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class fileclass:
def __init__(self, input):
self.Filename = input
self.Size = os.path.getsize(input)
def summary(self):
print(f'File is named {self.Filename} and has size {self.Size}')
def __lt__(obj1, obj2):
if obj1.Size<obj2.Size:
print(f'{obj1.Filename} is smaller than {obj2.Filename}\n')
if obj2.Size<obj1.Size:
classdef fileclass
properties
Filename
Size
end
methods
function obj = fileclass(inputfile)
obj.Filename = inputfile;
% Example x,y,z
x = [-15:1:1];
y = sin(x/2);
z = (x/10).^3;
figure('color','w'); plot3(x,y,z,'o-','markersize',8,'color',[1,.5,.5],'linewidth',2,'markerfacecolor','k'); grid on
coords_tbl = array2table([x',y',z']);
zlims = get(gca,'ZLim')
set(gca,'nextplot','add','linewidth',1);
@neurojojo
neurojojo / joydivisionplot.m
Created March 12, 2022 19:46
joydivisionplot.m
figure('color','w'); ax = axes('nextplot','add');
yd = 2; % Alter this variable to space your Tseries further apart on the y-axis
rowfun( @(cellnumber,tseries) plot(ax,1+tseries{1}+yd*cellnumber,'color','k'),...
mytable(:,{'CellNumber','Tseries'}) )
set(ax,'YTick',[],'YColor','w','TickDir','out')
dictionary_of_texts = dict()
for filename,pdf_text in zip(files,pdf_as_text):
if len( pdf_text )!=0:
dictionary_of_texts[filename] = pdf_text
try:
for filename,pdf_text in zip(problem_pdfs,image_pdf_text):
dictionary_of_texts[filename] = pdf_text
except:
# Variables:
# (1) pdf_as_text
# where some list elements are empty because an attempt was made to
# read in a PDF that is a scanned image (not typed text)
# (2) files
# a list of file names and paths to the PDFs
!apt-get install poppler-utils
!pip install pdf2image
import pickle, yfinance as yf
stock_tseries_df = pd.DataFrame()
for x in ssr_database.iterrows():
try:
thisstock = yf.download( x[1].Ticker, start=x[1].Datetime.date(), end=x[1].NextDay.date(), interval = '30m' )
tmp = pd.DataFrame( [ x[1].Ticker, x[1].Datetime, x[1].NextDay, \
thisstock['Close'].values[0:13],thisstock['Close'].values[14:],\
import pickle
stock_tseries_df = pd.DataFrame()
for x in ssr_database.iterrows():
try:
thisstock = yf.download( x[1].Ticker, start=x[1].Datetime.date(), end=x[1].NextDay.date(), interval = '30m' )
tmp = pd.DataFrame( [ x[1].Ticker, x[1].Datetime, x[1].NextDay, thisstock['Close'].values[0:13],thisstock['Close'].values[14:],thisstock['Volume'].values[0:13],thisstock['Volume'].values[14:]] ).transpose()
stock_tseries_df = pd.concat( [stock_tseries_df,tmp] )
import re, pandas as pd
from dateutil import parser
lines = [];
with open('ssr.csv','r') as f:
while 1:
myline = f.readline()
if re.search('[A-Z]+,',myline) is not None: # A line containing stock information
lines.append( [re.search('[A-Z]+',myline).group(0),\
import requests
import urllib3
from datetime import datetime
urllib3.disable_warnings()
headers = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/42.0.2311.90 Safari/537.36'}
date_field = f'{datetime.now().year}{datetime.now().month:02}{datetime.now().day:02}'
url = f'https://www.nasdaqtrader.com/dynamic/symdir/shorthalts/shorthalts{date_field}.txt'
response = requests.get(url, headers=headers, verify=False).text;