dspm_localization/area.py at main · InatiLab/dspm_localization · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 10 14:08:43 2025
@author: Leela Srinivasan

Functions to read and manipulate AFNI SurfClust outputs
"""

import os
import sys
import re
import pandas as pd


def get_fs_path(subj, deriv_dir):
    """

    Parameters
    ----------
    subj : str
        subject with FreeSurfer recon-all run

    Returns
    -------
    subj_fs_dir : str
        path to subject specific FreeSurfer folder.
    session : str
        clinical/altclinical.

    """
    for file in os.listdir(deriv_dir):
        if subj+'_' in file:
            subj_fs_dir=os.path.join(deriv_dir,file)
            if 'alt' in file:
                session='ses-altclinical'
            else:
                session='ses-clinical'
    return subj_fs_dir, session


def list_to_textfile(path, input_list):
    """

    Parameters
    ----------
    path : str
        desired path.
    input_list : list
        desired list.

    Returns
    -------
    None.

    """
    with open(path, 'w') as f:
        for line in input_list:
            f.write(f"{line}\n")


def get_subject_info(f):
    """


    Parameters
    ----------
    f : str
        path to file.

    Returns
    -------
    subject_info : list
        list of subject info.

    """
    col=pd.read_csv(f, header=None)[0]
    subject_info=[eval(x) for x in col]
    return subject_info


def split_row(input_string):
    """

    Parameters
    ----------
    input_string : str
        AFNI Column header string.

    Returns
    -------
    list
        AFNI Column names, split from original header.

    """
    return [x for x in re.split('  ', input_string) if x not in ['', ' ']]


def verify_clusters(f):
    """

    Parameters
    ----------
    f : str
        Path to txt file output.

    Returns
    -------
    bool
        True if clusters exist, False if not.

    """

    with open(f, "r") as text_file:
        contents=text_file.readlines()
        if contents[0]=='Empty cluster list.\n':
            return False
    return True


def afnisummary_to_df(f):
    """

    Parameters
    ----------
    f : str
        Path to txt file output.

    Returns
    -------
    df : df
        df containing table information from AFNI text report.
    total_voxels : str
        String integer value containing total PVS voxels in the nifti volume.

    """

    #Read table, skip opening lines and remove unwanted hashed lines, preserving summary footer
    table=pd.read_csv(f, delimiter='\t', skiprows=25)

    #Append split strings to new df with corresponding columns
    df=pd.DataFrame(columns=split_row(table.columns[0]))
    for i in range(0, len(table)):
        df.loc[i]=split_row(table.loc[i, :].values[0])

    return df


def df_to_csv(df, outname):
    """

    Parameters
    ----------
    df : df
        df containing table information from AFNI text report.
    outname : str
        path to output file..

    Returns
    -------
    None.

    """
    df.to_csv(outname)