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100 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TensorFlow, Mini-Batch/Stochastic GradientDescent With Moment
Step1: Input
Generamos la muestra de grado 5
Step2: Problema
Calcular los coeficientes que mejor se ajusten a la muestra sabie... | Python Code:
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes=True)
%matplotlib inline
import sys
import time
from IPython.display import Image
sys.path.append('/home/pedro/git/ElCuadernillo/ElCuadernillo/20160301_TensorFlowGradientDescentWithMomentum'... |
101 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementat... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of t... |
102 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2021 Google LLC
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the Licens... | Python Code:
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
Explanation: Copyright 2021 Google LLC
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
ht... |
103 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Jupyter Notebooks
Share the compute process with everyone
How to Install
pip3 install jupyter
How to Run
jupyter notebook
Uses
PDF books
Blog posts
Inline graphics
Multiple languages availab... | Python Code:
%%%timeit
maths = list()
for x in range(10):
maths.append(x**x)
%%%timeit
maths = [x**x for x in range(10)]
# maths
Explanation: Jupyter Notebooks
Share the compute process with everyone
How to Install
pip3 install jupyter
How to Run
jupyter notebook
Uses
PDF books
Blog posts
Inline graphics
Multiple ... |
104 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Licensed under the Apache License, Version 2.0 (the "License").
DCGAN
Step1: Import TensorFlow and enable eager execution
Step2: Load the dataset
We ... | Python Code:
# to generate gifs
!pip install imageio
Explanation: Copyright 2018 The TensorFlow Authors.
Licensed under the Apache License, Version 2.0 (the "License").
DCGAN: An example with tf.keras and eager
<table class="tfo-notebook-buttons" align="left"><td>
<a target="_blank" href="https://colab.research.google... |
105 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
My First Query
One of the most powerful features of Marvin 2.0 is ability to query the newly created DRP and DAP databases. You can do this in two ways
Step1: Let's search for galaxies with... | Python Code:
# Python 2/3 compatibility
from __future__ import print_function, division, absolute_import
from marvin import config
config.mode = 'remote'
config.setRelease('MPL-4')
from marvin.tools.query import Query
Explanation: My First Query
One of the most powerful features of Marvin 2.0 is ability to query the ne... |
106 | 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', 'bnu', 'bnu-esm-1-1', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: BNU
Source ID: BNU-ESM-1-1
Topic: Ocean
Sub-Topics: Timestepping Framework, ... |
107 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: Create a TFX pipeline using templates with Local orchestrator
<div class="devsite-table-wrapper"><table class="tfo-notebook-buttons" align="lef... | 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... |
108 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Indexing and Selection
| Operation | Syntax | Result |
|-------------------------------|----------------|-----------|
| Select column | df[col]... | Python Code:
import pandas as pd
import numpy as np
produce_dict = {'veggies': ['potatoes', 'onions', 'peppers', 'carrots'],'fruits': ['apples', 'bananas', 'pineapple', 'berries']}
produce_df = pd.DataFrame(produce_dict)
produce_df
Explanation: Indexing and Selection
| Operation | Syntax | R... |
109 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Breadth First Search, Queue Based Implementation
Implementation
deque is the constructor for a double ended queue.
Step1: The function search takes three arguments to solve a search problem... | Python Code:
from collections import deque
Explanation: Breadth First Search, Queue Based Implementation
Implementation
deque is the constructor for a double ended queue.
End of explanation
def search(start, goal, next_states):
Frontier = deque([start])
Parent = { start: start }
while Frontier:
st... |
110 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2A.data - Matplotlib
Tutoriel sur matplotlib.
Step1: Aparté
Les librairies de visualisation en python se sont beaucoup développées (10 plotting librairies).
La référence reste matplotlib, ... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 2A.data - Matplotlib
Tutoriel sur matplotlib.
End of explanation
#Pour intégrer les graphes à votre notebook, il suffit de faire
%matplotlib inline
#ou alors
%pylab inline
#pylab charge également numpy. C'est la commande du calcul... |
111 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep learning loss functions
Inline plots
Step1: We want to use Theano so that we can use it's auto-differentiation, since I'm too lazy to work out the derivatives of these functions by han... | Python Code:
%matplotlib inline
Explanation: Deep learning loss functions
Inline plots:
End of explanation
import os
import numpy as np
import pandas as pd
import torch, torch.nn as nn, torch.nn.functional as F
from matplotlib import pyplot as plt
import seaborn as sns
sns.set()
EPSILON = 1.0e-12
SAVE_PLOTS = True
Expl... |
112 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Graded = 7/8
Step1: & for multiple parameters
Step2: 2) What genres are most represented in the search results?
Edit your previous printout to also display a list of their genres in the fo... | Python Code:
import requests
response = requests.get('https://api.spotify.com/v1/search?query=lil&type=artist&market=US&limit=50')
Explanation: Graded = 7/8
End of explanation
data = response.json()
data.keys()
artist_data = data['artists']
artist_data.keys()
lil_names = artist_data['items']
#lil_names = list of dictio... |
113 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lab 4
Step1: Load dataset
Step2: Figure 4.1 - Default data set
Step3: 4.3 Logistic Regression
Figure 4.2
Step4: Table 4.1
Step5: scikit-learn
Step6: statsmodels
Step7: Table 4.2
Step8... | Python Code:
# %load ../standard_import.txt
import pandas as pd
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import sklearn.linear_model as skl_lm
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.discriminant_analysis import Quadratic... |
114 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Filtragem no domínio da frequência
As operações de filtragem podem ser realizadas tanto no domínio do espaço quanto de frequência, Os filtros em frequência são normalmente classificados em tr... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import scipy.signal as sci
from numpy.fft import fft2, ifft2
import sys,os
ia898path = os.path.abspath('../../')
if ia898path not in sys.path:
sys.path.append(ia898path)
import ia898.src as ia
f = mpi... |
115 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tvorba obchodní strategie - křížení klouzavých průměrů
Informace o notebooku a modulech
Step1: Rychlý přehled základních běžných typů strategií
Pro automatické obchodování, které využívá an... | Python Code:
NB_VERSION = 1,0
import sys
import datetime
import numpy as np
import pandas as pd
import pandas_datareader as pdr
import pandas_datareader.data as pdr_web
import quandl as ql
from matplotlib import __version__ as matplotlib_version
from seaborn import __version__ as seaborn_version
import statsmodels.api ... |
116 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to Load CSV and Numpy File Types in TensorFlow 2.0
Learning Objectives
Load a CSV file into a tf.data.Dataset.
