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6,000 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 2
Lógica proposicional
"Poder-se-á definir a Lógica como a ciência das regras que legitimam
a utilização da palavra portanto." B. Ruyer in Logique.
Proposição
No caso das instruções... | Python Code:
#
# Tabela da Negação
#
for p in [True,False]:
print('not',p,"=", not p)
Explanation: Chapter 2
Lógica proposicional
"Poder-se-á definir a Lógica como a ciência das regras que legitimam
a utilização da palavra portanto." B. Ruyer in Logique.
Proposição
No caso das instruções if e while, a execução dum... |
6,001 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial Part 9
Step1: Hyperparameter Optimization
Let's start by loading the HIV dataset. It classifies over 40,000 molecules based on whether they inhibit HIV replication.
Step2: Now le... | Python Code:
!curl -Lo conda_installer.py https://raw.githubusercontent.com/deepchem/deepchem/master/scripts/colab_install.py
import conda_installer
conda_installer.install()
!/root/miniconda/bin/conda info -e
!pip install --pre deepchem
import deepchem
deepchem.__version__
Explanation: Tutorial Part 9: Advanced Model ... |
6,002 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
MNIST end to end on Kubeflow on GKE
This example guides you through
Step1: Install the required libraries
Run the next cell to import the libraries required to train this model.
Step2: Wai... | Python Code:
import logging
import os
import uuid
from importlib import reload
from oauth2client.client import GoogleCredentials
credentials = GoogleCredentials.get_application_default()
Explanation: MNIST end to end on Kubeflow on GKE
This example guides you through:
Taking an example TensorFlow model and modifying it... |
6,003 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compare the Different Corpora
Corpora
Step1: Compare the fraction of emotional sentences per text
For the different corpora.
An emotional sentence is a sentence for which at least one HEEM ... | Python Code:
# Render our plots inline
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import os
pd.set_option('display.mpl_style', 'default') # Make the graphs a bit prettier
plt.rcParams['figure.figsize'] = (16, 6)
# adjust to your local directories
embem_data_dir = '/home/j... |
6,004 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Feedback k domácím projektům
Jde tento kód napsat jednodušeji, aby ale dělal úplně totéž?
Step1: Ano, lze
Step2: A co tento?
Step3: Ten taky
Step4: Nejmenší číslo
Upovídané řešení z dom... | Python Code:
for radek in range(4):
radek += 1
for value in range(radek):
print('X', end=' ')
print('')
Explanation: Feedback k domácím projektům
Jde tento kód napsat jednodušeji, aby ale dělal úplně totéž?
End of explanation
for radek in range(1, 5):
print('X ' * radek)
Explanation: Ano, lze :-)
End of exp... |
6,005 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
← Back to Index
Sheet Music Representations
Music can be represented in many different ways. The printed, visual form of a musical work is called a score or sheet music. For example, he... | Python Code:
ipd.SVG("https://upload.wikimedia.org/wikipedia/commons/2/27/MozartExcerptK331.svg")
ipd.YouTubeVideo('dP9KWQ8hAYk')
Explanation: ← Back to Index
Sheet Music Representations
Music can be represented in many different ways. The printed, visual form of a musical work is called a score or sheet music. Fo... |
6,006 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SuchLinkedTrees
In the last article, we saw how to use SuchTree to probe the topology of
very large trees. In this article, we're going to look at the other component
of the package, SuchLin... | Python Code:
%pylab inline
%config InlineBackend.figure_format='retina'
from SuchTree import SuchTree, SuchLinkedTrees
import seaborn
import pandas
from scipy.cluster.hierarchy import ClusterWarning
from scipy.stats import pearsonr
warnings.simplefilter( 'ignore', UserWarning )
Explanation: SuchLinkedTrees
In the last ... |
6,007 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 class="title">Text Classification and Clustering</h1>
<ul>
<li>Research Seminar Information Retrieval
<li>Humboldt-University Berlin
<li>2015-07-01
<li>Stefan Baerisch
<ul/>
# Gliederung... | Python Code:
# Baseline Classifier : Weist jedem Wert die häufigste Klasse zu.
from collections import Counter
model = Counter()
def fit(value, cls):
model.update([cls])
def predict(value):
return model.most_common(1)[0][0]
#Drei Aufrufe von train,
fit("Banana","fruit")
fit("Apple","fruit")
fit("Bean","Vegetab... |
6,008 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data preprocessing
Here will download and subset NCEP reanalysis data, and read in files created from the DesInventar database. Then create a map showing the regions where disaster records a... | Python Code:
#--- Libraries
import pandas as pd # statistics packages
import numpy as np # linear algebra packages
import matplotlib.pyplot as plt # plotting routines
import seaborn as sns # more plot... |
6,009 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 3, Table 3
This notebook explains how I used the Harvard General Inquirer to streamline interpretation of a predictive model.
I'm italicizing the word "streamline" because I want to ... | Python Code:
# some standard modules
import csv, os, sys
from collections import Counter
import numpy as np
from scipy.stats import pearsonr
# now a module that I wrote myself, located
# a few directories up, in the software
# library for this repository
sys.path.append('../../lib')
import FileCabinet as filecab
Explan... |
6,010 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Experience
Based on wordnet as ground truth, we tried to learn a classifier to detect antonymics relations between words (small != big / good != bad)
To do so we will explore the carthesian ... | Python Code:
summaryDf = pd.DataFrame([extractSummaryLine(l) for l in open('../../data/learnedModel/anto/summary.txt').readlines()],
columns=['bidirectional', 'strict', 'clf', 'feature', 'post', 'precision', 'recall', 'f1'])
summaryDf.sort_values('f1', ascending=False)[:10]
Explanation: Experien... |
6,011 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of Contents
<a href='#motivation'>Motivation</a>
<a href='#constructor'>Constructing a dataset</a>
<a href='#attributes'>Attributes</a>
<a href='#access'>Accessing samples</a>
<a href=... | Python Code:
import sys, os
import numpy as np
import matplotlib
%matplotlib
%matplotlib inline
import matplotlib.pyplot as plt
n = 10 # number of samples
p = 3 # number of features
X = np.random.random([n, p]) # random data for illustration
y = [1]*5 + [2]*5 # random labels ...
