Note that the metal... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
data = np.genfromtxt('data/run05_kde_props_tmp3.txt')
data = np.array([x for x in data if x[30] > -0.5]) # remove stars that our outside of the model grid
Explanation: Float $Y_i$ & Float $\alpha_{MLT}$
First, we load the appropriate lib... |
12,247 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Disaggregation and Metrics
Step1: Dividing data into train and test set
Step2: Let us use building 1 for demo purposes
Step3: Let's split data at April 30th
Step4: REDD data set has got ... | Python Code:
from __future__ import print_function, division
import time
from matplotlib import rcParams
import matplotlib.pyplot as plt
%matplotlib inline
rcParams['figure.figsize'] = (13, 6)
plt.style.use('ggplot')
from nilmtk import DataSet, TimeFrame, MeterGroup, HDFDataStore
from nilmtk.disaggregate import Combina... |
12,248 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Support Vector Machines
Step1: Kernel SVMs
Predictions in a kernel-SVM are made using the formular
$$
\hat{y} = \alpha_0 + \alpha_1 y_1 k(\mathbf{x^{(1)}}, \mathbf{x}) + ... + \alpha_n y_n ... | Python Code:
from sklearn.datasets import load_digits
from sklearn.cross_validation import train_test_split
digits = load_digits()
X_train, X_test, y_train, y_test = train_test_split(digits.data / 16., digits.target % 2, random_state=2)
from sklearn.svm import LinearSVC, SVC
linear_svc = LinearSVC(loss="hinge").fit(X_t... |
12,249 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The Google Research Authors.
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 ... | Python Code:
# Uses pip3 to install necessary package (lightgbm)
!pip3 install lightgbm
# Resets the IPython kernel to import the installed package.
import IPython
app = IPython.Application.instance()
app.kernel.do_shutdown(True)
import os
from git import Repo
# Current working directory
repo_dir = os.getcwd() + '/re... |
12,250 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analyzing patient data
Words are useful, but what’s more useful are the sentences and stories we build with them.
A lot of powerful tools are built into languages like Python, even more live... | Python Code:
import numpy
Explanation: Analyzing patient data
Words are useful, but what’s more useful are the sentences and stories we build with them.
A lot of powerful tools are built into languages like Python, even more live in the libraries they are used to build
We need to import a library called NumPy
Use this ... |
12,251 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Grid algorithm for a beta-binomial hierarchical model
Bayesian Inference with PyMC
Copyright 2021 Allen B. Downey
License
Step2: Heart Attack Data
This example is based on Chapter 10... | Python Code:
# If we're running on Colab, install libraries
import sys
IN_COLAB = 'google.colab' in sys.modules
if IN_COLAB:
!pip install pymc3
!pip install arviz
!pip install empiricaldist
# PyMC generates a FutureWarning we don't need to deal with yet
import warnings
warnings.filterwarnings("ignore", cate... |
12,252 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python Coffee, November 5, 2015
Import required libraries
Step1: The previous import code requires that you have pandas, numpy and matplotlib installed. If you are using conda
you already h... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline
Explanation: Python Coffee, November 5, 2015
Import required libraries
End of explanation
import plotly.tools as tls
import plotly.plotly as py
import cufflinks as cf
import plo... |
12,253 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise Introduction
We will return to the automatic rotation problem you worked on in the previous exercise. But we'll add data augmentation to improve your model.
The model specification ... | Python Code:
from tensorflow.keras.applications import ResNet50
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Flatten, GlobalAveragePooling2D
num_classes = 2
resnet_weights_path = '../input/resnet50/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5'
my_new_model = Sequenti... |
12,254 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Convolutional Autoencoder on MNIST dataset
Learning Objective
1. Build an autoencoder architecture (consisting of an encoder and decoder) in Keras
2. Define the loss using the reconstructive... | Python Code:
import glob
import os
import time
import imageio
import matplotlib.pyplot as plt
import numpy as np
import PIL
import tensorflow as tf
from IPython import display
from tensorflow.keras import layers
Explanation: Convolutional Autoencoder on MNIST dataset
Learning Objective
1. Build an autoencoder architect... |
12,255 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1A.algo - Programmation dynamique et plus court chemin
La programmation dynamique est une façon des calculs qui revient dans beaucoup d'algorithmes. Elle s'applique dès que ceux-ci peuvent s... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 1A.algo - Programmation dynamique et plus court chemin
La programmation dynamique est une façon des calculs qui revient dans beaucoup d'algorithmes. Elle s'applique dès que ceux-ci peuvent s'écrire de façon récurrente.
