Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
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10,500 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PathMovers
This notebook is an introduction to handling PathMover and MoveChange instances. It mostly covers the questions on
1. how to check if a certain mover was part of a change.
2. Wh... | Python Code:
import openpathsampling as p
Explanation: PathMovers
This notebook is an introduction to handling PathMover and MoveChange instances. It mostly covers the questions on
1. how to check if a certain mover was part of a change.
2. What are the possible changes a mover can generate.
3. ...
Load OPENPATHSAMPL... |
10,501 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright © 2019 The TensorFlow Authors.
Step1: TensorFlow Data Validation
An Example of a Key TFX Library
This example colab notebook illustrates how TensorFlow Data Validation (TFDV)... | 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... |
10,502 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2-Dimensional Frame Analysis - Version 04
This program performs an elastic analysis of 2-dimensional structural frames. It has the following features
Step1: Test Frame
Nodes
Step2: Suppor... | Python Code:
from __future__ import print_function
import salib as sl
sl.import_notebooks()
from Tables import Table
from Nodes import Node
from Members import Member
from LoadSets import LoadSet, LoadCombination
from NodeLoads import makeNodeLoad
from MemberLoads import makeMemberLoad
from collections import OrderedDi... |
10,503 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
.. gps-receivers
Step1: Here, we used
Step2: As you can see,
Step3: Alternatively, we might use the record id field to key our code off a specific type of NMEA message
Step4: Another a... | Python Code:
# nbconvert: hide
from __future__ import absolute_import, division, print_function
import sys
sys.path.append("../features/steps")
import test
socket = test.mock_module("socket")
path = "../data/gps"
client = "172.10.0.20"
socket.socket().recvfrom.side_effect = test.recvfrom_file(path=path, client=client, ... |
10,504 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CNTK 103 Part A
Step1: Data download
We will download the data into local machine. The MNIST database is a standard handwritten digits that has been widely used for training and testing of ... | Python Code:
# Import the relevant modules to be used later
from __future__ import print_function
import gzip
import matplotlib.image as mpimg
import matplotlib.pyplot as plt
import numpy as np
import os
import shutil
import struct
import sys
try:
from urllib.request import urlretrieve
except ImportError:
fr... |
10,505 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
License
Copyright (C) 2017 J. Patrick Hall, jphall@gwu.edu
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (t... | Python Code:
import pandas as pd # pandas for handling mixed data sets
import numpy as np # numpy for basic math and matrix operations
Explanation: License
Copyright (C) 2017 J. Patrick Hall, jphall@gwu.edu
Permission is hereby granted, free of charge, to any person obtaining a copy of this ... |
10,506 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sample weight adjustment
The objective of this tutorial is to familiarize ourselves with SampleWeight the samplics class for adjusting sample weights. In practice, it is necessary to adjust ... | Python Code:
import numpy as np
import pandas as pd
import samplics
from samplics.datasets import PSUSample, SSUSample
from samplics.weighting import SampleWeight
Explanation: Sample weight adjustment
The objective of this tutorial is to familiarize ourselves with SampleWeight the samplics class for adjusting sample we... |
10,507 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Support Vector Machine
SVMs are a set of supervised learning method used for classification, regression and outliers detection
1 Classification
SVC, NuSVC and LinearSVC are classes capable o... | Python Code:
from sklearn import svm
X = [[0,0], [1,1]]
y = [0, 1]
clf = svm.SVC()
clf.fit(X, y)
clf.predict([[2,2]])
Explanation: Support Vector Machine
SVMs are a set of supervised learning method used for classification, regression and outliers detection
1 Classification
SVC, NuSVC and LinearSVC are classes capable ... |
10,508 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
JSON examples and exercise
get familiar with packages for dealing with JSON
study examples with JSON strings and files
work on exercise to be completed and submitted
reference
Step1: impo... | Python Code:
import pandas as pd
import numpy as np
Explanation: JSON examples and exercise
get familiar with packages for dealing with JSON
study examples with JSON strings and files
work on exercise to be completed and submitted
reference: http://pandas.pydata.org/pandas-docs/stable/io.html#io-json-reader
data sour... |
10,509 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TF-DNNRegressor - SeLU - Spitzer Calibration Data
This script show a simple example of using tf.contrib.learn library to create our model.
The code is divided in following steps
Step1: Load... | Python Code:
import pandas as pd
import numpy as np
import tensorflow as tf
tf.logging.set_verbosity(tf.logging.ERROR)
import warnings
warnings.filterwarnings("ignore")
%matplotlib inline
from matplotlib import pyplot as plt
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import Standar... |
10,510 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
$$ \LaTeX \text{ command declarations here.}
\newcommand{\R}{\mathbb{R}}
\renewcommand{\vec}[1]{\mathbf{#1}}
\newcommand{\X}{\mathcal{X}}
\newcommand{\D}{\mathcal{D}}
\newcommand{\G}{\mathca... | Python Code:
import numpy as np
parts_of_speech = DETERMINER, NOUN, VERB, END = 0, 1, 2, 3
words = THE, DOG, WALKED, IN, PARK, END = 0, 1, 2, 3, 4, 5
# transition probabilities
A = np.array([
# D N V E
[0.1, 0.8, 0.1, 0.0], # D: determiner most likely to go to noun
[0.1, 0.1, 0.6, 0.2],... |
10,511 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Group Significant GO terms by Frequently Seen Words
We use data from a 2014 Nature paper
Step1: 2. Count all words in the significant GO term names.