np.set_printoptions(precisio... |
6,012 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ATM 623
Step1: Contents
The observed seasonal cycle from NCEP Reanalysis data
Analytical toy model of the seasonal cycle
Exploring the amplitude of the seasonal cycle with an EBM
The season... | Python Code:
# Ensure compatibility with Python 2 and 3
from __future__ import print_function, division
Explanation: ATM 623: Climate Modeling
Brian E. J. Rose, University at Albany
Lecture 19: Modeling the seasonal cycle of surface temperature
Warning: content out of date and not maintained
You really should be looki... |
6,013 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework #1
This notebook contains the first homework for this class, and is due on Friday, October 23rd, 2016 at 11
Step2: Section 3 | Python Code:
# write any code you need here!
# Create additional cells if you need them by using the
# 'Insert' menu at the top of the browser window.
Explanation: Homework #1
This notebook contains the first homework for this class, and is due on Friday, October 23rd, 2016 at 11:59 p.m.. Please make sure to get st... |
6,014 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Statements Assessment Test
Lets test your knowledge!
Use for, split(), and if to create a Statement that will print out words that start with 's'
Step1: Use range() to print all the even nu... | Python Code:
st = 'Print only the words that start with s in this sentence'
#Code here
st = 'Print only the words that start with s in this sentence'
for word in st.split():
if word[0] == 's':
print(word )
Explanation: Statements Assessment Test
Lets test your knowledge!
Use for, split(), and if to create a... |
6,015 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploration
Exploration of prepocessed DF
Step1: Input
Privacy restriction
Step2: Exploration
Step3: Preparation for Modeling
Missing Values
Step4: DFs for Modeling
Step5: Dummie Encodi... | Python Code:
import numpy as np
import pandas as pd
import math
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: Exploration
Exploration of prepocessed DF
End of explanation
file_path = "../data/events_df.pkl"
df = pd.read_pickle(file_path)
print(df.shape)
print(df.dtypes)
df.head()
Explanation: Input
Pr... |
6,016 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Markov chains for finding CpG islands
Step5: As training data, we use some already-called CpG islands. These were called in a prior study that used a kind of Hidden Markov Model. Relevant... | Python Code:
from __future__ import print_function
import random
import re
import gzip
from itertools import islice
from operator import itemgetter
import numpy as np
from future.standard_library import install_aliases
install_aliases()
from urllib.request import urlopen, urlcleanup, urlretrieve
Explanation: Markov cha... |
6,017 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hour of Code 2015
For Mr. Clifford's Class (5C)
Perry Grossman
December 2015
Introduction
From the Hour of Code to the Power of Co
How to use programming skills for data analysis, or "data s... | Python Code:
# you can also access this directly:
from PIL import Image
im = Image.open("DataScienceProcess.jpg")
im
#path=\'DataScienceProcess.jpg'
#image=Image.open(path)
Explanation: Hour of Code 2015
For Mr. Clifford's Class (5C)
Perry Grossman
December 2015
Introduction
From the Hour of Code to the Power of Co
How... |
6,018 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Facies classification using Convolutional Neural Networks
Team StoDIG - Statoil Deep-learning Interest Group
David Wade, John Thurmond & Eskil Kulseth Dahl
In this python notebook we propos... | Python Code:
%%sh
pip install pandas
pip install scikit-learn
pip install keras
pip install sklearn
from __future__ import print_function
import time
import numpy as np
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.colors as colors
from mpl_toolkits.axes_grid1 import make_axes... |
6,019 | Given the following text description, write Python code to implement the functionality described.
Description:
Count number of ways to reach a given score in a game
Returns number of ways to reach score n . ; table [ i ] will store count of solutions for value i . Initialize all table values as 0. ; Base case ( If give... | Python Code:
def count(n ) :
table =[0 for i in range(n + 1 ) ]
table[0 ] = 1
for i in range(3 , n + 1 ) :
table[i ] += table[i - 3 ]
for i in range(5 , n + 1 ) :
table[i ] += table[i - 5 ]
for i in range(10 , n + 1 ) :
table[i ] += table[i - 10 ]
return table[n ]
n = 20
print(' Count ... |
6,020 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Description
This is a test of SimulatedAnnealing.
Basics
Step4: Set Parameters
State in MetropolisSampler is np.array([float]).
The smaller the re_scaling be, the faster it anneals.
Step5: ... | Python Code:
import sys
sys.path.append('../sample/')
from simulated_annealing import Temperature, SimulatedAnnealing
from random import uniform, gauss
import numpy as np
import matplotlib.pyplot as plt
Explanation: Description
This is a test of SimulatedAnnealing.
Basics
End of explanation
def temperature_of_time(t, r... |
6,021 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Nucleosynthetic yields
These are key to every chemical evolution model. Chempy supports three nucleosynthetic channels at the moment
Step1: Hyper Nova (HN) is only provided for Nomoto 2013 ... | Python Code:
%pylab inline
from Chempy.parameter import ModelParameters
from Chempy.yields import SN2_feedback, AGB_feedback, SN1a_feedback, Hypernova_feedback
from Chempy.infall import PRIMORDIAL_INFALL, INFALL
# This loads the default parameters, you can check and change them in paramter.py
a = ModelParameters()
# I... |
6,022 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
EAS Testing - Antutu benchmark on Android
The goal of this experiment is to run benchmarks on a Hikey running Android with an EAS kernel and collect results. The analysis phase will consist ... | Python Code:
import logging
reload(logging)
log_fmt = '%(asctime)-9s %(levelname)-8s: %(message)s'
logging.basicConfig(format=log_fmt)
# Change to info once the notebook runs ok
logging.getLogger().setLevel(logging.INFO)
%pylab inline
import copy
import os
from time import sleep
from subprocess import Popen
import pand... |
6,023 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Quick Setup
Step1: Download Data - MNIST
The MNIST dataset contains labeled images of handwritten digits, where each example is a 28x28 pixel image of grayscale values in the range [0,255] ... | Python Code:
# Create a SystemML MLContext object
from systemml import MLContext, dml
ml = MLContext(sc)
Explanation: Quick Setup
End of explanation
%%sh
mkdir -p data/mnist/
cd data/mnist/
curl -O https://pjreddie.com/media/files/mnist_train.csv
curl -O https://pjreddie.com/media/files/mnist_test.csv
Explanation: Down... |
6,024 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Week 5 - Crafting the public interface.
