From 593a29fa3094b3b9af70ac3933cea1ba412ccc17 Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Wed, 15 May 2024 12:26:02 -0400
Subject: [PATCH 01/16] Adds higher level carpot_plot function

---
 nireports/reportlets/modality/dwi.py | 95 ++++++++++++++++++++++++++++
 nireports/tests/test_dwi.py          | 21 +++++-
 2 files changed, 115 insertions(+), 1 deletion(-)

diff --git a/nireports/reportlets/modality/dwi.py b/nireports/reportlets/modality/dwi.py
index 117b16f5..6f7b19d7 100644
--- a/nireports/reportlets/modality/dwi.py
+++ b/nireports/reportlets/modality/dwi.py
@@ -28,6 +28,7 @@
 from matplotlib import pyplot as plt
 from mpl_toolkits.mplot3d import art3d
 from nilearn.plotting import plot_anat
+from nireports.reportlets.nuisance import plot_carpet as nw_plot_carpet
 
 
 def plot_dwi(dataobj, affine, gradient=None, **kwargs):
@@ -405,3 +406,97 @@ def plot_gradients(
         plt.suptitle(title)
 
     return ax
+
+
+def plot_carpet(
+    nii,
+    gtab,
+    segmentation=None,
+    sort_by_bval=False,
+    output_file=None,
+    segment_labels=None,
+    detrend=False,
+):
+    """
+    Return carpet plot using niworkflows carpet_plot
+
+    Parameters
+    ----------
+    nii : Nifti1Image
+        DW imaging data
+    gtab : :obj:`GradientTable`
+        DW imaging data gradient data
+    segmentation : Nifti1Image
+        Boolean or segmentation mask of DW imaging data
+    sort_by_bval : :obj:`bool`
+        Flag to reorder time points by bvalue
+    output_file : :obj:`string`
+        Path to save the plot
+    segment_labels : :obj:`dict`
+        Dictionary of segment labels
+        e.g. {'Cerebral_White_Matter': [2, 41],
+              'Cerebral_Cortex': [3, 42],
+              'Ventricle': [4, 14, 15, 43, 72]}
+    detrend : :obj:`bool`
+        niworkflows plot_carpet detrend flag
+
+    Returns
+    ---------
+    matplotlib GridSpec object
+    """
+    segments = None
+
+    nii_data = nii.get_fdata()
+
+    b0_data = nii_data[..., gtab.b0s_mask]
+    dw_data = nii_data[..., ~gtab.b0s_mask]
+
+    bzero = np.mean(b0_data, -1)
+
+    nii_data_div_b0 = dw_data / bzero[..., np.newaxis]
+
+    sort_inds = (
+        np.argsort(gtab.bvals[~gtab.b0s_mask] if sort_by_bval
+                   else np.arange(len(gtab.bvals[~gtab.b0s_mask])))
+    )
+    nii_data_div_b0 = nii_data_div_b0[..., sort_inds]
+
+    # Reshape
+    nii_data_reshaped = nii_data_div_b0.reshape(-1, nii_data_div_b0.shape[-1])
+
+    if segmentation is not None:
+        segmentation_data = np.asanyarray(segmentation.dataobj, dtype=np.int16)
+
+        # Apply mask
+        segmentation_reshaped = segmentation_data.reshape(-1)
+        nii_data_masked = nii_data_reshaped[segmentation_reshaped > 0, :]
+        segmentation_masked = segmentation_reshaped[segmentation_reshaped > 0]
+
+        if segment_labels is not None:
+            segments = dict()
+            labels = list(segment_labels.keys())
+            for label in labels:
+                indices = np.array([], dtype=int)
+                for ii in segment_labels[label]:
+                    indices = np.concatenate(
+                        [indices, np.where(segmentation_masked == ii)[0]]
+                    )
+                segments[label] = indices
+
+    else:
+        nii_data_masked = nii_data_reshaped
+
+    bad_row_ind = np.where(~np.isfinite(nii_data_masked))[0]
+
+    good_row_ind = np.ones(nii_data_masked.shape[0], dtype=bool)
+    good_row_ind[bad_row_ind] = False
+
+    nii_data_masked = nii_data_masked[good_row_ind, :]
+
+    # Plot
+    return nw_plot_carpet(
+        nii_data_masked,
+        detrend=detrend,
+        segments=segments,
+        output_file=output_file
+    )
diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index 6e43fea4..3b3bd154 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -27,7 +27,10 @@
 import pytest
 from matplotlib import pyplot as plt
 
-from nireports.reportlets.modality.dwi import plot_dwi, plot_gradients
+import os.path as op
+import dipy.core.gradients as dpg
+from nireports.reportlets.modality.dwi \
+    import plot_dwi, plot_gradients, plot_carpet
 
 
 def test_plot_dwi(tmp_path, testdata_path, outdir):
@@ -69,3 +72,19 @@ def test_plot_gradients(tmp_path, testdata_path, dwi_btable, outdir):
 
     if outdir is not None:
         plt.savefig(outdir / f"{dwi_btable}.svg", bbox_inches="tight")
+
+
+def test_plot_carpet(tmp_path, testdata_path, outdir):
+    """Check the carpet plot"""
+
+    testdata_name = "ds000114_sub-01_ses-test_desc-trunc_dwi"
+
+    nii_path = testdata_path / f'{testdata_name}.nii.gz'
+    bvec_path = testdata_path / f'{testdata_name}.bvec'
+    bval_path = testdata_path / f'{testdata_name}.bval'
+
+    nii = nb.load(nii_path)
+    gtab = dpg.gradient_table(bval_path, bvec_path)
+    image_path = outdir / f'{testdata_name}_carpet.png'
+
+    plot_carpet(nii, gtab, output_file=image_path)