Load Numpy data
Introduction
In this lab, you load CSV data from a file in... | 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 functools
import numpy as np
... |
117 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Problem set 3 (90 pts)
Important note
Step1: Algorithm must halt before num_iter_fix + num_iter_adapt iterations if the following condition is satisfied $$ \boxed{\|\lambda_k - \lambda_{k-1... | Python Code:
import numpy as np
import scipy as sp
from scipy import sparse
from scipy.sparse import linalg
import networkx as nx
from networkx.linalg.algebraicconnectivity import fiedler_vector
import matplotlib.pyplot as plt
# INPUT:
# A - adjacency matrix (scipy.sparse.csr_matrix)
# num_iter_fix - number of iteratio... |
118 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Red Hat Insights Core
Insights Core is a framework for collecting and processing data about systems. It allows users to write components that collect and transform sets of raw data into type... | Python Code:
import sys
sys.path.insert(0, "../..")
from insights.core import dr
# Here's our component type with the clever name "component."
# Insights Core provides several types that we'll come to later.
class component(dr.ComponentType):
pass
Explanation: Red Hat Insights Core
Insights Core is a framework for ... |
119 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook was created by Mykola Veremchuk (mykola.veremchuk@xfel.eu), Svitozar Serkez. Source and license info is on GitHub. June 2019.
PFS tutorial N4. Converting synchrotron radiation ... | Python Code:
import numpy as np
import logging
from ocelot import *
from ocelot.rad import *
from ocelot.optics.wave import dfl_waistscan, screen2dfl, RadiationField
from ocelot.gui.dfl_plot import plot_dfl, plot_dfl_waistscan
from ocelot import ocelog
ocelog.setLevel(logging.ERROR) #suppress logger output
# Activate i... |
120 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Statistical inference and Estimation Theory
Motivation
Much of data science and machine learning (ML) is concerned with estimation
Step2: Now let us import some Python libraries an... | Python Code:
# Copyright (c) Thalesians Ltd, 2018-2019. All rights reserved
# Copyright (c) Paul Alexander Bilokon, 2018-2019. All rights reserved
# Author: Paul Alexander Bilokon <paul@thalesians.com>
# Version: 1.1 (2019.01.24)
# Previous versions: 1.0 (2018.08.31)
# Email: paul@thalesians.com
# Platform: Tested on W... |
121 | 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', 'pcmdi', 'sandbox-3', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: PCMDI
Source ID: SANDBOX-3
Topic: Ocnbgchem
Sub-Topics: Tracers.
Pr... |
122 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1A.algo - La distance d'édition (correction)
Correction.
Step1: Exercice 1
Step2: Exercice 2
Step3: Que se passe-t-il lorsqu'on enlève la condition or min(len(m1), len(m2)) <= 1 ?
ve... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
def dist_hamming(m1,m2):
d = 0
for a,b in zip(m1,m2):
if a != b :
d += 1
return d
dist_hamming("close", "cloue")
Explanation: 1A.algo - La distance d'édition (correction)
Correction.
End of explanation
def dist... |
123 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Evolution d'indicateurs dans les communes
Step1: Jointure entre 2 fichiers
Step2: Il y a bien les colonnes "status", "mean_altitude", "superficie", "is_metropole" et "metropole_name"
Nom... | Python Code:
commune_metropole = pd.read_csv('data/commune_metropole.csv', encoding='utf-8')
commune_metropole.shape
commune_metropole.head()
insee = pd.read_csv('data/insee.csv',
sep=";", # séparateur du fichier
dtype={'COM' : np.dtype(str)}, # On force la ... |
124 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Executed
Step1: Load software and filenames definitions
Step2: Data folder
Step3: List of data files
Step4: Data load
Initial loading of the data
Step5: Laser alternation selection
At t... | Python Code:
ph_sel_name = "all-ph"
data_id = "7d"
# ph_sel_name = "all-ph"
# data_id = "7d"
Explanation: Executed: Mon Mar 27 11:34:11 2017
Duration: 8 seconds.
usALEX-5samples - Template
This notebook is executed through 8-spots paper analysis.
For a direct execution, uncomment the cell below.
End of explanation
from... |
125 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Spectral Clustering Algorithms
Notebook version
Step1: 1. Introduction
The key idea of spectral clustering algorithms is to search for groups of connected data. I.e, rather than pursuing co... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
# use seaborn plotting defaults
import seaborn as sns; sns.set()
from sklearn.cluster import KMeans
from sklearn.datasets.samples_generator import make_blobs, make_circles
from sklearn.utils import shuffle
from sk... |
126 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
List manipulation in Python
Goal for this assignment
The goal for this assignment is to learn to use the various methods for Python's list data type.
Your name
// put your name here!
Part 1
... | Python Code:
even_numbers = [2, 4, 6, 8, 10, 12, 14]
s1 = even_numbers[1:5] # returns the 2nd through 4th elements
print("s1:", s1)
s2 = even_numbers[2:] # returns the 3rd element thorugh the end
print("s2:", s2)
s3 = even_numbers[:-2] # returns everything but the last two elements
print("s3:", s3)
s4 = even_number... |
127 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial 1 of 3
Step1: A detailed tutorial on dictionaries can be found here. The dict does not offer much functionality aside from basic storage of arbitrary objects, and it is meant to b... | Python Code:
foo = dict() # Create an empty dict
foo['bar'] = 1 # Store an integer under the key 'bar'
print(foo['bar']) # Retrieve the integer stored in 'bar'
Explanation: Tutorial 1 of 3: Getting Started with OpenPNM
This tutorial is intended to show the basic outline of how OpenPNM works, and necessarily ... |
128 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Autoencoder
This notebook demonstrates the invocation of the SystemML autoencoder script, and alternative ways of passing in/out data.