Learning Objectives
Explain what a public interface is
Discuss the advantages of defining a public interface
Compare different public interfaces
Desig... | Python Code:
class Item(object):
def __init__(self, name, description, location):
self.name = name
self.description = description
self.location = location
def update_location(self, new_location):
pass
class Equipment(Item):
pass
class Consumable(It... |
6,025 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Now that we know how to read the data, we will add some processing to generate a gridded field.<br />
In the first part, we will use the loop on the files to store all the data, then in the ... | Python Code:
year = 2015
month = 7
%matplotlib inline
import glob
import os
import netCDF4
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from matplotlib import colors
Explanation: Now that we know how to read the data, we will add some processing to generate a gridded fiel... |
6,026 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
파이썬 기본 자료형 1부
파이썬 언어에서 사용되는 값들의 기본 자료형을 살펴본다.
변수에 할당될 수 있는 가장 단순한 자료형에는 네 종류가 있다
Step1: 변수를 선언하고 값을 바로 확인할 수 있다.
Step2: 파이썬을 계산기처럼 활용할 수도 있다.
Step3: 주의
Step4: 나머지를 계산하는 연산자는 % 이다.
Step5... | Python Code:
print("Hello World")
Explanation: 파이썬 기본 자료형 1부
파이썬 언어에서 사용되는 값들의 기본 자료형을 살펴본다.
변수에 할당될 수 있는 가장 단순한 자료형에는 네 종류가 있다:
정수 자료형(int):
..., -3, -2, -1, 0, 1, 2, 3, 등등
1 + 2, -2 * 3, 등등
부동소수점 자료형(float):
1.2, 0.333333, -1.2, -3.7680, 등등
2.0 \ 3.5, 3.555 + 3.4 * 7.9, 등등
불리언 자료형(bool): True, False를 포함하여 두 값으로 계... |
6,027 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Importing Necessary Modules
To discover something new is to explore where it has never been explored.
Added Conv Visuals Also (Working)
Step1: Loading The Dataset
Step2: Normalising The D... | Python Code:
import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import matplotlib.pyplot as plt #for plotting
from collections import Counter
from sklearn.metrics import confusion_matrix
import itertools
import seaborn as sns
from subprocess import check_output
pr... |
6,028 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TabNet
Step1: Authenticate your GCP account
If you are using AI Platform Notebooks, your environment is already
authenticated. Skip this step.
If you are using Colab, run the cell below and... | Python Code:
PROJECT_ID = "[<your-project-id>]"
Explanation: TabNet: Attentive Interpretable Tabular Learning
<table align="left">
<td>
<a href="https://colab.research.google.com/github/GoogleCloudPlatform/ml-on-gcp/blob/master/tutorials/explanations/ai-explanations-tabnet-algorithm.ipynb">
<img src="https:... |
6,029 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Artifact correction with Maxwell filter
This tutorial shows how to clean MEG data with Maxwell filtering.
Maxwell filtering in MNE can be used to suppress sources of external
intereference a... | Python Code:
import mne
from mne.preprocessing import maxwell_filter
data_path = mne.datasets.sample.data_path()
Explanation: Artifact correction with Maxwell filter
This tutorial shows how to clean MEG data with Maxwell filtering.
Maxwell filtering in MNE can be used to suppress sources of external
intereference and c... |
6,030 | 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... |
6,031 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Over-dispersed Age-Period-Cohort Models
We replicate the data example in Harnau and Nielsen (2017) in Section 6.
The work on this vignette was supported by the European Research Council, gra... | Python Code:
import apc
# Turn off a FutureWarnings
import warnings
warnings.simplefilter('ignore', FutureWarning)
Explanation: Over-dispersed Age-Period-Cohort Models
We replicate the data example in Harnau and Nielsen (2017) in Section 6.
The work on this vignette was supported by the European Research Council, grant... |
6,032 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: Derivation of the inversion stencil using a non-symmetric forward-backward scheme
Derivation of a non-symmetric stencil of
$$b = \nabla\cdot(A\nabla_\perp f)+Bf$$
using a forward ste... | Python Code:
from IPython.display import display
from sympy import init_printing
from sympy import symbols, expand, together, as_finite_diff, collect
from sympy import Function, Eq, Subs
from collections import deque
init_printing()
def finiteDifferenceOfOneTerm(factors, wrt, stencil):
Finds the finite differe... |
6,033 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mining performance hotspots with JProfiler, jQAssistant, Neo4j and Pandas
TL;DR I show how I determine the parts of an application that trigger unnecessary SQL statements by using graph anal... | Python Code:
with open (r'input/spring-petclinic/JDBC_Probe_Hot_Spots_jmeter_test.xml') as log:
[print(line[:97] + "...") for line in log.readlines()[:10]]
Explanation: Mining performance hotspots with JProfiler, jQAssistant, Neo4j and Pandas
TL;DR I show how I determine the parts of an application that trigger unn... |
6,034 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
constitutive
Step1: L_iso
Provides the elastic stiffness tensor for an isotropic material.
The two first arguments are a couple of elastic properties. The third argument specifies which co... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from simmit import smartplus as sim
import os
Explanation: constitutive : The Constitutive Library
End of explanation
E = 70000.0
nu = 0.3
L = sim.L_iso(E,nu,"Enu")
print np.array_str(L, precision=4, suppress_small=True)
d = sim.check_sy... |
6,035 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Predicting Breast Cancer Proliferation Scores with Apache Spark and Apache SystemML
Preprocessing
Setup
Step1: Execute Preprocessing & Save
Step2: Sample Data
TODO | Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
import os
import shutil
import matplotlib.pyplot as plt
import numpy as np
from breastcancer.preprocessing import preprocess, save, train_val_split
# Ship a fresh copy of the `breastcancer` package to the Spark workers.
# Note: The zip must include the ... |
6,036 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotting sensor layouts of EEG systems
This example illustrates how to load all the EEG system montages
shipped in MNE-python, and display it on the fsaverage template subject.