From 1c2aaff1e00e3c7d09fd207238a5b78f4093ccb2 Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Wed, 15 May 2024 13:49:39 -0400
Subject: [PATCH 02/16] Adds default if outdir None

---
 nireports/tests/test_dwi.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index 3b3bd154..3623301f 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -85,6 +85,10 @@ def test_plot_carpet(tmp_path, testdata_path, outdir):
 
     nii = nb.load(nii_path)
     gtab = dpg.gradient_table(bval_path, bvec_path)
-    image_path = outdir / f'{testdata_name}_carpet.png'
+
+    image_path = None
+
+    if outdir is not None:
+        image_path = outdir / f'{testdata_name}_carpet.svg'
 
     plot_carpet(nii, gtab, output_file=image_path)

From 7783b9c5c7b8761635ecd6b32985023570c81dfc Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Wed, 15 May 2024 14:10:57 -0400
Subject: [PATCH 03/16] Removes dipy dependency

---
 nireports/reportlets/modality/dwi.py | 14 +++++++-------
 nireports/tests/test_dwi.py          | 11 +++--------
 2 files changed, 10 insertions(+), 15 deletions(-)

diff --git a/nireports/reportlets/modality/dwi.py b/nireports/reportlets/modality/dwi.py
index 6f7b19d7..1a0c63bb 100644
--- a/nireports/reportlets/modality/dwi.py
+++ b/nireports/reportlets/modality/dwi.py
@@ -410,7 +410,7 @@ def plot_gradients(
 
 def plot_carpet(
     nii,
-    gtab,
+    bvals,
     segmentation=None,
     sort_by_bval=False,
     output_file=None,
@@ -424,8 +424,8 @@ def plot_carpet(
     ----------
     nii : Nifti1Image
         DW imaging data
-    gtab : :obj:`GradientTable`
-        DW imaging data gradient data
+    bvals : :obj:`numpy.ndarray`
+        Rounded bvals
     segmentation : Nifti1Image
         Boolean or segmentation mask of DW imaging data
     sort_by_bval : :obj:`bool`
@@ -448,16 +448,16 @@ def plot_carpet(
 
     nii_data = nii.get_fdata()
 
-    b0_data = nii_data[..., gtab.b0s_mask]
-    dw_data = nii_data[..., ~gtab.b0s_mask]
+    b0_data = nii_data[..., bvals == 0]
+    dw_data = nii_data[..., bvals > 0]
 
     bzero = np.mean(b0_data, -1)
 
     nii_data_div_b0 = dw_data / bzero[..., np.newaxis]
 
     sort_inds = (
-        np.argsort(gtab.bvals[~gtab.b0s_mask] if sort_by_bval
-                   else np.arange(len(gtab.bvals[~gtab.b0s_mask])))
+        np.argsort(bvals[bvals > 0] if sort_by_bval
+                   else np.arange(len(bvals[bvals > 0])))
     )
     nii_data_div_b0 = nii_data_div_b0[..., sort_inds]
 
diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index 3623301f..4cbebe55 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -28,7 +28,6 @@
 from matplotlib import pyplot as plt
 
 import os.path as op
-import dipy.core.gradients as dpg
 from nireports.reportlets.modality.dwi \
     import plot_dwi, plot_gradients, plot_carpet
 
@@ -79,16 +78,12 @@ def test_plot_carpet(tmp_path, testdata_path, outdir):
 
     testdata_name = "ds000114_sub-01_ses-test_desc-trunc_dwi"
 
-    nii_path = testdata_path / f'{testdata_name}.nii.gz'
-    bvec_path = testdata_path / f'{testdata_name}.bvec'
-    bval_path = testdata_path / f'{testdata_name}.bval'
-
-    nii = nb.load(nii_path)
-    gtab = dpg.gradient_table(bval_path, bvec_path)
+    nii = nb.load(testdata_path / f'{testdata_name}.nii.gz')
+    bvals = np.loadtxt(testdata_path / f'{testdata_name}.bval')
 
     image_path = None
 
     if outdir is not None:
         image_path = outdir / f'{testdata_name}_carpet.svg'
 
-    plot_carpet(nii, gtab, output_file=image_path)
+    plot_carpet(nii, bvals, output_file=image_path)

From 51b7f80808a9135d0981352e664d401615073797 Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Wed, 15 May 2024 14:55:10 -0400
Subject: [PATCH 04/16] Adds segmentation to test and makes bval optional

---
 nireports/reportlets/modality/dwi.py | 36 +++++++++++++---------------
 nireports/tests/test_dwi.py          | 11 ++++++++-
 2 files changed, 27 insertions(+), 20 deletions(-)

diff --git a/nireports/reportlets/modality/dwi.py b/nireports/reportlets/modality/dwi.py
index 1a0c63bb..bc21a6dd 100644
--- a/nireports/reportlets/modality/dwi.py
+++ b/nireports/reportlets/modality/dwi.py
@@ -410,7 +410,7 @@ def plot_gradients(
 
 def plot_carpet(
     nii,
-    bvals,
+    bvals=None,
     segmentation=None,
     sort_by_bval=False,
     output_file=None,
@@ -448,28 +448,29 @@ def plot_carpet(
 
     nii_data = nii.get_fdata()
 
-    b0_data = nii_data[..., bvals == 0]
-    dw_data = nii_data[..., bvals > 0]
+    if bvals is not None:
+        b0_data = nii_data[..., bvals == 0]
+        dw_data = nii_data[..., bvals > 0]
 
-    bzero = np.mean(b0_data, -1)
+        bzero = np.mean(b0_data, -1)
 
-    nii_data_div_b0 = dw_data / bzero[..., np.newaxis]
+        nii_data = dw_data / bzero[..., np.newaxis]
 
