First draft of CLI implementation passed

The code must be ran in the folder where the cli code is created. The
input nifti must be present in this folder. There are important things
to analyze here regarding saving the files.

cli/tissue_to_mr.py

@@ -1,6 +1,8 @@
 import click
 import os
 import sys
+import logging
+import nibabel as nib
 # With the next line we add to path the project folder to navigate into functions folder
 sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
 
@@ -9,16 +11,9 @@
 
 # tissue_to_mr --input [labeled_nifti] --type [choose_MR_property] --output [name=default]
 
-@click.command()
-@click.option('-i',"--input",help="Input must be segmented label nifti")
-@click.option("--type",help="Please choose MR property to convert to")
-@click.option('-o',"--output",help="Output name (optional)")
-def hello(input,type,output):
-    if output == None:
-        output = "default"
-        click.echo(f"Input: {input} Type: {type} Output:{output}")
-    else:
-        click.echo(f"Input: {input} Type: {type} Output:{output}")
+@click.group
+def my_commands():
+    pass
 
 PROPERTIES = {
     "t2s" : "T2 star",
@@ -28,18 +23,32 @@ def hello(input,type,output):
     "t2" : "T2",
 }
 @click.command()
-@click.option('-i',"--input",help="Input must be segmented label nifti")
-@click.option("--type",type=click.Choice(PROPERTIES.keys()), help="Please choose MR property to convert to")
-def converter(input,type):
+@click.argument("input_file", required=True) #, help="Input must be segmented label nifti",type=click.Path(exists=True))
+@click.option('-s',"--segtool", help="State what segmentator was used")
+@click.argument('output_file', required=False, type=click.Path())
+@click.option('-t',"--type",required=True, type=click.Choice(PROPERTIES.keys()), help="Please choose MR property to convert to")
+def converter(input_file,segtool,output_file, type):
     # We need to check if the input is a  nifti file
-    if is_nifti(input):
-        new_vol = volume(input)
+    if is_nifti(input_file):
+        print("start")
+        logging.info(f"Creating a new volume with {type} values")
+        file = nib.load(input_file)
+        print("file loaded")
+        new_vol = volume(file)
+        print("a")
         # Using the type:
         new_vol.create_segmentation_labels() # Automatically adding the names to known labels
-        new_vol.create_type_vol(type)
-    else:
-        print("Input must be a nifti file")
+        print("b")
+        if output_file == None:
 
+            new_vol.create_type_vol(type) # Thiscreates and saves a Nifti file
+        else:
+            new_vol.create_type_vol(type,output_file)
+
+        print(f"Input segmented by:{segtool}")
+    else:
+        print("Input must be a Nifti file (.nii or .nii.gz extensions)")
 
+my_commands.add_command(converter)
 if __name__ == "__main__":
-    converter()
+    my_commands()

functions/utils/utils.py

@@ -12,7 +12,7 @@ def is_nifti(filepath):
     Returns:
         bool: True if the file is a NIfTI file, False otherwise.
     """
-    if filepath[-4:] == '.nii':
+    if filepath[-4:] == '.nii' or filepath[-7:] == '.nii.gz':
         return True
     else:
         return False

functions/volume.py

@@ -192,26 +192,25 @@ def show_labels(self):
             label = self.segmentation_labels[i]
             print(label) # Calling __str__ from label
 
-    def create_type_vol(self,type):
+    def create_type_vol(self,type,output_name="default"):
         # This function is for the CLI app
         # Depending on the type we automatically call the specific function
         #
         if type =='sus':
             self.create_sus_dist()
-            self.save_sus_dist_nii()
+            self.save_sus_dist_nii(output_name)
         if type =='t2s':
             self.create_t2_star_vol()
-            self.save_t2star_dist()
+            self.save_t2star_dist(output_name)
         if type =='pd':
             self.create_pd_vol()
-            self.save_pd_dist()
+            self.save_pd_dist(output_name)
         if type =='t1':
             print("T1 value volume comming soon!")
         if type =='t2':
             print("T2 volume comming soon!")
 
