From 9d8cda1ffbac9c4ed1d347c9a9693038683fea9b Mon Sep 17 00:00:00 2001 From: ChesterHuynh Date: Mon, 14 Oct 2019 16:24:00 -0400 Subject: [PATCH 1/6] Changing docstrings and added function to plot distribution of voxel intensities --- .../electrode_clustering.py | 149 ++++++++---- .../contact_localization/visualize_results.py | 60 +++-- .../electrode_clustering/grouping.py | 115 +++++++--- .../processing/electrode_clustering/mask.py | 49 +++- .../electrode_clustering/postprocess.py | 215 +++++++++++++----- 5 files changed, 436 insertions(+), 152 deletions(-) diff --git a/neuroimg/pipeline/contact_localization/electrode_clustering.py b/neuroimg/pipeline/contact_localization/electrode_clustering.py index 276e54d..da6ca19 100644 --- a/neuroimg/pipeline/contact_localization/electrode_clustering.py +++ b/neuroimg/pipeline/contact_localization/electrode_clustering.py @@ -20,17 +20,23 @@ def load_data(ct_scan, brainmask_ct): """ - Load each brain image scan as a NiBabel image object - :param ct_scan: Nifti image file of CT scan - :param brainmask_ct: Nifti image file of corresponding brain mask in CT voxels - :param elecinitfile: Space-delimited text file of contact labels and contact - coordinates in mm space - :return: - ct_img: NiBabel image object of CT scan input - brainmask_ct: NiBabel image object of brain mask in CT - elecinitfile: A dictionary of contact coordinates in mm space. Keys are - individual contact labels, and values are the corresponding coordinates - in mm space. + Load each brain image scan as a NiBabel image object. + + Parameters + –––------- + ct_scan: str + Path to Nifti image file of CT scan. + + brainmask_ct: str + Path to Nifti image file of corresponding brain mask in CT voxels. + + Returns + ------- + ct_img: NiBabel image object + NiBabel image object of CT scan input. + + brainmask_ct: NiBabel image object + NiBabel image object of brain mask in CT. """ ct_img = nb.load(ct_scan) @@ -40,13 +46,18 @@ def load_data(ct_scan, brainmask_ct): def load_elecs_data(elecfile): """ - Load each brain image scan as a NiBabel image object - :param elecfile: Space-delimited text file of contact labels and contact - coordinates in mm space - :return: - ct_img: NiBabel image object of CT scan input - brainmask_ct: NiBabel image object of brain mask in CT - elecinitfile: A dictionary of contact coordinates in mm space. Keys are + Load each brain image scan as a NiBabel image object. + + Parameters + ---------- + elecfile: str + Space-delimited text file of contact labels and contact + coordinates in mm space. + + Returns + ------- + elecinitfile: dict() + A dictionary of contact coordinates in mm space. Keys are individual contact labels, and values are the corresponding coordinates in mm space. """ @@ -78,11 +89,18 @@ def load_elecs_data(elecfile): def compute_centroids(chanxyzvoxels): """ - Function to return the centroids of each channel label given a list of voxels per channel label. - - :param chanxyzvoxels: dictionary of electrodes and corresponding dictionary - of channels to centroid xyz coordinates. - :return: centroids: list of centroids + Function to return the centroids of each channel label given a list + of voxels per channel label. + + Parameters + ---------- + chanxyzvoxels: dict() + dictionary of electrodes and corresponding dictionary of channels + to centroid xyz coordinates. + + Returns + ------- + list of centroids. """ centroids = {} for channel, voxels in chanxyzvoxels.items(): @@ -96,10 +114,19 @@ def apply_atlas(fspatdir, destrieuxfilepath, dktfilepath): Map centroids to an atlas (e.g. Desikan-Killiany, Destriuex) and apply white matter and brain masks to label centroids as white matter or out of the brain. - :param final_centroids_xyz: dictionary of electrodes and corresponding - dictionary of channels to centroid xyz coordinates. - :return elec_labels_destriuex: array of contacts labeled with Destriuex atlas - :return elec_labels_DKT: array of contacts labeled with Desikan-Killiany atlas + + Parameters + –--------- + final_centroids_xyz: dict() + dictionary of electrodes and corresponding dictionary of channels + to centroid xyz coordinates. + + Returns + ------- + elec_labels_destriuex: dict() + array of contacts labeled with Destriuex atlas. + elec_labels_DKT: dict() + array of contacts labeled with Desikan-Killiany atlas. """ try: sys.path.insert(0, "/Users/ChesterHuynh/img_pipe") @@ -146,10 +173,25 @@ def apply_wm_and_brainmask(final_centroids_xyz, atlasfilepath, wmpath, bmpath): """ Apply white matter and brainmask labels to final centroid output and save in .mat files - :param final_centroids_xyz: - :param elecfile: - :param PATIENT_OUTPUT_DIR: - :return elec_labels: + + Parameters + ---------- + final_centroids_xyz: dict() + Dictionary of predicted centroids in xyz (mm) coordinates. + + atlasfilepath: str + Path to .txt file to save the xyz coordinates of centroids. + + wmpath: str + Path to white matter mask file. + + bmpath: str + Path to brain matter mask file. + + Returns + ------- + Anatomy matrix with columns of coordinates, anatomical label, + and channel label. """ dat = scipy.io.loadmat(atlasfilepath) elecmatrix = dat["elecmatrix"] @@ -186,21 +228,51 @@ def apply_wm_and_brainmask(final_centroids_xyz, atlasfilepath, wmpath, bmpath): def _brightness_frequencies(self, maskedCT): + """ + Compute the brightness frequencies for all intensity values. + + Parameters + ---------- + maskedCT: np.ndarray of 3 dimensions. + Normalized, brain-masked CT 3D image array. + + Returns + ------- + Dictionary of voxel intensities and the number of points + with that frequency. + """ brightness_freqs = {} pdb.set_trace() for i in range(len(maskedCT)): for j in range(len(maskedCT)): - for k, vox in enumerate(maskedCT): - if vox in points_by_brightness: - brightness_freqs[vox] += 1 + for k, intens in enumerate(maskedCT): + if intens in points_by_brightness: + brightness_freqs[intens] += 1 else: - brightness_freqs[vox] = 1 + brightness_freqs[intens] = 1 return brightness_freqs def _compute_brightness_distribution(self, maskedCT, start=0.4, stop=0.8, step=0.05): """ - Compute the brightness distribution and color label ones that are 0 and 1 + Compute the brightness distribution and color label ones that are 0 and 1, + and save the plot of this distribution. + + Parameters + ---------- + maskedCT: np.ndarray of 3 dimensions. + Normalized, brain-masked CT 3D image array. + + start: float + Starting threshold to use when partitioning points into groups of + above and below threshold value. + + stop: float + Threshold to stop at when partitioning points into groups of above + and below threshold value. + + step: float + Amount to increment the threshold by. """ brightness_freqs = self._brightness_frequencies(maskedCT / 255) threshvec = np.arange(start, stop, step) @@ -231,9 +303,8 @@ def _compute_brightness_distribution(self, maskedCT, start=0.4, stop=0.8, step=0 def main(ctimgfile, brainmaskfile, elecinitfile): # hyperparameters: - radius = 4 # radius (in voxels) of cylindrical boundary - # Threshold for applying naive clustering algorithm - threshold = 0.630 # WHAT IS THE RANGE OF THRESHOLD VALUES? [0,1]? + radius = 4 # radius (in CT voxels) of cylindrical boundary + threshold = 0.630 # Between 0 and 1. Zero-out voxels with intensity < threshold. gap_tolerance = 12.5 # maximum distance between two adjacent nodes # Load data diff --git a/neuroimg/pipeline/contact_localization/visualize_results.py b/neuroimg/pipeline/contact_localization/visualize_results.py index c8db982..a040309 100644 --- a/neuroimg/pipeline/contact_localization/visualize_results.py +++ b/neuroimg/pipeline/contact_localization/visualize_results.py @@ -17,6 +17,22 @@ def summary_PCA_plots(figurefilepath, final_centroids, elec_in_brain): + """ + Construct PCA plots to visually show deviations in predicted centroids + and manually labeled centroids. + + Parameters + ---------- + figurefilepath: str + File path to save the image to + + final_centroids: dict() + Dictionary of the centroidsfor each contact along an electrode + found by clustering algorithm. + + elec_in_brain: dict() + Dictionary of manually labeled centroids + """ if not os.path.exists(os.path.dirname(figurefilepath)): os.mkdir(os.path.dirname(figurefilepath)) @@ -85,10 +101,17 @@ def l2_error(figurefilepath, final_centroids, elec_in_brain): """ Function that computes the Euclidean distance (l2) between centroids computed by algorithm and the validation data, which are centroids manually inputted by user. - :param final_centroids: dictionary of properly labeled centroids grouped by electrode - in CT voxels - :param elec_in_brain: electrode coordinates in CT voxels - :return error_per_channel: error in each channel (accurate prediction is between 0-3) + + Parameters + ---------- + final_centroids: dict() + dictionary of properly labeled centroids grouped by electrode in CT voxels + elec_in_brain: dict() + electrode coordinates in CT voxels + + Returns + ------- + Error in each channel (accurate prediction is between 0-3). """ numelectrodes = len(final_centroids.keys()) print(f"Plotting results for {numelectrodes} electrodes.") @@ -139,15 +162,26 @@ def l2_error(figurefilepath, final_centroids, elec_in_brain): def load_data(elecfile): """ - Load each brain image scan as a NiBabel image object - :param elecfile: Space-delimited text file of contact labels and contact - coordinates in mm space - :return: - ct_img: NiBabel image object of CT scan input - brainmask_ct: NiBabel image object of brain mask in CT - elecinitfile: A dictionary of contact coordinates in mm space. Keys are - individual contact labels, and values are the corresponding coordinates - in mm space. + Load each brain image scan as a NiBabel image object. + + Parameters + ---------- + elecfile: str + Path to space-delimited text file of contact labels and contact + coordinates in mm space. + + Returns + ------- + ct_img: NiBabel image object + NiBabel image object of CT scan input. + + brainmask_ct: NiBabel image object + NiBabel image object of brain mask in CT. + + elecinitfile: dict() + A dictionary of contact coordinates in mm space. Keys are + individual contact labels, and values are the corresponding + coordinates in mm space. """ elec_coords_mm = {} diff --git a/neuroimg/processing/electrode_clustering/grouping.py b/neuroimg/processing/electrode_clustering/grouping.py index 3b28dcb..a8bb150 100644 --- a/neuroimg/processing/electrode_clustering/grouping.py +++ b/neuroimg/processing/electrode_clustering/grouping.py @@ -7,18 +7,34 @@ class Cluster: @classmethod def find_clusters(self, maskedCT, pointsOnly=True): """ - Function to apply a thresholding based algorithm and then running connected clustering using skimage. - This will then return clusters of voxels that belong to distinct contact groups. + Function to apply a thresholding based algorithm and then running + connected clustering using skimage. This will then return clusters + of voxels that belong to distinct contact groups. http://scikit-image.org/docs/dev/api/skimage.measure.html#skimage.measure.label - :param maskedCT: Brain-masked CT scan - :param brainmaskinCT: Brain mask in CT space - :param pointsOnly: True if it is desired to remove background and return a list of all contact coordinates. - If False, the function returns a 3D array of the same dimensions as the inputted image array. - :return: - allclusters: Dictionary of clusters found at various thresholds. The keys are threshold values; + + Parameters + ---------- + maskedCT: np.ndarray of 3 dimensions + Brain-masked CT scan + + brainmaskinCT: np.ndarray of 3 dimensions with same shape as masked CT + Brain mask in CT space + + pointsOnly: bool + True if it is desired to remove background and return + a list of all contact coordinates. If False, the function + returns a 3D array of the same dimensions as the inputted + image array. + + Returns + ------- + allclusters: dict() + Dictionary of clusters found at various thresholds. The keys are threshold values; the values are dictionaries of clusters with their corresponding list of coordinates of points in each clsuter. - numobj: List of the number of clusters found for the range of thresholds + + numobj: List[int] + List of the number of clusters found for the range of thresholds """ masktype = "keep" @@ -78,15 +94,28 @@ class CylindricalGroup: @classmethod def test_point_in_cylinder(self, pt1, pt2, r, q): """ - Tests whether a point q lies within a cylinder with points pt1 and pt2 that - define the axis of the cylinder and a specified radius r. Used formulas provided here: + Tests whether a point q lies within a cylinder with points + pt1 and pt2 that define the axis of the cylinder and a + specified radius r. Used formulas provided here: https://www.flipcode.com/archives/Fast_Point-In-Cylinder_Test.shtml - :param pt1: first point to bound the cylinder - :param pt2: second point to bound the cylinder - :param r: the radius of the cylinder - :param q: the point to test whether it lies within the cylinder - :return True if q lies in the cylinder, else False. + Parameters + ---------- + pt1: np.ndarray of dimensions 