2a. Get list of significant GO term name... | Python Code:
%run goea_nbt3102_fncs.ipynb
goeaobj = get_goeaobj_nbt3102('fdr_bh')
# Read Nature data from Excel file (~400 study genes)
studygeneid2symbol = read_data_nbt3102()
# Run Gene Ontology Enrichment Analysis using Benjamini/Hochberg FDR correction
geneids_study = studygeneid2symbol.keys()
goea_results_all = go... |
10,512 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I have a Pandas DataFrame that looks something like: | Problem:
import pandas as pd
df = pd.DataFrame({'col1': {0: 'a', 1: 'b', 2: 'c'},
'col2': {0: 1, 1: 3, 2: 5},
'col3': {0: 2, 1: 4, 2: 6},
'col4': {0: 3, 1: 6, 2: 2},
'col5': {0: 7, 1: 2, 2: 3},
'col6': {0: 2, 1: 9, 2: 5},
... |
10,513 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Speci... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'csir-csiro', 'sandbox-3', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: CSIR-CSIRO
Source ID: SANDBOX-3
Topic: Ocnbgchem
Sub-Topics: Tr... |
10,514 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ICPW annual time series
At the Task Force meeting in May 2017, it was decided that the TOC trends analysis should include rolling regressions based on the annually aggregated data (rather th... | Python Code:
# Data paths
clim_xls = (r'C:\Data\James_Work\Staff\Heleen_d_W\ICP_Waters\TOC_Trends_Analysis_2015'
r'\CRU_Climate_Data\cru_climate_summaries.xlsx')
stn_xls = (r'C:\Data\James_Work\Staff\Heleen_d_W\ICP_Waters\TOC_Trends_Analysis_2015'
r'\CRU_Climate_Data\cru_stn_elevs.csv')
chem_fold... |
10,515 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
← Back to Index
Longest Common Subsequence
To motivate dynamic time warping, let's look at a classic dynamic programming problem
Step1: Test
Step2: The time complexity of the above re... | Python Code:
def lcs(x, y):
if x == "" or y == "":
return ""
if x[0] == y[0]:
return x[0] + lcs(x[1:], y[1:])
else:
z1 = lcs(x[1:], y)
z2 = lcs(x, y[1:])
return z1 if len(z1) > len(z2) else z2
Explanation: ← Back to Index
Longest Common Subsequence
To motivate dy... |
10,516 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
QuTiP example
Step1: Hamoltonian
Step2: Dispersive cQED Model Implementation
Step3: The results obtained from the physical implementation agree with the ideal result.
Step4: The gates ar... | Python Code:
%matplotlib inline
import numpy as np
from qutip import *
from qutip.qip.models.circuitprocessor import *
from qutip.qip.models.cqed import *
Explanation: QuTiP example: Physical implementation of Cavity-Qubit model
Author: Anubhav Vardhan (anubhavvardhan@gmail.com)
For more information about QuTiP see htt... |
10,517 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
numpynet from sklearn mnist data set works
numpynet/classy from digits data set doesn't work
trying numpynet with digits data set here works
what is the numpynet/classy difference?
Step1: c... | Python Code:
'''
Little example on how to use the Network class to create a model and perform
a basic classification of the MNIST dataset
'''
#from NumPyNet.layers.input_layer import Input_layer
from NumPyNet.layers.connected_layer import Connected_layer
from NumPyNet.layers.convolutional_layer import Convolutional_lay... |
10,518 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I'm using tensorflow 2.10.0. | Problem:
import tensorflow as tf
x=[b'\xd8\xa8\xd9\x85\xd8\xb3\xd8\xa3\xd9\x84\xd8\xa9',
b'\xd8\xa5\xd9\x86\xd8\xb4\xd8\xa7\xd8\xa1',
b'\xd9\x82\xd8\xb6\xd8\xa7\xd8\xa1',
b'\xd8\xac\xd9\x86\xd8\xa7\xd8\xa6\xd9\x8a',
b'\xd8\xaf\xd9\x88\xd9\x84\xd9\x8a']
def g(x):
return [tf.compat.as_str_any(a) for a... |
10,519 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">TensorFlow Neural Network Lab</h1>
<img src="image/notmnist.png">
In this lab, you'll use all the tools you learned from Introduction to TensorFlow to label images of Engl... | Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
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
from tqdm import tqdm
from zipfile import ZipFile
p... |
10,520 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Examples of many applications with Notebook Launcher
This notebook is a quick(ish) test of most of the main applications people use, taken from fastbook, and ran with Accelerate across mult... | Python Code:
#|all_slow
#|all_multicuda
from fastai.vision.all import *
from fastai.text.all import *
from fastai.tabular.all import *
from fastai.collab import *
from accelerate import notebook_launcher
from fastai.distributed import *
Explanation: Examples of many applications with Notebook Launcher
This notebook is... |
10,521 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Write your Own Perceptron
In our examples, we have seen different algorithms and we could use scikit learn functions to get the paramters. However, do you know how is it implemented? To unde... | Python Code:
# import our packages
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline
Explanation: Write your Own Perceptron
In our examples, we have seen different algorithms and we could use scikit learn functions to get the paramters. However, do you know how is it implemented? To understand ... |
10,522 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using Cytoscape.js in Jupyter Notebook
by Keiichiro Ono
Introduction
If you use Jupyetr Notebook with cyREST, you can script your workflow. And in some cases, you may want to embed the resu... | Python Code:
# Package to render networks in Cytoscape.js
from py2cytoscape import cytoscapejs as cyjs
# And standard JSON utility
import json
Explanation: Using Cytoscape.js in Jupyter Notebook
by Keiichiro Ono
Introduction
If you use Jupyetr Notebook with cyREST, you can script your workflow. And in some cases, you ... |
10,523 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Release of hammer-cli gem
Requirements
push access to https
Step1: Update the following notebook settings
Step2: Ensure the repo is up to date
Step3: Run tests localy
Step4: Update relea... | Python Code:
%cd ..