This notebook is supported with SystemML 0.14.0 and abo... | Python Code:
!pip show systemml
import pandas as pd
from systemml import MLContext, dml
ml = MLContext(sc)
print(ml.info())
sc.version
Explanation: Autoencoder
This notebook demonstrates the invocation of the SystemML autoencoder script, and alternative ways of passing in/out data.
This notebook is supported with Syste... |
129 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
#0 Journal paper critique
<center>
<img src=hw_2_data/bale_2005.png width="400"></img>
<img src=hw_2_data/bale_2005_caption.png width="400"></img>
</center>
The figure trying to three messag... | Python Code:
from bokeh.plotting import figure, output_notebook, show
from bokeh.models import HoverTool
from bokeh.layouts import row
import numpy as np
output_notebook()
Explanation: #0 Journal paper critique
<center>
<img src=hw_2_data/bale_2005.png width="400"></img>
<img src=hw_2_data/bale_2005_caption.png width="... |
130 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I want to process a gray image in the form of np.array. | Problem:
import numpy as np
im = np.array([[0,0,0,0,0,0],
[0,0,5,1,2,0],
[0,1,8,0,1,0],
[0,0,0,7,1,0],
[0,0,0,0,0,0]])
mask = im == 0
rows = np.flatnonzero((~mask).sum(axis=1))
cols = np.flatnonzero((~mask).sum(axis=0))
if rows.shape[0] == 0:
result = np.a... |
131 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Enhanced Deep Residual Networks for single-image super-resolution
Author
Step1: Download the training dataset
We use the DIV2K Dataset, a prominent single-image super-resolution dataset wit... | Python Code:
import numpy as np
import tensorflow as tf
import tensorflow_datasets as tfds
import matplotlib.pyplot as plt
from tensorflow import keras
from tensorflow.keras import layers
AUTOTUNE = tf.data.AUTOTUNE
Explanation: Enhanced Deep Residual Networks for single-image super-resolution
Author: Gitesh Chawda<br>... |
132 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fire up graphlab create
Step1: Load some house value vs. crime rate data
Dataset is from Philadelphia, PA and includes average house sales price in a number of neighborhoods. The attribute... | Python Code:
import graphlab
Explanation: Fire up graphlab create
End of explanation
sales = graphlab.SFrame.read_csv('Philadelphia_Crime_Rate_noNA.csv/')
sales
Explanation: Load some house value vs. crime rate data
Dataset is from Philadelphia, PA and includes average house sales price in a number of neighborhoods. T... |
133 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Robust Kalman filtering for vehicle tracking
We will try to pinpoint the location of a moving vehicle with high accuracy from noisy sensor data. We'll do this by modeling the vehicle state a... | Python Code:
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
def plot_state(t,actual, estimated=None):
'''
plot position, speed, and acceleration in the x and y coordinates for
the actual data, and optionally for the estimated data
'''
trajectories = [actual]
if estimated is... |
134 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Energy Meter Examples
Linux Kernel HWMon
More details can be found at https
Step1: Import required modules
Step2: Target Configuration
The target configuration is used to describe and conf... | Python Code:
import logging
from conf import LisaLogging
LisaLogging.setup()
Explanation: Energy Meter Examples
Linux Kernel HWMon
More details can be found at https://github.com/ARM-software/lisa/wiki/Energy-Meters-Requirements#linux-hwmon.
End of explanation
# Generate plots inline
%matplotlib inline
import os
# Supp... |
135 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementat... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of t... |
136 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2D Fast Accurate Fourier Transform
with an extra gpu array for the 33th complex values
Step1: Loading FFT routines
Step2: Initializing Data
Gaussian
Step3: $W$ TRANSFORM FROM AXES-0
After... | Python Code:
import numpy as np
import ctypes
from ctypes import *
import pycuda.gpuarray as gpuarray
import pycuda.driver as cuda
import pycuda.autoinit
from pycuda.compiler import SourceModule
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import math
%matplotlib inline
Explanation: 2D Fast Accura... |
137 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of contents
Mathematical Background
The Null space and its orthogonal
Probabilistic interpretation of the curvature
Code documentation
A convenient basis
The Markov chain
Computation o... | Python Code:
import numpy as np, random, scipy.linalg
Explanation: Table of contents
Mathematical Background
The Null space and its orthogonal
Probabilistic interpretation of the curvature
Code documentation
A convenient basis
The Markov chain
Computation of the curvature
Appendix
Lemmas: the structure of zero modes
Ma... |
138 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Welcome to the jupyter notebook! To run any cell, press Shift+Enter or Ctrl+Enter.
IMPORTANT
Step1: Notebook Basics
A cell contains any type of python inputs (expression, function definiti... | Python Code:
# Useful starting lines
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
%load_ext autoreload
%autoreload 2
Explanation: Welcome to the jupyter notebook! To run any cell, press Shift+Enter or Ctrl+Enter.
IMPORTANT : Please have a look at Help->User Interface Tour and Help->Keyboa... |
139 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Predicting Blood Donations
Step1: Clean Data
Are there any missing values?
Step2: Visualize Data
Table
Step3: Insights from Summary stats table
Step4: Plot data as a scatter plot (w/r 'M... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
data_dir = '../data/raw/'
data_filename = 'blood_train.csv'
df_blood = pd.read_csv(data_dir+data_filename)
df_blood.head()
Explanation: Predicting Blood Donations: Initial Data Exploration
To do:
- Import ... |
140 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lab 4
Ryan Rose
Scientific Computing
9/21/2016
Step1: Loading Fifty Books
First, we load all fifty books from their text files.