Step1: Check... | Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Joan Massich <mailsik@gmail.com>
#
# License: BSD Style.
import os.path as op
import mne
from mne.channels.montage import get_builtin_montages
from mne.datasets import fetch_fsaverage
from mne.viz import set_3d_title, set_3d_view
Explan... |
6,037 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Core Test
Step2: Mesh Test
Step3: FunctionSpace Test
Step4: Exporter Test | Python Code:
!echo "deb https://dl.bintray.com/feelpp/ubuntu bionic latest" | tee -a /etc/apt/sources.list
!wget -qO - https://bintray.com/user/downloadSubjectPublicKey?username=bintray | apt-key add -
!apt update
!apt install feelpp-quickstart feelpp-data
!apt install python3-mpi4py python3-feelpp ssh
Explanation: <a... |
6,038 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Peer in THRG Generated Graphs
Dev Space
System
Step1: Network Dynamics
Let's examine the network dynamics
Step2: THRG
Using time1.py we learn or derive the production rules from the given ... | Python Code:
# imports
import networkx as nx
%matplotlib inline
import matplotlib.pyplot as plt
params = {'legend.fontsize':'small',
'figure.figsize': (7,7),
'axes.labelsize': 'small',
'axes.titlesize': 'small',
'xtick.labelsize':'small',
'ytick.labelsize':'small'}
plt.... |
6,039 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of Contents
<p><div class="lev1 toc-item"><a href="#Honors-Physics-PHYS1010" data-toc-modified-id="Honors-Physics-PHYS1010-1"><span class="toc-item-num">1 </span>Honors Phys... | Python Code:
from PIL import Image, ImageDraw
import math, colorsys, numpy
from matplotlib import colors
from IPython.display import Image as ipythonImage
Explanation: Table of Contents
<p><div class="lev1 toc-item"><a href="#Honors-Physics-PHYS1010" data-toc-modified-id="Honors-Physics-PHYS1010-1"><span class="toc-ite... |
6,040 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Uncertainty in Deep Learning
A common criticism of deep learning models is that they tend to act as black boxes. A model produces outputs, but doesn't given enough context to interpret them... | Python Code:
!pip install --pre deepchem
import deepchem
deepchem.__version__
Explanation: Uncertainty in Deep Learning
A common criticism of deep learning models is that they tend to act as black boxes. A model produces outputs, but doesn't given enough context to interpret them properly. How reliable are the model'... |
6,041 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cargue de datos s SciDB
1) Verificar Prerequisitos
Python
SciDB-Py requires Python 2.6-2.7 or 3.3
Step1: NumPy
tested with version 1.9 (1.13.1)
Step2: Requests
tested with version 2.7 (2.1... | Python Code:
import sys
sys.version_info
Explanation: Cargue de datos s SciDB
1) Verificar Prerequisitos
Python
SciDB-Py requires Python 2.6-2.7 or 3.3
End of explanation
import numpy as np
np.__version__
Explanation: NumPy
tested with version 1.9 (1.13.1)
End of explanation
import requests
requests.__version__
Explana... |
6,042 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A1
Step1: Step 1
Step2: Run the above function to call the API and assign the responses to variables
Step3: Export the API raw data files. This section has been commented out in order to ... | Python Code:
import json
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import requests
from datetime import datetime
%matplotlib inline
Explanation: A1: Data curation
Dane Jordan
Import necessary libraries that will be used
End of explanation
# since we will be performing api calls at least fiv... |
6,043 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Atmos
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', 'uhh', 'sandbox-2', 'atmos')
Explanation: ES-DOC CMIP6 Model Properties - Atmos
MIP Era: CMIP6
Institute: UHH
Source ID: SANDBOX-2
Topic: Atmos
Sub-Topics: Dynamical Core, Radiation, T... |
6,044 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Use tensorboard to visualize tensorflow graph, plot quantitative metrics about the execution of your graph, and show addinal data like images that pass through it.
Step1: Tensorboard operat... | Python Code:
import tensorboard as tb
import tensorflow as tf
Explanation: Use tensorboard to visualize tensorflow graph, plot quantitative metrics about the execution of your graph, and show addinal data like images that pass through it.
End of explanation
def variable_summaries (var):
with tf.name_scope ('summari... |
6,045 | Given the following text description, write Python code to implement the functionality described.
Description:
Swap the elements between any two given quadrants of a Matrix
Python3 program for the above approach ; Function to iterate over the X quadrant and swap its element with Y quadrant ; Iterate over X quadrant ; S... | Python Code:
N , M = 6 , 6
def swap(mat , startx_X , starty_X , startx_Y , starty_Y ) :
row , col = 0 , 0
i = startx_X
while(bool(True ) ) :
col = 0
j = startx_X
while(bool(True ) ) :
temp = mat[i ][j ]
mat[i ][j ] = mat[startx_Y + row ][starty_Y + col ]
mat[startx_Y + row ][starty_Y + col ] = te... |
6,046 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
19 - Introduction to Deep Learning - MLP
by Alejandro Correa Bahnsen and Jesus Solano
version 1.4, May 2019
Part of the class Practical Machine Learning
This notebook is licensed under a Cre... | Python Code:
# Import the required packages
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import scipy
# Package imports
import numpy as np
import matplotlib.pyplot as plt
import sklearn
import sklearn.datasets
import sklearn.linear_model
Explanation: 19 - Introduction to Deep... |
6,047 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 5
Examples and Exercises from Think Stats, 2nd Edition
http
Step1: Exponential distribution
Here's what the exponential CDF looks like with a range of parameters.
Step2: Here's the... | Python Code:
from os.path import basename, exists
def download(url):
filename = basename(url)
if not exists(filename):
from urllib.request import urlretrieve
local, _ = urlretrieve(url, filename)
print("Downloaded " + local)
download("https://github.com/AllenDowney/ThinkStats2/raw/master... |
6,048 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step3: General intro
Step4: Defining the structure of the network
For the neural network to train on your data, you need the following <a href="https
Step5: Training
Step6: Test | Python Code:
%matplotlib inline
import os
from urllib import urlretrieve
import math
import tensorflow as tf
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
f... |
6,049 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Welcome to the Python Plotting Tutorial for Com597I!
