I am working on 2 images, image-1 is a xarray DataArray, image-2 is a raster .tif data. I want to overlay the 2 data to see the land use types (image-2) that falls within a particular value in the xarray (image-1). Below is my code:
import netCDF4 as nc
import xarray as xr
import rasterio
import rioxarray
#import the dataset
era_5 = (r'F:\2ND_ARTICLE_II\ERA-5\ERA-5_All_Nigin.nc')
era_5 = xr.open_dataset(era_5)
era_5 = era_5['tp']
#import the tiff
lulc1 = rioxarray.open_rasterio(r'F:\2ND_ARTICLE_II\LULC\lulc_clp_Nig.tif', masked=True)
Now my question is how to determine the image deference that corresponds to a particular land use type between the two images.
Related
I'm struggling to come up with a solution using Plotly to reproduce the following code which uses matplotlib.
import matplotlib.pyplot as plt
import numpy as np
plt.figure(figsize=(10, 5), dpi=100)
image = np.random.random([300, 5000])
image2 = np.ones([300, 5000])
plt.imshow(image, vmin=0, vmax=1, cmap="gray_r", aspect="auto", alpha=0.5)
plt.imshow(image2, vmin=0, vmax=1, cmap="seismic", aspect="auto", alpha=0.5)
plt.show()
My goal is to merge two arrays together using transparency parameters for each array. One array is displayed in grey color, another in red color (or seismic). Plotly imshow does not have alpha parameter, so I'm a bit confused about how to implement this simple code using plotly. I need this for my dash plotly app.
I finished the linked tutorial and tried to modify it to get somethings else from a different website. I am trying to get the margin table of HHI but the website is coded in a strange way that I am quite confused.
I find the child element of the parent that have the text with xpath://a[#name="HHI"], its parent is <font size="2"></font> and contains the text I wanted but there is a lot of tags named exactly <font size="2"></font> so I can't just use xpath://font[#size="2"].
Attempt to use the full xpath would print out half of the website content.
the full xpath:
/html/body/table/tbody/tr/td/table/tbody/tr/td/table/tbody/tr[3]/td/pre/font/table/tbody/tr/td[2]/pre/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font/font
Is there anyway to select that particular font tag and print the text?
website:
https://www.hkex.com.hk/eng/market/rm/rm_dcrm/riskdata/margin_hkcc/merte_hkcc.htm
Tutorial
https://www.youtube.com/watch?v=PXMJ6FS7llk&t=8740s&ab_channel=freeCodeCamp.org
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.chrome.service import Service
import pandas as pd
# prepare it to automate
from datetime import datetime
import os
import sys
import csv
application_path = os.path.dirname(sys.executable) # export the result to the same file as the executable
now = datetime.now() # for modify the export name with a date
month_day_year = now.strftime("%m%d%Y") # MMDDYYYY
website = "https://www.hkex.com.hk/eng/market/rm/rm_dcrm/riskdata/margin_hkcc/merte_hkcc.htm"
path = "C:/Users/User/PycharmProjects/Automate with Python – Full Course for Beginners/venv/Scripts/chromedriver.exe"
# headless-mode
options = Options()
options.headless = True
service = Service(executable_path=path)
driver = webdriver.Chrome(service=service, options=options)
driver.get(website)
containers = driver.find_element(by="xpath", value='') # or find_elements
hhi = containers.text # if using find_elements, = containers[0].text
print(hhi)
Update:
Thank you to Conal Tuohy, I learn a few new tricks in Xpath. The website is written in a strange way that even with the Xpath that locate the exact font tag, the result would still print all text in every following tags.
I tried to make a list of different products by .split("Back to Top") then slice out the first item and use .split("\n"). I will .split() the lists within list until it can neatly fit into a dataframe with strike prices as index and maturity date as column.
Probably not the most efficient way but it works for now.
product = "HHI"
containers = driver.find_element(by="xpath", value=f'//font[a/#name="{product}"]')
hhi = containers.text.split("Back to Top")
# print(hhi)
hhi1 = hhi[0].split("\n")
df = pd.DataFrame(hhi1)
# print(df)
df.to_csv(f"{product}_{month_day_year}.csv")
You're right that HTML is just awful! But if you're after the text of the table, it seems to me you ought to select the text node that follows the B element that follows the a[#name="HHI"]; something like this:
//a[#name="HHI"]/following-sibling::b/following-sibling::text()[1]
EDIT
Of course that XPath won't work in Selenium because it identifies a text node rather than an element. So your best result is to return the font element that directly contains the //a[#name="HHI"], which will include some cruft (the Back to Top link, etc) but which will at least contain the tabular data you want:
//a[#name="HHI"]/parent::font
i.e. "the parent font element of the a element whose name attribute equals HHI"
or equivalently:
//font[a/#name="HHI"]
i.e. "the font element which has, among its child a elements, one whose name attribute equals HHI"
I'd like to add a picture to some of my tkinter labels, and I found a page with many of them (there are, of course, many similar pages), including some that I want.