Explanation: Release of hammer-cli gem
Requirements
push access to https://github.com/theforeman/hammer-cli
push access to rubygems.org for hammer-cli
sudo yum install transifex-client python-slugify asciidoc
ensure neither the git push or gem push don't require interractive auth. If you can't use a... |
10,524 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Playback Using the Notebook Audio Widget
This interface is used often when developing algorithms that involve processing signal samples that result in audible sounds. You will see this in th... | Python Code:
Audio('c_major.wav')
Explanation: Playback Using the Notebook Audio Widget
This interface is used often when developing algorithms that involve processing signal samples that result in audible sounds. You will see this in the tutorial. Processing is done before hand as an analysis task, then the samples ar... |
10,525 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
One of the comments by our manuscript reviewers was on our claim of the 2009 H1N1 and 2013 H7N9 viruses. In order to substantiate our claim of recapitulating their lineages, I w... | Python Code:
import networkx as nx
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import json
from collections import defaultdict
from datetime import datetime, date
from random import randint
from networkx.readwrite.json_graph import node_link_data
%matplotlib inline
G = nx.read_gpickle('201509... |
10,526 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The python-awips package provides access to the entire AWIPS Maps Database for use in Python GIS applications. Map objects are returned as <a href="http
Step1: Request County Boundaries fo... | Python Code:
from __future__ import print_function
from awips.dataaccess import DataAccessLayer
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import numpy as np
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
from cartopy.feature import ShapelyFeature,NaturalEarthFeature
from shap... |
10,527 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multi-Layer Perceptron Inpainting with MNIST
In the MLP demo, we saw how to use the multi-layer VAMP (ML-VAMP) method for denoising with a prior based on a multi-layer perceptron. We illust... | Python Code:
# Add the vampyre path to the system path
import os
import sys
vp_path = os.path.abspath('../../')
if not vp_path in sys.path:
sys.path.append(vp_path)
import vampyre as vp
# Load the other packages
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: Mul... |
10,528 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
BigQuery Pipeline
Google Cloud Datalab, with the pipeline subcommand, enables productionizing (i.e. scheduling and orchestrating) notebooks that accomplish ETL with BigQuery and GCS. It uses... | Python Code:
import datetime
import google.datalab.bigquery as bq
import google.datalab.contrib.bigquery.commands
import google.datalab.contrib.pipeline.airflow
import google.datalab.contrib.pipeline.composer
import google.datalab.kernel
import google.datalab.storage as storage
from google.datalab import Context
projec... |
10,529 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analysis of U.S. Incomes by Occupation and Gender
Notebook by Harish Kesava Rao
Use of this dataset should cite the Bureau of Labor Statistics as per their copyright information
Step1: We a... | Python Code:
import pandas as pd
from pandas import DataFrame, Series
Explanation: Analysis of U.S. Incomes by Occupation and Gender
Notebook by Harish Kesava Rao
Use of this dataset should cite the Bureau of Labor Statistics as per their copyright information: The Bureau of Labor Statistics (BLS) is a Federal governme... |
10,530 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploratory Data Analysis
Author
Step1: The first three lines of code import libraries we are using and renames to shorter names.
Matplotlib is a python 2D plotting library which produces p... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
%matplotlib inline
anscombe_i = pd.read_csv('../datasets/anscombe_i.csv')
anscombe_ii = pd.read_csv('../datasets/anscombe_ii.csv')
anscombe_iii = pd.read_csv('../datasets/anscombe_iii.csv')
anscombe_iv = pd.read_csv('../datasets/anscomb... |
10,531 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
New Term Topics Methods and Document Coloring
Step1: We're setting up our corpus now. We want to show off the new get_term_topics and get_document_topics functionalities, and a good way to ... | Python Code:
from gensim.corpora import Dictionary
from gensim.models import ldamodel
import numpy
%matplotlib inline
Explanation: New Term Topics Methods and Document Coloring
End of explanation
texts = [['bank','river','shore','water'],
['river','water','flow','fast','tree'],
['bank','water','fall','f... |
10,532 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using SGD on MNIST
Background
... about machine learning (a reminder from lesson 1)
The good news is that modern machine learning can be distilled down to a couple of key techniques that are... | Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
from fastai.imports import *
from fastai.torch_imports import *
from fastai.io import *
path = 'data/mnist/'
Explanation: Using SGD on MNIST
Background
... about machine learning (a reminder from lesson 1)
The good news is that modern machine learning c... |
10,533 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Advanced Logistic Regression in TensorFlow 2.0
Learning Objectives
Load a CSV file using Pandas
Create train, validation, and test sets
Define and train a model using Keras (including settin... | Python Code:
# You can use any Python source file as a module by executing an import statement in some other Python source file.
# The import statement combines two operations; it searches for the named module, then it binds the
# results of that search to a name in the local scope.
import tensorflow as tf
from tensorf... |
10,534 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Considering Outliers and Novelty Detection
Step1: Finding more things that can go wrong with your data
Understanding the difference between anomalies and novel data
Examining a Fast and Sim... | Python Code:
import numpy as np
from scipy.stats.stats import pearsonr
np.random.seed(101)
normal = np.random.normal(loc=0.0, scale= 1.0, size=1000)
print 'Mean: %0.3f Median: %0.3f Variance: %0.3f' % (np.mean(normal), np.median(normal), np.var(normal))
outlying = normal.copy()
outlying[0] = 50.0
print 'Mean: %0.3f Med... |
10,535 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Connect to Source and test connection
Using 4 instances
Step1: Enumerate the parameter combinations
Step2: Specify the model changes
(Much like we do when setting up a PEST job)
Step3: Sp... | Python Code:
## Veneer started elsewhere (probably from a command line using veneer.manager.start)
ports = list(range(15004,15008))
ports
bv = BulkVeneer(ports)
v = bv.veneers[1]
network = v.network()
network.as_dataframe().plot()
network.outlet_nodes()
outlet_node = network.outlet_nodes()[0]['properties']['name'] + '$... |
10,536 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
t-SNE Tutorial
Step1: Zklastrowane punkty w 2D
Działanie t-SNE na dwóch oddalonych od siebie klastrach punktów w 2D
Zadanie 1
Napisz funkcję, która pokaże punkty ze zbioru przed oraz po tra... | Python Code:
import numpy as np
import scipy
import sklearn
import matplotlib.pyplot as plt
from functions import *
from sklearn import manifold, datasets
from sklearn.manifold import TSNE
Explanation: t-SNE Tutorial
End of explanation
def plot_2D_cluster(cluster_size, perplexity):
pass
Explanation: Zklastrowane pu... |
10,537 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Finding Lane Lines on the Road
In this project, I will use the OpenCV & Python to identify lane lines on the road. Firstly, I can develop the pipeline on a series of individual images, and l... | Python Code:
#importing some useful packages
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import cv2
%matplotlib inline
import math
Explanation: Finding Lane Lines on the Road
In this project, I will use the OpenCV & Python to identify lane lines on the road. Firstly, I can develo... |
10,538 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multivariate Regression
Let's grab a small little data set of Blue Book car values
Step1: We can use pandas to split up this matrix into the feature vectors we're interested in, and the val... | Python Code:
import pandas as pd
df = pd.read_excel('http://cdn.sundog-soft.com/Udemy/DataScience/cars.xls')
df.head()
Explanation: Multivariate Regression
Let's grab a small little data set of Blue Book car values:
End of explanation
import statsmodels.api as sm
df['Model_ord'] = pd.Categorical(df.Model).codes
X = df[... |
10,539 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Modular neural nets
In the previous HW, we computed the loss and gradient for a two-layer neural network in a single monolithic function. This isn't very difficult for a small two-lay... | Python Code:
# As usual, a bit of setup
import numpy as np
import matplotlib.pyplot as plt
from cs231n.gradient_check import eval_numerical_gradient_array, eval_numerical_gradient
from cs231n.layers import *
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots
plt.rcParams['image.... |
10,540 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: TF Lattice Aggregate Function Models
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Import... | 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... |
10,541 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Built-In Data Structures
Python also has several built-in compound types, which act as containers for other types.
| Type Name | Example |Description ... | Python Code:
a = [2, 3, 5, 7]
Explanation: Built-In Data Structures
Python also has several built-in compound types, which act as containers for other types.
| Type Name | Example |Description |
|-----------|---------------------------|---------------------------------------... |
10,542 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
AMICI documentation example of the steady state solver logic
This is an example to document the internal logic of the steady state solver, which is used in preequilibration and postequilibra... | Python Code:
from IPython.display import Image
fig = Image(filename=('../../../documentation/gfx/steadystate_solver_workflow.png'))
fig
Explanation: AMICI documentation example of the steady state solver logic
This is an example to document the internal logic of the steady state solver, which is used in preequilibratio... |
10,543 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Training a better model
Step1: Are we underfitting?
Our validation accuracy so far has generally been higher than our training accuracy. That leads to two obvious questions
Step2: ...and l... | Python Code:
from theano.sandbox import cuda
%matplotlib inline
from imp import reload
import utils; reload(utils)
from utils import *
from __future__ import division, print_function
#path = "data/dogscats/sample/"
path = "data/dogscats/"
model_path = path + 'models/'
if not os.path.exists(model_path): os.mkdir(model_... |
10,544 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Graph Convolutions
In this tutorial we will learn more about "graph convolutions." These are one of the most powerful deep learning tools for working with molecular data. The... | Python Code:
!pip install --pre deepchem
Explanation: Introduction to Graph Convolutions
In this tutorial we will learn more about "graph convolutions." These are one of the most powerful deep learning tools for working with molecular data. The reason for this is that molecules can be naturally viewed as graphs.
Note h... |
10,545 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Training on Cloud AI Platform</h1>
This notebook illustrates distributed training on Cloud AI Platform (formerly known as Cloud ML Engine).
Step1: Now that we have the TensorFlow code w... | Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
# Ensure the right version of Tensorflow is installed.
!pip freeze | grep tensorflow==2.1
# change these to try this notebook out
BUCKET = 'cloud-training-demos-ml'
PROJECT = 'cloud-training-demos'
REGION = 'us-central1'
import os
os.enviro... |
10,546 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Self-Driving Car Engineer Nanodegree
Deep Learning
Project
Step1: Step 1
Step2: Include an exploratory visualization of the dataset
Visualize the German Traffic Signs Dataset using the pic... | Python Code:
# Load pickled data
import pickle
# TODO: Fill this in based on where you saved the training and testing data
training_file = ?
validation_file=?
testing_file = ?
with open(training_file, mode='rb') as f:
train = pickle.load(f)
with open(validation_file, mode='rb') as f:
valid = pickle.load(f)
with... |
10,547 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chemicals in Cosmetics - Data Bootcamp Report
Manuela Lopez Giraldo
May 12, 2017
Report Outline
Step1: To extract exact figures for current products, it would be best to clean up the datase... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime as dt
%matplotlib inline
import matplotlib as mpl
import sys
url = 'https://chhs.data.ca.gov/api/views/7kri-yb7t/rows.csv?accessType=DOWNLOAD'
CosmeticsData = pd.read_csv(url)
CosmeticsData.head()
Explanation: Chemicals ... |
10,548 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Implementing a basic neural network
By Brett Naul (UC Berkeley)
In this exercise we'll implement and train a simple single-layer neural network classifier using numpy. First, let's create so... | Python Code:
# Imports / plotting configuration
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_context('poster')
plt.rcParams['image.interpolation'] = 'nearest' # hard classification boundaries
plt.rcParams['image.cmap'] = 'viridis'
np.random.seed(13)
# Generate spi... |
10,549 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
練習 Theano 的 Scan Function
Step1: 撰寫一個 A 的 K 次計算函式
[0 1 2 3 4 5 6 7 8 9 ] >>> [ 0. 1. 4. 9. 16. 25. 36. 49. 64. 81.]
k 為 integer ，代表多少次方
a 為 底
Step2: result 為用 tensor 來接
updat... | Python Code:
import theano
import theano.tensor as T
Explanation: 練習 Theano 的 Scan Function
End of explanation
k = T.iscalar('K')
a = T.vector('A')
i = T.vector('A')
result, updates = theano.scan(fn=lambda pre , k : pre*a ,
outputs_info = i,
non_sequences=a,
... |
10,550 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Reading SETI Hackathon Data
This tutorial will show you how to programmatically download the SETI code challenge data to your local file space and
start to analyze it.