Step2: Cleaning up the Data
Next, we create a mapping of tit... | Python Code:
## Imports!
%matplotlib inline
import os
import re
import string
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from matplotlib.mlab import PCA
from scipy.cluster.vq import kmeans, vq
Explanation: Lab 4
Ryan Rose
Scientific Computing
9/21/2016
End of explanation
os.chdir("/home/ryan... |
141 | 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', 'mri', 'mri-esm2-0', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: MRI
Source ID: MRI-ESM2-0
Topic: Ocean
Sub-Topics: Timestepping Framework, Ad... |
142 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interact Exercise 4
Imports
Step2: Line with Gaussian noise
Write a function named random_line that creates x and y data for a line with y direction random noise that has a normal distribut... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from random import randint
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display
Explanation: Interact Exercise 4
Imports
End of explanation
def random_line(m, b, sigma, size=10):
Create a ... |
143 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Loading MDAnalysis
Step1: The Universe
The basic object to load structures and trajectories into MDAnalysis are Universes. Universe take a topology and a trajectory (optional) as arguments
... | Python Code:
import MDAnalysis as mda
mda.__version__
Explanation: Loading MDAnalysis
End of explanation
TOPOLOGY = 'data/adk.psf'
u = mda.Universe(TOPOLOGY)
Explanation: The Universe
The basic object to load structures and trajectories into MDAnalysis are Universes. Universe take a topology and a trajectory (optional)... |
144 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hosted Settings
Step1: Part 1
Step2: Question 3.1. Some stufff
<img src="https | Python Code:
from client.api.notebook import Notebook
ok = Notebook('ipy.ok')
ok.auth(force=True)
Explanation: Hosted Settings:
In a hosted environment such as jupyterhub:
- run pip install okpy>=1.8.2 --upgrade
Local Setting
For Local Dev:
run jupyter notebook from the root ok-client folder
Running from a distr... |
145 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example of using pygosa
We illustrate hereafter the use of the pygosa module.
Step1: We define Sobol use-case, which is very common in case of sensitivity analysis
Step2: Design of experim... | Python Code:
import openturns as ot
import numpy as np
import pygosa
%pylab inline
Explanation: Example of using pygosa
We illustrate hereafter the use of the pygosa module.
End of explanation
model = ot.SymbolicFunction(["x1","x2","x3"], ["sin(x1) + 7*sin(x2)^2 + 0.1*(x3^4)*sin(x1)"])
dist = ot.ComposedDistribution( 3... |
146 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<pre>
함수의 return은 오직 한개의 객체만 리턴한다.
보통 튜플로 리턴을 할 경우 여러개의 변수로 한번에 받게 할 수 있어 마치 return이 여러개의 값을 동시에 리턴하는 것처럼 보이지만
튜플이라는 객체 하나를 리턴하는 것이다.
</pre>
Step1: 함수가 생성되면 함수 자체도 객체이다. 그리고 그객체의 주소를 swap라... | Python Code:
def swap(a,b):
return b,a #튜플이 반환된다.
a = 1
b = 2
a,b = swap(a,b)
print(a,b)
print(swap)
Explanation: <pre>
함수의 return은 오직 한개의 객체만 리턴한다.
보통 튜플로 리턴을 할 경우 여러개의 변수로 한번에 받게 할 수 있어 마치 return이 여러개의 값을 동시에 리턴하는 것처럼 보이지만
튜플이라는 객체 하나를 리턴하는 것이다.
</pre>
End of explanation
def intersect(prelist, postlist):
re... |
147 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Сравнение S4G и 2MASS массовых моделей
Идея в том, чтобы сравнить полные массы галактик из S4G и из 2MASS фотометрии, чтобы понять, почему диски так недооцениваются.
Данные из https
Step1: ... | Python Code:
sun_abs_mags = {'U' : 5.61,
'B' : 5.48,
'V' : 4.83,
'R' : 4.42,
'I' : 4.08,
'J' : 3.64,
'H' : 3.32,
'K' : 3.28,
'3.6' : 3.24, # Oh et al. 2008
'u' : 6.77, #SDSS ba... |
148 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Revision control software
J.R. Johansson (jrjohansson at gmail.com)
The latest version of this IPython notebook lecture is available at http
Step1: In any software development, one of the m... | Python Code:
from IPython.display import Image
Explanation: Revision control software
J.R. Johansson (jrjohansson at gmail.com)
The latest version of this IPython notebook lecture is available at http://github.com/jrjohansson/scientific-python-lectures.
The other notebooks in this lecture series are indexed at http://j... |
149 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
0. Preparation and setup
One Python library that makes GraphX support available to our Jupyter notebooks is not yet bound to the runtime by default.
To get it added to the Spark context you... | Python Code:
!pip install --user --upgrade --no-deps pixiedust
Explanation: 0. Preparation and setup
One Python library that makes GraphX support available to our Jupyter notebooks is not yet bound to the runtime by default.
To get it added to the Spark context you have to use the !pip magic cell command install first... |
150 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tiingo-Python
This notebook shows basic usage of the tiingo-python library. If you're running this on mybinder.org, you can run this code without installing anything on your computer. You ca... | Python Code:
TIINGO_API_KEY = 'REPLACE-THIS-TEXT-WITH-A-REAL-API-KEY'
# This is here to remind you to change your API key.
if not TIINGO_API_KEY or (TIINGO_API_KEY == 'REPLACE-THIS-TEXT-WITH-A-REAL-API-KEY'):
raise Exception("Please provide a valid Tiingo API key!")
from tiingo import TiingoClient
config = {
'a... |
151 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
General info on the fullCyc dataset (as it pertains to SIPSim validation)
Simulating 12C gradients
Determining if simulated taxon abundance distributions resemble the true distributions
Simu... | Python Code:
%load_ext rpy2.ipython
%%R
workDir = '/home/nick/notebook/SIPSim/dev/fullCyc/'
physeqDir = '/home/nick/notebook/SIPSim/dev/fullCyc_trim/'
physeqBulkCore = 'bulk-core_trm'
physeqSIP = 'SIP-core_unk_trm'
ampFragFile = '/home/nick/notebook/SIPSim/dev/bac_genome1147/validation/ampFrags_kde.pkl'
Explanation: Ge... |
152 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Here I'm process by chunks the entire region.
