Update documentation

docs/conf.py

@@ -86,11 +86,10 @@
     "navbar_sidebarrel": False,
     "bootstrap_version": "3",
     "navbar_links": [
-        ("Quickstart", "quickstart"),
-        ("How-to?", "how_to"),
         ("Gallery", "auto_examples/index"),
-        ("Releases", "https://github.com/SarthakJariwala/seaborn-image/releases", True),
         ("Reference", "reference"),
+        ("How-to?", "how_to"),        
+        ("Releases", "https://github.com/SarthakJariwala/seaborn-image/releases", True),
     ],
 }
 

docs/how_to.rst

@@ -49,10 +49,10 @@ Modify scale bar properties
     import seaborn_image as isns
 
     # change scalebar color
-    isns.set_scalebar(rc={"color": "red"})
+    isns.set_scalebar(color="red")
 
     # change scalebar position
-    isns.set_scalebar(rc={"location": "upper right"})
+    isns.set_scalebar(location="upper right")
 
 
 Add label to colorbar
@@ -75,8 +75,8 @@ Use image filters
     isns.filterplot(data, filter="sobel")
 
 
-Change image plot properties
-----------------------------
+Globally change image plot properties
+-------------------------------------
 
 .. code-block:: python
 

docs/index.rst

@@ -28,14 +28,15 @@ seaborn-image: image data visualization
 Description
 ===========
 
-Seaborn-image is a *seaborn like* Python **image** visualization and processing library
-based on matplotlib, scikit-image and scipy.
+Seaborn-image is a Python **image** visualization library based on matplotlib, scikit-image and scipy.
 
-The aim of seaborn-image is to provide a high-level API to **process and plot attractive images quickly**
+Seaborn-image provides a high-level API to **draw attractive and informative images quickly**
 **and effectively**.
 
-To get started with ``seaborn_image``, check out the :doc:`quickstart page <quickstart>`.
-To view example images, check out the :doc:`gallery page <auto_examples/index>`.
+It is heavily inspired by `**seaborn** <https://seaborn.pydata.org/>`_, a high-level visualization library
+for drawing attractive statistical graphics in Python.
+
+To view example images, check out the :doc:`gallery page <auto_examples/index>` and :doc:`reference <reference>`.
 For specific how-to questions, refer to the :doc:`how-to page <how_to>`.
 
 Check out the source code on `github <https://github.com/SarthakJariwala/seaborn-image>`_.
@@ -52,36 +53,42 @@ Installation
 Usage
 =====
 
-Check out the :doc:`quickstart page <quickstart>` for a walk through
-of the sample features below.
-
 Simple usage
 ************
 
 .. code-block:: python
 
     import seaborn_image as isns
 
-    """Set context like seaborn"""
+    """Global settings for images"""
     isns.set_context("notebook")
+    isns.set_image(cmap="deep", despine=True)
+    isns.set_scalebar(color="red")
 
-    """Plot publishable quality image in one line"""
+    """Plot image"""
     isns.imgplot(data)
 
-    """Add a scalebar"""
+    """Image with a scalebar"""
     isns.imgplot(data, dx=1, units="um")
 
-Apply image filters (from scipy and skimage) and plot
-*****************************************************
+    """Get basic image stats"""
+    isns.imgplot(data, describe=True)
 
-.. code-block:: python
+Visualize image distribution
+****************************
 
-    import seaborn_image as isns
+..code-block:: python
+
+    isns.imghist(data)
 
-    isns.filterplot(data, filter="gaussian")
+Filter image and plot
+*********************
 
+.. code-block:: python
 
-For more information on getting strated, refer to the :doc:`quickstart guide <quickstart>`.
+    isns.filterplot(data, filt="gaussian", sigma=2.5)
+
+For more information check out examples in :doc:`api <reference>` and :doc:`gallery <auto_examples/index>`.
 
