include figures in overview

README.md

@@ -28,6 +28,14 @@ Wayne Crismani, St Vincent's Institute of Medical Research and the University of
 
 ## Compatibility
 
+synapsis relies heavily on the bioconductor package EBImage, which currently supports jpeg, png and tiff image files.
+
+Currently, synapsis also supports
+
+- [x] .nd2 (NIKON), see [nd2converter.py][], which converts a three channel image into three separate jpegs of foci, SC and DAPI (unused) channels from original .nd2 files.
+
+
+
 ## Using synapsis
 
 synapsis has four main functions. These are:
@@ -44,15 +52,15 @@ We summarise them in the following subsections:
 
 ### auto_crop
 
-input: Original grey scale image files of (1) Synaptonemal complexes (e.g. SYCP3 anti-body) and (2) Foci (e.g. MLH1, MLH3 anti-body) channels from e.g. Nikon .nd2 files.
+input: Original grey scale image files of (1) Synaptonemal complexes ("SC", e.g. SYCP3 anti-body) and (2) foci (e.g. MLH1, MLH3 anti-body) channels from e.g. Nikon .nd2 files.
 
-output: crops in channels (1) '*dna.jpeg' and (2) '*foci.jpeg' around individual cells.
+output: crops in SC (red) and foci (green) around individual cells.
 
 ![cropping](resources/figures/cropping_procedure.png)
 
 ### get_pachytene
 
-input: crops in channels (1) '*dna.jpeg' and (2) '*foci.jpeg' around individual cells, from previous auto_crop.
+input: crops in channels (1) (red) and (2) (green) around individual cells, from previous auto_crop.
 
 output: only keeps crops if cells are in pachytene phase (based on channel (1))
 
@@ -105,3 +113,5 @@ This project is a [workflowr][] project, where we make use of a [project templat
 [project template]: https://gitlab.svi.edu.au/biocellgen-public/aaaa_2019_project-template
 
 [issue]: https://gitlab.svi.edu.au/lmcneill/synapsis/-/issues
+
+[nd2converter.py]: https://gitlab.svi.edu.au/lmcneill/synapsis/source/nd2converter.py

source/nd2converter.py

+from nd2reader import ND2Reader
+import matplotlib.pyplot as plt
+import numpy as np
+import os
+import glob
+from PIL import Image
+
+parent_dir = 'data-folder/sharepoint'
+filenames = []
+
+for file in glob.glob(os.path.join(parent_dir, '*nd2')):
+    filenames.append(file)
+filenames = sorted(filenames)
+print(filenames)
+
+for name in filenames:
+
+    with ND2Reader(str(name)) as images:
+        plt.figure(figsize = (10,10))
+        plt.gca().set_axis_off()
+        plt.subplots_adjust(top = 1, bottom = 0, right = 1, left = 0,
+                hspace = 0, wspace = 0)
+        plt.margins(0,0)
+        plt.gca().xaxis.set_major_locator(plt.NullLocator())
+        plt.gca().yaxis.set_major_locator(plt.NullLocator())
+        plt.imshow(images[0],cmap = 'gray')
+    ### keep metadata... e.g.
+    ## savefig(fname, dpi=None, facecolor='w', edgecolor='w',
+    ## orientation='portrait', papertype=None, format=None,
+    ## transparent=False, bbox_inches=None, pad_inches=0.1,
+    ## frameon=None, metadata=None)
+        plt.savefig(str(name)+'cells.jpeg')
+        plt.figure(figsize = (10,10))
+        plt.gca().set_axis_off()
+        plt.subplots_adjust(top = 1, bottom = 0, right = 1, left = 0,
+            hspace = 0, wspace = 0)
+        plt.margins(0,0)
+        plt.gca().xaxis.set_major_locator(plt.NullLocator())
+        plt.gca().yaxis.set_major_locator(plt.NullLocator())
+        plt.imshow(images[1],cmap = 'gray')
+        plt.savefig(str(name)+'foci.jpeg')
+        plt.figure(figsize = (10,10))
+        plt.gca().set_axis_off()
+        plt.subplots_adjust(top = 1, bottom = 0, right = 1, left = 0,
+                hspace = 0, wspace = 0)
+        plt.margins(0,0)
+        plt.gca().xaxis.set_major_locator(plt.NullLocator())
+        plt.gca().yaxis.set_major_locator(plt.NullLocator())
+        plt.imshow(images[2],cmap = 'gray')
+        plt.savefig(str(name)+'dna.jpeg')