-    sort_inds = (
-        np.argsort(bvals[bvals > 0] if sort_by_bval
-                   else np.arange(len(bvals[bvals > 0])))
-    )
-    nii_data_div_b0 = nii_data_div_b0[..., sort_inds]
+        sort_inds = (
+            np.argsort(bvals[bvals > 0] if sort_by_bval
+                       else np.arange(len(bvals[bvals > 0])))
+        )
+        nii_data = nii_data[..., sort_inds]
 
     # Reshape
-    nii_data_reshaped = nii_data_div_b0.reshape(-1, nii_data_div_b0.shape[-1])
+    nii_data = nii_data.reshape(-1, nii_data.shape[-1])
 
     if segmentation is not None:
         segmentation_data = np.asanyarray(segmentation.dataobj, dtype=np.int16)
 
         # Apply mask
         segmentation_reshaped = segmentation_data.reshape(-1)
-        nii_data_masked = nii_data_reshaped[segmentation_reshaped > 0, :]
+        nii_data = nii_data[segmentation_reshaped > 0, :]
         segmentation_masked = segmentation_reshaped[segmentation_reshaped > 0]
 
         if segment_labels is not None:
@@ -483,19 +484,16 @@ def plot_carpet(
                     )
                 segments[label] = indices
 
-    else:
-        nii_data_masked = nii_data_reshaped
-
-    bad_row_ind = np.where(~np.isfinite(nii_data_masked))[0]
+    bad_row_ind = np.where(~np.isfinite(nii_data))[0]
 
-    good_row_ind = np.ones(nii_data_masked.shape[0], dtype=bool)
+    good_row_ind = np.ones(nii_data.shape[0], dtype=bool)
     good_row_ind[bad_row_ind] = False
 
-    nii_data_masked = nii_data_masked[good_row_ind, :]
+    nii_data = nii_data[good_row_ind, :]
 
     # Plot
     return nw_plot_carpet(
-        nii_data_masked,
+        nii_data,
         detrend=detrend,
         segments=segments,
         output_file=output_file
diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index 4cbebe55..17e11b0e 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -81,9 +81,18 @@ def test_plot_carpet(tmp_path, testdata_path, outdir):
     nii = nb.load(testdata_path / f'{testdata_name}.nii.gz')
     bvals = np.loadtxt(testdata_path / f'{testdata_name}.bval')
 
+    nii_data = nii.get_fdata()
+    segmentation = nii_data > 3000
+    segment_labels = {"<3000": [0], ">3000": [1]}
+
     image_path = None
 
     if outdir is not None:
         image_path = outdir / f'{testdata_name}_carpet.svg'
 
-    plot_carpet(nii, bvals, output_file=image_path)
+    plot_carpet(nii,
+                bvals=bvals,
+                segmentation=segmentation,
+                segment_labels=segment_labels,
+                output_file=image_path
+                )

From 2a135cc1b6a5a0c8b87bca11d90e1a687412564f Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Wed, 15 May 2024 15:10:28 -0400
Subject: [PATCH 05/16] Updates test segmentation

---
 nireports/tests/test_dwi.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index 17e11b0e..fb14844d 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -82,8 +82,8 @@ def test_plot_carpet(tmp_path, testdata_path, outdir):
     bvals = np.loadtxt(testdata_path / f'{testdata_name}.bval')
 
     nii_data = nii.get_fdata()
-    segmentation = nii_data > 3000
-    segment_labels = {"<3000": [0], ">3000": [1]}
+    segmentation = round(3*np.rand(nii_data.shape))
+    segment_labels = {"0": [0], "1": [1], "2": [2], "3": [3]}
 
     image_path = None
 

From f22f6c15204987db79786e3c0d7bb60cbe8bdae0 Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Wed, 15 May 2024 15:26:00 -0400
Subject: [PATCH 06/16] Random segmentation

---
 nireports/tests/test_dwi.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index fb14844d..71a215ba 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -82,7 +82,10 @@ def test_plot_carpet(tmp_path, testdata_path, outdir):
     bvals = np.loadtxt(testdata_path / f'{testdata_name}.bval')
 
     nii_data = nii.get_fdata()
-    segmentation = round(3*np.rand(nii_data.shape))
+    segmentation = np.round(3*np.random.rand(nii_data.shape[0],
+                                             nii_data.shape[1],
+                                             nii_data.shape[2],
+                                             nii_data.shape[3]))
     segment_labels = {"0": [0], "1": [1], "2": [2], "3": [3]}
 
     image_path = None

From 2a56cf9b27de51c66f2fe026631cc63f4d008dc7 Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Wed, 15 May 2024 15:35:05 -0400
Subject: [PATCH 07/16] Changes segmentation to np array

---
 nireports/reportlets/modality/dwi.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/nireports/reportlets/modality/dwi.py b/nireports/reportlets/modality/dwi.py
index bc21a6dd..1a1f5fbe 100644
--- a/nireports/reportlets/modality/dwi.py
+++ b/nireports/reportlets/modality/dwi.py
@@ -426,8 +426,9 @@ def plot_carpet(
         DW imaging data
     bvals : :obj:`numpy.ndarray`
         Rounded bvals
-    segmentation : Nifti1Image
+    segmentation : :obj:`numpy.ndarray`
         Boolean or segmentation mask of DW imaging data
+        e.g. np.asanyarray(Nifti1Image.dataobj, dtype=np.int16)
     sort_by_bval : :obj:`bool`
         Flag to reorder time points by bvalue
     output_file : :obj:`string`
@@ -466,10 +467,8 @@ def plot_carpet(
     nii_data = nii_data.reshape(-1, nii_data.shape[-1])
 
     if segmentation is not None:
-        segmentation_data = np.asanyarray(segmentation.dataobj, dtype=np.int16)
-
         # Apply mask
-        segmentation_reshaped = segmentation_data.reshape(-1)
+        segmentation_reshaped = segmentation.reshape(-1)
         nii_data = nii_data[segmentation_reshaped > 0, :]
         segmentation_masked = segmentation_reshaped[segmentation_reshaped > 0]
 