1 x 3 + first point to bound the cylinder. + + pt2: np.ndarray of dimensions 1 x 3 + second point to bound the cylinder. + + r: int + the radius of the cylinder + + q: np.ndarray of dimensions 1 x 3 + the point to test whether it lies within the cylinder + + Returns + ------- + True if q lies in the cylinder, else False. """ vec = pt2 - pt1 length_sq = npl.norm(vec) ** 2 @@ -108,26 +137,52 @@ def points_in_cylinder(self, pt1, pt2, r, points_to_test): """ Tests whether a list of points lies within a cylinder with points pt1 and pt2 that define the axis of the cylinder and a specified radius r. - :param pt1: first point to bound the cylinder - :param pt2: second point to bound the cylinder - :param r: the radius of the cylinder - :param points_to_test: list of points to test - :return: points_list: all the points that lie in the cylinder + + Parameters + ---------- + pt1: np.ndarray of dimensions 1 x 3 + first point to bound the cylinder. + + pt2: np.ndarray of dimensions 1 x 3 + second point to bound the cylinder. + + r: int + the radius of the cylinder. + + points_to_test: List[np.ndarray of dimensions 1 x 3] + list of points to test. + + Returns + ------- + List of all the points that lie in the cylinder """ return [point for point in points_to_test if self.test_point_in_cylinder(pt1, pt2, r, point)] @classmethod def cylinder_filter(self, elec_in_brain, clusters, radius): """ - Applies a cylindrical filtering on the raw threshold-based clustering by generating - bounding cylinders given a sparse collection of contact coordinates. - :param elec_in_brain: Dictionary of contacts that fall within the brain - :param clusters: Dictionary of clusters found at a given threshold - :param radius: Radius with which to form cylindrical boundaries - :return: clusters_by_cylinder: Dictionary of clusters sorted by the cylinder/electrode - in which they fall. The keys of the dictionary are electrode labels, the values of the - dictionary are the cluster points from the threshold-based clustering algorithm that - fell into a cylinder. + Applies a cylindrical filtering on the raw threshold-based + clustering by generating bounding cylinders given a sparse + collection of contact coordinates. + + Parameters + ---------- + elec_in_brain: dict() + Dictionary of contacts that fall within the brain. + + clusters: dict() + Dictionary of clusters found at a given threshold. + + radius: dict() + Radius with which to form cylindrical boundaries. + + Returns + ------- + Dictionary of clusters sorted by the cylinder/electrode + in which they fall. The keys of the dictionary are electrode + labels, the values of the dictionary are the cluster points + from the threshold-based clustering algorithm that fell + into a cylinder. """ # Separate components of all points found in clustering algorithm diff --git a/neuroimg/processing/electrode_clustering/mask.py b/neuroimg/processing/electrode_clustering/mask.py index e8a8344..e7b5810 100644 --- a/neuroimg/processing/electrode_clustering/mask.py +++ b/neuroimg/processing/electrode_clustering/mask.py @@ -8,9 +8,19 @@ class MaskVolume: def apply_mask(self, mask_data, brain_img_data): """ Applies a binarized brain mask to an input CT image file - :param mask_data: 3D array of brain mask - :param brain_img_data: 3D array of CT brain scan - :return: masked_brain: The masked CT image as a 3D array + + Parameters + –--------- + mask_data: np.ndarray of 3 dimensions + 3D array of brain mask. + + brain_img_data: np.ndarray of 3 dimensions + 3D array of CT brain image that is the same shape as mask_data. + + + Returns + ------- + 3D array of masked CT image that is the same shape as input arrays. """ mask_data[mask_data > 0] = 1 @@ -22,11 +32,21 @@ def apply_mask(self, mask_data, brain_img_data): def filter_electrodes_bm(self, elec_coords_mm, brainmasked_ct_img): """ Filters out electrodes that do not fall within brain matter of a CT image - :param elec_coords_mm: A dictionary of contact coordinates in mm space - :param brainmasked_ct_img: A brainmasked CT NiBabel image object - :return: elecvoxels_in_brain: A dictionary of contact coordinates in CT voxels that fall - within the binarized brain mask. The keys are individual contact labels, the values - are the corresponding coordinates in CT space. + + Parameters + –--------- + elec_coords_mm: dict() + A dictionary of contact coordinates in mm space. + + brainmasked_ct_img: NiBabel image object + A brain-masked CT image in the form of NiBabel image object. + + + Returns + ------- + A dictionary of contact coordinates in CT voxels that fall + within the binarized brain mask. The keys are individual contact + labels, the values are the corresponding coordinates in CT space. """ brainmasked_ct_data = brainmasked_ct_img.get_fdata() brainmasked_ct_affine = brainmasked_ct_img.affine @@ -52,10 +72,17 @@ def filter_electrodes_bm(self, elec_coords_mm, brainmasked_ct_img): @classmethod def sort_contacts(self, elec_in_brain): """ - Groups the individual contacts by the electrode to which they correspond - :param elec_in_brain: A dictionary of contact coordinates in CT voxels that fall + Groups the individual contacts by the electrode to which they correspond. + + Parameters + –--------- + elec_in_brain: dict() + A dictionary of contact coordinates in CT voxels that fall within the brain matter. - :return: voxels_per_electrode: A dictionary of contact coordinates in CT voxels that + + Returns + ------- + A dictionary of contact coordinates in CT voxels that fall within the brain. The keys are electrode labels, and the values are lists of the coordinates of all the contacts that correspond to a given electrode. """ diff --git a/neuroimg/processing/electrode_clustering/postprocess.py b/neuroimg/processing/electrode_clustering/postprocess.py index 8d8b887..d91a173 100644 --- a/neuroimg/processing/electrode_clustering/postprocess.py +++ b/neuroimg/processing/electrode_clustering/postprocess.py @@ -17,18 +17,34 @@ def process_abnormal_clusters( qtile=0.875, ): """ - Truncates the clusters closest to the skull, which tend to be oversized, and - separates clusters that appear to have grouped two contacts together. The cluster is filtered - with 90% quantile filtering, using a coordinate from user-input as the mean for the cluster. - :param clusters: Dictionary of clusters found at a given threshold - :param elec_in_brain: Dictionary of all the contacts found within the brain - :param cylindrical_filter_clusters: Dictionary of points first sorted by the cylindrical electrode - in which they fall and then the cluster in which they fall. The keys of the dictionary are - electrode labels, the values of the dictionary are the cluster points from the threshold-based + Truncates the clusters closest to the skull, which tend to be + oversized, and separates clusters that appear to have grouped two + contacts together. The cluster is filtered with 90% quantile filtering, + using a coordinate from user-input as the mean for the cluster. + + Parameters + –--------- + clusters: dict() + Dictionary of clusters found at a given threshold. + + elec_in_brain: dict() + Dictionary of all the contacts found within the brain. + + cylindrical_filter_clusters: dict() + Dictionary of points first sorted by the cylindrical electrode + in which they fall and then the cluster in which they fall. + The keys of the dictionary are electrode labels, the values of + the dictionary are the cluster points from the threshold-based clustering algorithm that fell into a cylinder. - :param sparse_elec_labels: sparse dictionary of electrode labels given by user input - :return: clusters: Updated dictionary of clusters found along each electrode - with the skull clusters having been resized through quantile filtering and large clusters having been separated. + + sparse_elec_labels: dict() + sparse dictionary of electrode labels given by user input + + Returns + ------- + Updated dictionary of clusters found along each electrode + with the skull clusters having been resized through quantile + filtering and large clusters having been separated. """ # Group cylindrically bounded clusters by electrodes @@ -155,9 +171,18 @@ def process_abnormal_clusters( def fill_one_point(self, p1, p2): """ Computes midpoint. - :param: p1: first point to compute midpoint. - :param: p2: second point to compute midpoint. - :return: midpoint of the two specified points. + + Parameters + –--------- + p1: np.ndarray of dimension 1 x 3 + first point to compute midpoint. + + p2: np.ndarray of dimension 1 x 3 + second point to compute midpoint. + + Returns + ------- + midpoint of the two specified points. """ return (p1 + p2) / 2 @@ -165,9 +190,18 @@ def fill_one_point(self, p1, p2): def fill_two_points(self, p1, p2): """ Computes trisection points. - :param: p1: first point to compute trisection points. - :param: p2: second point to compute trisection points. - :return: two points which trisect the line segment formed by p1 and p2 + + Parameters + ---------- + p1: np.ndarray of dimension 1 x 3 + first point to compute trisection points. + + p2: np.ndarray of dimension 1 x 3 + second point to compute trisection points. + + Returns + ------- + Two points which trisect the line segment formed by p1 and p2. """ return (2 / 3) * p1 + (1 / 3) * p2, (1 / 3) * p1 + (2 / 3) * p2 @@ -175,9 +209,18 @@ def fill_two_points(self, p1, p2): def fill_three_points(self, p1, p2): """ Computes quadrisection points. - :param: p1: first point to compute quadrisection points. - :param: p2: second point to compute qaudrisection points. - :return: three points which quadrisect the line segment formed by p1 and p2 + + Parameters + –--------- + p1: np.ndarray of dimension 1 x 3 + first point to compute quadrisection points. + + p2: np.ndarray of dimension 1 x 3 + second point to compute qaudrisection points. + + Returns + ------- + Three points which quadrisect the line segment formed by p1 and p2. """ return ( (1 / 4) * p1 + (3 / 4) * p2, @@ -188,13 +231,28 @@ def fill_three_points(self, p1, p2): @classmethod def shift_downstream_labels(self, electrode_name, idx, shift_factor, chan_dict): """ - Helps to relabel downstream labels from a given index to maintain sorted order. - :param: electrode_name: string that contains electrode name (e.g. L') - :param: idx: index from which shifting should start - :param: shift_factor: how much to shift downstream labels by - :param: chan_dict: dictionary of channels with standard labeling and their - corresponding coordinates. - :return: updated version of chan_dict with shifted labels to allow for easy insertion + Helps to relabel downstream labels from a given index to maintain + sorted order. + + Parameters + ---------- + electrode_name: str + string that contains electrode name (e.g. L') + + idx: int + index from which shifting should start + + shift_factor: int + how much to shift downstream labels by + + chan_dict: dict + dictionary of channels with standard labeling and their + corresponding coordinates. + + Returns + ------- + Updated version of chan_dict with shifted labels to allow + for easy insertion. """ start = len(list(chan_dict.keys())) for i in range(start, idx - 1, -1): @@ -209,12 +267,19 @@ def compute_dists(self, centroid_dict): """ Compute the distances between a given channel and its immediate neighbor on the right. The last channel has a distance set to 0. - :param: centroid_dict: a dictionary with keys being electrode names and values being - dictionaries consisting of entries of channel names and their corresponding centroid - coordinates. - :return: dists: a dictionary with keys being electrode names and values being dictionaries - consisting of entries of channel names and their corresponding distances as described - above. + + Parameters + ---------- + centroid_dict: dict() + a dictionary with keys being electrode names and values being + dictionaries consisting of entries of channel names and their + corresponding centroid coordinates. + + Returns + ------- + a dictionary with keys being electrode names and values being + dictionaries consisting of entries of channel names and their + corresponding distances as described above. """ dists = {elec: {} for elec in list(centroid_dict.keys())} @@ -232,9 +297,16 @@ def compute_dists(self, centroid_dict): @classmethod def _strip_nans(self, channels): """ - Strip any nan values from a channel array - :param channels: numpy array of channels and possibly nan values - :return temp: numpy array with the same channels excluding nan values + Strip any nan values from a channel array. + + Parameters + ---------- + channels: np.ndarray of dimension 1 x n + numpy array of channels and possibly nan values. + + Returns + ------- + numpy array with the same channels excluding nan values. """ channels = np.array(channels) temp = [chan for chan in channels if not np.isnan(chan).all()] @@ -243,14 +315,25 @@ def _strip_nans(self, channels): @classmethod def reassign_labels(self, centroid_dict): """ - Assigns labels which follow the standard labeling convention for SEEG electrodes. - :param centroid_dict: A dictionary where the keys are each electrode name and values - are dictionaries with entries of channels (does not necessarily have to follow standard - labeling convention) and their corresponding coordinates. - :return result: A dictionary where channels are correctly assigned and sorted in order. - If the electrode name has a ', then the first entry in the dictionary will be the smallest - number (usually 1) and every subsequent entry will be larger. Otherwise, the first entry - in the dictionary will be the largest number and every subsequent entry will be smaller. + Assigns labels which follow the standard labeling convention for SEEG + electrodes. + + Parameters + ---------- + centroid_dict: dict() + A dictionary where the keys are each electrode name and values + are dictionaries with entries of channels (does not necessarily + have to follow standard labeling convention) and their + corresponding coordinates. + + Returns + ------- + A dictionary where channels are correctly assigned and sorted in + order. If the electrode name has a ', then the first entry in the + dictionary will be the smallest number (usually 1) and every + subsequent entry will be larger. Otherwise, the first entry + in the dictionary will be the largest number and every subsequent + entry will be smaller. """ pca = PCA() result = {} @@ -286,17 +369,26 @@ def fill_gaps(self, final_centroids, dists, gap_tolerance): """ Assist in filling in gaps in clustering. - :param: final_centroids: a dictionary with keys being electrode names and values being - dictionaries consisting of entries of channel names and their corresponding centroid - coordinates. - :param: dists: a dictionary with keys being electrode names and values being dictionaries - consisting of entries of channel names and their corresponding distance to their most - immediate neighbor on their right. The rightmost channel for a given electrode has a - distance set to 0. - :param: gap_tolerance: maximum distance we will allow two adjacent contacts to be before - no longer considering them adjacent. - :return: updated versions of final_centroids with adjusted labeling and dists with updated - distances. + Parameters + –--------- + final_centroids: dict() + a dictionary with keys being electrode names and values being + dictionaries consisting of entries of channel names and their + corresponding centroid coordinates. + dists: dict() + a dictionary with keys being electrode names and values being + dictionaries consisting of entries of channel names and their + corresponding distance to their most immediate neighbor on their + right. The rightmost channel for a given electrode has a distance + set to 0. + gap_tolerance: dict() + maximum distance we will allow two adjacent contacts to be before + no longer considering them adjacent. + + Returns + ------- + Updated versions of final_centroids with adjusted labeling and + dists with updated distances. """ for electrode in dists: for i, chan in enumerate(dists[electrode]): @@ -377,10 +469,15 @@ def vox_2_xyz(self, final_centroids_voxels, affine): Convert finalized dictionary of centroids from CT voxel coordinates to xyz coordinates. - :param final_centroids_voxels: Properly labeled dictioanry of centroids - in CT voxel coordinates - :return final_centroids_xyz: Properly labeled dictionary of centroids in - xyz coordinates + Parameters + ---------- + + final_centroids_voxels: dict() + Properly labeled dictioanry of centroids in CT voxel coordinates. + + Returns + ------- + Properly labeled dictionary of centroids in xyz coordinates """ final_centroids_xyz = {} for electrode in final_centroids_voxels.keys(): From 49fd4f706dbac02d1b2c5385a75dad52e2166b41 Mon Sep 17 00:00:00 2001 From: Adam Li Date: Tue, 15 Oct 2019 22:44:02 -0400 Subject: [PATCH 2/6] Deleting random dirs. --- .gitmodules | 3 --- img_pipe | 1 - ndreg | 1 - 3 files changed, 5 deletions(-) delete mode 100644 .gitmodules delete mode 160000 img_pipe delete mode 160000 ndreg diff --git a/.gitmodules b/.gitmodules deleted file mode 100644 index 0fda3a0..0000000 --- a/.gitmodules +++ /dev/null @@ -1,3 +0,0 @@ -[submodule "ndreg"] - path = ndreg - url = https://github.com/neurodata/ndreg.git diff --git a/img_pipe b/img_pipe deleted file mode 160000 index 3511f02..0000000 --- a/img_pipe +++ /dev/null @@ -1 +0,0 @@ -Subproject commit 3511f02e10e0e815b923770d1c05397bf44c2b1f diff --git a/ndreg b/ndreg deleted file mode 160000 index d5b731d..0000000 --- a/ndreg +++ /dev/null @@ -1 +0,0 @@ -Subproject commit d5b731d8a131c3a901492796cf8d06684b5c74c3 From 1245744613dba19f4f71fe7f576438994b8933f3 Mon Sep 17 00:00:00 2001 From: Adam Li Date: Tue, 15 Oct 2019 22:47:08 -0400 Subject: [PATCH 3/6] Fixing import. --- .../contact_localization/electrode_clustering.py | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/neuroimg/pipeline/contact_localization/electrode_clustering.py b/neuroimg/pipeline/contact_localization/electrode_clustering.py index 276e54d..e94d4ab 100644 --- a/neuroimg/pipeline/contact_localization/electrode_clustering.py +++ b/neuroimg/pipeline/contact_localization/electrode_clustering.py @@ -17,6 +17,12 @@ from neuroimg.processing.electrode_clustering.grouping import Cluster, CylindricalGroup from neuroimg.processing.electrode_clustering.postprocess import PostProcessor +try: + sys.path.insert(0, "/Users/ChesterHuynh/img_pipe") + from img_pipe import img_pipe +except ImportError as e: + print(e, flush=True) + return def load_data(ct_scan, brainmask_ct): """ @@ -101,13 +107,6 @@ def apply_atlas(fspatdir, destrieuxfilepath, dktfilepath): :return elec_labels_destriuex: array of contacts labeled with Destriuex atlas :return elec_labels_DKT: array of contacts labeled with Desikan-Killiany atlas """ - try: - sys.path.insert(0, "/Users/ChesterHuynh/img_pipe") - from img_pipe import img_pipe - except ImportError as e: - print(e, flush=True) - return - destriuexname = os.path.splitext(os.path.basename(destrieuxfilepath))[0] dktname = os.path.splitext(os.path.basename(dktfilepath))[0] From 15298d45c3f527b57acf64214af7d94e78465cad Mon Sep 17 00:00:00 2001 From: Adam Li Date: Tue, 15 Oct 2019 22:50:14 -0400 Subject: [PATCH 4/6] Fixing travis.yml. --- .travis.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.travis.yml b/.travis.yml index 37d536e..6488b45 100644 --- a/.travis.yml +++ b/.travis.yml @@ -9,7 +9,7 @@ install: - export PATH="$HOME/miniconda/bin:$PATH" - hash -r - conda config --set always_yes yes --set changeps1 no - - conda update -q conda +# - conda update -q conda - conda info -a - conda create -q -n test-env python=$TRAVIS_PYTHON_VERSION - conda activate test-env From 733914141fa32ee2bc8f965383b840231b81c2cd Mon Sep 17 00:00:00 2001 From: Adam Li Date: Tue, 15 Oct 2019 22:52:34 -0400 Subject: [PATCH 5/6] Fixing local config to run on workstation. --- neuroimg/pipeline/config/localconfig.yaml | 59 ++++++++--------------- 1 file changed, 20 insertions(+), 39 deletions(-) diff --git a/neuroimg/pipeline/config/localconfig.yaml b/neuroimg/pipeline/config/localconfig.yaml index 16df1e1..c7e90df 100644 --- a/neuroimg/pipeline/config/localconfig.yaml +++ b/neuroimg/pipeline/config/localconfig.yaml @@ -1,51 +1,37 @@ ############## define directories that we work with ############# rawdatadir: # "/home/ksr/Desktop/contact_localization/raw" - "/Users/ChesterHuynh/sarmalab/contact_localization_proj/rawdata" - # "/home/adam2392/hdd2/data/neuroimaging/raw" +# "/Users/ChesterHuynh/sarmalab/contact_localization_proj/rawdata" + "/home/adam2392/hdd2/data/neuroimaging/raw" # "/Users/adam2392/Dropbox/phd_research/data/neuroimaging_results/raw/" ############# define FreeSurfer Subject Directory ############# fs_outputdatadir: # "/home/ksr/Desktop/contact_localization/freesurfer_output" - "/Users/ChesterHuynh/sarmalab/contact_localization_proj/fs_outputdata" - # "/home/adam2392/hdd2/data/neuroimaging/freesurfer_output/" +# "/Users/ChesterHuynh/sarmalab/contact_localization_proj/fs_outputdata" + "/home/adam2392/hdd2/data/neuroimaging/freesurfer_output/" # "/Users/adam2392/Dropbox/phd_research/data/neuroimaging_results/freesurfer_output/" ############# define list of files to run this for ############# patients: [ -# 'efri06', -# 'efri07', -# 'efri10', -# 'efri12', -# 'efri13', -# 'efri15', -# 'efri16' -# 'efri17', -# 'efri18', -# 'efri21' -# 'efri02', -# 'efri09', -# 'efri14', -# 'efri20' # 'pt1', 'pt2', 'pt3', 'pt6', 'pt8', 'pt10', 'pt11', 'pt12', 'pt13', 'pt14', 'pt15', 'pt16', 'pt17', - # 'la02', -# 'la17', -# 'la23', - # 'la03', - 'la04', - # 'la05', - # 'la06', - # 'la07', - # 'la08', - # #'la09', - # 'la10', - # 'la11', - # 'la12', - # 'la13', - # 'la15', - #'la16', +# 'la03', +# 'la04', +# 'la05', + 'la02', + 'la06', + 'la07', + 'la08', + 'la09', + 'la10', + 'la11', + 'la12', + 'la13', + 'la15', + 'la16', + 'la17', + 'la23', # 'la21', # 'la22', # 'la24', @@ -74,11 +60,6 @@ patients: # 'nl21', # 'nl22', # 'nl23', -# 'umf001', -# 'umf002', -# 'umf003', -## 'umf004', -# 'umf005', # 'tvb1', # 'tvb2', # 'tvb5', From ee0ad937119625a812d8497b4259e3fcd2e7b708 Mon Sep 17 00:00:00 2001 From: Adam Li Date: Tue, 12 Nov 2019 23:53:05 -0500 Subject: [PATCH 6/6] Adding docs, and cleaning up how we initialize folders inside snakemake. --- CONTRIBUTING.md | 8 +- README.md | 63 +- docs/Makefile | 19 + docs/conf.py | 173 ++ docs/contributing.rst | 168 ++ docs/{ => extra_docs}/README.md | 0 .../ContactLocInstructions_minimal.odt | Bin .../contact_localization_walkthrough.pptx | Bin .../localizingelectrodes_instructions.docx | Bin .../localizingelectrodes_instructions.pdf | Bin docs/{ => extra_docs}/data-description.md | 0 docs/index.rst | 20 + docs/install.rst | 43 + docs/license.rst | 680 ++++++++ docs/make.bat | 35 + .../reference/pipeline.rst | 0 .../__init__.py => docs/reference/utils.rst | 0 docs/requirements.txt | 5 + docs/tests.md | 36 - docs/tutorial.rst | 68 + .../tutorials/contact_localization.rst | 0 .../tutorials/standard_freesurfer.rst | 0 .../tutorials/visualization.rst | 0 .../dev/create_surface_files_mricloud.py | 42 - .../format/dev/create_volume_voxel_files.py | 46 - .../format/dev/elec_endpoints_example.txt | 3 - neuroimg/format/dev/gain_matrix_seeg.py | 215 --- neuroimg/format/dev/register_electrodes.py | 68 - neuroimg/pipeline/README.md | 8 +- neuroimg/pipeline/config/cluster.json | 28 - neuroimg/pipeline/config/localconfig.yaml | 44 +- .../config/preformat_config.schema.yaml | 23 +- .../pipeline/contact_localization/Snakefile | 175 +- ...roimaging_pipeline_contactlocalization.pdf | Bin 11787 -> 0 bytes .../dev/conform_coordspace.py | 82 - .../convert_ielvis_to_imgpipe.py | 66 - .../snake_convert_ielvis_to_imgpipe | 90 - .../matlab/_old/la03_CT_acpc_f.nii | Bin 82313568 -> 0 bytes .../matlab/_old/run_localization_fieldtrip.m | 86 - .../_old/run_localization_fieldtrip_v2.m | 73 - .../matlab/_old/test_CT_adam.m | 1474 ----------------- .../utils}/__init__.py | 0 .../{ => utils}/convert_coordspace.py | 0 .../{ => utils}/convert_to_txt.py | 0 .../{ => utils}/visualize_results.py | 0 neuroimg/pipeline/coregistration/Snakefile | 241 +-- ...g_neuroimaging_pipeline_coregistration.pdf | Bin 8041 -> 0 bytes .../coregistration/run_lddmm_coregister.py | 75 - neuroimg/pipeline/coregistration/run_ndreg.py | 111 -- .../diffusion_tensor_imaging/dti_snakefile | 162 -- .../pipeline/dev/post_conversions_snakefile | 310 ---- .../dev/postprocess_analysis/Snakefile | 123 -- .../run_volume_computation.py | 119 -- .../resection_ablation_estimation/__init__.py | 0 ..._neuroimaging_pipeline_resectionvolume.pdf | Bin 14157 -> 0 bytes .../resectvolume_snakefile | 360 ---- .../pipeline/dev/visualize_data_snakefile | 55 - neuroimg/pipeline/fileutils.py | 44 + neuroimg/pipeline/reconstruction/Snakefile | 227 +-- ...g_neuroimaging_pipeline_reconstruction.pdf | Bin 8110 -> 0 bytes .../dag_pipeline_reconstruction.pdf | Bin 0 -> 33891 bytes neuroimg/pipeline/tvb_packaging/Snakefile | 159 +- 62 files changed, 1512 insertions(+), 4315 deletions(-) create mode 100644 docs/Makefile create mode 100644 docs/conf.py create mode 100755 docs/contributing.rst rename docs/{ => extra_docs}/README.md (100%) rename docs/{ => extra_docs}/contact_localization/ContactLocInstructions_minimal.odt (100%) rename docs/{ => extra_docs}/contact_localization/contact_localization_walkthrough.pptx (100%) rename docs/{ => extra_docs}/contact_localization/localizingelectrodes_instructions.docx (100%) rename docs/{ => extra_docs}/contact_localization/localizingelectrodes_instructions.pdf (100%) rename docs/{ => extra_docs}/data-description.md (100%) create mode 100644 docs/index.rst create mode 100755 docs/install.rst create mode 100755 docs/license.rst create mode 100644 docs/make.bat rename neuroimg/format/dev/__init__.py => docs/reference/pipeline.rst (100%) rename neuroimg/pipeline/contact_localization/dev/__init__.py => docs/reference/utils.rst (100%) create mode 100644 docs/requirements.txt delete mode 100644 docs/tests.md create mode 100755 docs/tutorial.rst rename neuroimg/pipeline/contact_localization/ielvis_visualization/__init__.py => docs/tutorials/contact_localization.rst (100%) rename neuroimg/pipeline/dev/__init__.py => docs/tutorials/standard_freesurfer.rst (100%) rename