End of expl... |
12,256 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
What is NLP?
Natural Language Processing (NLP) is often taught at the academic level from the perspective of computational linguists. However, as data scientists, we have a richer view of th... | Python Code:
# Take a moment to explore what is in this directory
dir(nltk)
Explanation: What is NLP?
Natural Language Processing (NLP) is often taught at the academic level from the perspective of computational linguists. However, as data scientists, we have a richer view of the natural language world - unstructured d... |
12,257 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
RNNs tutorial
Step1: An LSTM/RNN overview
Step2: Note that when we create the builder, it adds the internal RNN parameters to the model.
We do not need to care about them, but they will be... | Python Code:
# we assume that we have the dynet module in your path.
# OUTDATED: we also assume that LD_LIBRARY_PATH includes a pointer to where libcnn_shared.so is.
from dynet import *
Explanation: RNNs tutorial
End of explanation
model = Model()
NUM_LAYERS=2
INPUT_DIM=50
HIDDEN_DIM=10
builder = LSTMBuilder(NUM_LAYERS... |
12,258 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1 Simple Octave/MATLAB Function
As a quick warm up, create a function to return a 5x5 identity matrix.
Step1: 2 Linear Regression with One Variable
In this part of this exercise, you will i... | Python Code:
A = np.eye(5)
print(A)
Explanation: 1 Simple Octave/MATLAB Function
As a quick warm up, create a function to return a 5x5 identity matrix.
End of explanation
datafile = 'ex1\\ex1data1.txt'
df = pd.read_csv(datafile, header=None, names=['Population', 'Profit'])
def plot_data(x, y):
plt.figure(figsize=(1... |
12,259 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<header class="w3-container w3-teal">
<img src="images/utfsm.png" alt="" height="100px" align="left"/>
<img src="images/mat.png" alt="" height="100px" align="right"/>
</header>
<br/><br/><br... | Python Code:
#Configuracion para recargar módulos y librerías cada vez
%reload_ext autoreload
%autoreload 2
... |
12,260 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Verification of the FUSED-Wind wrapper
common inputs
Step2: FUSED-Wind implementation
Step3: pure python implementation
Step4: Asserting new implementation
Step5: There was a bug correct... | Python Code:
wf.WindFarm?
v80 = wt.WindTurbine('Vestas v80 2MW offshore','V80_2MW_offshore.dat',70,40)
HR1 = wf.WindFarm(name='Horns Rev 1',yml='hornsrev.yml')#,v80)
WD = range(0,360,1)
Explanation: Verification of the FUSED-Wind wrapper
common inputs
End of explanation
##Fused inputs
inputs = dict(
wind_speed=8.0,... |
12,261 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Contents
This notebook covers the basics of creating TransferFunction object, obtaining time and energy resolved responses, plotting them and using IO methods available. Finally, artificial ... | Python Code:
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline
Explanation: Contents
This notebook covers the basics of creating TransferFunction object, obtaining time and energy resolved responses, plotting them and using IO methods available. Finally, artificial responses are introduced whic... |
12,262 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic usage of Sklearn
Step1: Text processing with Scikit learn
We can use CountVectorizer to extract a bag of words representation from a collection of documents, using the SciKit-Learn me... | Python Code:
import sklearn
import numpy as np
import matplotlib.pyplot as plt
data = np.array([[1,2], [2,3], [3,4], [4,5], [5,6]])
x = data[:,0]
y = data[:,1]
data, x, y
Explanation: Basic usage of Sklearn
End of explanation
from sklearn.feature_extraction.text import CountVectorizer
vectorizer = CountVectorizer(min_d... |
12,263 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Config files with specifications
Epoch files
Epoch files are config files which specify a set of options repeatedly on different date/times, represented by sections of the config file. When ... | Python Code:
%cat epochs_spec.cfg
%cat epochs.cfg
Explanation: Config files with specifications
Epoch files
Epoch files are config files which specify a set of options repeatedly on different date/times, represented by sections of the config file. When a value for an option for a given date is requested, the value in t... |
12,264 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Lists have a very simple method to insert elements: | Problem:
import numpy as np
a = np.array([[1,2],[3,4]])
pos = [1, 2]
element = np.array([[3, 5], [6, 6]])
pos = np.array(pos) - np.arange(len(element))
a = np.insert(a, pos, element, axis=0) |
12,265 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Peak Magnetic Field Strength
Magnetic models of young stars have their peak magnetic field strength prescribed where $R = 0.5 R_{\star}$. This works well and permits models of young stars wi... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
radial_points = np.arange(0.01, 1.0, 0.01) # units of Rstar
bfield_scaling = radial_points**(-3.0) # see equation (1)
bfield_surface = np.arange(0.5, 4.1, 0.5) # units of kiloGauss
Explanation: Peak Magnetic Field Strength
Mag... |
12,266 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Download the list of occultation periods from the MOC at Berkeley.