This is intended as a self-guided exercise to help you explore python plotting. Please follow the document, follow the links and read the... | Python Code:
# This section imports some important libraries that we'll need.
# the most important is the second line. After you run this, "plt" will be
# the plotting library in python.
import numpy
import matplotlib.pyplot as plt
%pylab inline
Explanation: Welcome to the Python Plotting Tutorial for Com597I!
This is ... |
6,050 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load some data
Step1: Load pairs of covers and non-covers
```Python
def get_pairs(clique_dict)
Step2: Cut chroma features to fixed-length arrays
```Python
def patchwork(chroma, n_patches=7... | Python Code:
# ratio = (5, 15, 80)
ratio = (1, 9, 90)
clique_dict, cliques_by_uri = SHS_data.read_cliques()
train_cliques, test_cliques, val_cliques = util.split_train_test_validation(clique_dict, ratio=ratio)
Explanation: Load some data
End of explanation
pairs, non_pairs = paired_data.get_pairs(train_cliques)
assert ... |
6,051 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
This is a basic tutorial on using Jupyter to use the scipy modules.
Example of plotting sine and cosine functions in the same plot
Install matplotlib through conda via
Step1: T... | Python Code:
import math
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 3 * math.pi, 50)
y = np.sin(x)
plt.plot(x, y)
plt.show()
Explanation: Introduction
This is a basic tutorial on using Jupyter to use the scipy modules.
Example of plotting sine and cosine functions ... |
6,052 | 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', 'nims-kma', 'sandbox-3', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: NIMS-KMA
Source ID: SANDBOX-3
Topic: Aerosol
Sub-Topics: Transport, E... |
6,053 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This example is kindly contributed by FreddyBaudine for reproducing pygae/galgebra#26 and pygae/galgebra#30 with modifications by utensil.
Please note before Python code, there's an invisibl... | Python Code:
from __future__ import print_function
import sys
from galgebra.printer import Format, xpdf
Format()
from sympy import symbols, sin, pi, latex, Array, permutedims
from galgebra.ga import Ga
from IPython.display import Math
Explanation: This example is kindly contributed by FreddyBaudine for reproducing pyg... |
6,054 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: tf.function과 함께 XLA 사용하기
<table class="tfo-notebook-buttons" align="left">
<td>
<img src="https
Step2: 그런 다음, 몇 가지 필요한 상수를 정의하고 MNIST 데이터세트를... | 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... |
6,055 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Is the Grass Wet?
This is an example used by Pearl in his book 'Causality'. I've used the conditional probability tables from here
Step1: We begin with some variables, each with 2 states ..... | Python Code:
from causalinfo import *
# You only need this if you want to draw pretty pictures of the Networksa
from nxpd import draw, nxpdParams
nxpdParams['show'] = 'ipynb'
Explanation: Is the Grass Wet?
This is an example used by Pearl in his book 'Causality'. I've used the conditional probability tables from here:
... |
6,056 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Word Cookie Solver
This program will find all of the words that can be made from a specified set of letters.
Setup
First, let's write some code to check if a single word can be made f... | Python Code:
def word_works(letters, word, allow_repeats=False):
Return True if word can be spelled using only letters. letters is a single
string. allow_repeats allows each letter to be used many times.
letters_remaining = letters.lower() # because dictionary words will be lowercase
for letter ... |
6,057 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1> Feature Engineering </h1>
In this notebook, you will learn how to incorporate feature engineering into your pipeline.
<ul>
<li> Working with feature columns </li>
<li> Adding feature cr... | Python Code:
!pip install --user apache-beam[gcp]==2.16.0
!pip install --user httplib2==0.12.0
Explanation: <h1> Feature Engineering </h1>
In this notebook, you will learn how to incorporate feature engineering into your pipeline.
<ul>
<li> Working with feature columns </li>
<li> Adding feature crosses in TensorFlow ... |
6,058 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment analysis with TFLearn
In this notebook, we'll continue Andrew Trask's work by building a network for sentiment analysis on the movie review data. Instead of a network written with ... | Python Code:
import pandas as pd
import numpy as np
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical
Explanation: Sentiment analysis with TFLearn
In this notebook, we'll continue Andrew Trask's work by building a network for sentiment analysis on the movie review data. Instead of a n... |
6,059 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regression Modeling in Practice
Assignment
Step1: Let's check that the quantitative variable are effectively centered.
Step2: The means are both very close to 0; confirming the centering.