From 2faac2c90bfa0ca4bd9e313b8b32c263f341171f Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Wed, 15 May 2024 15:55:14 -0400
Subject: [PATCH 08/16] Segmentation fixes

---
 nireports/reportlets/modality/dwi.py | 1 +
 nireports/tests/test_dwi.py          | 3 +--
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/nireports/reportlets/modality/dwi.py b/nireports/reportlets/modality/dwi.py
index 1a1f5fbe..a2014133 100644
--- a/nireports/reportlets/modality/dwi.py
+++ b/nireports/reportlets/modality/dwi.py
@@ -428,6 +428,7 @@ def plot_carpet(
         Rounded bvals
     segmentation : :obj:`numpy.ndarray`
         Boolean or segmentation mask of DW imaging data
+        Data corresponding to 0 values will be dropped
         e.g. np.asanyarray(Nifti1Image.dataobj, dtype=np.int16)
     sort_by_bval : :obj:`bool`
         Flag to reorder time points by bvalue
diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index 71a215ba..9d8f8bb6 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -84,8 +84,7 @@ def test_plot_carpet(tmp_path, testdata_path, outdir):
     nii_data = nii.get_fdata()
     segmentation = np.round(3*np.random.rand(nii_data.shape[0],
                                              nii_data.shape[1],
-                                             nii_data.shape[2],
-                                             nii_data.shape[3]))
+                                             nii_data.shape[2]))
     segment_labels = {"0": [0], "1": [1], "2": [2], "3": [3]}
 
     image_path = None

From 41f1daf0d06a64c2727da441eb1900081974626d Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Thu, 16 May 2024 10:54:29 -0400
Subject: [PATCH 09/16] Adds get_segment_labels()

---
 nireports/reportlets/modality/dwi.py | 49 ++++++++++++++++++++++++++++
 1 file changed, 49 insertions(+)

diff --git a/nireports/reportlets/modality/dwi.py b/nireports/reportlets/modality/dwi.py
index a2014133..25cda5c7 100644
--- a/nireports/reportlets/modality/dwi.py
+++ b/nireports/reportlets/modality/dwi.py
@@ -498,3 +498,52 @@ def plot_carpet(
         segments=segments,
         output_file=output_file
     )
+
+
+def get_segment_labels(
+        filepath,
+        keywords,
+        delimiter=" ",
+        index_position=0,
+        label_position=1
+):
+    """
+    Return segment labels for plot_carpet function
+    Parameters
+    ----------
+    filepath : :obj:`string`
+        Path to segment label text file, such as freesurfer label file
+    keywords : list of :obj:`string`
+        List of label keywords.
+        All labels containing the keyword will be grouped together.
+        e.g. ["Cerebral_White_Matter", "Cerebral_Cortex", "Ventricle"]
+    delimiter : :obj:`string`
+        Delimiter between label index and label string in label file
+        (' ' for freesurfer label file)
+    index_position : :obj:`int`
+        Position of label index in label file
+        (0 for freesurfer label file)
+    label_position : :obj:`int`
+        Position of label string in label file
+        (1 for freesurfer label file)
+    Returns
+    ---------
+    dict
+    e.g. {'Cerebral_White_Matter': [2, 41],
+          'Cerebral_Cortex': [3, 42],
+          'Ventricle': [4, 14, 15, 43, 72]}
+    """
+    segment_labels = {}
+
+    with open(filepath, "r") as f:
+        labels = f.read()
+
+    labels_s = [label.split(delimiter) for label in labels.split("\n")
+                if label != ""]
+
+    for keyword in keywords:
+        ind = [int(i[index_position]) for i in labels_s
+               if keyword in i[label_position]]
+        segment_labels[keyword] = ind
+
+    return segment_labels

From 1465cd5a905c2e7017976cb50043795c752c0bf2 Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Thu, 16 May 2024 15:51:09 -0400
Subject: [PATCH 10/16] Breaks higher level function into preprocessing
 functions

---
 nireports/reportlets/modality/dwi.py          | 160 +++++++++++-------
 .../aseg.auto_noCCseg.label_intensities.txt   |  47 +++++
 nireports/tests/test_dwi.py                   |  41 +++--
 3 files changed, 166 insertions(+), 82 deletions(-)
 create mode 100644 nireports/tests/data/aseg.auto_noCCseg.label_intensities.txt

diff --git a/nireports/reportlets/modality/dwi.py b/nireports/reportlets/modality/dwi.py
index 25cda5c7..8315e101 100644
--- a/nireports/reportlets/modality/dwi.py
+++ b/nireports/reportlets/modality/dwi.py
@@ -28,7 +28,6 @@
 from matplotlib import pyplot as plt
 from mpl_toolkits.mplot3d import art3d
 from nilearn.plotting import plot_anat
-from nireports.reportlets.nuisance import plot_carpet as nw_plot_carpet
 
 
 def plot_dwi(dataobj, affine, gradient=None, **kwargs):
@@ -408,96 +407,128 @@ def plot_gradients(
     return ax
 
 
-def plot_carpet(
+def nii_to_carpetplot_data(
     nii,
     bvals=None,
-    segmentation=None,
+    divide_by_b0=True,
+    drop_b0=True,
     sort_by_bval=False,
-    output_file=None,
-    segment_labels=None,
-    detrend=False,
+    mask_nii=None,
+    segment_labels=None
 ):
     """
-    Return carpet plot using niworkflows carpet_plot
+    Convert nii to data matrix for carpet plot
 