Step1: Algorithm for processing Chunks
Make a partition given the extent
Produce a tuple (minx ,maxx,miny,maxy) for each element on the partiti... | Python Code:
# Load Biospytial modules and etc.
%matplotlib inline
import sys
sys.path.append('/apps')
import django
django.setup()
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
## Use the ggplot style
plt.style.use('ggplot')
from external_plugins.spystats import tools
%run ../testvariogram.py
... |
153 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Self-Driving Car Engineer Nanodegree
Project
Step1: Read in an Image
Step10: Ideas for Lane Detection Pipeline
Some OpenCV functions (beyond those introduced in the lesson) that might be u... | 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 pdb
Explanation: Self-Driving Car Engineer Nanodegree
Project: Finding Lane Lines on the Road
In this project, you will use the tools you learned about in... |
154 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Country Converter
The country converter (coco) is a Python package to convert country names into different classifications and between different naming versions. Internally it uses regular e... | Python Code:
import country_converter as coco
converter = coco.CountryConverter()
Explanation: Country Converter
The country converter (coco) is a Python package to convert country names into different classifications and between different naming versions. Internally it uses regular expressions to match country names.
... |
155 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Case study
Step1: 3. Normalization of dataset A with entry sensing
Step2: 3. Normalization of dataset B with blind normalization | Python Code:
# Setup of general parameters for the recovery experiment.
n_restarts = 10
rank = 6
n_measurements = 2800
shape = (50, 70) # samples, features
missing_fraction = 0.1
noise_amplitude = 2.0
m_blocks_size = 5 # size of each block
correlation_threshold = 0.75
correlation_strength = 1.0
bias_model = 'image'
# C... |
156 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hand Following example
In this notebook, you will use Pypot and an Inverse Kinematics toolbox to make Torso's hands follow each other.
Your Torso has two arms, and you can use simple methods... | Python Code:
import time
import numpy as np
from pypot.creatures import PoppyTorso
Explanation: Hand Following example
In this notebook, you will use Pypot and an Inverse Kinematics toolbox to make Torso's hands follow each other.
Your Torso has two arms, and you can use simple methods to get and set the position of ea... |
157 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tramp Steamer Problem
Al Duke 3/11/2022
<p style="text-align
Step1: I will encode the graph as a python dictionary. Each vertex is a key. The value for this key is another dictionary. Thi... | Python Code:
graph = {
"A": {"B": (12, 3), "C":(25, 6), },
"B": {"C": (11, 2), },
"C": {"A": (30, 6), "D": (16, 4), },
"D": {"A": (12, 2), },
}
Explanation: Tramp Steamer Problem
Al Duke 3/11/2022
<p style="text-align: center"> <b>Figure 1. Tramp Steamer</b> </p>
Imagine you own a cargo ship that ... |
158 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Setting up a PEST interface from MODFLOW6 using the PstFrom class
The PstFrom class is a generalization of the prototype PstFromFlopy class. The generalization in PstFrom means users need to... | Python Code:
import os
import shutil
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import pyemu
import flopy
Explanation: Setting up a PEST interface from MODFLOW6 using the PstFrom class
The PstFrom class is a generalization of the prototype PstFromFlopy class. The generalization in PstFrom me... |
159 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualize the hyperparameter tuning process
Author
Step1: Introduction
KerasTuner prints the logs to screen including the values of the
hyperparameters in each trial for the user to monitor... | Python Code:
!pip install keras-tuner -q
Explanation: Visualize the hyperparameter tuning process
Author: Haifeng Jin<br>
Date created: 2021/06/25<br>
Last modified: 2021/06/05<br>
Description: Using TensorBoard to visualize the hyperparameter tuning process in KerasTuner.
End of explanation
import numpy as np
import k... |
160 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this notebook a simple Q learner will be trained and evaluated. The Q learner recommends when to buy or sell shares of one particular stock, and in which quantity (in fact it determines t... | Python Code:
# Basic imports
import os
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime as dt
import scipy.optimize as spo
import sys
from time import time
from sklearn.metrics import r2_score, median_absolute_error
from multiprocessing import Pool
%matplotlib inline
%pylab inline
... |
161 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Non-linear power flow after LOPF
In this example, the dispatch of generators is optimised using the linear OPF, then a non-linear power flow is run on the resulting dispatch.
Data sources
Gr... | Python Code:
import pypsa
import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
%matplotlib inline
network = pypsa.examples.scigrid_de(from_master=True)
Explanation: Non-linear power flow after LOPF
In this example, the dispatch of generators is optimised using the ... |
162 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
문서 전처리
모든 데이터 분석 모형은 숫자로 구성된 고정 차원 벡터를 독립 변수로 하고 있으므로 문서(document)를 분석을 하는 경우에도 숫자로 구성된 특징 벡터(feature vector)를 문서로부터 추출하는 과정이 필요하다. 이러한 과정을 문서 전처리(document preprocessing)라고 한다.
BOW (Bag of W... | Python Code:
from sklearn.feature_extraction.text import CountVectorizer
corpus = [
'This is the first document.',
'This is the second second document.',
'And the third one.',
'Is this the first document?',
'The last document?',
]
vect = CountVectorizer()
vect.fit(corpus)
vect.vocabulary_
vect.t... |
163 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Euler's method
We look at numerically solving differential equations. Most scientific software packages already include a wide variety of numerical integrators. Here we'll write our own simp... | Python Code:
%matplotlib inline
import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt
def input(t):
f = np.cos(t)
return f
def msd(state, t, m, c, k):
x, xd = state
pos_dot = xd
vel_dot = 1/m*(input(t) - c*xd - k*x)
state_dot = [pos_dot, vel_dot]
return state_... |
164 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: Introduction to Tensors
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Tensors are multi-d... | 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... |
165 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DAT210x - Programming with Python for DS
Module5- Lab6
Step1: A Convenience Function
This method is for your visualization convenience only. You aren't expected to know how to put this toge... | Python Code:
import random, math
import pandas as pd
import numpy as np
import scipy.io
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot') # Look Pretty
# Leave this alone until indicated:
Test_PCA = False
Explanation: DAT210x - Programming with Python for DS
Module5-... |
166 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian Linear Regression
Step1: From
Step2: Next, let's create vectors of our ages and heights.