Note that the occultation periods typically only are stored at Berkeley for the future and not for the past. So this is onl... | Python Code:
fname = io.download_occultation_times(outdir='../data/')
print(fname)
Explanation: Download the list of occultation periods from the MOC at Berkeley.
Note that the occultation periods typically only are stored at Berkeley for the future and not for the past. So this is only really useful for observation pl... |
12,267 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Image Mark
Image is a Mark object, used to visualize images in standard format (png, jpg etc...), in a bqplot Figure
It takes as input an ipywidgets Image widget
The ipywidgets Image
Ste... | Python Code:
import os
import ipywidgets as widgets
import bqplot.pyplot as plt
from bqplot import LinearScale
image_path = os.path.abspath('../../data_files/trees.jpg')
with open(image_path, 'rb') as f:
raw_image = f.read()
ipyimage = widgets.Image(value=raw_image, format='jpg')
ipyimage
Explanation: The Image Mar... |
12,268 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualize channel over epochs as images in sensor topography
This will produce what is sometimes called event related
potential / field (ERP/ERF) images.
One sensor topography plot is produc... | Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import matplotlib.pyplot as plt
import mne
from mne import io
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
Explanation: V... |
12,269 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Python 2
Command-Line Programs
<section class="objectives panel panel-warning">
<div class="panel-heading">
<h2 id="learning-objectives"><span class="fa fa-certificate"></spa... | Python Code:
import sys
import numpy
def main():
script = sys.argv[0]
filename = sys.argv[1]
data = numpy.loadtxt(filename, delimiter=',')
for m in data.mean(axis=1):
print(m)
Explanation: Introduction to Python 2
Command-Line Programs
<section class="objectives panel panel-warning">
<div class=... |
12,270 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Image features exercise
Complete and hand in this completed worksheet (including its outputs and any supporting code outside of the worksheet) with your assignment submission. For more detai... | Python Code:
import random
import numpy as np
from cs231n.data_utils import load_CIFAR10
import matplotlib.pyplot as plt
from __future__ import print_function
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams['image.c... |
12,271 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
.. _tut_intro_pyton
Step1: If you come from a background of matlab, remember that indexing in python
starts from zero | Python Code:
a = 3
print(type(a))
b = [1, 2.5, 'This is a string']
print(type(b))
c = 'Hello world!'
print(type(c))
Explanation: .. _tut_intro_pyton:
Introduction to Python
Python is a modern, general-purpose, object-oriented, high-level programming
language. First make sure you have a working python environment and
de... |
12,272 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Two particle equilibrium
If you haven't read the One particle equilibrium notebook yet, go and read it now.
In the previous notebook we showed that we can use Magpy to compute the correct th... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
from tqdm import tqdm_notebook
#import tqdm
import magpy as mp
%matplotlib inline
Explanation: Two particle equilibrium
If you haven't read the One particle equilibrium notebook yet, go and read it now.
In the previo... |
12,273 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data in Quilt is organized in terms of data packages. A data package is a logical group of files, directories, and metadata.
Initializing a package
To edit a new empty package, use the packa... | Python Code:
import quilt3
p = quilt3.Package()
Explanation: Data in Quilt is organized in terms of data packages. A data package is a logical group of files, directories, and metadata.