     Parameters
     ----------
     nii : Nifti1Image
         DW imaging data
-    bvals : :obj:`numpy.ndarray`
+    bvals : :obj:`numpy.ndarray`, optional
         Rounded bvals
-    segmentation : :obj:`numpy.ndarray`
-        Boolean or segmentation mask of DW imaging data
-        Data corresponding to 0 values will be dropped
-        e.g. np.asanyarray(Nifti1Image.dataobj, dtype=np.int16)
-    sort_by_bval : :obj:`bool`
+    divide_by_b0 : :obj:`bool`, optional
+        Divide data by mean b0
+    drop_b0 : :obj:`bool`, optional
+        Flag to drop b0 data
+    sort_by_bval : :obj:`bool`, optional
         Flag to reorder time points by bvalue
-    output_file : :obj:`string`
-        Path to save the plot
-    segment_labels : :obj:`dict`
+    mask_nii : Nifti1Image, optional
+        Boolean or segmentation mask of DW imaging data
+    segment_labels : :obj:`dict`, optional
         Dictionary of segment labels
         e.g. {'Cerebral_White_Matter': [2, 41],
               'Cerebral_Cortex': [3, 42],
               'Ventricle': [4, 14, 15, 43, 72]}
-    detrend : :obj:`bool`
-        niworkflows plot_carpet detrend flag
 
     Returns
     ---------
-    matplotlib GridSpec object
+    data : N x T :obj:`numpy.array`
+        The functional data to be plotted
+        (*N* sampling locations by *T* timepoints).
+    segments: :obj:`dict`
+        A mapping between segment labels (e.g., `"Left Cortex"`)
+        and list of indexes in the data array.
     """
-    segments = None
 
     nii_data = nii.get_fdata()
 
-    if bvals is not None:
-        b0_data = nii_data[..., bvals == 0]
-        dw_data = nii_data[..., bvals > 0]
+    if mask_nii is None:
+        mask_data = np.ones(nii_data.shape[0:2])
+    else:
+        mask_data = np.asanyarray(mask_nii.dataobj, dtype=np.int16)
 
-        bzero = np.mean(b0_data, -1)
+    if bvals is not None:
+        if divide_by_b0:
+            b0_data = nii_data[..., bvals == 0]
+            bzero = np.mean(b0_data, -1)
+            nii_data = nii_data / bzero[..., np.newaxis]
 
-        nii_data = dw_data / bzero[..., np.newaxis]
+        if drop_b0:
+            nii_data = nii_data[..., bvals > 0]
+            bvals = bvals[bvals > 0]
 
-        sort_inds = (
-            np.argsort(bvals[bvals > 0] if sort_by_bval
-                       else np.arange(len(bvals[bvals > 0])))
-        )
-        nii_data = nii_data[..., sort_inds]
+        if sort_by_bval:
+            sort_inds = np.argsort(bvals)
+            nii_data = nii_data[..., sort_inds]
 
     # Reshape
-    nii_data = nii_data.reshape(-1, nii_data.shape[-1])
-
-    if segmentation is not None:
-        # Apply mask
-        segmentation_reshaped = segmentation.reshape(-1)
-        nii_data = nii_data[segmentation_reshaped > 0, :]
-        segmentation_masked = segmentation_reshaped[segmentation_reshaped > 0]
-
-        if segment_labels is not None:
-            segments = dict()
-            labels = list(segment_labels.keys())
-            for label in labels:
-                indices = np.array([], dtype=int)
-                for ii in segment_labels[label]:
-                    indices = np.concatenate(
-                        [indices, np.where(segmentation_masked == ii)[0]]
-                    )
-                segments[label] = indices
-
-    bad_row_ind = np.where(~np.isfinite(nii_data))[0]
-
-    good_row_ind = np.ones(nii_data.shape[0], dtype=bool)
+    data = nii_data.reshape(-1, nii_data.shape[-1])
+    mask_data = mask_data.reshape(-1)
+
+    # Apply mask
+    data = data[mask_data > 0, :]
+    mask_data = mask_data[mask_data > 0]
+
+    # Remove bad rows
+    bad_row_ind = np.where(~np.isfinite(data))[0]
+    good_row_ind = np.ones(data.shape[0], dtype=bool)
     good_row_ind[bad_row_ind] = False
 
-    nii_data = nii_data[good_row_ind, :]
+    data = data[good_row_ind, :]
+    mask_data = mask_data[good_row_ind]
 
-    # Plot
-    return nw_plot_carpet(
-        nii_data,
-        detrend=detrend,
-        segments=segments,
-        output_file=output_file
-    )
+    # Get segments dict
+    if mask_nii is None or segment_labels is None:
+        segments = None
+    else:
+        segments = get_segments(mask_data, segment_labels)
+
+    return data, segments
+
+
+def get_segments(
+    segment_mask,
+    segment_labels
+):
+    """
+    Return segments dict for plot_carpet function
+
+    Parameters
+    ----------
+    segment_mask : :obj:`numpy.ndarray`
+        Segmentation mask of DW imaging data
+    segment_labels : :obj:`dict`
+        Dictionary of segment labels
+        e.g. {'Cerebral_White_Matter': [2, 41],
+              'Cerebral_Cortex': [3, 42],
+              'Ventricle': [4, 14, 15, 43, 72]}
+
+    Returns
+    ---------
+    segments: :obj:`dict`
+        A mapping between segment labels (e.g., `"Left Cortex"`)
+        and list of indexes in the data array.
+    """
+    segments = dict()
+
+    for label, idx in segment_labels.items():
+        indices = np.array([], dtype=int)
+        for ii in idx:
+            indices = np.concatenate(
+                [indices, np.nonzero(segment_mask == ii)]
+            )
+        segments[label] = indices
+
+    return segments
 