Step3: Now let's visualize our data to make sure that linear regression is appropriate fo... | Python Code:
from __future__ import print_function, division
% matplotlib inline
import warnings
warnings.filterwarnings('ignore')
import math
import numpy as np
from thinkbayes2 import Pmf, Cdf, Suite, Joint, EvalNormalPdf
import thinkplot
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Bayesian Linea... |
167 | Given the following text description, write Python code to implement the functionality described.
Description:
Find a triplet that sum to a given value
returns true if there is triplet with sum equal to ' sum ' present in A [ ] . Also , prints the triplet ; Sort the elements ; Now fix the first element one by one and f... | Python Code:
def find3Numbers(A , arr_size , sum ) :
A . sort()
for i in range(0 , arr_size - 2 ) :
l = i + 1
r = arr_size - 1
while(l < r ) :
if(A[i ] + A[l ] + A[r ] == sum ) :
print("Triplet ▁ is ", A[i ] , ' , ▁ ' , A[l ] , ' , ▁ ' , A[r ] ) ;
return True
elif(A[i ] + A[l ] + A[r ] < sum ) :... |
168 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
3 Types, Functions and Flow Control
Data types
Step1: Numbers
Step2: If this should not make sense, you can print some documentation
Step3: Strings
Step4: Slicing
Step5: String Operatio... | Python Code:
x_int = 3
x_float = 3.
x_string = 'three'
x_list = [3, 'three']
type(x_float)
type(x_string)
type(x_list)
Explanation: 3 Types, Functions and Flow Control
Data types
End of explanation
abs(-1)
import math
math.floor(4.5)
math.exp(1)
math.log(1)
math.log10(10)
math.sqrt(9)
round(4.54,1)
Explanation: Numbers... |
169 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Get the Data
Step2: Get the regions and color them
Step5: Build the plot
We build it using html to use the html slider widget instead of the ipython widget. This makes the plot more... | Python Code:
# Links via http://www.gapminder.org/data/
population_url = "http://spreadsheets.google.com/pub?key=phAwcNAVuyj0XOoBL_n5tAQ&output=xls"
fertility_url = "http://spreadsheets.google.com/pub?key=phAwcNAVuyj0TAlJeCEzcGQ&output=xls"
life_expectancy_url = "http://spreadsheets.google.com/pub?key=tiAiXcrneZrUnnJ9... |
170 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Binary logistic regression using Sklearn
Step2: PyTorch data and model
Step3: BFGS
Step4: SGD
Step5: Momentum
Step6: SPS | Python Code:
!pip install git+https://github.com/IssamLaradji/sps.git
import sklearn
import scipy
import scipy.optimize
import matplotlib.pyplot as plt
from mpl_toolkits import mplot3d
from mpl_toolkits.mplot3d import Axes3D
import seaborn as sns
import warnings
warnings.filterwarnings("ignore")
import itertools
import... |
171 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Numerical Summaries of Data
Congratulations, you have some data. Now what? Well, ideally, you'll have a research question to match. In practice, that's not always true or even possibl... | Python Code:
import os
import requests
# get some CSV data from the SDSS SQL server
URL = "http://skyserver.sdss.org/dr12/en/tools/search/x_sql.aspx"
cmd =
SELECT TOP 10000
p.u, p.g, p.r, p.i, p.z, s.class, s.z, s.zerr
FROM
PhotoObj AS p
JOIN
SpecObj AS s ON s.bestobjid = p.objid
WHERE
p.u BETWEEN 0 A... |
172 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Definition of model variables
Model domain / grid parameters
Step1: Definition of wave parameters
Step2: Definition of sediment parameters
Step3: Model initialisation function
Loading the... | Python Code:
file1='../data/gbr_south.csv'
file2='../data/topoGBR1000.csv'
# Bathymetric filename
bfile = file1
# Resolution factor
rfac = 4
Explanation: Definition of model variables
Model domain / grid parameters
End of explanation
# Wave heights (m)
H0 = 2
# Define wave source direction at boundary
# (angle in degr... |
173 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using FISSA with Suite2p
suite2p is a blind source separation toolbox for cell detection and signal extraction.
Here we illustrate how to use suite2p to detect cell locations, and then use ... | Python Code:
# FISSA toolbox
import fissa
# suite2p toolbox
import suite2p
# For plotting our results, use numpy and matplotlib
import matplotlib.pyplot as plt
import numpy as np
Explanation: Using FISSA with Suite2p
suite2p is a blind source separation toolbox for cell detection and signal extraction.
Here we illustr... |
174 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
EITC Housing Benefits
In this notebook, we try to estimate the cost of a hypothetical EITC program to aid with rental housing payments. The aim is to supply a family with enough EITC to have... | Python Code:
##Load modules and set data path:
import pandas as pd
import numpy as np
import numpy.ma as ma
import re
data_path = "C:/Users/SpiffyApple/Documents/USC/RaphaelBostic/EITChousing"
output_container = {}
#################################################################
################### load tax data #####... |
175 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<hr>
<h1>Predicting Benign and Malignant Classes in Mammograms Using Thresholded Data</h1>
<p>Jay Narhan</p>
June 2017
This is an application of the best performing models but using threshol... | Python Code:
import os
import sys
import time
import numpy as np
from tqdm import tqdm
import sklearn.metrics as skm
from sklearn import metrics
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
from skimage import color
import keras.callbacks as cb
import keras.utils.np_utils as np_utils... |
176 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fast chem_evol
Created by Benoit Côté
This notebook presents and tests the pre_calculate_SSPs implementation in chem_evol.py. When many timesteps are required in OMEGA, the computational ti... | Python Code:
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from NuPyCEE import omega
from NuPyCEE import sygma
Explanation: Fast chem_evol
Created by Benoit Côté
This notebook presents and tests the pre_calculate_SSPs implementation in chem_evol.py. When many timesteps are required in OMEGA, the... |
177 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Flint, MI water crisis - part II
Student names
Type the names of everybody in your group here!