... | Python Code:
# Magic command to insert the graph directly in the notebook
%matplotlib inline
# Load a useful Python libraries for handling data
import pandas as pd
import numpy as np
import statsmodels.formula.api as smf
import seaborn as sns
import matplotlib.pyplot as plt
from IPython.display import Markdown, display... |
6,060 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
$\newcommand{\xv}{\mathbf{x}}
\newcommand{\Xv}{\mathbf{X}}
\newcommand{\piv}{\mathbf{\pi}}
\newcommand{\yv}{\mathbf{y}}
\newcommand{\Yv}{\mathbf{Y}}
\newcommand{\zv}{\mathbf{z}}
\newcommand{... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: $\newcommand{\xv}{\mathbf{x}}
\newcommand{\Xv}{\mathbf{X}}
\newcommand{\piv}{\mathbf{\pi}}
\newcommand{\yv}{\mathbf{y}}
\newcommand{\Yv}{\mathbf{Y}}
\newcommand{\zv}{\mathbf{z}}
\newcommand{\av}{\mathbf{a}}
\newcommand{\Wv}{... |
6,061 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
全体の流れ
分析の前準備
BigQueryから収集したデータの抽出
データを扱いやすく整形
統計情報を確認
データの可視化
データの特徴
外気温は比較的一定
CPU温度はよく変化する
分析の実施
CPU温度が外気温を越えて熱くならないようにコントロールしたい。そのためにどうデータを扱うかのサンプルを確認する。ここで作ったモデルを実際にプロダクション環境に組み込めることを想定して... | Python Code:
%%bq query -n requests
SELECT datetime, cpu_temperature, temperature
FROM `soracom_handson.raspi_env`
order by datetime asc
import google.datalab.bigquery as bq
import pandas as pd
df_from_bq = requests.execute(output_options=bq.QueryOutput.dataframe()).result()
# データの確認
df_from_bq
# 文字列型でデータが取得されているので変換
... |
6,062 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Распределение товаров по категориям
Инициализация
Step1: Загружаю данные о продуктах
Описание полей
Step2: Загружаем все возможные наименования продуктов
У разных поставщиков один и тот-же... | Python Code:
import os
import sys
from django.utils import timezone
sys.path.append('/home/ubuntu/anodos.ru/anodos/')
os.environ['DJANGO_SETTINGS_MODULE'] = 'anodos.settings'
from django.core.wsgi import get_wsgi_application
application = get_wsgi_application()
%matplotlib inline
import numpy as np
import pandas as pd
... |
6,063 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Winpython Default checker
Step1: Compilers
Step2: Cython (a compiler for writing C extensions for the Python language)
WinPython 3.5 and 3.6 users may not have mingwpy available, and so ne... | Python Code:
import warnings
#warnings.filterwarnings("ignore", category=DeprecationWarning)
#warnings.filterwarnings("ignore", category=UserWarning)
#warnings.filterwarnings("ignore", category=FutureWarning)
# warnings.filterwarnings("ignore") # would silence all warnings
%matplotlib inline
# use %matplotlib widget f... |
6,064 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Test a Perceptual Phenomenon - Stroop data
Katie Truong
Step1: Introduction
In a Stroop experiment, participants are shown two lists of word of color names, printed in different ink colors,... | Python Code:
import pandas as pd
import numpy as np
import scipy.stats as st
import matplotlib.pyplot as plt
import seaborn as sns
import math
Explanation: Test a Perceptual Phenomenon - Stroop data
Katie Truong
End of explanation
stroopdata = pd.read_csv("stroopdata.csv")
stroopdata
Explanation: Introduction
In a Stro... |
6,065 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Learning to Play Pong
{tip}
For a production-grade implementation of distributed
reinforcement learning, use [Ray RLlib](https
Step1: Hyperparameters
Here we'll define a couple of the hyper... | Python Code:
import numpy as np
import os
import ray
import time
import gym
Explanation: Learning to Play Pong
{tip}
For a production-grade implementation of distributed
reinforcement learning, use [Ray RLlib](https://docs.ray.io/en/master/rllib/index.html).
In this example, we'll train a very simple neural network to ... |
6,066 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Implementing a Neural Network
In this exercise we will develop a neural network with fully-connected layers to perform classification, and test it out on the CIFAR-10 dataset.
Step2: ... | Python Code:
# A bit of setup
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.neural_net import TwoLayerNet
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams['image.cmap'] = 'gray'
# for aut... |
6,067 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
load image as ndarray
http
Step1: let's do k-mean
my version will take more than 10 mins... ok. I know why I shouldn't implement my own ML library.
In the future I will only implement ML al... | Python Code:
from skimage import io
# cast to float, you need to do this otherwise the color would be weird after clustring
pic = io.imread('data/bird_small.png') / 255.
io.imshow(pic)
pic.shape
# serialize data
data = pic.reshape(128*128, 3)
Explanation: load image as ndarray
http://scikit-image.org/
End of explanatio... |
6,068 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Reading BCH/BATCH Files
BCH/BATCH files are created by FEMAG during a calculation. They hold most of the results.
Their values are grouped into different sections such as
Step1: Show the ca... | Python Code:
import femagtools.bch
bch = femagtools.bch.read('TEST_002.BCH')
Explanation: Reading BCH/BATCH Files
BCH/BATCH files are created by FEMAG during a calculation. They hold most of the results.
Their values are grouped into different sections such as: Flux, Torque, Machine, dqPar etc.
The actual number of sec... |
6,069 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
two different ways to implement categorical cross entropy in TensorFlow
| Python Code::
import tensorflow as tf
from tensorflow.keras.losses import CategoricalCrossentropy
y_true = [[0, 1, 0], [1, 0, 0]]
y_pred = [[0.15, 0.75, 0.1], [0.75, 0.15, 0.1]]
cross_entropy_loss = CategoricalCrossentropy()
print(cross_entropy_loss(y_true, y_pred).numpy())
import tensorflow as tf
from tensorflow.keras... |
6,070 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Google form analysis tests
Purpose
Step1: Sorted total answers to questions
<a id=sortedtotalanswers />
Step2: Cross-samples t-tests
<a id=crossttests />
Purpose
Step3: Conclusion | Python Code:
%run "../Functions/2. Google form analysis.ipynb"
Explanation: Google form analysis tests
Purpose: determine in what extent the current data can accurately describe correlations, underlying factors on the score.