Please see the Step_1... | Python Code:
#The ibmseti package contains some useful tools to faciliate reading the data.
#The `ibmseti` package version 1.0.5 works on Python 2.7.
# !pip install --user ibmseti
#A development version runs on Python 3.5.
# !pip install --user ibmseti==2.0.0.dev5
# If running on DSX, YOU WILL NEED TO RESTART YOUR ... |
10,551 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparing initial sampling methods on integer space
Holger Nahrstaedt 2020 Sigurd Carlsen October 2019
.. currentmodule
Step1: Random sampling
Step2: Sobol
Step3: Classic latin hypercube ... | Python Code:
print(__doc__)
import numpy as np
np.random.seed(1234)
import matplotlib.pyplot as plt
from skopt.space import Space
from skopt.sampler import Sobol
from skopt.sampler import Lhs
from skopt.sampler import Halton
from skopt.sampler import Hammersly
from skopt.sampler import Grid
from scipy.spatial.distance ... |
10,552 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Representing text as numerical data
From the scikit-learn documentation
Step1: From the scikit-learn documentation
Step2: From the scikit-learn documentation
Step3: In order to make a pre... | Python Code:
# example text for model training (SMS messages)
simple_train = ['call you tonight', 'Call me a cab', 'please call me... PLEASE!']
# import and instantiate CountVectorizer (with the default parameters)
from sklearn.feature_extraction.text import CountVectorizer
vect = CountVectorizer()
# learn the 'vocabul... |
10,553 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CIFAR10 classification using HOG features
Load CIFAR10 dataset
Step1: Preprocessing
Step2: Lets look how images looks like
Step3: Feature extraction
We use HOG descriptor from scikit-imag... | Python Code:
import myutils
raw_data_training, raw_data_testing = myutils.load_CIFAR_dataset(shuffle=False)
# raw_data_training = raw_data_training[:5000]
class_names = myutils.load_CIFAR_classnames()
n_training = len( raw_data_training )
n_testing = len( raw_data_testing )
print('Loaded CIFAR10 database with {} traini... |
10,554 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numerical Integration
Preliminaries
We have to import the array library numpy and the plotting library matplotlib.pyplot, note that we define shorter aliases for these.
Next we import from n... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from numpy import cos, exp, pi, sin, sqrt
from IPython.display import Latex, display
plt.style.use(['fivethirtyeight', './00_mplrc'])
Explanation: Numerical Integration
Preliminaries
We have to import the array library numpy and the plo... |
10,555 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ordinary Differential Equations
Step1: Part 1 | Python Code:
# Setup
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
# Setup
f0 = 1.
omega0 = 2. * np.pi * f0
a = 1.
Explanation: Ordinary Differential Equations : Practical work on the harmonic oscillator
In this example, you will simulate an harmonic o... |
10,556 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Modelos de Classificação
Este laboratório irá cobrir os passos para tratar a base de dados de taxa de cliques (click-through rate - CTR) e criar um modelo de classificação para tentar determ... | Python Code:
# Data for manual OHE
# Note: the first data point does not include any value for the optional third feature
#from pyspark import SparkContext
#sc =SparkContext()
sampleOne = [(0, 'mouse'), (1, 'black')]
sampleTwo = [(0, 'cat'), (1, 'tabby'), (2, 'mouse')]
sampleThree = [(0, 'bear'), (1, 'black'), (2, 'sa... |
10,557 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Random Basis Functions Test
In this notebook we test our random basis functions against the kernel functions they are designed to approximate. This is a qualitative test in that we just plot... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as pl
from revrand.basis_functions import RandomRBF, RandomLaplace, RandomCauchy, RandomMatern32, RandomMatern52, \
FastFoodRBF, OrthogonalRBF, FastFoodGM, BasisCat
from revrand import Parameter, Positive
# Style
pl.style.use('ggplot')
pl.r... |
10,558 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Equation for Neuron Paper
A dendritic segment can robustly classify a pattern by subsampling a small number of cells from a larger population. Assuming a random distribution of patterns, ... | Python Code:
oxp = Symbol("Omega_x'")
b = Symbol("b")
n = Symbol("n")
theta = Symbol("theta")
s = Symbol("s")
a = Symbol("a")
subsampledOmega = (binomial(s, b) * binomial(n - s, a - b)) / binomial(n, a)
subsampledFpF = Sum(subsampledOmega, (b, theta, s))
subsampledOmegaSlow = (binomial(s, b) * binomial(n - s, a - b))
... |
10,559 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Binary with Spots
Setup
Let's first make sure we have the latest version of PHOEBE 2.0 installed. (You can comment out this line if you don't use pip for your installation or don't want to u... | Python Code:
!pip install -I "phoebe>=2.0,<2.1"
Explanation: Binary with Spots
Setup
Let's first make sure we have the latest version of PHOEBE 2.0 installed. (You can comment out this line if you don't use pip for your installation or don't want to update to the latest release).
End of explanation
%matplotlib inline
i... |
10,560 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Übungsblatt 11
Präsenzaufgaben
Aufgabe 1 Grammatikinduktion
In dieser Aufgabe soll vollautomatisch aus Daten (Syntaxbäumen) eine probabilistische, kontextfreie Grammatik e... | Python Code:
test_sentences = [
"the men saw a car .",
"the woman gave the man a book .",
"she gave a book to the man .",
"yesterday , all my trouble seemed so far away ."