 
 def get_segment_labels(
@@ -508,7 +539,8 @@ def get_segment_labels(
         label_position=1
 ):
     """
-    Return segment labels for plot_carpet function
+    Get segment labels from file by keyword for get_segments function
+
     Parameters
     ----------
     filepath : :obj:`string`
@@ -517,13 +549,13 @@ def get_segment_labels(
         List of label keywords.
         All labels containing the keyword will be grouped together.
         e.g. ["Cerebral_White_Matter", "Cerebral_Cortex", "Ventricle"]
-    delimiter : :obj:`string`
+    delimiter : :obj:`string`, optional
         Delimiter between label index and label string in label file
         (' ' for freesurfer label file)
-    index_position : :obj:`int`
+    index_position : :obj:`int`, optional
         Position of label index in label file
         (0 for freesurfer label file)
-    label_position : :obj:`int`
+    label_position : :obj:`int`, optional
         Position of label string in label file
         (1 for freesurfer label file)
     Returns
diff --git a/nireports/tests/data/aseg.auto_noCCseg.label_intensities.txt b/nireports/tests/data/aseg.auto_noCCseg.label_intensities.txt
new file mode 100644
index 00000000..5c453366
--- /dev/null
+++ b/nireports/tests/data/aseg.auto_noCCseg.label_intensities.txt
@@ -0,0 +1,47 @@
+1 Left_Cerebral_Exterior 1.64 0.0  0
+2 Left_Cerebral_White_Matter 1.00 0.0 105
+3 Left_Cerebral_Cortex 1.20 0.0 69
+4 Left_Lateral_Ventricle 1.30 0.0 24
+5 Left_Inf_Lat_Vent 1.27 0.0 41
+7 Left_Cerebellum_White_Matter 1.08 0.0 91
+8 Left_Cerebellum_Cortex 1.32 0.0 73
+9 Left_Thalamus 1.26 0.0 103
+10 Left_Thalamus_Proper 1.03 0.0 93
+11 Left_Caudate 1.10 0.0 75
+12 Left_Putamen 1.16 0.0 94
+13 Left_Pallidum 1.05 0.0 101
+14 Third_Ventricle 1.64 0.0 42
+15 Fourth_Ventricle 1.72 0.0 26
+16 Brain_Stem 1.07 0.0 83
+17 Left_Hippocampus 1.27 0.0 72
+18 Left_Amygdala 1.32 0.0 76
+24 CSF 1.64 0.0 60
+26 Left_Accumbens_area 1.10 0.0 68
+28 Left_VentralDC 1.07 0.0 91
+40 Right_Cerebral_Exterior 1.64 0.0  0
+41 Right_Cerebral_White_Matter 1.00 0.0 103
+42 Right_Cerebral_Cortex 1.20 0.0 69
+43 Right_Lateral_Ventricle 1.94 0.0 25
+44 Right_Inf_Lat_Vent 1.29 0.0 30
+46 Right_Cerebellum_White_Matter 1.05 0.0 89
+47 Right_Cerebellum_Cortex 1.28 0.0 70
+48 Right_Thalamus 1.26 0.0  0
+49 Right_Thalamus_Proper 1.05 0.0 85
+50 Right_Caudate 1.24 0.0 81
+51 Right_Putamen 1.16 0.0 88
+52 Right_Pallidum 1.03 0.0 99
+53 Right_Hippocampus 1.29 0.0 72
+54 Right_Amygdala 1.29 0.0 72
+58 Right_Accumbens_area 1.24 0.0 80
+60 Right_VentralDC 1.05 0.0 94
+72 Fifth_Ventricle 1.64 0.0 50
+75  1.64 0.0  0
+76  1.64 0.0  0
+77 WM_hypointensities 1.00 0.0 77
+78 Left_WM_hypointensities 1.00 0.0  0
+79 Right_WM_hypointensities 1.00 0.0  0
+80 non_WM_hypointensities 1.00 0.0 44
+81 Left_non_WM_hypointensities 1.00 0.0  0
+82 Right_non_WM_hypointensities 1.00 0.0  0
+186  1.00 0.0  0
+187  1.00 0.0  0
diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index 9d8f8bb6..3eb8bb7b 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -27,9 +27,10 @@
 import pytest
 from matplotlib import pyplot as plt
 
-import os.path as op
 from nireports.reportlets.modality.dwi \
-    import plot_dwi, plot_gradients, plot_carpet
+    import plot_dwi, plot_gradients, nii_to_carpetplot_data, get_segment_labels
+
+from nireports.reportlets.nuisance import plot_carpet
 
 
 def test_plot_dwi(tmp_path, testdata_path, outdir):
@@ -73,28 +74,32 @@ def test_plot_gradients(tmp_path, testdata_path, dwi_btable, outdir):
         plt.savefig(outdir / f"{dwi_btable}.svg", bbox_inches="tight")
 
 
-def test_plot_carpet(tmp_path, testdata_path, outdir):
-    """Check the carpet plot"""
+def test_nii_to_carpetplot_data(tmp_path, testdata_path, outdir):
+    """Check the nii to carpet plot data function"""
 
     testdata_name = "ds000114_sub-01_ses-test_desc-trunc_dwi"
 
     nii = nb.load(testdata_path / f'{testdata_name}.nii.gz')
     bvals = np.loadtxt(testdata_path / f'{testdata_name}.bval')
 