Especially concerning the answerTemporalities[0] groups: are there underlying groups explaining... |
6,071 | 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', 'miroc', 'miroc-es2l', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: MIROC
Source ID: MIROC-ES2L
Topic: Ocean
Sub-Topics: Timestepping Framework... |
6,072 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Extracting the IRIS XGB Models and Analysis from Redis Labs Cloud
This notebook demonstrates how to extract the machine learning Models + Analysis from the Redis Labs Cloud (https
Step1: 2)... | Python Code:
# Setup the Sci-pype environment
import sys, os
# Only Redis Labs is needed for this notebook:
os.environ["ENV_DEPLOYMENT_TYPE"] = "RedisLabs"
# Load the Sci-pype PyCore as a named-object called "core" and environment variables
from src.common.load_ipython_env import *
Explanation: Extracting the IRIS XGB ... |
6,073 | 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', 'cnrm-cerfacs', 'cnrm-esm2-1', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: CNRM-CERFACS
Source ID: CNRM-ESM2-1
Topic: Aerosol
Sub-Topics: ... |
6,074 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Filter out video games which have no title
Filter out video games which have less than 5 ratings
Filter out users which have less than 5 ratings
Merge ratings and videogames dataframe on pro... | Python Code:
correlated_items = ratings_pivot.corr()["B002I0JZOC"].sort_values(ascending=False).head(5)
correlated_items.index
Explanation: Filter out video games which have no title
Filter out video games which have less than 5 ratings
Filter out users which have less than 5 ratings
Merge ratings and videogames datafr... |
6,075 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NERC region maps
NERC shapefiles are from Tamayao, M.-A. M., Michalek, J. J., Hendrickson, C. & Azevedo, I. M. L. Regional Variability and Uncertainty of Electric Vehicle Life Cycle CO2 Emis... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import geopandas as gpd
import os
from os.path import join
import pandas as pd
import sys
sns.set(style='white')
cwd = os.getcwd()
data_path = join(cwd, '..', 'Data storage')
figure_path = join(cwd,'..', 'Figures')
... |
6,076 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise from Think Stats, 2nd Edition (thinkstats2.com)<br>
Allen Downey
Step1: Exercise 5.1
In the BRFSS (see Section 5.4), the distribution of heights is roughly normal with parameters µ... | Python Code:
from __future__ import print_function, division
import thinkstats2
import thinkplot
from brfss import *
import populations as p
import random
import pandas as pd
import test_models
%matplotlib inline
Explanation: Exercise from Think Stats, 2nd Edition (thinkstats2.com)<br>
Allen Downey
End of explanation
i... |
6,077 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Time Series Stationary Measures
I'm going to try different metrics to measure whether a time series is stationary, because there are different types of stationary, different metrics measure ... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from pandas.plotting import autocorrelation_plot
from statsmodels.tsa.stattools import kpss
from statsmodels.tsa.stattools import adfuller
# This is the original time series
def parser(x):
return pd.datetime.strptime('190'+x, '%Y-%m... |
6,078 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Web service
Since Parselmouth is a normal Python library, it can also easily be used within the context of a web server. There are several Python frameworks that allow to quickly set up a we... | Python Code:
%%writefile server.py
from flask import Flask, request, jsonify
import tempfile
app = Flask(__name__)
@app.route('/pitch_track', methods=['POST'])
def pitch_track():
import parselmouth
# Save the file that was sent, and read it into a parselmouth.Sound
with tempfile.NamedTemporaryFile() as tmp:... |
6,079 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian optimization with context variables
In this notebook we are going to see how to use Emukit to solve optimization problems in which certain variables are fixed during the optimizatio... | Python Code:
from emukit.test_functions import branin_function
from emukit.core import ParameterSpace, ContinuousParameter, DiscreteParameter
from emukit.core.initial_designs import RandomDesign
from GPy.models import GPRegression
from emukit.model_wrappers import GPyModelWrapper
from emukit.bayesian_optimization.acqui... |
6,080 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Advanced
Step1: As always, let's do imports and initialize a logger and a new Bundle. See Building a System for more details.
Step2: Accessing Settings
Settings are found with their own c... | Python Code:
!pip install -I "phoebe>=2.2,<2.3"
Explanation: Advanced: Settings
The Bundle also contains a few Parameters that provide settings for that Bundle. Note that these are not system-wide and only apply to the current Bundle. They are however maintained when saving and loading a Bundle.
Setup
Let's first mak... |
6,081 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
IST256 Lesson 13
Visualizations
Zybook Ch10
Links
Participation
Step1: A. y[ ['b'] == 'x' ]
B. y[ y['b'] == 'x' ]
C. y['b'] == 'x'
D. y[ y['b'] == y['x'] ]
Vote Now
Step2: A. y[ 'a','c' ... | Python Code:
import pandas as pd
x = [ { 'a' :2, 'b' : 'x', 'c' : 10},
{ 'a' :4, 'b' : 'y', 'c' : 3},
{ 'a' :1, 'b' : 'x', 'c' : 6} ]
y = pd.DataFrame(x)
Explanation: IST256 Lesson 13
Visualizations
Zybook Ch10
Links
Participation: https://poll.ist256.com
Zoom Chat!
Agenda
Last Lecture... but we ain't gone... |
6,082 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fitting Models Exercise 2
Imports
Step1: Fitting a decaying oscillation
For this problem you are given a raw dataset in the file decay_osc.npz. This file contains three arrays
Step2: Now, ... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import scipy.optimize as opt
Explanation: Fitting Models Exercise 2
Imports
End of explanation
# YOUR CODE HERE
#raise NotImplementedError()
with np.load('decay_osc.npz') as data:
tdata = data['tdata']
ydata = data['ydata']
d... |
6,083 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a id='top'></a>
Kolmogorov-Smirnov test
In this notebook we will illustrate the use of the Kolmogorov-Smirnov test (K-S test) using functions from the SciPy stats module. In particular, we ... | Python Code:
import sys
import math
import numpy as np
import scipy as sp
import matplotlib as mpl
import pandas as pd
Explanation: <a id='top'></a>
Kolmogorov-Smirnov test
In this notebook we will illustrate the use of the Kolmogorov-Smirnov test (K-S test) using functions from the SciPy stats module. In particular, w... |
6,084 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I have set up a GridSearchCV and have a set of parameters, with I will find the best combination of parameters. My GridSearch consists of 12 candidate models total. | Problem:
import numpy as np
import pandas as pd
from sklearn.model_selection import GridSearchCV
GridSearch_fitted = load_data()
assert type(GridSearch_fitted) == sklearn.model_selection._search.GridSearchCV
full_results = pd.DataFrame(GridSearch_fitted.cv_results_) |
6,085 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LeNet Lab Solution
Source
Step1: The MNIST data that TensorFlow pre-loads comes as 28x28x1 images.