 
-
     def create_sus_dist(self):
         # Code for create a susceptibility distribution volume
         # Using the label class
@@ -233,12 +232,20 @@ def create_sus_dist(self):
 
         return self.sus_dist
 
-    def save_sus_dist_nii(self):
+    def save_sus_dist_nii(self, fn):
         # Method to save the susceptibility distribution created to nifti
-        temp_img = nib.Nifti1Image(self.sus_dist, affine=self.nifti.affine)
-        path = os.path.join('output','sus_dist.nii.gz')
-        # Save the new NIfTI image to a file
-        nib.save(temp_img,path)
+        if fn == "default":
+            fn = 'sus_dist.nii.gz'
+            temp_img = nib.Nifti1Image(self.sus_dist, affine=self.nifti.affine)
+            path = os.path.join('output', fn)
+            # Save the new NIfTI image to a file
+            nib.save(temp_img,path)
+        else:
+            temp_img = nib.Nifti1Image(self.sus_dist, affine=self.nifti.affine)
+            path = os.path.join('output', fn)
+            # Save the new NIfTI image to a file
+            nib.save(temp_img,path)
+
         del temp_img
         del path
 
@@ -261,12 +268,19 @@ def create_pd_vol(self):
                         self.pd_dist[i,j,k] = pd
 
         return self.pd_dist
-    def save_pd_dist(self):
+    def save_pd_dist(self, fn = 'default'):
         # Method to save the proton density distribution created to nifti
-        temp_img = nib.Nifti1Image(self.pd_dist, affine=self.nifti.affine)
-        # Save the new NIfTI image to a file
-        path = os.path.join('output', 'pd_dist.nii.gz')
-        nib.save(temp_img,path)
+        if fn == "default":
+            fn = 'pd_dist.nii.gz'
+            temp_img = nib.Nifti1Image(self.pd_dist, affine=self.nifti.affine)
+            path = os.path.join('output', fn)
+            # Save the new NIfTI image to a file
+            nib.save(temp_img,path)
+        else:
+            temp_img = nib.Nifti1Image(self.pd_dist, affine=self.nifti.affine)
+            path = os.path.join('output', fn)
+            # Save the new NIfTI image to a file
+            nib.save(temp_img,path)
         del temp_img
         del path
     def create_t2_star_vol(self):
@@ -287,12 +301,19 @@ def create_t2_star_vol(self):
                         self.t2star_vol[i,j,k] = t2star
 
         return self.t2star_vol
-    def save_t2star_dist(self):
+    def save_t2star_dist(self, fn = "default"):
         # Method to save the proton density distribution created to nifti
-        temp_img = nib.Nifti1Image(self.t2star_vol, affine=self.nifti.affine)
-        # Save the new NIfTI image to a file
-        path = os.path.join('output', 't2_star.nii.gz')
-        nib.save(temp_img,path)
+        if fn == "default":
+            fn = 't2_star.nii.gz'
+            temp_img = nib.Nifti1Image(self.t2star_vol, affine=self.nifti.affine)
+            path = os.path.join('output', fn)
+            # Save the new NIfTI image to a file
+            nib.save(temp_img,path)
+        else:
+            temp_img = nib.Nifti1Image(self.t2star_vol, affine=self.nifti.affine)
+            path = os.path.join('output', fn)
+            # Save the new NIfTI image to a file
+            nib.save(temp_img,path)
         del temp_img
         del path
     def save_sus_csv(self):

requirements.txt

@@ -1,3 +1,4 @@
+click
 pandas
 nibabel
 nilearn

setup.py

@@ -1,6 +1,34 @@
 from setuptools import find_packages, setup
+from os import path
+
+# Get directory where this current file is saved
+here = path.abspath(path.dirname(__file__))
+
+with open(path.join(here, "README.rst"), encoding="utf-8") as f:
+    long_description = f.read()
 
 setup(
-    name="functions",
-    packages=find_packages(),
+    name="tissue-to-MRproperty",
+    description = "Code that creates a volume from a segmented Nifti file to a selected MR property",
+    long_description = long_description,
+    keywords='',
+    entry_points = {
+        'console_scripts': [
+        "tissue_to_MR = tissue-to-MRproperty.cli.tissue_to_mr:converter"
+        ]
+    },
+    packages=find_packages(exclude=["docs"]),
+    install_requires=[
+        "click",
+        "pandas",
+        "nibabel",
+        "nilearn",
+        "numpy",
+        "matplotlib",
+        "ipykernel",
+        "ipython",
+        "treelib",
+        "pytest",
+        "jupyterlab"
+    ]
 )