Vacc vs non analysis

.gitignore

@@ -3,4 +3,5 @@
 *pycache*
 .DS_Store
 *.pyc
-venv/*
+venv/*
+.vscode

README.md

@@ -15,7 +15,7 @@ On a typical Windows, Mac, or Linux computer:
 * Create a conda environment: `conda create --name multisero python=3.7`
 * Activate conda environment: `conda activate multisero`
 * Pip install dependencies: `pip install -r requirements.txt`
-* Add the package to PYTHONPATH. Inside the package directory (...\serology-COVID19), do: `export PYTHONPATH=$PYTHONPATH:$(pwd)` 
+* If operating from CLI, add the package to PYTHONPATH by navigating to package directory (eg: ...\serology-COVID19), and type `export PYTHONPATH=$PYTHONPATH:$(pwd)`
 
 For installation notes for Jetson Nano, see [these notes](docs/installation.md).
 
@@ -47,10 +47,12 @@ optional arguments:
   -m METADATA, --metadata METADATA
                         specify the file name for the experiment metadata.
                         Assumed to be in the same directory as images.
-                        Default: 'multisero_output_data_metadata.xlsx'
+                        Default: 'multisero_output_data_metadata.xlsx', therefore
+                        metadata flag is NOT necessary when running in -e mode IF
+                        metadata file has the default filename.
 ```
 ### Extract OD from antigen array images
-`python multisero.py -e -i <input> -o <output> -m <METADATA>` will take metadata for antigen array and images as input, and output optical densities for each antigen.
+`python multisero.py -e -i <input> -o <output>` will take metadata for antigen array and images as input, and output optical densities for each antigen.
 The optical densities are stored in an excel file at the following path: `<output>/multisero_<input>_<year><month><day>_<hour><min>/median_ODs.xlsx`
 
 If rerunning some of the wells, the input metadata file needs to contain a sheet named 'rerun_wells'

array_analyzer/extract/image_parser.py → multiSero/array_analyzer/extract/image_parser.py

@@ -12,7 +12,7 @@
 from skimage import measure
 
 from .img_processing import thresh_and_binarize
-from array_analyzer.transform.point_registration import icp
+from multiSero.array_analyzer.transform.point_registration import icp
 
 """
 method is
@@ -338,7 +338,7 @@ def find_fiducials_markers(props_,
     return cent_map
 
 
-def grid_from_centroids(props_, n_rows, n_cols, grid_spacing=82):
+def grid_from_centroids(props_, n_rows, n_cols, grid_spacing=90):
     """
     based on the region props, creates a dictionary of format:
         key = (centroid_x, centroid_y)

array_analyzer/extract/metadata.py → multiSero/array_analyzer/extract/metadata.py

@@ -3,8 +3,8 @@
 import pandas as pd
 import shutil
 
-import array_analyzer.extract.txt_parser as txt_parser
-import array_analyzer.extract.constants as constants
+import multiSero.array_analyzer.extract.txt_parser as txt_parser
+import multiSero.array_analyzer.extract.constants as constants
 
 
 class MetaData:

array_analyzer/extract/txt_parser.py → multiSero/array_analyzer/extract/txt_parser.py

@@ -9,8 +9,6 @@
 import pandas as pd
 import math
 
-import array_analyzer.extract.constants as constants
-
 """
 functions like "create_<extension>_dict" parse files of <extension> and return:
 fiduc: list of dict describing fiducial positions

array_analyzer/load/report.py → multiSero/array_analyzer/load/report.py

@@ -5,7 +5,7 @@
 import os
 import pandas as pd
 
-import array_analyzer.extract.constants as constants
+import multiSero.array_analyzer.extract.constants as constants
 
 
 class ReportWriter:

array_analyzer/transform/array_generation.py → multiSero/array_analyzer/transform/array_generation.py

@@ -2,10 +2,10 @@
 import numpy as np
 import pandas as pd
 
-import array_analyzer.extract.constants as constants
-import array_analyzer.extract.img_processing as img_processing
-import array_analyzer.extract.txt_parser as txt_parser
-import array_analyzer.utils.spot_regionprop as regionprop
+import multiSero.array_analyzer.extract.constants as constants
+import multiSero.array_analyzer.extract.img_processing as img_processing
+import multiSero.array_analyzer.extract.txt_parser as txt_parser
+import multiSero.array_analyzer.utils.spot_regionprop as regionprop
 
 
 def build_centroid_binary_blocks(cent_list, image_, params_, return_type='region'):
@@ -59,7 +59,7 @@ def build_centroid_binary_blocks(cent_list, image_, params_, return_type='region
         return target
 
 
-def get_spot_intensity(coords, im, background, search_range=3):
+def get_spot_intensity(coords, im, background, search_range=2):
     """
     Extract signal and background intensity at each spot given the spot coordinate
     with the following steps:

array_analyzer/transform/point_registration.py → multiSero/array_analyzer/transform/point_registration.py

@@ -2,7 +2,7 @@
 import logging
 import numpy as np
 
-import array_analyzer.extract.constants as constants
+import multiSero.array_analyzer.extract.constants as constants
 
 
 def icp(source, target, max_iterate=50, matrix_diff=1.):
@@ -166,10 +166,12 @@ def get_translation_matrix(particle):
         b = particle[3] * np.sin(particle[2] * np.pi / 180)