-    nii_data = nii.get_fdata()
-    segmentation = np.round(3*np.random.rand(nii_data.shape[0],
-                                             nii_data.shape[1],
-                                             nii_data.shape[2]))
-    segment_labels = {"0": [0], "1": [1], "2": [2], "3": [3]}
-
     image_path = None
 
     if outdir is not None:
-        image_path = outdir / f'{testdata_name}_carpet.svg'
-
-    plot_carpet(nii,
-                bvals=bvals,
-                segmentation=segmentation,
-                segment_labels=segment_labels,
-                output_file=image_path
-                )
+        image_path = outdir / f'{testdata_name}_nii_to_carpet.svg'
+
+    data, segments = nii_to_carpetplot_data(nii, bvals=bvals)
+
+    plot_carpet(data, segments, output_file=image_path)
+
+
+def test_get_segment_labels(tmp_path, testdata_path):
+    """Check the segment label function"""
+
+    testdata_name = "aseg.auto_noCCseg.label_intensities.txt"
+
+    filepath = testdata_path / testdata_name
+    keywords = ["Cerebral_White_Matter", "Cerebral_Cortex", "Ventricle"]
+
+    segment_labels = get_segment_labels(filepath, keywords)
+
+    assert segment_labels is not None

From 51198f29e7756466d82d21ee78cdf640b2476eb7 Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Thu, 16 May 2024 15:59:08 -0400
Subject: [PATCH 11/16] Updates default when no mask

---
 nireports/reportlets/modality/dwi.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nireports/reportlets/modality/dwi.py b/nireports/reportlets/modality/dwi.py
index 8315e101..63258db5 100644
--- a/nireports/reportlets/modality/dwi.py
+++ b/nireports/reportlets/modality/dwi.py
@@ -452,7 +452,7 @@ def nii_to_carpetplot_data(
     nii_data = nii.get_fdata()
 
     if mask_nii is None:
-        mask_data = np.ones(nii_data.shape[0:2])
+        mask_data = np.ones(nii_data.shape[0:3])
     else:
         mask_data = np.asanyarray(mask_nii.dataobj, dtype=np.int16)
 

From 3adb4cd8ab7c172f8d9b49642e379523bca18ac8 Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Fri, 17 May 2024 10:23:17 -0400
Subject: [PATCH 12/16] Expands test

---
 nireports/tests/test_dwi.py | 17 ++++++++++++++++-
 1 file changed, 16 insertions(+), 1 deletion(-)

diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index 3eb8bb7b..df6b2a24 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -82,12 +82,27 @@ def test_nii_to_carpetplot_data(tmp_path, testdata_path, outdir):
     nii = nb.load(testdata_path / f'{testdata_name}.nii.gz')
     bvals = np.loadtxt(testdata_path / f'{testdata_name}.bval')
 
+    mask_data = np.round(82 * np.random.rand(nii.shape[0],
+                                             nii.shape[1],
+                                             nii.shape[2],
+                                             nii.shape[3]))
+
+    mask_nii = nb.Nifti1Image(mask_data, np.eye(4))
+
+    filepath = testdata_path / "aseg.auto_noCCseg.label_intensities.txt"
+    keywords = ["Cerebral_White_Matter", "Cerebral_Cortex", "Ventricle"]
+
+    segment_labels = get_segment_labels(filepath, keywords)
+
     image_path = None
 
     if outdir is not None:
         image_path = outdir / f'{testdata_name}_nii_to_carpet.svg'
 
-    data, segments = nii_to_carpetplot_data(nii, bvals=bvals)
+    data, segments = nii_to_carpetplot_data(nii,
+                                            bvals=bvals,
+                                            mask_nii=mask_nii,
+                                            segment_labels=segment_labels)
 
     plot_carpet(data, segments, output_file=image_path)
 

From 901bd4deb0548c3cc9a493602c0e69b50e188e7e Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Fri, 17 May 2024 10:32:10 -0400
Subject: [PATCH 13/16] Updates test

---
 nireports/tests/test_dwi.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index df6b2a24..19af7560 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -101,6 +101,7 @@ def test_nii_to_carpetplot_data(tmp_path, testdata_path, outdir):
 
     data, segments = nii_to_carpetplot_data(nii,
                                             bvals=bvals,
+                                            drop_b0=False,
                                             mask_nii=mask_nii,
                                             segment_labels=segment_labels)
 

From aed7b041d98ec821ad24289f2dd892f90b186320 Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Fri, 17 May 2024 10:37:28 -0400
Subject: [PATCH 14/16] Updates test segmentation

---
 nireports/tests/test_dwi.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index 19af7560..88fa7097 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -84,8 +84,7 @@ def test_nii_to_carpetplot_data(tmp_path, testdata_path, outdir):
 
     mask_data = np.round(82 * np.random.rand(nii.shape[0],
                                              nii.shape[1],
-                                             nii.shape[2],
-                                             nii.shape[3]))
+                                             nii.shape[2]))
 
     mask_nii = nb.Nifti1Image(mask_data, np.eye(4))
 
@@ -101,7 +100,6 @@ def test_nii_to_carpetplot_data(tmp_path, testdata_path, outdir):
 
     data, segments = nii_to_carpetplot_data(nii,
                                             bvals=bvals,
-                                            drop_b0=False,
                                             mask_nii=mask_nii,
                                             segment_labels=segment_labels)
 

From c3eee8d4d2748fdaac595b41eb8d839d04d0c238 Mon Sep 17 00:00:00 2001
From: Teresa Gomez <46339554+teresamg@users.noreply.github.com>
Date: Fri, 17 May 2024 10:44:45 -0400
Subject: [PATCH 15/16] Updates get_segments()