Initializing a package
To edit a new empty package, use the package constructor:
End of explanation
quilt3.Package.install(
"examp... |
12,274 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
RNNs tutorial
Step1: An LSTM/RNN overview
Step2: Note that when we create the builder, it adds the internal RNN parameters to the ParameterCollection.
We do not need to care about them, bu... | Python Code:
# we assume that we have the dynet module in your path.
# OUTDATED: we also assume that LD_LIBRARY_PATH includes a pointer to where libcnn_shared.so is.
import dynet as dy
Explanation: RNNs tutorial
End of explanation
pc = dy.ParameterCollection()
NUM_LAYERS=2
INPUT_DIM=50
HIDDEN_DIM=10
builder = dy.LSTMBu... |
12,275 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian Imputation
Real-world datasets often contain many missing values. In those situations, we have to either remove those missing data (also known as "complete case") or replace them by... | Python Code:
!pip install -q numpyro@git+https://github.com/pyro-ppl/numpyro
# first, we need some imports
import os
from IPython.display import set_matplotlib_formats
from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
from jax import numpy as jnp
from jax import random
from jax.scipy.special i... |
12,276 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Landice
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', 'nerc', 'sandbox-2', 'landice')
Explanation: ES-DOC CMIP6 Model Properties - Landice
MIP Era: CMIP6
Institute: NERC
Source ID: SANDBOX-2
Topic: Landice
Sub-Topics: Glaciers, Ice.
Prop... |
12,277 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<span style="color
Step1: <span style="color
Step2: <span style="color
Step3: <span style="color
Step4: <span style="color
Step5: <span style="color | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
pd.set_option('max_columns', 50)
mpl.rcParams['lines.linewidth'] = 2
%matplotlib inline
Explanation: <span style="color:black; font-family:Helvetica; font-size:2.5em;">Practical Code to Calculating Customer Life... |
12,278 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic Input and Output
Basic Output - print()
In Python, we talk about the terminal - by this we really just mean the screen, or maybe a window on the screen.
Python 3 can output to the term... | Python Code:
print(42)
print('Boris')
pint[47
print'Jane
Explanation: Basic Input and Output
Basic Output - print()
In Python, we talk about the terminal - by this we really just mean the screen, or maybe a window on the screen.
Python 3 can output to the terminal using the print() function. In the very early days of c... |
12,279 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CrowdTruth for Sparse Multiple Choice Tasks
Step1: Declaring a pre-processing configuration
The pre-processing configuration defines how to interpret the raw crowdsourcing input. To do this... | Python Code:
import pandas as pd
test_data = pd.read_csv("../data/event-text-sparse-multiple-choice.csv")
test_data.head()
Explanation: CrowdTruth for Sparse Multiple Choice Tasks: Event Extraction
In this tutorial, we will apply CrowdTruth metrics to a sparse multiple choice crowdsourcing task for Event Extraction fro... |
12,280 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<small><i>This notebook was prepared by Donne Martin. Source and license info is on GitHub.</i></small>
Challenge Notebook
Problem
Step1: Unit Test
The following unit test is expected to fa... | Python Code:
def list_of_chars(list_chars):
# TODO: Implement me
if li
return list_chars[::-1]
Explanation: <small><i>This notebook was prepared by Donne Martin. Source and license info is on GitHub.</i></small>
Challenge Notebook
Problem: Implement a function to reverse a string (a list of characters)... |
12,281 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Intro to deep learning in Chainer
Welcome - this interactive tutorial will introduce you to deep learning in Chainer, to prepare for the DIY practical tutorial.
0. iPython
First off, you nee... | Python Code:
a = 100
print("a is", a)
a + 200
Explanation: Intro to deep learning in Chainer
Welcome - this interactive tutorial will introduce you to deep learning in Chainer, to prepare for the DIY practical tutorial.
0. iPython
First off, you need to know how to run code & see the results. When you see Exercise, it ... |
12,282 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hypocycloid definition and animation
Deriving the parametric equations of a hypocycloid
On May 11 @fermatslibrary posted a gif file, https
Step1: We refer to the figure in the above cell to... | Python Code:
from IPython.display import Image
Image(filename='generate-hypocycloid.png')
Explanation: Hypocycloid definition and animation
Deriving the parametric equations of a hypocycloid
On May 11 @fermatslibrary posted a gif file, https://twitter.com/fermatslibrary/status/862659602776805379, illustrating the motio... |
12,283 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Rock Paper Scissors with Python
Here's a couple of versions. The first is the most verbose, most explicit version. It plays best two of three.