But I'm having a strange behavior with this.
The code
import tkinter as tk
from tkinter import ttk
import html
root = tk.Tk()
root.geometry("200x100")
s = html.unescape('🏁') # chequered flag
text = "some text"
label_text = "{}{}".format(text, s)
my_label = ttk.Label(root, text=label_text)
my_label.pack()
t = chr(9917)
another = "football ball"
another_text = "{}{}".format(t, another)
another_label = ttk.Label(root, text=another_text)
another_label.pack()
root.mainloop()
produces the following window:
On the other hand, if I replace label_text = "{}{}".format(text, s) with label_text = "{}{}".format(s, text) the flag appears twice instead (once before "some text" and another after).
Apparently this only happens with html images.
For example, with the second label, I have the expected behavior.
Is there something I'm doing wrong here, or should I just avoid these images in tkinter?
i wouldnt avoid them yet i wouldnt advise them either. Because tkinter propbably uses regular images its propbably not used to emojis. My recommendation is to use regular images instead of emojis.
I am trying to do number plate recognition using tesseract 4.0.0-beta.1. In tesseract documentation, it is told to create box files in the form . I tried using "makebox" function. But, it is not detecting every character properly. Then, somewhere i read that this function is for version 3.x.
I later tried "wordstrbox" function. But the box file which is created in this way is empty. Can someone tell me how to create box files for tesseract 4.0.0-beta.1.
Use pytesseract.image_to_data()
import pytesseract
import cv2
from pytesseract import Output
img = cv2.imread('image.jpg')
d = pytesseract.image_to_data(img, output_type=Output.DICT)
n_boxes = len(d['level'])
for i in range(n_boxes):
(text,x,y,w,h) = (d['text'][i],d['left'][i],d['top'][i],d['width'][i],d['height'][i])
cv2.rectangle(img, (x,y), (x+w,y+h) , (0,255,0), 2)
cv2.imshow('img',img)
cv2.waitkey(0)
Among the data returned by pytesseract.image_to_data():
left is the distance from the upper-left corner of the bounding box,
to the left border of the image.
top is the distance from the upper-left corner of the bounding box,
to the top border of the image.
width and height are the width and height of the bounding box.
conf is the model's confidence for the prediction for the word within
that bounding box. If conf is -1, that means that the corresponding
bounding box contains a block of text, rather than just a single
word.
The bounding boxes returned by pytesseract.image_to_boxes() enclose letters so I believe pytesseract.image_to_data() is what you're looking for.
I've found AlfyFaisy's answer very helpful and just wanted to share the code to view the bounding boxes of single characters. The differences regard the keys of the dictionary that is output by the image_to_boxes method:
import pytesseract
import cv2
from pytesseract import Output
img = cv2.imread('image.png')
height = img.shape[0]
width = img.shape[1]
d = pytesseract.image_to_boxes(img, output_type=Output.DICT)
n_boxes = len(d['char'])
for i in range(n_boxes):
(text,x1,y2,x2,y1) = (d['char'][i],d['left'][i],d['top'][i],d['right'][i],d['bottom'][i])
cv2.rectangle(img, (x1,height-y1), (x2,height-y2) , (0,255,0), 2)
cv2.imshow('img',img)
cv2.waitKey(0)
At least on my machine (Python 3.6.8, cv2 4.1.0) the cv2 method is waitKey(0) with a capital K.
This is the output I got:
I have plots of 3-axis accelerometer time-series data (t,x,y,z) in separate subplots I'd like to zoom together. That is, when I use the "Zoom to Rectangle" tool on one plot, when I release the mouse all 3 plots zoom together.
Previously, I simply plotted all 3 axes on a single plot using different colors. But this is useful only with small amounts of data: I have over 2 million data points, so the last axis plotted obscures the other two. Hence the need for separate subplots.
I know I can capture matplotlib/pyplot mouse events (http://matplotlib.sourceforge.net/users/event_handling.html), and I know I can catch other events (http://matplotlib.sourceforge.net/api/backend_bases_api.html#matplotlib.backend_bases.ResizeEvent), but I don't know how to tell what zoom has been requested on any one subplot, and how to replicate it on the other two subplots.
I suspect I have the all the pieces, and need only that one last precious clue...
-BobC
The easiest way to do this is by using the sharex and/or sharey keywords when creating the axes:
from matplotlib import pyplot as plt
ax1 = plt.subplot(2,1,1)
ax1.plot(...)
ax2 = plt.subplot(2,1,2, sharex=ax1)
ax2.plot(...)
You can also do this with plt.subplots, if that's your style.
fig, ax = plt.subplots(3, 1, sharex=True, sharey=True)
Interactively this works on separate axes
for ax in fig.axes:
ax.set_xlim(0, 50)
fig.draw()