---
 nireports/reportlets/modality/dwi.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nireports/reportlets/modality/dwi.py b/nireports/reportlets/modality/dwi.py
index 63258db5..84465e82 100644
--- a/nireports/reportlets/modality/dwi.py
+++ b/nireports/reportlets/modality/dwi.py
@@ -524,7 +524,7 @@ def get_segments(
         indices = np.array([], dtype=int)
         for ii in idx:
             indices = np.concatenate(
-                [indices, np.nonzero(segment_mask == ii)]
+                [indices, np.nonzero(segment_mask == ii)[0]]
             )
         segments[label] = indices
 

From 75cc84eb35489984bac7a3ec868110c5471a2897 Mon Sep 17 00:00:00 2001
From: Oscar Esteban <code@oscaresteban.es>
Date: Mon, 1 Jul 2024 15:09:19 +0200
Subject: [PATCH 16/16] sty: revise format

---
 nireports/reportlets/modality/dwi.py | 27 +++++++--------------------
 nireports/tests/test_dwi.py          | 26 +++++++++++++-------------
 2 files changed, 20 insertions(+), 33 deletions(-)

diff --git a/nireports/reportlets/modality/dwi.py b/nireports/reportlets/modality/dwi.py
index 84465e82..1d45702b 100644
--- a/nireports/reportlets/modality/dwi.py
+++ b/nireports/reportlets/modality/dwi.py
@@ -414,7 +414,7 @@ def nii_to_carpetplot_data(
     drop_b0=True,
     sort_by_bval=False,
     mask_nii=None,
-    segment_labels=None
+    segment_labels=None,
 ):
     """
     Convert nii to data matrix for carpet plot
@@ -495,10 +495,7 @@ def nii_to_carpetplot_data(
     return data, segments
 
 
-def get_segments(
-    segment_mask,
-    segment_labels
-):
+def get_segments(segment_mask, segment_labels):
     """
     Return segments dict for plot_carpet function
 
@@ -518,26 +515,18 @@ def get_segments(
         A mapping between segment labels (e.g., `"Left Cortex"`)
         and list of indexes in the data array.
     """
-    segments = dict()
+    segments = {}
 
     for label, idx in segment_labels.items():
         indices = np.array([], dtype=int)
         for ii in idx:
-            indices = np.concatenate(
-                [indices, np.nonzero(segment_mask == ii)[0]]
-            )
+            indices = np.concatenate([indices, np.nonzero(segment_mask == ii)[0]])
         segments[label] = indices
 
     return segments
 
 
-def get_segment_labels(
-        filepath,
-        keywords,
-        delimiter=" ",
-        index_position=0,
-        label_position=1
-):
+def get_segment_labels(filepath, keywords, delimiter=" ", index_position=0, label_position=1):
     """
     Get segment labels from file by keyword for get_segments function
 
@@ -570,12 +559,10 @@ def get_segment_labels(
     with open(filepath, "r") as f:
         labels = f.read()
 
-    labels_s = [label.split(delimiter) for label in labels.split("\n")
-                if label != ""]
+    labels_s = [label.split(delimiter) for label in labels.split("\n") if label != ""]
 
     for keyword in keywords:
-        ind = [int(i[index_position]) for i in labels_s
-               if keyword in i[label_position]]
+        ind = [int(i[index_position]) for i in labels_s if keyword in i[label_position]]
         segment_labels[keyword] = ind
 
     return segment_labels
diff --git a/nireports/tests/test_dwi.py b/nireports/tests/test_dwi.py
index 88fa7097..c90c81ce 100644
--- a/nireports/tests/test_dwi.py
+++ b/nireports/tests/test_dwi.py
@@ -27,9 +27,12 @@
 import pytest
 from matplotlib import pyplot as plt
 
-from nireports.reportlets.modality.dwi \
-    import plot_dwi, plot_gradients, nii_to_carpetplot_data, get_segment_labels
-
+from nireports.reportlets.modality.dwi import (
+    get_segment_labels,
+    nii_to_carpetplot_data,
+    plot_dwi,
+    plot_gradients,
+)
 from nireports.reportlets.nuisance import plot_carpet
 
 
@@ -79,12 +82,10 @@ def test_nii_to_carpetplot_data(tmp_path, testdata_path, outdir):
 
     testdata_name = "ds000114_sub-01_ses-test_desc-trunc_dwi"
 
-    nii = nb.load(testdata_path / f'{testdata_name}.nii.gz')
-    bvals = np.loadtxt(testdata_path / f'{testdata_name}.bval')
+    nii = nb.load(testdata_path / f"{testdata_name}.nii.gz")
+    bvals = np.loadtxt(testdata_path / f"{testdata_name}.bval")
 
-    mask_data = np.round(82 * np.random.rand(nii.shape[0],
-                                             nii.shape[1],
-                                             nii.shape[2]))
+    mask_data = np.round(82 * np.random.rand(nii.shape[0], nii.shape[1], nii.shape[2]))
 
     mask_nii = nb.Nifti1Image(mask_data, np.eye(4))
 
@@ -96,12 +97,11 @@ def test_nii_to_carpetplot_data(tmp_path, testdata_path, outdir):
     image_path = None
 
     if outdir is not None:
-        image_path = outdir / f'{testdata_name}_nii_to_carpet.svg'
+        image_path = outdir / f"{testdata_name}_nii_to_carpet.svg"
 
-    data, segments = nii_to_carpetplot_data(nii,
-                                            bvals=bvals,
-                                            mask_nii=mask_nii,
-                                            segment_labels=segment_labels)
+    data, segments = nii_to_carpetplot_data(
+        nii, bvals=bvals, mask_nii=mask_nii, segment_labels=segment_labels
+    )
 
     plot_carpet(data, segments, output_file=image_path)