neuroimg/pipeline/dev/diffusion_tensor_imaging/__init__.py => docs/tutorials/visualization.rst (100%) delete mode 100644 neuroimg/format/dev/create_surface_files_mricloud.py delete mode 100644 neuroimg/format/dev/create_volume_voxel_files.py delete mode 100644 neuroimg/format/dev/elec_endpoints_example.txt delete mode 100755 neuroimg/format/dev/gain_matrix_seeg.py delete mode 100644 neuroimg/format/dev/register_electrodes.py delete mode 100644 neuroimg/pipeline/contact_localization/dag_neuroimaging_pipeline_contactlocalization.pdf delete mode 100644 neuroimg/pipeline/contact_localization/dev/conform_coordspace.py delete mode 100644 neuroimg/pipeline/contact_localization/ielvis_visualization/convert_ielvis_to_imgpipe.py delete mode 100644 neuroimg/pipeline/contact_localization/ielvis_visualization/snake_convert_ielvis_to_imgpipe delete mode 100644 neuroimg/pipeline/contact_localization/matlab/_old/la03_CT_acpc_f.nii delete mode 100644 neuroimg/pipeline/contact_localization/matlab/_old/run_localization_fieldtrip.m delete mode 100644 neuroimg/pipeline/contact_localization/matlab/_old/run_localization_fieldtrip_v2.m delete mode 100755 neuroimg/pipeline/contact_localization/matlab/_old/test_CT_adam.m rename neuroimg/pipeline/{dev/postprocess_analysis => contact_localization/utils}/__init__.py (100%) rename neuroimg/pipeline/contact_localization/{ => utils}/convert_coordspace.py (100%) rename neuroimg/pipeline/contact_localization/{ => utils}/convert_to_txt.py (100%) rename neuroimg/pipeline/contact_localization/{ => utils}/visualize_results.py (100%) delete mode 100644 neuroimg/pipeline/coregistration/dag_neuroimaging_pipeline_coregistration.pdf delete mode 100644 neuroimg/pipeline/coregistration/run_lddmm_coregister.py delete mode 100644 neuroimg/pipeline/coregistration/run_ndreg.py delete mode 100644 neuroimg/pipeline/dev/diffusion_tensor_imaging/dti_snakefile delete mode 100644 neuroimg/pipeline/dev/post_conversions_snakefile delete mode 100644 neuroimg/pipeline/dev/postprocess_analysis/Snakefile delete mode 100644 neuroimg/pipeline/dev/postprocess_analysis/run_volume_computation.py delete mode 100644 neuroimg/pipeline/dev/resection_ablation_estimation/__init__.py delete mode 100644 neuroimg/pipeline/dev/resection_ablation_estimation/dag_neuroimaging_pipeline_resectionvolume.pdf delete mode 100644 neuroimg/pipeline/dev/resection_ablation_estimation/resectvolume_snakefile delete mode 100644 neuroimg/pipeline/dev/visualize_data_snakefile create mode 100644 neuroimg/pipeline/fileutils.py delete mode 100644 neuroimg/pipeline/reconstruction/dag_neuroimaging_pipeline_reconstruction.pdf create mode 100644 neuroimg/pipeline/reconstruction/dag_pipeline_reconstruction.pdf diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 406632e..ae75d06 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -1,4 +1,4 @@ -Contributing to EEGIO +Contributing to NeuroimgPipe ====================== (adopted from scikit-learn) @@ -6,15 +6,15 @@ Contributing to EEGIO The latest contributing guide is available in the repository at `docs/contributing.rst`, or online at: -There are many ways to contribute to EEGIO, with the most common ones +There are many ways to contribute to NeuroimgPipe, with the most common ones being contribution of code or documentation to the project. Improving the documentation is no less important than improving the library itself. If you find a typo in the documentation, or have made improvements, do not hesitate to submit a GitHub pull request. Documentation can be found under the -[doc/](https://github.com/adam2392/eegio/tree/master/doc) directory. +[doc/](https://github.com/adam2392/neuroimg_pipeline/tree/master/doc) directory. But there are many other ways to help. In particular answering queries on the -[issue tracker](https://github.com/adam2392/eegio/issues), and +[issue tracker](https://github.com/adam2392/neuroimg_pipeline/issues), and investigating bugs are very valuable contributions that decrease the burden on the project maintainers. diff --git a/README.md b/README.md index bf3d7e7..913155f 100644 --- a/README.md +++ b/README.md @@ -7,13 +7,11 @@ ![GitHub repo size](https://img.shields.io/github/repo-size/adam2392/neuroimg_pipeline) -By: Adam Li - -Date: 10/4/18 - -This repo describes Sarma lab effort to pipeline explicitly a neuroimaging data workflow that involves T1 MRI, CT, DTI +This repo describes Sarma lab effort to pipeline explicitly a neuroimaging data workflow that involves T1 MRI, CT, and iEEG data (ECoG, or SEEG). +For incorporation of DTI data, see ndmeg: https://github.com/neurodata/ndmg + - Setup and Installation @@ -30,21 +28,20 @@ and iEEG data (ECoG, or SEEG). - [ ] Add support for MRICloud running using R-script. Possibly convert to Python script. - [ ] Create Python pipeline for running everything, or submit PR to Chang Lab's to run SEEG. - [ ] Create unit and integration tests using pytest that test: pipeline in both snakemake and Python -- [ ] Add visualization features for SEEG that can be synced into Chang's lab repo. - [ ] Add Docker container for project # Setup and Installation There are a couple of tools that you need to install in your system before everything is working. You ar recommended to use a Linux based OS. Follow links and tutorials on each respective tool to install. Preferably this is done via Docker, or Singularity, but if not, then: -0. Anaconda and Python3.6+ - * Conda (https://docs.anaconda.com/anaconda/install/) - * This is mainly necessary to run img_pipe (ECoG localization with Chang Lab repo), snakemake, and any Python wrapper code +Anaconda and Python3.6+ : + * Conda (https://docs.anaconda.com/anaconda/install/) + * This is mainly necessary to run img_pipe (ECoG localization with Chang Lab repo), snakemake, and any Python wrapper code i. Conda env - # probably doesn't work + # create environment conda create -n neuroimgpipe conda activate neuroimgpipe @@ -63,9 +60,6 @@ Follow links and tutorials on each respective tool to install. Preferably this i conda install -c conda-forge pyvtk pip install img-pipe==2019.3.15.2 - iii. (Optional and outdated) Update all submodules - - git submodule update --init --recursive ## Modules to Install 1. Reconstruction @@ -100,14 +94,20 @@ Follow links and tutorials on each respective tool to install. Preferably this i 8. (Optional) Nonlinear Registration NDREG: * NDReg (https://github.com/neurodata/ndreg) +# Data Organization + +We use BIDS. +See https://github.com/bids-standard/bids-starter-kit/wiki/The-BIDS-folder-hierarchy + # Running Your Own Image Patients 0. Setup your raw data directory for your patient to be read in: * /patient_id/ - - /premri/ - - /postct/ - - /dti/ (optional) + - /mri/ + - /ct/ + + For more details, see BIDS: https://bids.neuroimaging.io/ 1. (Optional) Setup data directory for your patient in FreeSurfer format: @@ -158,12 +158,6 @@ data directories of your data. This is under pipeline/config/localconfig.yaml -## Docker and Singularity -TBD -1. Freesurfer with FSL -2. MRTrix3 -3. NDReG - # Pipeline Description At a high level, this pipeline is taking neuroimaging data of a patient to produce usable data about the brain's geometry, regional parcellation into atlas regions, connectivity between brain regions measured by white matter tracts, and channel localization in MRI space. @@ -228,8 +222,8 @@ At a high level, this pipeline is taking neuroimaging data of a patient to produ TBD # Localizing Electrodes Process -For NCSL specific Readme, check out: [link](docs/contact_localization/localizingelectrodes_instructions.pdf) -For general-purpose Readme, check out: [link](docs/contact_localization/localizingelectrodes_instructions.pdf) +For NCSL specific Readme, check out: [link](docs/extra_docs/contact_localization/localizingelectrodes_instructions.pdf) +For general-purpose Readme, check out: [link](docs/extra_docs/contact_localization/localizingelectrodes_instructions.pdf) To only localize contacts using fieldtrip toolbox GUI, or img_pipe GUI, then follow these instructions: 1. Install SPM (preferably 12): https://www.fil.ion.ucl.ac.uk/spm/software/spm12/ @@ -266,27 +260,6 @@ language. sphinx-quickstart - -# Testing -Install testing and formatting libs: - - conda install sphinx black pytest pytest-cov coverage - pip install coverage-badge - -Run tests - - black neuroimg/* - black tests/* - pylint ./neuroimg/ - pre-commit run black --all-files - pytest --cov-config=.coveragerc --cov=./neuroimg/ tests/ - coverage-badge -f -o coverage.svg - -Tests is organized into two directories right now: -1. eegio/: consists of all unit tests related to various parts of eegio. -2. api/: consists of various integration tests tha test when eegio should work. - - ### Pipeline Process Visualized [DAG of Pipeline in Snakemake](neuroimg/pipeline/dag_neuroimaging_pipeline.pdf) diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 0000000..298ea9e --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,19 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line. +SPHINXOPTS = +SPHINXBUILD = sphinx-build +SOURCEDIR = . +BUILDDIR = _build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) \ No newline at end of file diff --git a/docs/conf.py b/docs/conf.py new file mode 100644 index 0000000..d84a494 --- /dev/null +++ b/docs/conf.py @@ -0,0 +1,173 @@ +# -*- coding: utf-8 -*- +# +# Configuration file for the Sphinx documentation builder. +# +# This file does only contain a selection of the most common options. For a +# full list see the documentation: +# http://www.sphinx-doc.org/en/master/config + +# -- Path setup -------------------------------------------------------------- + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. +# +# import os +# import sys +# sys.path.insert(0, os.path.abspath('.')) + + +# -- Project information ----------------------------------------------------- + +project = 'neuroimgpipe' +copyright = '2019, Adam Li' +author = 'Adam Li' + +# The short X.Y version +version = '' +# The full version, including alpha/beta/rc tags +release = '0.1' + + +# -- General configuration --------------------------------------------------- + +# If your documentation needs a minimal Sphinx version, state it here. +# +# needs_sphinx = '1.0' + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ +] + +# Add any paths that contain templates here, relative to this directory. +templates_path = ['_templates'] + +# The suffix(es) of source filenames. +# You can specify multiple suffix as a list of string: +# +# source_suffix = ['.rst', '.md'] +source_suffix = '.rst' + +# The master toctree document. +master_doc = 'index' + +# The language for content autogenerated by Sphinx. Refer to documentation +# for a list of supported languages. +# +# This is also used if you do content translation via gettext catalogs. +# Usually you set "language" from the command line for these cases. +language = None + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This pattern also affects html_static_path and html_extra_path. +exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] + +# The name of the Pygments (syntax highlighting) style to use. +pygments_style = None + + +# -- Options for HTML output ------------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +html_theme = 'alabaster' + +# Theme options are theme-specific and customize the look and feel of a theme +# further. For a list of options available for each theme, see the +# documentation. +# +# html_theme_options = {} + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_static_path = ['_static'] + +# Custom sidebar templates, must be a dictionary that maps document names +# to template names. +# +# The default sidebars (for documents that don't match any pattern) are +# defined by theme itself. Builtin themes are using these templates by +# default: ``['localtoc.html', 'relations.html', 'sourcelink.html', +# 'searchbox.html']``. +# +# html_sidebars = {} + + +# -- Options for HTMLHelp output --------------------------------------------- + +# Output file base name for HTML help builder. +htmlhelp_basename = 'neuroimgpipedoc' + + +# -- Options for LaTeX output ------------------------------------------------ + +latex_elements = { + # The paper size ('letterpaper' or 'a4paper'). + # + # 'papersize': 'letterpaper', + + # The font size ('10pt', '11pt' or '12pt'). + # + # 'pointsize': '10pt', + + # Additional stuff for the LaTeX preamble. + # + # 'preamble': '', + + # Latex figure (float) alignment + # + # 'figure_align': 'htbp', +} + +# Grouping the document tree into LaTeX files. List of tuples +# (source start file, target name, title, +# author, documentclass [howto, manual, or own class]). +latex_documents = [ + (master_doc, 'neuroimgpipe.tex', 'neuroimgpipe Documentation', + 'Adam Li', 'manual'), +] + + +# -- Options for manual page output ------------------------------------------ + +# One entry per manual page. List of tuples +# (source start file, name, description, authors, manual section). +man_pages = [ + (master_doc, 'neuroimgpipe', 'neuroimgpipe Documentation', + [author], 1) +] + + +# -- Options for Texinfo output ---------------------------------------------- + +# Grouping