         t_matrix = np.array([[a, b, particle[0]],
                             [-b, a, particle[1]]])
+        #t_matrix = np.array([[0, 0, particle[0]],
+                           #[0, 0, particle[1]]])
         return t_matrix
 
     def particle_filter(self,
-                        max_iter=100,
+                        max_iter=1000,
                         stop_criteria=.1,
                         iter_decrease=.8,
                         nbr_outliers=0):
@@ -256,6 +258,7 @@ def particle_filter(self,
         self.registered_dist = min_dist / (self.fiducial_coords.shape[0] - nbr_outliers)
         self.logger.info("Particle filter min dist: {}".format(self.registered_dist))
         if self.registered_dist > constants.REG_DIST_THRESH:
+        #if self.registered_dist > 300:
             self.registration_ok = False
         else:
             self.registration_ok = True

array_analyzer/utils/spot_regionprop.py → multiSero/array_analyzer/utils/spot_regionprop.py

@@ -3,7 +3,7 @@
 from skimage import measure
 from skimage.morphology import disk
 
-import array_analyzer.extract.constants as constants
+import multiSero.array_analyzer.extract.constants as constants
 
 
 class SpotRegionprop:

array_analyzer/workflows/interpolation_wf.py → multiSero/array_analyzer/workflows/interpolation_wf.py

@@ -4,16 +4,16 @@
 import pandas as pd
 import skimage.io as io
 
-import array_analyzer.extract.image_parser as image_parser
-import array_analyzer.extract.txt_parser as txt_parser
-import array_analyzer.extract.img_processing as img_processing
-import array_analyzer.load.debug_plots as debug_plots
-import array_analyzer.load.report as report
-import array_analyzer.extract.constants as constants
-import array_analyzer.transform.array_generation as array_gen
-import array_analyzer.extract.background_estimator as background_estimator
-import array_analyzer.utils.io_utils as io_utils
-from array_analyzer.extract.metadata import MetaData
+import multiSero.array_analyzer.extract.image_parser as image_parser
+import multiSero.array_analyzer.extract.txt_parser as txt_parser
+import multiSero.array_analyzer.extract.img_processing as img_processing
+import multiSero.array_analyzer.load.debug_plots as debug_plots
+import multiSero.array_analyzer.load.report as report
+import multiSero.array_analyzer.extract.constants as constants
+import multiSero.array_analyzer.transform.array_generation as array_gen
+import multiSero.array_analyzer.extract.background_estimator as background_estimator
+import multiSero.array_analyzer.utils.io_utils as io_utils
+from multiSero.array_analyzer.extract.metadata import MetaData
 
 
 def interp(input_dir, output_dir):

array_analyzer/workflows/registration_workflow.py → multiSero/array_analyzer/workflows/registration_workflow.py

@@ -1,21 +1,18 @@
-import cv2 as cv
 import logging
-import numpy as np
 import os
 import pandas as pd
 import time
 
-import array_analyzer.extract.background_estimator as background_estimator
-import array_analyzer.extract.image_parser as image_parser
-import array_analyzer.extract.img_processing as img_processing
-import array_analyzer.extract.metadata as metadata
-import array_analyzer.extract.txt_parser as txt_parser
-import array_analyzer.extract.constants as constants
-import array_analyzer.load.debug_plots as debug_plots
-import array_analyzer.load.report as report
-import array_analyzer.transform.point_registration as registration
-import array_analyzer.transform.array_generation as array_gen
-import array_analyzer.utils.io_utils as io_utils
+import multiSero.array_analyzer.extract.background_estimator as background_estimator
+import multiSero.array_analyzer.extract.img_processing as img_processing
+import multiSero.array_analyzer.extract.metadata as metadata
+import multiSero.array_analyzer.extract.txt_parser as txt_parser
+import multiSero.array_analyzer.extract.constants as constants
+import multiSero.array_analyzer.load.debug_plots as debug_plots
+import multiSero.array_analyzer.load.report as report
+import multiSero.array_analyzer.transform.point_registration as registration
+import multiSero.array_analyzer.transform.array_generation as array_gen
+import multiSero.array_analyzer.utils.io_utils as io_utils
 
 
 def point_registration(input_dir, output_dir):

array_analyzer/workflows/well_wf.py → multiSero/array_analyzer/workflows/well_wf.py

@@ -1,15 +1,14 @@
-import array_analyzer.extract.image_parser as image_parser
-import array_analyzer.extract.img_processing as processing
-import array_analyzer.extract.constants as constants
-from array_analyzer.extract.metadata import MetaData
-import array_analyzer.utils.io_utils as io_utils
+import multiSero.array_analyzer.extract.image_parser as image_parser
+import multiSero.array_analyzer.extract.img_processing as processing
+import multiSero.array_analyzer.extract.constants as constants
+from multiSero.array_analyzer.extract.metadata import MetaData
+import multiSero.array_analyzer.utils.io_utils as io_utils
 
 import time
 import skimage.io as io
 import pandas as pd
 import string
 import os
-import re
 import numpy as np