]
import nltk
from nltk.corpus import treebank
from nltk.grammar import ProbabilisticProduction, PCFG
# Production count: the number... |
10,561 | 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)
Explanation: A Simple Autoencoder
We'll start off by building a simple autoencoder to c... |
10,562 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Predicting Movie Review Sentiment with BERT on TF Hub
If you’ve been following Natural Language Processing over the past year, you’ve probably heard of BERT
Step1: In addition to the standa... | Python Code:
from sklearn.model_selection import train_test_split
import pandas as pd
import tensorflow as tf
import tensorflow_hub as hub
from datetime import datetime
Explanation: Predicting Movie Review Sentiment with BERT on TF Hub
If you’ve been following Natural Language Processing over the past year, you’ve prob... |
10,563 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Toplevel
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specif... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'csiro-bom', 'sandbox-3', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: CSIRO-BOM
Source ID: SANDBOX-3
Sub-Topics: Radiative Forcings.
Pr... |
10,564 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Review
Before we start let's do some quick review from last time.
Let's create a new numpy arrray. Fill it with any values you want.
Let's say I want to calculate the average between the 1s... | Python Code:
k = np.array([1,3,5,5,6,6,7,10,23123123,31232]) # create a new array
k
k[1]
k[0]
k[4]
k[10] # even though the list has 9 items, the index actually goes from 0 to 9
k[9]
Explanation: Review
Before we start let's do some quick review from last time.
Let's create a new numpy arrray. Fill it with any values ... |
10,565 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Truck Fleet puzzle
This tutorial includes everything you need to set up decision optimization engines, build constraint programming models.
When you finish this tutorial, you'll have a f... | Python Code:
from sys import stdout
try:
import docplex.cp
except:
if hasattr(sys, 'real_prefix'):
#we are in a virtual env.
!pip install docplex
else:
!pip install --user docplex
Explanation: The Truck Fleet puzzle
This tutorial includes everything you need to set up decision optimi... |
10,566 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vertex AI Pipelines
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Install the latest GA version of google-cloud-pipeline-components library as well.
... | Python Code:
import os
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install --upgrade google-cloud-aiplatform $USER_FLAG
Explanation: Vertex AI Pipelines: AutoML tabular regression pipelines using google-cloud-pipeline-comp... |
10,567 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Translate dataset
The main language of the project is English
Step1: New names are based on the "Nome do Dado" column of the table available at data/2016-08-08-datasets-format.html, not "El... | Python Code:
import pandas as pd
data = pd.read_csv('../data/2016-08-08-AnoAtual.csv')
data.shape
data.head()
data.iloc[0]
Explanation: Translate dataset
The main language of the project is English: works well mixed in programming languages like Python and provides a low barrier for non-Brazilian contributors. Today, t... |
10,568 | Given the following text description, write Python code to implement the functionality described.
Description:
Finding Quadrant of a Coordinate with respect to a Circle
Python3 Program to find the quadrant of a given coordinate w . rt . the centre of a circle ; Thus function returns the quadrant number ; Coincides with... | Python Code:
import math
def getQuadrant(X , Y , R , PX , PY ) :
if(PX == X and PY == Y ) :
return 0 ;
val =(math . pow(( PX - X ) , 2 ) + math . pow(( PY - Y ) , 2 ) ) ;
if(val > pow(R , 2 ) ) :
return - 1 ;
if(PX > X and PY >= Y ) :
return 1 ;
if(PX <= X and PY > Y ) :
return 2 ;
if... |
10,569 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CSCS530 Winter 2016
Complex Systems 530 - Computer Modeling of Complex Systems (Winter 2016)
Course ID
Step1: Initializing a network
In some problems, we can define our own rules to "grow" ... | Python Code:
%matplotlib inline
# Imports
import networkx as nx
import numpy
import matplotlib.pyplot as plt
import pandas
import seaborn; seaborn.set()
seaborn.set_style("darkgrid")
# Import widget methods
from IPython.html.widgets import *
Explanation: CSCS530 Winter 2016
Complex Systems 530 - Computer Modeling of Co... |
10,570 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Single Station Analysis - Historic
Building on the API Exploration Notebook and the Filtering Observed Arrivals notebook. Let's explore a different approach for analyzing the data. Note that... | Python Code:
import datetime
from psycopg2 import connect
import configparser
import pandas as pd
import pandas.io.sql as pandasql
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider
%matplotlib qt
try:
con.close()
except:
print("No existing connection... ... |
10,571 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Gauss integration of Finite Elements
Step1: Predefinition
The constitutive model tensor in Voigt notation (plane strain) is
$$C = \frac{(1 - \nu) E}{(1 - 2\nu) (1 + \nu) }
\begin{pmatrix}
1... | Python Code:
from __future__ import division
from sympy.utilities.codegen import codegen
from sympy import *
from sympy import init_printing
from IPython.display import Image
init_printing()
r, s, t, x, y, z = symbols('r s t x y z')
k, m, n = symbols('k m n', integer=True)
rho, nu, E = symbols('rho, nu, E')
Explanatio... |
10,572 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<table align="left">
<td>
<a href="https
Step1: Restart the kernel
After you install the additional packages, you need to restart the notebook kernel so it can find the packages.
Step... | Python Code:
import sys
if "google.colab" in sys.modules:
USER_FLAG = ""
else:
USER_FLAG = "--user"
! pip3 install -U tensorflow==2.8 $USER_FLAG
! pip3 install --upgrade google-cloud-aiplatform $USER_FLAG
Explanation: <table align="left">
<td>
<a href="https://colab.research.google.com/github/GoogleCloudP... |
10,573 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: Estimators
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Advantages
Similar to a tf.keras... | 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... |
10,574 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
BayesSearchCV
skopt
pip3 install scikit-optimize
BayesSearchCV implements a "fit" and a "score" method. It also implements "predict", "predict_proba", "decision_function", "transform" and "i... | Python Code:
import pandas as pd
import numpy as np
import xgboost as xgb
import lightgbm as lgb
from skopt import BayesSearchCV
from sklearn.model_selection import StratifiedKFold, KFold
%config InlineBackend.figure_format = 'retina'
ITERATIONS = 10 # 1000
TRAINING_SIZE = 100000 # 20000000
TEST_SIZE = 25000
# Load dat... |
10,575 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NNabla by Examples
This tutorial demonstrates how you can write a script to train a neural network by using a simple hand digits classification task.