However, the LeNet architecture only accepts 32x32xC images, where C is the number of colo... | Python Code:
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", reshape=False)
X_train, y_train = mnist.train.images, mnist.train.labels
X_validation, y_validation = mnist.validation.images, mnist.validation.labels
X_test, y_test = mnist.tes... |
6,086 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Showing Csound k-Values in Matplotlib Animation
The goal of this notebook is to show how Csound control signals can be seen in real-time in the Python Matplotlib using the Animation module. ... | Python Code:
%matplotlib qt5
Explanation: Showing Csound k-Values in Matplotlib Animation
The goal of this notebook is to show how Csound control signals can be seen in real-time in the Python Matplotlib using the Animation module. This can be quite instructive for teaching Csound. Written by Joachim Heintz, August 201... |
6,087 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Trend analysis with bootstrap resampling
Python / Numpy implementation of the trend analysis presented in Gardiner et al., 2008
The following model is used to fit the annual trend (drift) + ... | Python Code:
import pprint
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
Explanation: Trend analysis with bootstrap resampling
Python / Numpy implementation of the trend analysis presented in Gardiner et al., 2008
The following model is used to fit the annual trend (drift) ... |
6,088 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lightning data analysis (from WWLN or Blitzortung)
Development notebook
This iPython notebook extracts lighning data from raw WWLN data files or Blitzortung network.
Code by
Step1: Notes
It... | Python Code:
# Load required packages
import numpy as np
import datetime as dt
from datetime import timedelta
import pandas as pd
from tqdm import tqdm
import os
import pkg_resources as pkg
import geopandas as gpd
from shapely.geometry import Point
from bokeh.plotting import Figure, show, output_notebook, vplot
from bo... |
6,089 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: This is a direct copy of the Earth to Venus mission plan. I'm doing this to make sure I get the functions correct, before proceeding further on the Earth to Mars.
Below is the capt... | Python Code:
class PlanetaryObject():
A simple class used to store pertinant information about the plantary object
def __init__(self, date, L, e, SMA, i, peri, asc, r, v, anom, fp, mu):
self.date = date # Event Date
self.L = L # Longitude
self.e = e # Eccentri... |
6,090 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ApJdataFrames 013
Step1: Table 1 - Spitzer IRAC/MIPS IC348 catalog
Step2: Table 2 - SED Derived $\alpha_{IRAC}$ and $A_V$
But really... spectral types
Step3: Table 3 - Convenient passband... | Python Code:
%pylab inline
import seaborn as sns
import warnings
warnings.filterwarnings("ignore")
import pandas as pd
from astropy.io import ascii
from astropy.table import Table, join
Explanation: ApJdataFrames 013: Lada2006
Title: Spitzer Observations of IC 348: The Disk Population at 2-3 Million Years
Authors: Char... |
6,091 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
"The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include
Step1: Pandas i... | Python Code:
# this would be a comment
# cells like this are like an advanced calculator
# for example:
2+2
Explanation: "The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transf... |
6,092 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
gensim doc2vec & IMDB sentiment dataset
TODO
Step1: The data is small enough to be read into memory.
Step2: Set-up Doc2Vec Training & Evaluation Models
Approximating experiment of Le & Mik... | Python Code:
import locale
import glob
import os.path
import requests
import tarfile
import sys
import codecs
dirname = 'aclImdb'
filename = 'aclImdb_v1.tar.gz'
locale.setlocale(locale.LC_ALL, 'C')
if sys.version > '3':
control_chars = [chr(0x85)]
else:
control_chars = [unichr(0x85)]
# Convert text to lower-cas... |
6,093 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Document retrieval from wikipedia data
Fire up GraphLab Create
Step1: Load some text data - from wikipedia, pages on people
Step2: Data contains
Step3: Explore the dataset and checkout th... | Python Code:
import graphlab
Explanation: Document retrieval from wikipedia data
Fire up GraphLab Create
End of explanation
people = graphlab.SFrame('people_wiki.gl/')
Explanation: Load some text data - from wikipedia, pages on people
End of explanation
people.head()
len(people)
Explanation: Data contains: link to wik... |
6,094 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Colaboratory
Before you start
When you open a new Colab from Github (like this one), you cannot save changes. So it's usually best to store the Colab in you personal drive "File > Save a ... | Python Code:
# YOUR ACTION REQUIRED:
# Execute this cell first using <CTRL-ENTER> and then using <SHIFT-ENTER>.
# Note the difference in which cell is selected after execution.
print('Hello world!')
Explanation: Colaboratory
Before you start
When you open a new Colab from Github (like this one), you cannot save changes... |
6,095 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Better ML Engineering with ML Metadata
Learning Objectives
Download the dataset
Create an InteractiveContext
Construct the TFX Pipeline
Query the MLMD Database
Introduction
Assume a scenario... | Python Code:
!pip install --upgrade pip
Explanation: Better ML Engineering with ML Metadata
Learning Objectives
Download the dataset
Create an InteractiveContext
Construct the TFX Pipeline
Query the MLMD Database
Introduction
Assume a scenario where you set up a production ML pipeline to classify penguins. The pipeline... |
6,096 | 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', 'nerc', 'hadgem3-gc31-hh', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: NERC
Source ID: HADGEM3-GC31-HH
Topic: Ocean
Sub-Topics: Timestepping F... |
6,097 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I’m trying to solve a simple ODE to visualise the temporal response, which works well for constant input conditions using the new solve_ivp integration API in SciPy. For example: | Problem:
import scipy.integrate
import numpy as np
N0 = 1
time_span = [0, 10]
def dN1_dt(t, N1):
input = 1-np.cos(t) if 0<t<2*np.pi else 0
return -100*N1 + input
sol = scipy.integrate.solve_ivp(fun=dN1_dt, t_span=time_span, y0=[N0,]) |
6,098 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example of DOV search methods for interpretations (formele stratigrafie)
Use cases explained below
Get 'formele stratigrafie' in a bounding box
Get 'formele stratigrafie' with specific prope... | Python Code:
%matplotlib inline
import inspect, sys
# check pydov path
import pydov
Explanation: Example of DOV search methods for interpretations (formele stratigrafie)
Use cases explained below
Get 'formele stratigrafie' in a bounding box
Get 'formele stratigrafie' with specific properties
Get 'formele stratigrafie' ... |
6,099 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Display Exercise 1
Imports
Put any needed imports needed to display rich output the following cell
Step1: Basic rich display
Find a Physics related image on the internet and display it in t... | Python Code:
from IPython.display import Image
from IPython.display import HTML
from IPython.display import IFrame
assert True # leave this to grade the import statements
Explanation: Display Exercise 1
Imports
Put any needed imports needed to display rich output the following cell:
End of explanation
Image(url = 'http... |
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