Step1: This version removes the explicit ties ... | Python Code:
import random
choices = ["Rock", "Paper", "Scissors"]
def choice():
selection = random.choice(choices)
return selection
def winner(player1, player2):
if player1 == "Rock" and player2 == "Rock":
result = "Tie"
elif player1 == "Rock" and player2 == "Paper":
result = "Player 2 ... |
12,284 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
wk1.4
warm-up
Instructions
Step1: Testing membership
Step2: Subsets and supersets
Step3: Removing items
Step4: Iterating over sets
Big takeaway
Step5: Set operations
Intersection
Any el... | Python Code:
# How to make a set
a = {1, 2, 3}
type(a)
# Getting a set from a list
b = set([1, 2, 3])
a == b
# How to make a frozen set
a = frozenset({1, 2, 3})
# Getting a set from a list
b = frozenset([1, 2, 3])
# Getting a set from a string
set("obtuse")
# Getting a set from a dictionary
c = set({'a':1, 'b':2})
type... |
12,285 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
阅读笔记
作者：方跃文
Email
Step1: ndarray 是 同构数据多维容器，that is to say, 所有元素必须是同类型的。
每个数组都有一个 shape （一个表示各维度大小的元祖）和一个 dtype （一个用于说明数组数据类型的对象）：
Step2: 虽然大多数数据分析工作不需要深入理解Numpy，但是精通面向数组的编程和思维方式是成为 Pyt... | Python Code:
import numpy.random as nrandom
data = nrandom.randn(3,2)
data
data*10
data + data
Explanation: 阅读笔记
作者：方跃文
Email: fyuewen@gmail.com
时间：始于2017年9月12日， 结束写作于
第四章笔记始于2017年10月17日，结束于2018年1月6日
第四章 Numpy基础：数组和矢量计算
时间： 2017年10月17日早晨
Numpy，即 numerical python的简称，是高性能科学计算和数据分析的基础包。它是本书所介绍的几乎所有高级工具的构建基础。其部分功能如... |
12,286 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Overlays
Spatial overlays allow you to compare two GeoDataFrames containing polygon or multipolygon geometries
and create a new GeoDataFrame with the new geometries representing the spatial... | Python Code:
%matplotlib inline
from shapely.geometry import Point
from geopandas import datasets, GeoDataFrame, read_file
from geopandas.tools import overlay
# NYC Boros
zippath = datasets.get_path('nybb')
polydf = read_file(zippath)
# Generate some circles
b = [int(x) for x in polydf.total_bounds]
N = 10
polydf2 = Ge... |
12,287 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Algorithms Exercise 2
Imports
Step2: Peak finding
Write a function find_peaks that finds and returns the indices of the local maxima in a sequence. Your function should
Step3: Here is a st... | Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import seaborn as sns
import numpy as np
Explanation: Algorithms Exercise 2
Imports
End of explanation
def find_peaks(a):
Find the indices of the local maxima in a sequence.
n = 0
x = []
if a[n] > a[n+1]:
x.append(n)
while ... |
12,288 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cross-Validation on the Iris Dataset
Here is an example on you to split the data on the iris dataset.
Let's re-use the results of the 2D PCA of the iris dataset
in order to explore clusterin... | Python Code:
# all of this is taken from the notebook '04_iris_clustering.ipynb'
import numpy as np
from sklearn.datasets import load_iris
iris = load_iris()
X = iris.data
y = iris.target
n_samples, n_features = iris.data.shape
print n_samples
Explanation: Cross-Validation on the Iris Dataset
Here is an example on you ... |
12,289 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementat... | Python Code:
%matplotlib inline
#%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of ... |
12,290 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Simple Autoencoder
We'll start off by building a simple autoencoder to compress the MNIST dataset. With autoencoders, we pass input data through an encoder that makes a compressed represen... | Python Code:
%matplotlib inline
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', validation_size=0)
img = mnist.train.images[2]
plt.imshow(img.reshape((28, 28)), cmap='Greys_r')
Explanati... |
12,291 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
XCS Tutorial
This is the official tutorial for the xcs package for Python 3. You can find the latest release and get updates on the project's status at the project home page.
