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fpi_step.py
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fpi_step.py
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"""
This script calculates annulus information for a given FPI step and band type.
It reads radius and frequency data from a CSV file, performs calculations,
and writes the results to a text file. The script loops through 20 annuli
for each band type and handles errors gracefully. It stops when empty annuli/ freq info is hit.
"""
import pandas as pd
import numpy as np
import csv, os
def calculate_annulus(csv_file, column_name, annulus_num):
"""
Calculates the annulus information for a given annulus number.
Arguments:
----------
csv_file : str
The path to the CSV file containing the radius and frequency data.
column_name : str
The column name containing the radius data for the specified FPI step and band type.
annulus_num : int
The annulus number for which to calculate the information.
Returns:
--------
tuple or str
Returns a tuple containing the annulus information if successful.
The tuple contains the following values:
r_min, r_max, freq_min, freq_max, freq_centre, freq_delta
Returns an error message if an issue occurs during the calculation.
"""
try:
# Reading Data
df = pd.read_csv(csv_file)
# Data Cleaning: Drop NaN rows for the specified column
df_cleaned = df.dropna(subset=[column_name])
# Data Extraction: Extract radius and frequency values
radius_values = df_cleaned[column_name].values
frequency_values = df_cleaned['frequency[GHz]'].values
# Annulus Calculation: Determine r_min, r_max, freq_min, and freq_max
r_min = round(radius_values[annulus_num - 1], 18)
r_max = round(radius_values[annulus_num], 18)
freq_min = frequency_values[annulus_num - 1]
freq_max = frequency_values[annulus_num]
freq_delta = freq_max - freq_min
freq_centre = (freq_max + freq_min)/2.0
return r_min, r_max, round(freq_min,2), round(freq_max,2), \
round(freq_centre,2), round(freq_delta,2)
except FileNotFoundError:
return "Error: CSV file not found."
except KeyError:
return f"Error: Column {column_name} not found."
except IndexError:
return f"Error: No frequency data for Annulus A{annulus_num}."
def annulus_FPIstep(step, csv_file = 'annulus_radii.csv'):
"""
Generates a text file containing annulus information for both LFA and HFA bands for a given FPI step.
Parameters:
-----------
step : str
The FPI step in the format "stepXXX" (e.g., "step210").
csv_file : str, optional
The path to the CSV file containing the radius and frequency data.
Default is 'annulus_radii.csv'.
Returns:
--------
File name str.
Writes the annulus information to a text file named `annulus_results_{step}.txt`.
Each line in the text file contains tab-separated values in the following format:
band_type, annulus_num, r_min, r_max, freq_min, freq_max, freq_centre, freq_delta
Notes:
------
- The function loops through 20 annuli for each band type ("LFA" and "HFA").
- The function will print an error message if an issue occurs during the calculation for any annulus.
Examples:
---------
>>> annulus_FPIstep("step210")
"""
# Initialize the text file
f_write = f"./fpi_data/annuli_data/annulus_results_{step}.txt"
with open(f_write, "w") as f:
f.write("wtype\tannulus_num\tfreq_channel\tr_min\tr_max \tfreq_min\tfreq_max\tfreq_centre\tfreq_delta\n")
# Loop over the band types (LFA and HFA)
for wtype in ["LFA", "HFA"]:
column_name = f"r_{step}_{wtype}"
# Loop over the annulus numbers (up to 20 as specified)
for annulus_num in range(1, 21): # Adjust the range according to your needs
result = calculate_annulus(csv_file, column_name, annulus_num)
if isinstance(result, tuple):
r_min, r_max, freq_min, freq_max, freq_centre, freq_delta = result
freq_channel = int(np.floor(freq_centre))
# Additional conditions based on band type and Freq
if (wtype == "LFA" and 209 <= freq_min and freq_max <= 316) or \
(wtype == "HFA" and 315 <= freq_min and freq_max <= 422):
# Write to the text file
with open(f_write, "a") as f:
f.write(
f"{wtype}\t{annulus_num}\t{freq_channel}\t{r_min}\t{r_max}\t"
f"{freq_min}\t{freq_max}\t{freq_centre}\t{freq_delta}\n"
)
else:
print(f"Skipping annulus {annulus_num} for {wtype} due to frequency range.")
elif isinstance(result, str):
print(f"An error occurred for HFA and annulus {annulus_num}: {result}")
break
return None
def process_steps(csv_file='annulus_radii.csv'):
"""
Processes the annulus_radii CSV file and returns a list of FPI steps.
Parameters:
-----------
csv_file : str, optional
The path to the CSV file containing the radius and frequency data.
Default is 'annulus_radii.csv'.
Returns:
--------
list
A list of FPI steps extracted from the CSV file.
"""
# fpi_steps = {}
fpi_steps = []
step_number = 1 # Initialize step number
with open(csv_file, mode='r') as file:
# reading the CSV file
csvFile = csv.reader(file)
# displaying the contents of the CSV file
for lines in csvFile:
column_names = lines
break # Stop after first line
# Filter out the relevant column names and populate the fpi_steps dictionary
for name in column_names:
if "_LFA" in name:
step = name.split('_')[1] # Assuming the format is always r_stepXXX_LFA
# fpi_steps[step] = step_number
# step_number += 1 # Increment step number
fpi_steps.append(step)
return fpi_steps
# fpi_steps = process_steps()
# print(fpi_steps)
# for step in fpi_steps:
# annulus_FPIstep(step)
def getall_freq_chl():
"""
Returns a list of all unique frequency channels from the annulus results files.
"""
# Get the list of fpi steps
fpi_steps = process_steps()
# Base directory for storing HDF5 files
annuli_dir = './fpi_data/annuli_data/'
freq_channel_list = []
for i, step in enumerate(fpi_steps):
fpistep_infotxt = os.path.join(annuli_dir, f"annulus_results_{step}.txt")
# Read the annulus results file
df = pd.read_csv(fpistep_infotxt, delimiter='\t')
# Get the unique freq_channel values
freq_channels = df['freq_channel'].unique()
# Append the freq_channel values to the list if they don't exist already
for freq_chl in freq_channels:
if freq_chl not in freq_channel_list:
freq_channel_list.append(freq_chl)
# print(f"Freq channel list: {freq_channel_list}")
return freq_channel_list