the document tree into Texinfo files. List of tuples +# (source start file, target name, title, author, +# dir menu entry, description, category) +texinfo_documents = [ + (master_doc, 'neuroimgpipe', 'neuroimgpipe Documentation', + author, 'neuroimgpipe', 'One line description of project.', + 'Miscellaneous'), +] + + +# -- Options for Epub output ------------------------------------------------- + +# Bibliographic Dublin Core info. +epub_title = project + +# The unique identifier of the text. This can be a ISBN number +# or the project homepage. +# +# epub_identifier = '' + +# A unique identification for the text. +# +# epub_uid = '' + +# A list of files that should not be packed into the epub file. +epub_exclude_files = ['search.html'] diff --git a/docs/contributing.rst b/docs/contributing.rst new file mode 100755 index 0000000..188fc9a --- /dev/null +++ b/docs/contributing.rst @@ -0,0 +1,168 @@ +Contributing to neuroimg_pipeline +====================== + +(adopted from scikit-learn) + +Submitting a bug report or a feature request +-------------------------------------------- + +We use GitHub issues to track all bugs and feature requests; feel free to open +an issue if you have found a bug or wish to see a feature implemented. + +In case you experience issues using this package, do not hesitate to submit a +ticket to the +`Bug Tracker `_. You are +also welcome to post feature requests or pull requests. + +It is recommended to check that your issue complies with the +following rules before submitting: + +- Verify that your issue is not being currently addressed by other + `issues `_ + or `pull requests `_. + +- If you are submitting a bug report, we strongly encourage you to follow the guidelines in + :ref:`filing_bugs`. + +.. _filing_bugs: + +How to make a good bug report +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +When you submit an issue to `Github +`__, please do your best to +follow these guidelines! This will make it a lot easier to provide you with good +feedback: + +- The ideal bug report contains a **short reproducible code snippet**, this way + anyone can try to reproduce the bug easily (see `this + `_ for more details). If your snippet is + longer than around 50 lines, please link to a `gist + `_ or a github repo. + +- If not feasible to include a reproducible snippet, please be specific about + what **estimators and/or functions are involved and the shape of the data**. + +- If an exception is raised, please **provide the full traceback**. + +- Please include your **operating system type and version number**, as well as + your **Python and neuroimg_pipeline versions**. This information + can be found by running the following code snippet:: + + import platform; print(platform.platform()) + import sys; print("Python", sys.version) + import neuroimg_pipeline; print("neuroimg_pipeline", neuroimg_pipeline.__version__) + +- Please ensure all **code snippets and error messages are formatted in + appropriate code blocks**. See `Creating and highlighting code blocks + `_ + for more details. + +Contributing Code +----------------- + +The preferred workflow for contributing to neuroimg_pipeline is to fork the main +repository on GitHub, clone, and develop on a branch. Steps: + +1. Fork the `project repository `__ by clicking + on the ‘Fork’ button near the top right of the page. This creates a copy + of the code under your GitHub user account. For more details on how to + fork a repository see `this + guide `__. + +2. Clone your fork of the neuroimg_pipeline repo from your GitHub account to your + local disk: + + .. code:: bash + + $ git clone git@github.com:YourLogin/neuroimg_pipeline.git + $ cd neuroimg_pipeline + +3. Create a ``feature`` branch to hold your development changes: + + .. code:: bash + + $ git checkout -b my-feature + + Always use a ``feature`` branch. It’s good practice to never work on + the ``master`` branch! + +4. Develop the feature on your feature branch. Add changed files using + ``git add`` and then ``git commit`` files: + + .. code:: bash + + $ git add modified_files + $ git commit + + to record your changes in Git, then push the changes to your GitHub + account with: + + .. code:: bash + + $ git push -u origin my-feature + +Pull Request Checklist +~~~~~~~~~~~~~~~~~~~~~~ + +We recommended that your contribution complies with the following rules +before you submit a pull request: + +- Follow the `coding-guidelines <#guidelines>`__. +- Give your pull request a helpful title that summarises what your contribution does. + In some cases ``Fix `` is enough. ``Fix #`` is not enough. +- All public methods should have informative docstrings with sample + usage presented as doctests when appropriate. +- At least one paragraph of narrative documentation with links to references in + the literature (with PDF links when possible) and the example. +- All functions and classes must have unit tests. These should include, + at the very least, type checking and ensuring correct computation/outputs. +- Ensure all tests are passing locally using ``pytest``. Install the necessary + packages by: + + .. code:: bash + + $ pip install pytest pytest-cov + + then run + + .. code:: bash + + $ pytest + + or you can run pytest on a single test file by + + .. code:: bash + + $ pytest path/to/test.py + +- Run an autoformatter. We use ``black`` and would like for you to + format all files using ``black``. You can run the following lines to + format your files. + + .. code:: bash + + $ pip install black + $ black path/to/module.py + +Guidelines +---------- + +Coding Guidelines +~~~~~~~~~~~~~~~~~ + +Uniformly formatted code makes it easier to share code ownership. neuroimg_pipeline +package closely follows the official Python guidelines detailed in +`PEP8 `__ that detail how +code should be formatted and indented. Please read it and follow it. + +Docstring Guidelines +~~~~~~~~~~~~~~~~~~~~ + +Properly formatted docstrings is required for documentation generation +by Sphinx. The pygraphstats package closely follows the numpydoc +guidelines. Please read and follow the +`numpydoc `__ +guidelines. Refer to the +`example.py `__ +provided by numpydoc. diff --git a/docs/README.md b/docs/extra_docs/README.md similarity index 100% rename from docs/README.md rename to docs/extra_docs/README.md diff --git a/docs/contact_localization/ContactLocInstructions_minimal.odt b/docs/extra_docs/contact_localization/ContactLocInstructions_minimal.odt similarity index 100% rename from docs/contact_localization/ContactLocInstructions_minimal.odt rename to docs/extra_docs/contact_localization/ContactLocInstructions_minimal.odt diff --git a/docs/contact_localization/contact_localization_walkthrough.pptx b/docs/extra_docs/contact_localization/contact_localization_walkthrough.pptx similarity index 100% rename from docs/contact_localization/contact_localization_walkthrough.pptx rename to docs/extra_docs/contact_localization/contact_localization_walkthrough.pptx diff --git a/docs/contact_localization/localizingelectrodes_instructions.docx b/docs/extra_docs/contact_localization/localizingelectrodes_instructions.docx similarity index 100% rename from docs/contact_localization/localizingelectrodes_instructions.docx rename to docs/extra_docs/contact_localization/localizingelectrodes_instructions.docx diff --git a/docs/contact_localization/localizingelectrodes_instructions.pdf b/docs/extra_docs/contact_localization/localizingelectrodes_instructions.pdf similarity index 100% rename from docs/contact_localization/localizingelectrodes_instructions.pdf rename to docs/extra_docs/contact_localization/localizingelectrodes_instructions.pdf diff --git a/docs/data-description.md b/docs/extra_docs/data-description.md similarity index 100% rename from docs/data-description.md rename to docs/extra_docs/data-description.md diff --git a/docs/index.rst b/docs/index.rst new file mode 100644 index 0000000..2955367 --- /dev/null +++ b/docs/index.rst @@ -0,0 +1,20 @@ +.. neuroimgpipe documentation master file, created by + sphinx-quickstart on Tue Nov 12 22:43:39 2019. + You can adapt this file completely to your liking, but it should at least + contain the root `toctree` directive. + +Welcome to neuroimgpipe's documentation! +======================================== + +.. toctree:: + :maxdepth: 2 + :caption: Contents: + + + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` diff --git a/docs/install.rst b/docs/install.rst new file mode 100755 index 0000000..2f66682 --- /dev/null +++ b/docs/install.rst @@ -0,0 +1,43 @@ +Install +======= + + +Below we assume you have the default Python environment already configured on +your computer and you intend to install ``neuroimgpipe`` inside of it. If you want +to create and work with Python virtual environments, please follow instructions +on `venv `_ and `virtual +environments `_. + +First, make sure you have the latest version of ``pip`` (the Python package manager) +installed. If you do not, refer to the `Pip documentation +`_ and install ``pip`` first. + +Install the released version +---------------------------- + +This pipeline is meant for you to adjust data paths and run locally. +You can manually download ``neuroimgpipe`` from +`GitHub `_ + + +Python package dependencies +--------------------------- +neuroimgpipe requires the following packages: + +- numpy +- pandas +- scipy +- snakemake +- skimage + + +Hardware requirements +--------------------- +`neuroimgpipe` package requires only a standard computer with enough RAM to support the in-memory operations. + +OS Requirements +--------------- +This package is supported for *Linux* and *macOS*. However, the package has been tested on the following systems: + +- Linux: N/A +- macOS: N/A \ No newline at end of file diff --git a/docs/license.rst b/docs/license.rst new file mode 100755 index 0000000..859b397 --- /dev/null +++ b/docs/license.rst @@ -0,0 +1,680 @@ +License +======= +neuroimgpipe is distributed with Apache 2.0 license. + +:: + + GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If the program does terminal interaction, make it output a short +notice like this when it starts in an interactive mode: + + Copyright (C) + This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. + This is free software, and you are welcome to redistribute it + under certain conditions; type `show c' for details. + +The hypothetical commands `show w' and `show c' should show the appropriate +parts of the General Public License. Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/docs/make.bat b/docs/make.bat new file mode 100644 index 0000000..27f573b --- /dev/null +++ b/docs/make.bat @@ -0,0 +1,35 @@ +@ECHO OFF + +pushd %~dp0 + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build +) +set SOURCEDIR=. +set BUILDDIR=_build + +if "%1" == "" goto help + +%SPHINXBUILD% >NUL 2>NUL +if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-build' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.http://sphinx-doc.org/ + exit /b 1 +) + +%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% +goto end + +:help +%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% + +:end +popd diff --git a/neuroimg/format/dev/__init__.py b/docs/reference/pipeline.rst similarity index 100% rename from neuroimg/format/dev/__init__.py rename to docs/reference/pipeline.rst diff --git a/neuroimg/pipeline/contact_localization/dev/__init__.py b/docs/reference/utils.rst similarity index 100% rename from neuroimg/pipeline/contact_localization/dev/__init__.py rename to docs/reference/utils.rst diff --git a/docs/requirements.txt b/docs/requirements.txt new file mode 100644 index 0000000..559f2e6 --- /dev/null +++ b/docs/requirements.txt @@ -0,0 +1,5 @@ +sphinx==1.8.5 +sphinx_rtd_theme>=0.4.2 +sphinxcontrib-rawfiles +numpydoc +nbsphinx \ No newline at end of file diff --git a/docs/tests.md b/docs/tests.md deleted file mode 100644 index d41242f..0000000 --- a/docs/tests.md +++ /dev/null @@ -1,36 +0,0 @@ -# Tests -1. test failed data - - Macauley/Kristin to insert fake data -2. test patient - - LA02 - - EFRI03 -3. test: - - test plotting brain regions - - test plotting seeg channels - - test getting brain_region -> seeg channels - - -1. Input -- take CT Images -- take MRI Image, brain envelope -- - -Methods: -- map brain envelope to the CT space and mask the skull out -- applying simple threshold - - can get clusters of bright spots that appear for varying different thresholds - - -- computing distance between each dot with all other clusters - - distance matrix - - use another threshold to decide which are connected and not - - loop through and check if they are in a line or not - - now each grouping is a vector of channels that represent an electrode -(note that it does not handle the case when the channels are not put into a line) - - -2. Output -- output list of channels grouped by electrodes -- excel sheet that can group these electrodes - - missing electrode when algorithm fails - -> can loop back to read into the function again with an entry point - \ No newline at end of file diff --git a/docs/tutorial.rst b/docs/tutorial.rst new file mode 100755 index 