I have the following string.
*******************************************************************************
* *
* int. normalized values of : *
* --------------------------- *
* % of irradiance at ground level *
* % of direct irr. % of diffuse irr. % of enviro. irr *
* 0.488 0.418 0.093 *
* reflectance at satellite level *
* atm. intrin. ref. background ref. pixel reflectance *
* 0.127 0.146 0.170 *
* *
* int. absolute values of *
* ----------------------- *
* irr. at ground level (w/m2/mic) *
* direct solar irr. atm. diffuse irr. environment irr *
* 592.299 507.010 113.283 *
* rad at satel. level (w/m2/sr/mic) *
* atm. intrin. rad. background rad. pixel radiance *
* 58.837 67.355 78.685 *
* *
* *
* sol. spect (in w/m2/mic) *
* 2054.457 *
* *
*******************************************************************************
I tried to extract values corresponding to "direct solar irr.","atm. diffuse irr."and "environment irr".
import re
def extract_values(text):
pattern = r"direct solar irr\.\s*atm. diffuse irr\.\s*environment irr\s*([\d\.]+)\s*([\d\.]+)\s*([\d\.]+)"
match = re.search(pattern, text)
if match:
return {
"direct solar irr.": match.group(1),
"atm. diffuse irr.": match.group(2),
"environment irr.": match.group(3)
}
But it produces None.
Could someone help me ?
Edit: Trying using BeautifulSoup:
enter code heredef extract_values(text):
soup = BeautifulSoup(text, 'html.parser')
# Get all text elements
lines = [line.strip() for line in soup.get_text().splitlines() if line.strip() != ""]
# Identify the line after the "direct solar irr." label
for i, line in enumerate(lines):
if "direct solar irr." in line:
# Look for the next line with a number
for subsequent_line in lines[i+1:]:
if re.search(r'\d', subsequent_line): # Check if the line has a digit
values = subsequent_line.split()
return {
"direct solar irr.": float(values[0]),
"atm. diffuse irr.": float(values[1]),
"environment irr.": float(values[2])
}
direct_solar_irr = extract_values(text)
direct solar irr.": float(values[0]),
ValueError: could not convert string to float: ‘*’
>Solution :
This is the regular pattern I designed. It is correct to apply this example, but I am not sure whether it can be applied to your specific scenario. This is actually a regular matching issue, not a Python code issue.
text = """
*******************************************************************************
* *
* int. normalized values of : *
* --------------------------- *
* % of irradiance at ground level *
* % of direct irr. % of diffuse irr. % of enviro. irr *
* 0.488 0.418 0.093 *
* reflectance at satellite level *
* atm. intrin. ref. background ref. pixel reflectance *
* 0.127 0.146 0.170 *
* *
* int. absolute values of *
* ----------------------- *
* irr. at ground level (w/m2/mic) *
* direct solar irr. atm. diffuse irr. environment irr *
* 592.299 507.010 113.283 *
* rad at satel. level (w/m2/sr/mic) *
* atm. intrin. rad. background rad. pixel radiance *
* 58.837 67.355 78.685 *
* *
* *
* sol. spect (in w/m2/mic) *
* 2054.457 *
* *
*******************************************************************************
"""
import re
def extract_values(text):
# pattern = r"direct solar irr\.\s*atm. diffuse irr\.\s*environment irr\s*([\d\.]+)\s*([\d\.]+)\s*([\d\.]+)"
pattern = r"direct solar irr\.\s*atm\. diffuse irr\.\s*environment irr.*\n.*?\s*([\d\.]+)\s*([\d\.]+)\s*([\d\.]+)"
match = re.search(pattern, text)
# print(match.groups())
if match and match.groups():
return {
"direct solar irr.": match.group(1),
"atm. diffuse irr.": match.group(2),
"environment irr.": match.group(3)
}
if __name__ == '__main__':
data = extract_values(text)
print(data)