Note
Step1: The tiny_digits module is l... | Python Code:
!pip install nnabla-ext-cuda100
!git clone https://github.com/sony/nnabla.git
%cd nnabla/tutorial
import nnabla as nn
import nnabla.functions as F
import nnabla.parametric_functions as PF
import nnabla.solvers as S
from nnabla.monitor import tile_images
import numpy as np
import matplotlib.pyplot as plt
im... |
10,576 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using a single Table vs EArray + Table
The PyTables community keep asking what can be considered a FAQ. Namely, should I use a single Table for storing my data, or should I split it in a Ta... | Python Code:
import numpy as np
import tables
tables.print_versions()
LEN_PMT = int(1.2e6)
NPMTS = 12
NEVENTS = 10
!rm PMT*.h5
def gaussian(x, mu, sig):
return np.exp(-np.power(x - mu, 2.) / (2 * np.power(sig, 2.)))
x = np.linspace(0, 1, 1e7)
rd = (gaussian(x, 1, 1.) * 1e6).astype(np.int32)
def raw_data(length):
... |
10,577 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploratory data analysis
Step1: Changes in fatal accidents following legalization?
One interesting source of exogenous variation Colorado and Washington's legalization of cannabis in 2014.... | Python Code:
sb.factorplot(x='HOUR',y='ST_CASE',hue='WEEKDAY',data=counts_df,
aspect=2,order=range(24),palette='nipy_spectral',dodge=.5)
sb.factorplot(x='MONTH',y='ST_CASE',hue='WEEKDAY',data=counts_df,
aspect=2,order=range(1,13),palette='nipy_spectral',dodge=.5)
Explanation: Exploratory dat... |
10,578 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to traverse to GO parents and ancestors
Traverse immediate parents or all ancestors with or without user-specified optional relationships
Parents and Ancestors described
Code to get Pare... | Python Code:
import os
from goatools.obo_parser import GODag
# Load a small test GO DAG and all the optional relationships,
# like 'regulates' and 'part_of'
godag = GODag('../tests/data/i126/viral_gene_silence.obo',
optional_attrs={'relationship'})
Explanation: How to traverse to GO parents and ancestors
... |
10,579 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
solarposition.py tutorial
This tutorial needs your help to make it better!
Table of contents
Step1: SPA output
Step2: Speed tests
Step3: This numba test will only work properly if you hav... | Python Code:
import datetime
# scientific python add-ons
import numpy as np
import pandas as pd
# plotting stuff
# first line makes the plots appear in the notebook
%matplotlib inline
import matplotlib.pyplot as plt
# seaborn makes your plots look better
try:
import seaborn as sns
sns.set(rc={"figure.figsize":... |
10,580 | 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: Lorenz system
The Lorenz system is one of the earliest studied examples of a system of differential equations that exhibits chaotic... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import odeint
from IPython.html.widgets import interact, fixed
Explanation: Ordinary Differential Equations Exercise 1
Imports
End of explanation
def lorentz_derivs(yvec, t, sigma, rho, beta):
Compute the the der... |
10,581 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Statistics for Hackers
An Exploration of Statistics Through Computational Simulation
A talk by Jake VanDerPlas for PyCon 2016
Slides available on speakerdeck
Motivation
There's no shortage o... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
# Suppress all warnings just to keep the notebook nice and clean.
# This must happen after all imports since numpy actually adds its
# RankWarning class back in.
import warnings
warnings.filterwarnings("ignore")
#... |
10,582 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: TFL 레이어로 Keras 모델 만들기
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: 필수 패키지 가져오기
Step3: UCI St... | 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... |
10,583 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Create Bilayer Topology with Stitch
OpenPNM includes numerous tools for manipulating and altering the topology. Most of these are found in the topotools submodule. This example will illustr... | Python Code:
import scipy as sp
import matplotlib.pyplot as plt
%matplotlib inline
# Import OpenPNM and the topotools submodule and initialize the workspace manager
import openpnm as op
from openpnm import topotools as tt
wrk = op.Workspace()
wrk.clear() # Clear the existing workspace (mostly for testing purposes)
wrk... |
10,584 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Create enriched movie dataset from The Movie Database API
MovieLens latest data can be downloaded at http
Step1: Generate random names for each unique user and save to ES
Step2: Enrich mov... | Python Code:
from pyspark.sql.functions import udf, col
from pyspark.sql.types import *
ms_ts = udf(lambda x: int(x) * 1000, LongType())
import csv
from pyspark.sql.types import *
with open("data/ml-latest-small/ratings.csv") as f:
reader = csv.reader(f)
cols = reader.next()
ratings = [l for l in reader]
ra... |
10,585 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SymPy
Step1: <h2>Elementary operations</h2>
Step2: <h2>Algebra<h2>
Step3: <h2>Calculus</h2>
Step5: Illustrating Taylor series
We will define a function to compute the Taylor series expan... | Python Code:
from IPython.display import display
from sympy.interactive import printing
printing.init_printing(use_latex='mathjax')
from __future__ import division
import sympy as sym
from sympy import *
x, y, z = symbols("x y z")
k, m, n = symbols("k m n", integer=True)
f, g, h = map(Function, 'fgh')
Explanation: SymP... |
10,586 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="http
Step1: Now we create a 5 by 5 grid with a spacing (dx and dy) of 1.
We also create an elevation field with value of 1. everywhere, except at the outlet, where the elevation is... | Python Code:
from landlab import RasterModelGrid
import numpy as np
Explanation: <a href="http://landlab.github.io"><img style="float: left" src="../../landlab_header.png"></a>
Setting watershed boundary conditions on a raster grid
This tutorial ilustrates how to set watershed boundary conditions on a raster grid.
Note... |
10,587 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analysis of the input data
What is typical customer/fraudster behavior?
Which type of aggregated information could be useful for the simulator?