Learning Goals (why are we asking you to do this?)
As discussed in last class, there are tw... | Python Code:
# THIS CELL READS IN THE FLINT DATASET - DO NOT CHANGE ANYTHING!
# Make plots inline
%matplotlib inline
# Make inline plots vector graphics instead of raster graphics
from IPython.display import set_matplotlib_formats
set_matplotlib_formats('pdf', 'svg')
# import modules for plotting and data analysis
impo... |
178 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Encoder-Decoder Analysis
Model Architecture
Step1: Perplexity on Each Dataset
Step2: Loss vs. Epoch
Step3: Perplexity vs. Epoch
Step4: Generations
Step5: BLEU Analysis
Step6: N-pairs B... | Python Code:
report_file = '/Users/bking/IdeaProjects/LanguageModelRNN/experiment_results/encdec_noing15_bow_200_512_04drb/encdec_noing15_bow_200_512_04drb.json'
log_file = '/Users/bking/IdeaProjects/LanguageModelRNN/experiment_results/encdec_noing15_bow_200_512_04drb/encdec_noing15_bow_200_512_04drb_logs.json'
import ... |
179 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Classify Data
Create a classifier for different kinds of plankton using supervised machine learning
Executing this Notebook requires a personal STOQS database. Follow the steps to build you... | Python Code:
from contrib.analysis.classify import Classifier
c = Classifier()
Explanation: Classify Data
Create a classifier for different kinds of plankton using supervised machine learning
Executing this Notebook requires a personal STOQS database. Follow the steps to build your own development system — this ... |
180 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Least squares fitting of models to data
This is a quick introduction to statsmodels for physical scientists (e.g. physicists, astronomers) or engineers.
Why is this needed?
Because most of s... | Python Code:
import numpy as np
import pandas as pd
import statsmodels.api as sm
Explanation: Least squares fitting of models to data
This is a quick introduction to statsmodels for physical scientists (e.g. physicists, astronomers) or engineers.
Why is this needed?
Because most of statsmodels was written by statistici... |
181 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Before we get started, a couple of reminders to keep in mind when using iPython notebooks
Step2: Fixing Data Types
Step4: Note when running the above cells that we are actively chan... | Python Code:
import unicodecsv
## Longer version of code (replaced with shorter, equivalent version below)
# enrollments = []
# f = open('enrollments.csv', 'rb')
# reader = unicodecsv.DictReader(f)
# for row in reader:
# enrollments.append(row)
# f.close()
with open('enrollments.csv', 'rb') as f:
reader = unico... |
182 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create Data
Step2: Create An Index Using The Column 'pid' As The Unique ID | Python Code:
# Ignore
%load_ext sql
%sql sqlite://
%config SqlMagic.feedback = False
Explanation: Title: Create An Index For A Table
Slug: create_index_for_a_table
Summary: Create An Index For A Table in SQL.
Date: 2016-05-01 12:00
Category: SQL
Tags: Basics
Authors: Chris Albon
Note: This tutorial was written u... |
183 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1.9 查找两字典的相同点
怎样在两字典中寻找相同点（相同的key or 相同的 value）
Step1: 为寻找两字典的相同点 可通过简单的在两字典keys() or items() method 中Return 结果 进行set 操作
Step2: 以上操作亦可用于修改or过滤dict element <br> if you want 以现有dict 来构造一个... | Python Code:
a = {
'x':1,
'y':2,
'z':3
}
b = {
'w':10,
'x':11,
'y':2
}
# In a ::: x : 1 ,y : 2
# In b ::: x : 11,y : 2
Explanation: 1.9 查找两字典的相同点
怎样在两字典中寻找相同点（相同的key or 相同的 value）
End of explanation
# Find keys in common
kc = a.keys() & b.keys()
print('a 和 b 共有的键',kc)
# Find keys in a that are n... |
184 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of Contents
Step1: Distribution of Passengers
Gender - Analysis | Graph
<a id="Gender - Analysis | Graph"></a>
Distribution of Genders in Passenger Population
Step2: Distribution o... | Python Code:
# Imports for pandas, and numpy
import numpy as np
import pandas as pd
# imports for seaborn to and matplotlib to allow graphing
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style="whitegrid")
%matplotlib inline
# import Titanic CSV - NOTE: adjust file path as neccessary
dTitTrain_DF = p... |
185 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href='http
Step1: Clean Up
Let's clean this up just a little!
Step2: Step 2
Step3: Decomposition
ETS decomposition allows us to see the individual parts!
Step5: Testing for Stationari... | Python Code:
import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
%matplotlib inline
df = pd.read_csv('monthly-milk-production-pounds-p.csv')
df.head()
df.tail()
Explanation: <a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>
<center>Copyright... |
186 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Introduction
This notebook generates the various data representations in lecture 12. It is easy to generalize this to other applications.