 
 Contents
@@ -90,13 +97,12 @@ Contents
 .. toctree::
    :maxdepth: 1
 
-   Quickstart <quickstart>
-   How-to? <how_to>
    Gallery <auto_examples/index>
+   Reference <reference>
+   How-to? <how_to>
    License <license>
    Authors <authors>
    Changelog <https://github.com/SarthakJariwala/seaborn-image/releases>
-   Reference <reference>
 
 
 Indices and tables

examples/plot_ImageGrid.py

@@ -0,0 +1,14 @@
+"""
+ImageGrid: Mutiple images on a single figure
+============================================
+"""
+
+import seaborn_image as isns
+
+# load images
+pol = isns.load_image("polymer")
+pl = isns.load_image("fluorescence")
+pol_out = isns.load_image("polymer outliers")
+
+g = isns.ImageGrid([pol, pl, pol_out], robust=[False, False, True], perc=[None, None, (2, 99.9)])
+g = isns.ImageGrid([pol, pl])

examples/plot_ImageGrid_2.py

@@ -0,0 +1,17 @@
+"""
+ImageGrid: Apply changes to individual images 
+=============================================
+"""
+
+import seaborn_image as isns
+
+# load images
+pol = isns.load_image("polymer")
+pl = isns.load_image("fluorescence")
+pol_out = isns.load_image("polymer outliers")
+
+g = isns.ImageGrid(
+    [pol, pl, pol_out],
+    robust=[False, False, True],
+    perc=[None, None, (2, 99.9)]
+)

examples/plot_fft.py

@@ -7,4 +7,4 @@
 
 img = isns.load_image("polymer")
 
-_ = isns.fftplot(img, cmap="viridis")
+ax = isns.fftplot(img, window_type="hann", cmap="viridis")

examples/plot_filter.py

@@ -1,10 +1,10 @@
 """
-Image Filter
-============
+Apply image filter
+==================
 """
 
 import seaborn_image as isns
 
 img = isns.load_image("polymer")
 
-_ = isns.filterplot(img, "median", size=5, cmap="ice")
+ax = isns.filterplot(img, "median", size=5, cmap="ice")

examples/plot_filtergrid.py

@@ -1,6 +1,6 @@
 """
-FilterGrid
-==========
+Interplay between filter parameters using FilterGrid
+====================================================
 """
 
 import seaborn_image as isns

examples/plot_image.py

@@ -7,6 +7,5 @@
 import seaborn_image as isns
 
 img = isns.load_image("polymer")
-img_scale = {"dx": 15, "units": "nm"}
 
-_ = isns.imgplot(img, dx=15, units="nm")
+ax = isns.imgplot(img, dx=15, units="nm")

examples/plot_image_hist.py

@@ -1,10 +1,10 @@
 """
-Image distribution
-==================
+Visualize image distribution
+============================
 
 """
 import seaborn_image as isns
 
 img = isns.load_image("polymer")
 
-_ = isns.imghist(img, cmap="YlGnBu_r", dx=15, units="nm")
+f = isns.imghist(img, cmap="YlGnBu_r", dx=15, units="nm")

examples/plot_image_robust.py

@@ -11,5 +11,5 @@
 
 f, axes = plt.subplots(1, 2)
 
-_ = isns.imgplot(img, ax=axes[0], cmap="inferno", despine=False)
-_ = isns.imgplot(img, ax=axes[1], robust=True, perc=(2, 99.99), cmap="inferno")
+ax0 = isns.imgplot(img, ax=axes[0], cmap="inferno")
+ax1 = isns.imgplot(img, ax=axes[1], robust=True, perc=(2, 99.99), cmap="inferno")

examples/plot_rgb_image.py

@@ -0,0 +1,14 @@
+"""
+RGB channels in RGB image
+=========================
+
+Split and plot the channels of the RGB image
+"""
+
+import seaborn_image as isns
+from skimage.data import astronaut
+
+# set image origin
+isns.set_image(origin="upper")
+
+g = isns.rgbplot(astronaut())