Where are structural differences between fraud... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from datetime import datetime, timedelta
import utils_data
from os.path import join
from IPython.display import display
dates_2016 = [datetime(2016, 1, 1) + timedelta(days=i) for i in range(366)]
Explanation: Analysis ... |
10,588 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Outline
Glossary
1. Radio Science using Interferometric Arrays
Previous
Step1: Import section specific modules
Step2: 1.10 The Limits of Single Dish Astronomy
In the previous section ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import HTML
HTML('../style/course.css') #apply general CSS
Explanation: Outline
Glossary
1. Radio Science using Interferometric Arrays
Previous: 1.9 A brief introduction to interferometry
Next: 1.11 Modern Interfe... |
10,589 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Some very basic python
Showing some very basic python, variables, arrays, math and plotting
Step1: Python versions
Python2 and Python3 are still being used today. So safeguard printing betw... | Python Code:
# setting a variable
a = 1.23
# just writing the variable will show it's value, but this is not the recommended
# way, because per cell only the last one will be printed and stored in the out[]
# list that the notebook maintains
a
a+1
# the right way to print is using the official **print** function in... |
10,590 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Práctica 1 - Introducción a Jupyter lab y libreria robots
Introducción a la libreria robots y sus simuladores
Recordando los resultados obtenidos en el documento anterior, tenemos que
Step1:... | Python Code:
def f(x, t):
# Se importan funciones matematicas necesarias
from numpy import cos
# Se desenvuelven las variables que componen al estado
q1, q̇1 = x
# Se definen constantes del sistema
g = 9.81
m1, J1 = 0.3, 0.0005
l1 = 0.2
τ1 = 0
# Se calculan las variables a d... |
10,591 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multiple Kernel Learning
By Saurabh Mahindre - <a href="https
Step1: Introduction
<em>Multiple kernel learning</em> (MKL) is about using a combined kernel i.e. a kernel consisting of a line... | Python Code:
%pylab inline
%matplotlib inline
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
# import all shogun classes
import shogun as sg
from shogun import *
Explanation: Multiple Kernel Learning
By Saurabh Mahindre - <a href="https://github.com/Saurabh7">github.com/Saurabh7</a>
This notebo... |
10,592 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1A.e - TD noté, 27 novembre 2012 (éléments de code pour le coloriage)
Coloriage d'une image, dessin d'une spirale avec matplotlib
Step1: construction de la spirale
On utilise une représent... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 1A.e - TD noté, 27 novembre 2012 (éléments de code pour le coloriage)
Coloriage d'une image, dessin d'une spirale avec matplotlib : éléments de code données avec l'énoncé.
End of ... |
10,593 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="images/JHI_STRAP_Web.png" style="width
Step1: After executing the code cell, you should see a table of values. The table has columns named gene1 and gene2, and rows that are index... | Python Code:
# Define your group, for this exercise
mygroup = "A" # <- change the letter in quotes
# Import Python libraries
import os # This lets us interact with the operating system
import pandas as pd # This allows us to use dataframes
import seaborn as sns # This gives us pretty graphics optio... |
10,594 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Neural network "playground"
imports
Step1: Caffe computation mode
CPU
Step2: GPU
Make sure you enabled GPU suppor, and have a compatible (ie. nvidia) GPU
Step3: Network loading and tests
... | Python Code:
import numpy as np
from cStringIO import StringIO
import matplotlib.pyplot as plt
import caffe
from IPython.display import clear_output, Image, display
import cv2
import PIL.Image
import os
os.chdir("start_deep/")
Explanation: Neural network "playground"
imports
End of explanation
caffe.set_mode_cpu()
Expl... |
10,595 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TfTransform #
Learning Objectives
1. Preproccess data and engineer new features using TfTransform
1. Create and deploy Apache Beam pipeline
1. Use processed data to train taxifare model lo... | Python Code:
!pip install --user apache-beam[gcp]==2.16.0
!pip install --user tensorflow-transform==0.15.0
Explanation: TfTransform #
Learning Objectives
1. Preproccess data and engineer new features using TfTransform
1. Create and deploy Apache Beam pipeline
1. Use processed data to train taxifare model locally then... |
10,596 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Convolutional Networks
So far we have worked with deep fully-connected networks, using them to explore different optimization strategies and network architectures. Fully-connected net... | Python Code:
# As usual, a bit of setup
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.cnn import *
from cs231n.data_utils import get_CIFAR10_data
from cs231n.gradient_check import eval_numerical_gradient_array, eval_numerical_gradient
from cs231n.layers import *
from cs231n.fast_layers impo... |
10,597 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
I will write lot about how statistical inference is done in psychological research. I think however that it will be helpfull to first point out few issues which I think are paramount to all ... | Python Code:
%pylab inline
d= np.loadtxt('b5.dat')
t=np.arange(0,d.size)/12.+1992
plt.plot(t,d)
plt.gca().set_xticks(np.arange(0,d.size/12)+1992)
plt.xlabel('year')
plt.ylabel('product shipments');
Explanation: I will write lot about how statistical inference is done in psychological research. I think however that it w... |
10,598 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Unpaired assembly challenge
You will implement software to assemble a genome from synthetic reads. We supply Python code snippets that you might use or adapt in your solutions, but you don'... | Python Code:
# Download the file containing the reads to "reads.fa" in current directory
! wget http://www.cs.jhu.edu/~langmea/resources/f2020_hw4_reads.fa
# Following line is so we can see the first few lines of the reads file
# from within IPython -- don't paste this into your Python code
! head f2020_hw4_reads.fa
Ex... |
10,599 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: Data Challenge
Files are stored in an S3 bucket. The purpose here is to fully analyze the data and make some predictions.
This workbook was exported to a Python script and the resulti... | Python Code:
def convert_list(query_string):
Parse the query string of the url into a dictionary.
Handle special cases:
- There is a single query "error=True" which is rewritten to 1 if True, else 0.
- Parsing the query returns a dictionary of key-value pairs. The value is a list.
We must get... |
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