Step2: Stem and leaf
The code below shows ho... | Python Code:
from __future__ import division
import matplotlib.pyplot as plt
import matplotlib as mpl
import palettable
import numpy as np
import math
import seaborn as sns
from collections import defaultdict
%matplotlib inline
# Here, we customize the various matplotlib parameters for font sizes and define a color sch... |
187 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dense Communities in Networks
In this problem, we study the problem of finding dense communities in networks. Assume $G$ = ($V,E$) is an undirected graph (e.g., representing a social network... | Python Code:
%pylab inline
import pylab
def initialVertices(numNodes):
V = set();
for i in range(numNodes):
V.add(i);
return V;
def initializeDeg(deg, S):
for s in S:
deg[s] = 0;
def computeDegree(S, edgesfile):
fedges = open(edgesfile, 'r');
deg = {};
initializeDeg(deg, ... |
188 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook was created by Sergey Tomin for Workshop
Step1: Change RF parameters for the comparison with ASTRA
Step2: Initializing SpaceCharge
Step3: Comparison with ASTRA
Beam tracking... | Python Code:
# the output of plotting commands is displayed inline within frontends,
# directly below the code cell that produced it
%matplotlib inline
from time import time
# this python library provides generic shallow (copy) and deep copy (deepcopy) operations
from copy import deepcopy
# import from Ocelot main m... |
189 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visual Diagnosis of Text Analysis with Baleen
This notebook has been created as part of the Yellowbrick user study. I hope to explore how visual methods might improve the workflow of text cl... | Python Code:
%matplotlib inline
import os
import sys
import nltk
import pickle
# To import yellowbrick
sys.path.append("../..")
Explanation: Visual Diagnosis of Text Analysis with Baleen
This notebook has been created as part of the Yellowbrick user study. I hope to explore how visual methods might improve the work... |
190 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Define the Data Generating Distribution
To examine different approximations to the true loss surface of a particular data generating distribution $P(X,Y)$ we must first define it. We will wo... | Python Code:
import numpy as np
class P():
def __init__(self, m, s):
self.m = m # Slope of line
self.s = s # Standard deviation of injected noise
def sample(self, size):
x = np.random.uniform(size=size)
y = []
for xi in x:
y.app... |
191 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Convolutional Generative Adversarial Network (DCGAN) Tutorial
This tutorials walks through an implementation of DCGAN as described in Unsupervised Representation Learning with Deep Conv... | Python Code:
#Import the libraries we will need.
import tensorflow as tf
import numpy as np
import input_data
import matplotlib.pyplot as plt
import tensorflow.contrib.slim as slim
import os
import scipy.misc
import scipy
Explanation: Deep Convolutional Generative Adversarial Network (DCGAN) Tutorial
This tutorials wal... |
192 | 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', 'uhh', 'sandbox-3', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: UHH
Source ID: SANDBOX-3
Sub-Topics: Radiative Forcings.
Properties: 85... |
193 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LAB 6
Step1: Step 3
Step2: Run the below cell, and copy the output into the Google Cloud Shell | Python Code:
%%bash
# Check your project name
export PROJECT=$(gcloud config list project --format "value(core.project)")
echo "Your current GCP Project Name is: "$PROJECT
import os
os.environ["BUCKET"] = "your-bucket-id-here" # Recommended: use your project name
Explanation: LAB 6: Serving baby weight predictions
Lea... |
194 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example of physical analysis with IPython
Step1: Reading simulation data
Step2: Looking at data, taking first rows
Step3: Plotting some feature
Step5: Adding interesting features
for eac... | Python Code:
%pylab inline
import numpy
import pandas
import root_numpy
folder = '/moosefs/notebook/datasets/Manchester_tutorial/'
Explanation: Example of physical analysis with IPython
End of explanation
def load_data(filenames, preselection=None):
# not setting treename, it's detected automatically
data = roo... |
195 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python for Probability, Statistics, and Machine Learning
Step1: Useful Inequalities
In practice, few quantities can be analytically calculated. Some knowledge
of bounding inequalities helps... | Python Code:
from pprint import pprint
import textwrap
import sys, re
Explanation: Python for Probability, Statistics, and Machine Learning
End of explanation
import sympy
import sympy.stats as ss
t=sympy.symbols('t',real=True)
x=ss.ChiSquared('x',1)
Explanation: Useful Inequalities
In practice, few quantities can be a... |
196 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Instalação do Pygame
O programa abaixo usa o Pygame e descreve como se pode criar uma janela de titulo "O PyGame é fixe!"
Para isso crie um novo ficheiro no menu File do IDLE, seleccionando ... | Python Code:
# Importa o modulo com o pygame
import pygame_sdl2 as pygame
# Inicia o motor de jogo
pygame.init()
# Indica as dimensões da janela
size=[700,500]
screen=pygame.display.set_mode(size)
# Escreve titulo na Janela
pygame.display.set_caption("O PyGame é fixe!")
# Usado para controlar a velocidade com que a ja... |
197 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tuples
Tuples are just like lists, but you can't change their values. The values that you give it first up, are the values that you are stuck with for the rest of the program. Again, each va... | Python Code:
months = ('January','February','March','April','May','June',\
'July','August','September','October','November',' December')
Explanation: Tuples
Tuples are just like lists, but you can't change their values. The values that you give it first up, are the values that you are stuck with for the rest of the pr... |
198 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Let's get some JSON data from the web - both a point layer and a polygon GeoJson dataset with some population data.
Step1: And take a look at what our data looks like
Step2: Look how far t... | Python Code:
import geopandas
states = geopandas.read_file(
"https://rawcdn.githack.com/PublicaMundi/MappingAPI/main/data/geojson/us-states.json",
driver="GeoJSON",
)
cities = geopandas.read_file(
"https://d2ad6b4ur7yvpq.cloudfront.net/naturalearth-3.3.0/ne_50m_populated_places_simple.geojson",
driver="... |
199 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Boletins de ocorrência registrados na Grande São Paulo em 2016
Neste passo-a-passo analisaremos um conjunto de dados referente às ocorrências policiais registradas na Grande São Paulo durant... | Python Code:
import numpy
import pandas
from matplotlib import pyplot
%matplotlib inline
pyplot.style.use('fivethirtyeight')
pyplot.rcParams['figure.figsize'] = [11, 8]
url = '../dat/boletins_ocorrencia_sp_clean_2016.csv.gz'
dat = pandas.read_csv(url, encoding='ISO-8859-1', low_memory=False)
dat.describe()
dat.head()
E... |
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