What is XCS?
XC... | Python Code:
import logging
logging.root.setLevel(logging.INFO)
Explanation: XCS Tutorial
This is the official tutorial for the xcs package for Python 3. You can find the latest release and get updates on the project's status at the project home page.
What is XCS?
XCS is a Python 3 implementation of the XCS algorithm a... |
12,292 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center>
<img src="../img/ods_stickers.jpg">
Открытый курс по машинному обучению
</center>
Автор материала
Step1: Основными структурами данных в Pandas являются классы Series и DataFrame. П... | Python Code:
# Python 2 and 3 compatibility
# pip install future
from __future__ import (absolute_import, division,
print_function, unicode_literals)
# отключим предупреждения Anaconda
import warnings
warnings.simplefilter('ignore')
import pandas as pd
import numpy as np
%matplotlib inline
impor... |
12,293 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Duhamel Integral
Problem Data
Step1: Natural Frequency, Damped Frequency
Step2: Computation
Preliminaries
We chose a time step and we compute a number of constants of the integration proce... | Python Code:
M = 600000
T = 0.6
z = 0.10
p0 = 400000
t0, t1, t2, t3 = 0.0, 1.0, 3.0, 6.0
Explanation: Duhamel Integral
Problem Data
End of explanation
wn = 2*np.pi/T
wd = wn*np.sqrt(1-z**2)
Explanation: Natural Frequency, Damped Frequency
End of explanation
dt = 0.05
edt = np.exp(-z*wn*dt)
fac = dt/(2*M*wd)
Explanation... |
12,294 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: 가중치 클러스터링 종합 가이드
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: 클러스터링된 모델 정의하기
전체 모델 클러스터링(순차적 ... | 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... |
12,295 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Iterators and Generators
In this section of the course we will be learning about the difference between iteration and generation in Python and how to construct our own Generators with the yi... | Python Code:
# Generator function for the cube of numbers (power of 3)
def gencubes(n):
for num in range(n):
yield num**3
for x in gencubes(10):
print x
Explanation: Iterators and Generators
In this section of the course we will be learning about the difference between iteration and generation in Python... |
12,296 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Parallel Monto-Carlo options pricing
This notebook shows how to use IPython.parallel to do Monte-Carlo options pricing in parallel. We will compute the price of a large number of options for... | Python Code:
%pylab inline
import sys
import time
from IPython.parallel import Client
import numpy as np
Explanation: Parallel Monto-Carlo options pricing
This notebook shows how to use IPython.parallel to do Monte-Carlo options pricing in parallel. We will compute the price of a large number of options for different s... |
12,297 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Atherosclerosis of the Aorta
Also known as heart disease or hardening of the arteries. This disease is the number one killer of Americans.
Step1: Peptic Ulcers
There have been long-standin... | Python Code:
print_synonyms('dx::440.0', model)
Explanation: Atherosclerosis of the Aorta
Also known as heart disease or hardening of the arteries. This disease is the number one killer of Americans.
End of explanation
#Crohn's Disease
print_synonyms('dx::555.9', model)
Explanation: Peptic Ulcers
There have been long-... |
12,298 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
adrasteia
01 Gaia Universe Model
Step1: Read in the data
Step2: I had to modify the raw data to get it to read in conveniently. I try not to modify raw data formats (for reproducibility p... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
%config InlineBackend.figure_format = "retina"
import pandas as pd
sns.set_context("talk")
Explanation: adrasteia
01 Gaia Universe Model: Milky Way Sample
gully
March 2016
Tasks:
- Read in the data
- Make a plot
End... |
12,299 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Evaluation, Cross-Validation, and Model Selection
By Heiko Strathmann - <a href="mailto
Step1: Types of splitting strategies
As said earlier Cross-validation is based upon splitting the dat... | Python Code:
%pylab inline
%matplotlib inline
# include all Shogun classes
from modshogun import *
# generate some ultra easy training data
gray()
n=20
title('Toy data for binary classification')
X=hstack((randn(2,n), randn(2,n)+1))
Y=hstack((-ones(n), ones(n)))
_=scatter(X[0], X[1], c=Y , s=100)
p1 = Rectangle((0, 0),... |
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