0000000..ef8ff51 --- /dev/null +++ b/docs/tutorial.rst @@ -0,0 +1,68 @@ +******** +Tutorial +******** + +.. _models_tutorials: + +Models +====== +This tutorial presents several random graph models: the Erdos-Renyi (ER) model, degree-corrected ER model, +stochastic block model (SBM), degree-corrected SBM, and random dot product graph model. These models provide a basis for studying random graphs. All models are shown fit to the same dataset. + +.. toctree:: + :maxdepth: 1 + + tutorials/models/models + +.. _simulations_tutorials: + +Simulations +=========== +The following tutorials demonstrate how to easily sample random graphs from graph models such as the Erdos-Renyi model, +stochastic block model, and random dot product graph (RDPG). + +.. toctree:: + :maxdepth: 1 + + tutorials/simulations/erdos_renyi + tutorials/simulations/sbm + tutorials/simulations/rdpg + +.. _embed_tutorials: + +Embedding +========= +Inference on random graphs depends on low-dimensional Euclidean representation of the vertices of graphs, known as *graph embeddings*, typically given by spectral decompositions of adjacency or Laplacian matrices. Below are tutorials for computing graph embeddings of single graph and multiple graphs. + +.. toctree:: + :maxdepth: 1 + + tutorials/embedding/AdjacencySpectralEmbed + tutorials/embedding/Omnibus + +.. _inference_tutorials: + +Inference +=========================== +Statistical testing on graphs requires specialized methodology in order to account +for the fact that the edges and nodes of a graph are dependent on one another. Below +are tutorials for robust statistical hypothesis testing on multiple graphs. + +.. toctree:: + :maxdepth: 1 + + tutorials/inference/latent_position_test + tutorials/inference/latent_distribution_test + +.. _plot_tutorials: + +Plotting +======== +The following tutorials present ways to visualize the graphs, such as its adjacency matrix, and graph embeddings. + +.. toctree:: + :maxdepth: 1 + + tutorials/plotting/heatmaps + tutorials/plotting/gridplot + tutorials/plotting/pairplot diff --git a/neuroimg/pipeline/contact_localization/ielvis_visualization/__init__.py b/docs/tutorials/contact_localization.rst similarity index 100% rename from neuroimg/pipeline/contact_localization/ielvis_visualization/__init__.py rename to docs/tutorials/contact_localization.rst diff --git a/neuroimg/pipeline/dev/__init__.py b/docs/tutorials/standard_freesurfer.rst similarity index 100% rename from neuroimg/pipeline/dev/__init__.py rename to docs/tutorials/standard_freesurfer.rst diff --git a/neuroimg/pipeline/dev/diffusion_tensor_imaging/__init__.py b/docs/tutorials/visualization.rst similarity index 100% rename from neuroimg/pipeline/dev/diffusion_tensor_imaging/__init__.py rename to docs/tutorials/visualization.rst diff --git a/neuroimg/format/dev/create_surface_files_mricloud.py b/neuroimg/format/dev/create_surface_files_mricloud.py deleted file mode 100644 index 1e3a841..0000000 --- a/neuroimg/format/dev/create_surface_files_mricloud.py +++ /dev/null @@ -1,42 +0,0 @@ -import sys - -import numpy as np - -sys.path.append("../../../") - - -def read_mricloud_lut(lut_filepath): - # - pass - - -def generate_surfaces(): - pass - # compute the subcortical and cortical surfaces - surf_subcort = surface_worker.get_subcortical_surfaces( - subcort_surf_direc, region_index_mapping - ) - surf_cort = surface_worker.get_cortical_surfaces( - cort_surf_direc, label_direc, region_index_mapping - ) - - # compute the region parameters for subcort and cort - regions, areas, orientations, centers - region_params_subcort = surface_worker.compute_region_params(surf_subcort, True) - region_params_cort = surface_worker.compute_region_params(surf_cort, False) - - nregions = max(region_index_mapping.trg_table.inds) + 1 - orientations = np.zeros((nregions, 3)) - areas = np.zeros(nregions) - centers = np.zeros((nregions, 3)) - cortical = np.zeros(nregions, dtype=bool) - - # loop through subcortical and cortical regions - for region_params, is_cortical in [ - (region_params_subcort, False), - (region_params_cort, True), - ]: - regions, reg_areas, reg_orientations, reg_centers = region_params - orientations[regions, :] = reg_orientations - areas[regions] = reg_areas - centers[regions, :] = reg_centers - cortical[regions] = is_cortical diff --git a/neuroimg/format/dev/create_volume_voxel_files.py b/neuroimg/format/dev/create_volume_voxel_files.py deleted file mode 100644 index 1fc4445..0000000 --- a/neuroimg/format/dev/create_volume_voxel_files.py +++ /dev/null @@ -1,46 +0,0 @@ -import os -import sys -import argparse -import nibabel as nb -import numpy as np - -from neuroimg.base.objects import GetSurface, RegionIndexMapping, StructuralDataset - -parser = argparse.ArgumentParser() -parser.add_argument("dk_file", help="The filepath to the destrieux parcellation") -parser.add_argument("destrieux_file", help="The filepath to the destrieux parcellation") -parser.add_argument("lut_file", help="The lut table file target.") -parser.add_argument("out_dk_file", help="The output dk filepath.") -parser.add_argument("out_destrieux_file", help="The output destrieux filepath.") - - -def read_file(filepath): - img = nb.load(filepath) - - return img - - -def create_voxel_volume_txt(img, outfilepath): - # create voxel volume python datastruct - # img_voxel_volume = img - - # filename = os.path.join(label_direc, hemisphere.value + ".aparc.annot") - # region_mapping, _, _ = nibabel.freesurfer.io.read_annot(filename) - - np.savetxt(outfilepath, img_voxel_volume, fmt="%d") - - -if __name__ == "__main__": - dk_file = parser.dk_file - destrieux_file = parser.destrieux_file - lut_file = parser.lut_file - dk_out_file = parser.out_dk_file - destrieux_out_file = parser.out_destrieux_file - - # read in the images - dk_img = read_file(dk_file) - destrieux_img = read_file(destrieux_file) - - # create voxel volume text files for each atlas - create_voxel_volume_txt(dk_img, dk_out_file) - create_voxel_volume_txt(destrieux_img, destrieux_out_file) diff --git a/neuroimg/format/dev/elec_endpoints_example.txt b/neuroimg/format/dev/elec_endpoints_example.txt deleted file mode 100644 index 45b981b..0000000 --- a/neuroimg/format/dev/elec_endpoints_example.txt +++ /dev/null @@ -1,3 +0,0 @@ -Name Target_x Target_y Target_z Entry_x Entry_y Entry_z Num_contacts Spacing_pattern -A 0.0 0.0 0.0 35.0 0.0 0.0 11 "3.5" -B 0.0 20.0 0.0 0.0 20.0 40.0 12 "3.5 3.5 3.5 3.5 6.0" \ No newline at end of file diff --git a/neuroimg/format/dev/gain_matrix_seeg.py b/neuroimg/format/dev/gain_matrix_seeg.py deleted file mode 100755 index 9d6ace5..0000000 --- a/neuroimg/format/dev/gain_matrix_seeg.py +++ /dev/null @@ -1,215 +0,0 @@ -#!/usr/bin/env python3 - -import argparse -import os -import zipfile - -import numpy as np - -SIGMA = 1.0 - - -def gain_matrix_dipole( - vertices: np.ndarray, - orientations: np.ndarray, - areas: np.ndarray, - region_mapping: np.ndarray, - nregions: int, - sensors: np.ndarray, -): - """ - - Parameters - ---------- - vertices np.ndarray of floats of size n x 3, where n is the number of vertices - orientations np.ndarray of floats of size n x 3 - region_mapping np.ndarray of ints of size n - sensors np.ndarray of floats of size m x 3, where m is the number of sensors - - Returns - ------- - np.ndarray of size m x n - - """ - - nverts = vertices.shape[0] - nsens = sensors.shape[0] - - reg_map_mtx = np.zeros((nverts, nregions), dtype=int) - for i, region in enumerate(region_mapping): - if region >= 0: - reg_map_mtx[i, region] = 1 - # reg_map_mtx[np.arange(region_mapping.size), region_mapping] = 1.0 - - gain_mtx_vert = np.zeros((nsens, nverts)) - for sens_ind in range(nsens): - a = sensors[sens_ind, :] - vertices - na = np.sqrt(np.sum(a ** 2, axis=1)) - gain_mtx_vert[sens_ind, :] = ( - areas * (np.sum(orientations * a, axis=1) / na ** 3) / (4.0 * np.pi * SIGMA) - ) - - return gain_mtx_vert @ reg_map_mtx - - -def gain_matrix_inv_square( - vertices: np.ndarray, - areas: np.ndarray, - region_mapping: np.ndarray, - nregions: int, - sensors: np.ndarray, -): - nverts = vertices.shape[0] - nsens = sensors.shape[0] - - reg_map_mtx = np.zeros((nverts, nregions), dtype=int) - for i, region in enumerate(region_mapping): - if region >= 0: - reg_map_mtx[i, region] = 1 - - gain_mtx_vert = np.zeros((nsens, nverts)) - for sens_ind in range(nsens): - a = sensors[sens_ind, :] - vertices - na = np.sqrt(np.sum(a ** 2, axis=1)) - gain_mtx_vert[sens_ind, :] = areas / na ** 2 - - return gain_mtx_vert @ reg_map_mtx - - -def compute_triangle_areas(vertices, triangles): - """Calculates the area of triangles making up a surface.""" - tri_u = vertices[triangles[:, 1], :] - vertices[triangles[:, 0], :] - tri_v = vertices[triangles[:, 2], :] - vertices[triangles[:, 0], :] - tri_norm = np.cross(tri_u, tri_v) - triangle_areas = np.sqrt(np.sum(tri_norm ** 2, axis=1)) / 2.0 - triangle_areas = triangle_areas[:, np.newaxis] - return triangle_areas - - -def compute_vertex_areas(vertices, triangles): - triangle_areas = compute_triangle_areas(vertices, triangles) - vertex_areas = np.zeros((vertices.shape[0])) - for triang, vertices in enumerate(triangles): - for i in range(3): - vertex_areas[vertices[i]] += 1.0 / 3.0 * triangle_areas[triang] - - return vertex_areas - - -def read_surf(directory: os.PathLike, use_subcort): - reg_map_cort = np.genfromtxt( - (os.path.join(directory, "region_mapping_cort.txt")), dtype=int - ) - reg_map_subc = np.genfromtxt( - (os.path.join(directory, "region_mapping_subcort.txt")), dtype=int - ) - - with zipfile.ZipFile(os.path.join(directory, "surface_cort.zip")) as zip: - with zip.open("vertices.txt") as fhandle: - verts_cort = np.genfromtxt(fhandle) - with zip.open("normals.txt") as fhandle: - normals_cort = np.genfromtxt(fhandle) - with zip.open("triangles.txt") as fhandle: - triangles_cort = np.genfromtxt(fhandle, dtype=int) - - with zipfile.ZipFile(os.path.join(directory, "surface_subcort.zip")) as zip: - with zip.open("vertices.txt") as fhandle: - verts_subc = np.genfromtxt(fhandle) - with zip.open("normals.txt") as fhandle: - normals_subc = np.genfromtxt(fhandle) - with zip.open("triangles.txt") as fhandle: - triangles_subc = np.genfromtxt(fhandle, dtype=int) - - vert_areas_cort = compute_vertex_areas(verts_cort, triangles_cort) - vert_areas_subc = compute_vertex_areas(verts_subc, triangles_subc) - - if not use_subcort: - return (verts_cort, normals_cort, vert_areas_cort, reg_map_cort) - else: - verts = np.concatenate((verts_cort, verts_subc)) - normals = np.concatenate((normals_cort, normals_subc)) - areas = np.concatenate((vert_areas_cort, vert_areas_subc)) - regmap = np.concatenate((reg_map_cort, reg_map_subc)) - - return (verts, normals, areas, regmap) - - -def read_regions(zip_name: os.PathLike, use_subcort): - with zipfile.ZipFile(zip_name) as zip: - with zip.open("centres.txt") as fhandle: - verts = np.genfromtxt(fhandle, usecols=[1, 2, 3]) - with zip.open("areas.txt") as fhandle: - areas = np.genfromtxt(fhandle) - with zip.open("average_orientations.txt") as fhandle: - normals = np.genfromtxt(fhandle) - with zip.open("cortical.txt") as fhandle: - cortical = np.genfromtxt(fhandle, dtype=int).astype(bool) - regmap = np.arange(0, verts.shape[0]) - - if not use_subcort: - return (verts[cortical], normals[cortical], areas[cortical], regmap[cortical]) - else: - return (verts, normals, areas, regmap) - - -def get_nregions(zip_name): - with zipfile.ZipFile(zip_name) as zip: - with zip.open("centres.txt") as fhandle: - num_lines = sum(1 for line in fhandle.readlines() if line.strip()) - return num_lines - - -def main(): - parser = argparse.ArgumentParser(description="Generate SEEG gain matrix.") - - # Defaults are not given on purpose to force the user to think about what is needed. - parser.add_argument( - "--mode", type=str, choices=["surface", "region"], required=True - ) - parser.add_argument( - "--formula", type=str, choices=["dipole", "inv_square"], required=True - ) - parser.add_argument( - "--surf_dir", - help="Directory with surfaces and region mapping. Required if mode is 'surface'.", - ) - - use_subcort_parser = parser.add_mutually_exclusive_group(required=True) - use_subcort_parser.add_argument( - "--use_subcort", dest="use_subcort", action="store_true" - ) - use_subcort_parser.add_argument( - "--no_use_subcort", dest="use_subcort", action="store_false" - ) - - parser.add_argument("tvb_zipfile", help="Path to the TVB zipfile.") - parser.add_argument("sensors_file", help="Path to the sensors file.") - parser.add_argument( - "gain_matrix", help="Path to the gain matrix in numpy format to be generated." - ) - - args = parser.parse_args() - if args.mode == "surface" and args.surf_dir is None: - parser.error("--surf_dir is required if mode is 'surface'") - - nregions = get_nregions(args.tvb_zipfile) - - if args.mode == "surface": - verts, normals, areas, regmap = read_surf(args.surf_dir, args.use_subcort) - elif args.mode == "region": - verts, normals, areas, regmap = read_regions(args.tvb_zipfile, args.use_subcort) - - sensors_pos = np.genfromtxt(args.sensors_file, usecols=[1, 2, 3]) - - if args.formula == "dipole": - gain_mtx = gain_matrix_dipole( - verts, normals, areas, regmap, nregions, sensors_pos - ) - elif args.formula == "inv_square": - gain_mtx = gain_matrix_inv_square(verts, areas, regmap, nregions, sensors_pos) - - np.savetxt(args.gain_matrix, gain_mtx) - - -if __name__ == "__main__": - main() diff --git a/neuroimg/format/dev/register_electrodes.py b/neuroimg/format/dev/register_electrodes.py deleted file mode 100644 index b7fcc0d..0000000 --- a/neuroimg/format/dev/register_electrodes.py +++ /dev/null @@ -1,68 +0,0 @@ -import os -import sys -import numpy as np -import argparse - -class ElectrodeRegistration(): - def __init__(self, subjid, brainmask_filepath, ): - - -if __name__ == '__main__': - - subjdir = '' - - # t1 mri filepath - t1mri_filepath = os.path.join(subjdir, 'mri', 'orig.mgz') - - # ct file path - ct_filepath = os.path.join(subjdir, 'ct', 'postopct.mgz') - - # brainmask data - brainmask_filepath = os.path.join(subjdir, 'mri', 'brainmask.mgz') - - # registration matrix - coregistration_filepath = os.path.join(subjdir, 'coregister', 'ct2t1.dat') - - - -% datapath = '/home/pierresacre/subjects/' ; -datapath = '/media/ncsl/Pierre/subjects/'; - -subjID = 1 ; -% params.letters = {'I','T','O','J','Q','B','E','U','C','F','X','P'} ; -params.num = [10 ,10 ,10 ,10 ,10, 10, 10, 10, 10, 10, 10, 10 ] ; -params.th = 0.75 -% params.D = 1.5+2.5+2.5 %5.5%3.5 - - -X = orig.vol ; -X = X(1:end,1:end-1,1:end-2) ; - -B = brainmask.vol ; -B = B(1:end,1:end-1,1:end-2) ; - -B_in_CT = brainmask_in_CT.vol ; -B_in_CT = B_in_CT(1:end,1:end-1,1:end-2) ; - -Y = CT.vol ; -Y = Y(1:end,1:end-1,1:end-2) ; - -r_MRI = 0:size(X,1)-1; % -c_MRI = 0:size(X,2)-1; % -s_MRI = 0:size(X,3)-1; % - -r_CT = 0:size(Y,1)-1; % -c_CT = 0:size(Y,2)-1; % -s_CT = 0:size(Y,3)-1; % - -[R_MRI,C_MRI,S_MRI] = ndgrid(r_MRI,c_MRI,s_MRI) ; - -[f,v_CRS_MRI] = isosurface(c_MRI,r_MRI,s_MRI,double(B>0)) ; - -% v_CRS_CT = inv( inv(orig.tkrvox2ras) * inv(R) * CT.tkrvox2ras ) * [ v_CRS_MRI.' ; ones(1,size(v_CRS_MRI,1))] ; -v_CRS_CT = inv(CT.tkrvox2ras) * R * orig.tkrvox2ras * [ v_CRS_MRI.' ; ones(1,size(v_CRS_MRI,1))] ; -v_CRS_CT = v_CRS_CT(1:3,:).' ; - -v_RAS_CT = R * orig.tkrvox2ras * [ v_CRS_MRI.' ; ones(1,size(v_CRS_MRI,1))] ; -v_RAS_CT = v_RAS_CT(1:3,:).' ; - diff --git a/neuroimg/pipeline/README.md b/neuroimg/pipeline/README.md index e7a9d52..272dc27 100644 --- a/neuroimg/pipeline/README.md +++ b/neuroimg/pipeline/README.md @@ -31,10 +31,4 @@ By: Adam Li Here, one runs a semi-automated pipeline for localizing the contacts in CT space, running a clustering algorithm and then mapping contacts into their corresponding MRI space. - The pipeline will assume contacts are in native MRI space. - -4. (Optional) Diffusion_Tensor_Imaging - - -5. (Optional) Resection_Ablation_Estimation - + The pipeline will assume contacts are in native MRI space. \ No newline at end of file diff --git a/neuroimg/pipeline/config/cluster.json b/neuroimg/pipeline/config/cluster.json index 95e2df2..e047fb3 100644 --- a/neuroimg/pipeline/config/cluster.json +++ b/neuroimg/pipeline/config/cluster.json @@ -13,32 +13,4 @@ "array": "1-1", "mem": "5000" }, - "fragility_model": - { - "time": "2:00:0", - "partition": "shared", - "array": "1-48", - "mem": "5000", - "jobname": "{wildcards.datasetname}_new_fragility_analysis" - }, - "merge_models": - { - "time": "0:30:0", - "jobname": "{wildcards.datasetname}_new_fragility_merge", - "array":"1-1" - }, - "plot_fragility_results": - { - "time": "0:30:0", - "jobname": "{wildcards.datasetname}_plot_map", - "array": "1-1" - }, - "eznet_train": - { - "partition": "gpu", - "ntasks-per-node": "6", - "jobname": "eznet_training", - "array":"1-1", - "time": "2:00:0" - } } \ No newline at end of file diff --git a/neuroimg/pipeline/config/localconfig.yaml b/neuroimg/pipeline/config/localconfig.yaml index c7e90df..9c639a8 100644 --- a/neuroimg/pipeline/config/localconfig.yaml +++ b/neuroimg/pipeline/config/localconfig.yaml @@ -1,6 +1,10 @@ ############## define directories that we work with ############# +# home directory that every dataset sits in +basedatadir: + "/home/adam2392/hdd2/data/neuroimaging/" + rawdatadir: -# "/home/ksr/Desktop/contact_localization/raw" +# "/home/ksr/Desktop/contact_localization/raw" # "/Users/ChesterHuynh/sarmalab/contact_localization_proj/rawdata" "/home/adam2392/hdd2/data/neuroimaging/raw" # "/Users/adam2392/Dropbox/phd_research/data/neuroimaging_results/raw/" @@ -34,42 +38,4 @@ patients: 'la23', # 'la21', # 'la22', -# 'la24', -# 'nl01', -# 'nl02', -# 'nl03', -# 'nl04', -# 'nl05', -# 'nl06', -# 'nl07', -# 'nl08', -# 'nl09', -# 'nl10', -# 'nl11', -# 'nl12', -# 'nl11', -# 'nl12', -# 'nl13', -# 'nl14', -# 'nl15', -# 'nl16', -# 'nl17', -# 'nl18', -# 'nl19', -# 'nl20', -# 'nl21', -# 'nl22', -# 'nl23', -# 'tvb1', -# 'tvb2', -# 'tvb5', -# 'tvb7', -# 'tvb8', -# 'tvb11', -# 'tvb12', -# 'tvb14', -# 'tvb17', -# 'tvb18', -# 'tvb19', -# 'tvb23' ] diff --git a/neuroimg/pipeline/config/preformat_config.schema.yaml b/neuroimg/pipeline/config/preformat_config.schema.yaml index 24efeea..615ec8f 100644 --- a/neuroimg/pipeline/config/preformat_config.schema.yaml +++ b/neuroimg/pipeline/config/preformat_config.schema.yaml @@ -12,25 +12,4 @@ properties: description: (optional) patient to run within this directory only required: - - rawdatadir - -#$schema: "" -#description: An experimental configuration sheet -#properties: -# rawdatadir: -# type: string -# description: directory of patients with predefined format -# outputdatadir: -# type: string -# description: directory of where to save all output data for neuroimaging preprocessing -# outputplotsdir: -# type: string -# description: directory to output summary plots -# patients: -# type: array -# description: list of patients to run within this directory only -# -#required: -# - rawdatadir -# - outputdatadir -# - patients \ No newline at end of file + - rawdatadir \ No newline at end of file diff --git a/neuroimg/pipeline/contact_localization/Snakefile b/neuroimg/pipeline/contact_localization/Snakefile index 8921fc1..4de2915 100644 --- a/neuroimg/pipeline/contact_localization/Snakefile +++ b/neuroimg/pipeline/contact_localization/Snakefile @@ -1,28 +1,29 @@ import os +import sys +sys.path.append("../../../") +from neuroimg.pipeline.fileutils import get_freesurfer_dir, get_rawct_dir, get_rawmri_dir -configfile: "../config/localconfig.yaml" +""" +A snakemake file for running contact localizations workflow on the neuroimaging data. -# get the environment variable for freesurfer - for use in getting access to lut's -HOME_DIR="../../" -SCRIPTS_UTIL_DIR = "../../neuroimg/format/" -ATLAS=['dk', 'destrieux'] +snakemake --dag | dot -Tpdf > dag_pipeline_contactlocalize.pdf -''' USER DEFINED DIRECTORIES TO STORE FINAL DATA IN ORGANIZED SUBFOLDERS ''' -FS_PATIENT_OUTPUT_DIR = os.path.join(config['fs_outputdatadir'], - "{patient_id}") +Runs tests to ensure data is all in the corresponding format: BIDS iEEG +""" -TVB_OUTPUT_DIR = os.path.join(FS_PATIENT_OUTPUT_DIR, - "tvb") -NATIVESPACE_OUTPUT_DIR = os.path.join(FS_PATIENT_OUTPUT_DIR, - "nativespace-transform") +configfile: "../config/localconfig.yaml" -COREGISTRATION_OUTPUT_DIR = os.path.join(config['fs_outputdatadir'], - "{patient_id}", - "CT") +# get the environment variable for freesurfer - for use in getting access to lut's +# get the freesurfer patient directory +FS_PATIENT_OUTPUT_DIR = get_freesurfer_dir(config) +RAW_CT_FOLDER = get_rawct_dir(config) +RAW_MRI_FOLDER = get_rawmri_dir(config) -ELECS_DIR = os.path.join(FS_PATIENT_OUTPUT_DIR, - "elecs") -FIGDIR = os.path.join(ELECS_DIR, "figs") +FSOUT_MRI_FOLDER = os.path.join(FS_PATIENT_OUTPUT_DIR, "mri") +FSOUT_CT_FOLDER = os.path.join(FS_PATIENT_OUTPUT_DIR, "CT") +FSOUT_ELECS_FOLDER = os.path.join(FS_PATIENT_OUTPUT_DIR, "elecs") + +FIGDIR = os.path.join(FSOUT_ELECS_FOLDER, "figs") subworkflow reconstruction_workflow: # workdir: @@ -43,25 +44,25 @@ subworkflow coregistration_workflow: # First rule rule all: input: - # clustered_center_points_flirt = expand(os.path.join(COREGISTRATION_OUTPUT_DIR, + # clustered_center_points_flirt = expand(os.path.join(FSOUT_CT_FOLDER, # '{patient_id}_native_flirt_elec_xyz.txt'), # patient_id = config['patients']), - # clustered_center_voxels = expand(os.path.join(ELECS_DIR, '{patient_id}_clusteredelec_voxels.mat'), patient_id = config['patients']), + # clustered_center_voxels = expand(os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_voxels.mat'), patient_id = config['patients']), figure_file = expand(os.path.join(FIGDIR, "summary_pca_elecs.png"), patient_id = config['patients']), shell: "echo 'done'" rule visualize_results: input: - centroids_voxels_file = os.path.join(ELECS_DIR, '{patient_id}_clusteredelec_xyz.mat'), - centroids_xyz_file = os.path.join(ELECS_DIR, '{patient_id}_clusteredelec_voxels.mat'), + centroids_voxels_file = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_xyz.mat'), + centroids_xyz_file = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_voxels.mat'), # DEPENDENCY ON RECONSTRUCTION WORKFLOW ctfile = os.path.join(FS_PATIENT_OUTPUT_DIR, "CT", "CT.nii"), brainmaskfile = os.path.join(FS_PATIENT_OUTPUT_DIR, "CT", "brainmask_inct.nii.gz"), - organizedclustered_center_points = os.path.join(ELECS_DIR, '{patient_id}_clusteredelec_xyz_dict.mat'), - organizedclustered_center_voxels = os.path.join(ELECS_DIR, '{patient_id}_clusteredelec_voxels_dict.mat'), + organizedclustered_center_points = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_xyz_dict.mat'), + organizedclustered_center_voxels = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_voxels_dict.mat'), # list of channel points (at least 2 per electrode) - electrode_initialization_file = os.path.join(ELECS_DIR, '{patient_id}_elecxyz.txt'), + electrode_initialization_file = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_elecxyz.txt'), params: fsdir = FS_PATIENT_OUTPUT_DIR, output: @@ -69,7 +70,7 @@ rule visualize_results: l2figure_file = os.path.join(FIGDIR, "summary_euclidean_distance_errors.png"), shell: "echo 'RUNNING VISUALIZATION CHECKS';" - "python ./visualize_results.py {input.centroids_voxels_file} " \ + "python ./utils/visualize_results.py {input.centroids_voxels_file} " \ "{input.centroids_xyz_file} " \ "{input.organizedclustered_center_points} " \ "{input.organizedclustered_center_voxels} " \ @@ -84,65 +85,64 @@ Rule to plot: - surface shown transparent with different regions colored - parcellated nodes in space with the contacts.xyz (centers) plotted """ -rule run_clustering_algorithm_on_CTimg: +rule find_electrodes_on_CT: input: # DEPENDENCY ON RECONSTRUCTION WORKFLOW - CT_NIFTI_IMG = os.path.join(FS_PATIENT_OUTPUT_DIR, "CT", "CT.nii"), - brainmask_inct_file = os.path.join(FS_PATIENT_OUTPUT_DIR, "CT", "brainmask_inct.nii.gz"), + CT_NIFTI_IMG = os.path.join(FSOUT_CT_FOLDER, "CT.nii"), + brainmask_inct_file = os.path.join(FSOUT_CT_FOLDER, "brainmask_inct.nii.gz"), # list of channel points (at least 2 per electrode) - electrode_initialization_file = os.path.join(ELECS_DIR, '{patient_id}_elecxyz.txt'), - # list of all channel points (all electrodes annotated) - chanxyz_file = os.path.join(ELECS_DIR, '{patient_id}_elecxyz.txt'), - # wm_inct_outputfile_nifti = os.path.join(COREGISTRATION_OUTPUT_DIR, "wm_in_ct.nii") + electrode_initialization_file = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_elecxyz.txt'), params: fsdir = FS_PATIENT_OUTPUT_DIR, patid = "{patient_id}" output: - clustered_center_points = os.path.join(ELECS_DIR, '{patient_id}_clusteredelec_xyz.mat'), - clustered_center_voxels = os.path.join(ELECS_DIR, '{patient_id}_clusteredelec_voxels.mat'), - organizedclustered_center_points = os.path.join(ELECS_DIR, '{patient_id}_clusteredelec_xyz_dict.mat'), - organizedclustered_center_voxels = os.path.join(ELECS_DIR, '{patient_id}_clusteredelec_voxels_dict.mat'), - binarized_ct_volume = os.path.join(COREGISTRATION_OUTPUT_DIR, "{patient_id}_binarized_ct.nii.gz") + clustered_center_points = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_xyz.mat'), + clustered_center_voxels = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_voxels.mat'), + organizedclustered_center_points = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_xyz_dict.mat'), + organizedclustered_center_voxels = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_voxels_dict.mat'), + binarized_ct_volume = os.path.join(FSOUT_CT_FOLDER, "{patient_id}_binarized_ct.nii.gz") shell: "echo 'RUNNING CLUSTERING ALGORITHM';" "python ./electrode_clustering.py " \ "{input.CT_NIFTI_IMG} " \ "{input.brainmask_inct_file} " \ "{input.electrode_initialization_file} " \ - "{input.chanxyz_file} " \ "{output.clustered_center_points} " \ "{output.clustered_center_voxels} " \ - "{output.organizedclustered_center_points} " \ - "{output.organizedclustered_center_voxels} " \ + "{output.organizedclustered_center_points} " \ + "{output.organizedclustered_center_voxels} " \ "{output.binarized_ct_volume} " \ "{params.fsdir} " \ - "{params.patid} " \ - # "{input.wm_inct_outputfile_nifti}" \ - ";" - -rule map_wm_to_ct: + "{params.patid};" + +rule validate_electrodes_on_CT: input: - wm_output_file = os.path.join(FS_PATIENT_OUTPUT_DIR, "mri", - "wm.mgz"), - CT_NIFTI_IMG = os.path.join(FS_PATIENT_OUTPUT_DIR, "CT", - "CT.nii"), + # DEPENDENCY ON RECONSTRUCTION WORKFLOW + CT_NIFTI_IMG = os.path.join(FSOUT_CT_FOLDER, "CT.nii"), + brainmask_inct_file = os.path.join(FSOUT_CT_FOLDER, "brainmask_inct.nii.gz"), + chanxyz_file = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_elecxyz.txt'), # list of channel points (at least 2 per electrode) + params: + fsdir = FS_PATIENT_OUTPUT_DIR, + patid = "{patient_id}" output: - wm_output_file_nifti = os.path.join(FS_PATIENT_OUTPUT_DIR, "mri", - "wm.nii.gz"), - # mapping matrix for post to pre in T1 - MAPPING_FILE = os.path.join(COREGISTRATION_OUTPUT_DIR, - "fsl_wm_to_ct_omat.txt"), - wm_inct_outputfile = os.path.join(COREGISTRATION_OUTPUT_DIR, - "wm_in_ct.nii.gz"), - wm_inct_outputfile_nifti = os.path.join(COREGISTRATION_OUTPUT_DIR, - "wm_in_ct.nii") + clustered_center_points = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_xyz.mat'), + clustered_center_voxels = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_voxels.mat'), + organizedclustered_center_points = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_xyz_dict.mat'), + organizedclustered_center_voxels = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_clusteredelec_voxels_dict.mat'), + binarized_ct_volume = os.path.join(FSOUT_CT_FOLDER, "{patient_id}_binarized_ct.nii.gz") shell: - "mri_convert {input.wm_output_file} {output.wm_output_file_nifti};" - "flirt -in {output.wm_output_file_nifti} \ - -ref {input.CT_NIFTI_IMG} \ - -omat {output.MAPPING_FILE} \ - -out {output.wm_inct_outputfile};" - "mri_convert {output.wm_inct_outputfile} {output.wm_inct_outputfile_nifti};" + "echo 'RUNNING CLUSTERING ALGORITHM';" + "python ./electrode_clustering.py " \ + "{input.CT_NIFTI_IMG} " \ + "{input.brainmask_inct_file} " \ + "{input.electrode_initialization_file} " \ + "{output.clustered_center_points} " \ + "{output.clustered_center_voxels} " \ + "{output.organizedclustered_center_points} " \ + "{output.organizedclustered_center_voxels} " \ + "{output.binarized_ct_volume} " \ + "{params.fsdir} " \ + "{params.patid};" """ Rule for conversion .mat -> .txt @@ -153,18 +153,15 @@ into txt files. """ rule convert_eleccoords_mat_to_txt: input: - clustered_center_points_mat = os.path.join(ELECS_DIR, - '{patient_id}_elec_f.mat'), - # clustered_center_points_flirt = os.path.join(ELECS_DIR, + clustered_center_points_mat = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_elec_f.mat'), + # clustered_center_points_flirt = os.path.join(FSOUT_ELECS_FOLDER, # '{patient_id}_flirt_elec_xyz.mat'), output: - clustered_center_points = os.path.join(ELECS_DIR, - '{patient_id}_elecxyz.txt'), - # clustered_center_points_flirt = os.path.join(ELECS_DIR, + clustered_center_points = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_elecxyz.txt'), + # clustered_center_points_flirt = os.path.join(FSOUT_ELECS_FOLDER, # '{patient_id}_flirt_elec_xyz.txt'), shell: - "python -m convert_to_txt {input.clustered_center_points_mat} " \ - "{output.clustered_center_points};" + "python -m ./utils/convert_to_txt {input.clustered_center_points_mat} {output.clustered_center_points};" # "python -m convert_to_txt {input.clustered_center_points_flirt} " \ # "{output.clustered_center_points_flirt};" @@ -178,13 +175,10 @@ rule convert_eleccoords_to_native_T1: input: # DEPENDENCY ON RECONSTRUCTION WORKFLOW # mapping matrix for post to pre in T1 - MAPPING_FILE_ORIG = reconstruction_workflow(os.path.join(COREGISTRATION_OUTPUT_DIR, - "fsl_ct-to-t1_omat.txt")), - clustered_center_points = os.path.join(ELECS_DIR, - '{patient_id}_elec_f.mat'), + MAPPING_FILE_ORIG = reconstruction_workflow(os.path.join(FSOUT_CT_FOLDER, "fsl_ct-to-t1_omat.txt")), + clustered_center_points = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_elec_f.mat'), output: - clustered_center_points_flirt = os.path.join(ELECS_DIR, - '{patient_id}_flirt_elec_xyz.mat'), + clustered_center_points_flirt = os.path.join(FSOUT_ELECS_FOLDER, '{patient_id}_flirt_elec_xyz.mat'), shell: "img2imgcoord -mm -src {input.clustered_center_points} \ -dest {output.clustered_center_points} -xfm {input.output_registration_file};" @@ -194,23 +188,16 @@ rule convert_coords_to_conformed_space: input: # DEPENDENCY ON RECONSTRUCTION WORKFLOW # mapping matrix for post to pre in T1 - MAPPING_FILE_ORIG = coregistration_workflow(os.path.join(COREGISTRATION_OUTPUT_DIR, - "fsl_ct-to-t1_omat.txt")), - register_conformed_file = os.path.join(NATIVESPACE_OUTPUT_DIR, - "register.conformed.dat"), - clustered_center_points = os.path.join(COREGISTRATION_OUTPUT_DIR, - '{patient_id}_elecxyz.txt'), - # clustered_center_voxels = os.path.join(COREGISTRATION_OUTPUT_DIR, + MAPPING_FILE_ORIG = coregistration_workflow(os.path.join(FSOUT_CT_FOLDER, "fsl_ct-to-t1_omat.txt")), + register_conformed_file = os.path.join(NATIVESPACE_OUTPUT_DIR, "register.conformed.dat"), + clustered_center_points = os.path.join(FSOUT_CT_FOLDER, '{patient_id}_elecxyz.txt'), + # clustered_center_voxels = os.path.join(FSOUT_CT_FOLDER, # '{patient_id}_elec_voxels.mat'), - CT_NIFTI_IMG = reconstruction_workflow(os.path.join(FS_PATIENT_OUTPUT_DIR, "CT", - "CT.nii.gz")), - MRI_NIFTI_IMG = reconstruction_workflow(os.path.join(FS_PATIENT_OUTPUT_DIR, "mri", - "T1.nii")), - CONFORM_MRI_NIFTI_IMG = os.path.join(FS_PATIENT_OUTPUT_DIR, "mri", - "T1.conform.nii.gz") + CT_NIFTI_IMG = reconstruction_workflow(os.path.join(FSOUT_CT_FOLDER, "CT.nii.gz")), + MRI_NIFTI_IMG = reconstruction_workflow(os.path.join(FSOUT_MRI_FOLDER, "origT1.nii")), + CONFORM_MRI_NIFTI_IMG = os.path.join(FSOUT_MRI_FOLDER, "T1.conform.nii.gz") output: - clustered_center_points_flirt = os.path.join(COREGISTRATION_OUTPUT_DIR, - '{patient_id}_native_flirt_elec_xyz.txt'), + clustered_center_points_flirt = os.path.join(FSOUT_CT_FOLDER, '{patient_id}_native_flirt_elec_xyz.txt'), shell: "python -m ./dev/convert_coordspace " \ "{input.CT_NIFTI_IMG} " \ diff --git a/neuroimg/pipeline/contact_localization/dag_neuroimaging_pipeline_contactlocalization.pdf b/neuroimg/pipeline/contact_localization/dag_neuroimaging_pipeline_contactlocalization.pdf deleted file mode 100644 index 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-import numpy as np - - -def transform(coords, src_img, dest_img, transform_mat): - coords_str = " ".join([str(x) for x in coords]) - - # print(coords_str) - cp = subprocess.run( - "echo %s | img2imgcoord -mm -src %s -dest %s -xfm %s" - % (coords_str, src_img, dest_img, transform_mat), - shell=True, - stdout=subprocess.PIPE, - ) - - transformed_coords = cp.stdout.decode("ascii").strip().split("\n")[-1] - # print(transformed_coords) - return np.array([float(x) for x in transformed_coords.split(" ") if x]) - - -def read_label_coords(elecfile): - labels = [] - labelsxyz = [] - - with open(elecfile, "r") as f: - for _row in f: - row = _row.split(" ") - labels.append(row[0]) - labelsxyz.append([float(x) for x in row[1:]]) - - return labels, labelsxyz - - -if __name__ == "__main__": - parser = argparse.ArgumentParser() - parser.add_argument("conformed_mri_nifti_img", help="The conformed MRI nifti img.") - parser.add_argument("mri_nifti_img", help="Brain MRI image space.") - parser.add_argument( - "register_conformed_file", help="The conformed mapping transformation file." - ) - parser.add_argument( - "clustered_points_file", - help="The output datafile with all the electrode points clustered.", - ) - parser.add_argument( - "outputcoordsfile", - help="The output datafile for electrodes mapped to correct coords.", - ) - args = parser.parse_args() - - # extract arguments from parser - conformed_mri_nifti_img = args.conformed_mri_nifti_img - mri_nifti_img = args.mri_nifti_img - register_conformed_file = args.register_conformed_file - clustered_points_file = args.clustered_points_file - outputcoordsfile = args.outputcoordsfile - - # read in electrodes file - labels, labelsxyz = read_label_coords(clustered_points_file) - - # run coordinat transformation - modified_coords = np.array( - [ - transform( - coords, mri_nifti_img, conformed_mri_nifti_img, register_conformed_file - ) - for coords in labelsxyz - ] - ) - - with open(outputcoordsfile, "w") as f: - for i, name in enumerate(labels): - f.write( - "%s %.6f %.6f %.6f\n" - % ( - name, - modified_coords[i][0], - modified_coords[i][1], - modified_coords[i][2], - ) - ) diff --git a/neuroimg/pipeline/contact_localization/ielvis_visualization/convert_ielvis_to_imgpipe.py b/neuroimg/pipeline/contact_localization/ielvis_visualization/convert_ielvis_to_imgpipe.py deleted file mode 100644 index 993448c..0000000 --- a/neuroimg/pipeline/contact_localization/ielvis_visualization/convert_ielvis_to_imgpipe.py +++ /dev/null @@ -1,66 +0,0 @@ -import argparse -import sys - -import nibabel as nb -import scipy.io -from nibabel.affines import apply_affine - -sys.path.append("../../") -from neuroimg.base.utils.data_structures_utils import MatReader - - -def convert_crs_to_ras(eleccoords, t1_img_file): - t1_img = nb.load(t1_img_file) - eleccoords_ras = apply_affine(t1_img.affine, eleccoords) - return eleccoords_ras - - -def read_label_coords(elecfile): - matreader = MatReader() - elecmat = matreader.loadmat(elecfile) - return elecmat - - -def save_as_matfile(elecmat, eleccoords_ras, outputcoordsfile): - elecmatrix_orig = elecmat["elecmatrix"] - elec_labels_orig = elecmat["anatomy"] - elecmontage = elecmat["eleclabels"] - - scipy.io.savemat( - outputcoordsfile, - { - "elecmatrix": elecmatrix_orig, - "anatomy": elec_labels_orig, - "eleclabels": elecmontage, - "elecmatrix_ras": eleccoords_ras, - }, - ) - - -if __name__ == "__main__": - parser = argparse.ArgumentParser() - parser.add_argument("mri_nifti_img", help="Brain MRI image space.") - parser.add_argument( - "elec_coords_file", - help="The output datafile with all the electrode points clustered.", - ) - parser.add_argument( - "outputcoordsfile", - help="The output datafile for electrodes mapped to correct coords.", - ) - args = parser.parse_args() - - # extract arguments from parser - mri_nifti_img = args.mri_nifti_img - elec_coords_file = args.elec_coords_file - outputcoordsfile = args.outputcoordsfile - - # read in electrodes file - elecmat = read_label_coords(elec_coords_file) - eleccoords = elecmat["elecmatrix"] - - # apply affine transformation to get the RAS coordinates of file - eleccoords_ras = convert_crs_to_ras(eleccoords, mri_nifti_img) - - # resave the elec-coords w/ an additional struct for the RAS coordinates - save_as_matfile(elecmat, eleccoords_ras, outputcoordsfile) diff --git a/neuroimg/pipeline/contact_localization/ielvis_visualization/snake_convert_ielvis_to_imgpipe b/neuroimg/pipeline/contact_localization/ielvis_visualization/snake_convert_ielvis_to_imgpipe deleted file mode 100644 index dcf6c93..0000000 --- a/neuroimg/pipeline/contact_localization/ielvis_visualization/snake_convert_ielvis_to_imgpipe +++ /dev/null @@ -1,90 +0,0 @@ -import os - - -""" -snakemake --dag | dot -Tpdf > dag_neuroimaging_pipeline_contactlocalization.pdf -""" - -configfile: "../config/localconfig.yaml" - -# get the environment variable for freesurfer - for use in getting access to lut's -HOME_DIR="../../" -SCRIPTS_UTIL_DIR = "../../neuroimg/format/" -ATLAS=['dk', 'destrieux'] - -''' USER DEFINED DIRECTORIES TO STORE FINAL DATA IN ORGANIZED SUBFOLDERS ''' -FS_PATIENT_OUTPUT_DIR = os.path.join(config['fs_outputdatadir'], - "{patient_id}") - -COREGISTRATION_OUTPUT_DIR = os.path.join(config['fs_outputdatadir'], - "{patient_id}", - "coregistration") - -ELECSDIR = os.path.join(FS_PATIENT_OUTPUT_DIR, "elecs") - -IELVIS_OUTPUT_DIR = os.path.join(FS_PATIENT_OUTPUT_DIR, "elec_recon") - - -# First rule -rule all: - input: - elecfile = expand(os.path.join(IELVIS_OUTPUT_DIR, - "brainmask.mgz"), - patient_id = config['patients']), - shell: - "echo 'done'" - - - -rule add_ras_data: - input: - MRI_NIFTI_IMG = os.path.join(FS_PATIENT_OUTPUT_DIR, - "mri", - "T1.nii"), - eleccoords_file = os.path.join(ELECSDIR, - "{patient_id}_elecs_all.mat"), - - output: - outputfile = os.path.join(ELECSDIR, - "{patient_id}_elecs_all_RAS.mat"), - shell: - "python -m convert_ielvis_to_imgpipe {input.MRI_NIFTI_IMG} " \ - "{input.eleccoords_file} " \ - "{output.outputfile};" - -""" -""" -rule move_files_to_ielvis: - input: - elecfile = os.path.join(ELECSDIR, - "{patient_id}_elecs_all_RAS.mat"), - # DEPENDENCY ON RECONSTRUCTION WORKFLOW - CT_NIFTI_IMG = os.path.join(FS_PATIENT_OUTPUT_DIR, "CT", - "CT.nii.gz"), - brainmask_file = os.path.join(FS_PATIENT_OUTPUT_DIR , - "mri", - "brainmask.mgz"), - # mapped image from CT -> MRI - CT_IN_PRE_NIFTI_IMG = os.path.join(FS_PATIENT_OUTPUT_DIR, "CT", - "rCT.nii.gz"), - MRI_NIFTI_IMG = os.path.join(FS_PATIENT_OUTPUT_DIR, - "mri", - "T1.nii"), - params: - IELVISDIR = IELVIS_OUTPUT_DIR, - output: - CT_IN_PRE_NIFTI_IMG = os.path.join(IELVIS_OUTPUT_DIR, - "CT_IN_T1.nii.gz"), - MRI_NIFTI_IMG = os.path.join(IELVIS_OUTPUT_DIR, - "T1.nii"), - brainmask_file = os.path.join(IELVIS_OUTPUT_DIR, - "brainmask.mgz"), - elecfile = os.path.join(IELVIS_OUTPUT_DIR, - "{patient_id}_elecs_all_RAS.mat"), - shell: - # "mkdir {params.IELVISDIR};" - "cp 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