extend boundary while calculating convolution for laplacian and 2d-cu…

…rvature

.devcontainer/devcontainer.json

@@ -2,10 +2,6 @@
     "image": "mcr.microsoft.com/vscode/devcontainers/base:ubuntu-22.04",
     // https://github.com/microsoft/vscode-dev-containers/tree/main/containers
     "features": {
-      "ghcr.io/devcontainers/features/python:1": {
-        "version": "3.11",
-        "installJupyterlab": true
-      },
       "node": {
         "version": "18"
       }
@@ -39,6 +35,6 @@
       "ms-python.vscode-pylance",
       "ms-python.python"
     ],
-    "postCreateCommand": "if [ -f requirements.txt ]; then pip install -r requirements.txt; fi",
+    "postCreateCommand": "bash ./.devcontainer/postCreateCommands.sh",
     "waitFor": "postCreateCommand"
   }

.devcontainer/postCreateCommands.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+sudo apt update
+sudo apt install -y --no-install-recommends \
+    fonts-open-sans \
+    python3 \
+    python3-pip
+if [ -f requirements.txt ]; then
+    pip install -r requirements.txt
+fi

docs/enhancements.md

@@ -50,8 +50,8 @@ Since the $x$ and $y$ scales represent different quantities (units), we also
 have a weight factor $w$.
 
 ```python showLineNumbers
-# diff2, x, y = arp.laplacian(data, x, y, bw=5, w='default')
-diff2, x, y = arp.laplacian(data, energy, angle)
+# diff2 = arp.laplacian(data, x, y, bw=5, w='default')
+diff2 = arp.laplacian(data, energy, angle)
 
 plt.imshow(diff2, vmax=0, cmap='terrain_r')
 plt.axis('off')
@@ -84,8 +84,8 @@ Scientific Instruments **82**, 043712 (2011)](https://doi.org/10.1063/1.3585113)
 
 
 ```python showLineNumbers
-# cv2d, x, y = arp.cv2d(data, x, y, bw=5, c1=0.001, c2=0.001, w='default')
-cv2d, x, y = arp.cv2d(data, energy, angle)
+# cv2d = arp.cv2d(data, x, y, bw=5, c1=0.001, c2=0.001, w='default')
+cv2d = arp.cv2d(data, energy, angle)
 
 plt.imshow(cv2d, vmax=0, cmap='terrain_r')
 plt.axis('off')

docs/glossary.md

@@ -31,7 +31,7 @@ Returns cropped 2D array and corresponding axes scaling vectors defined by
 ## cv2d
 
 ```python
-cv2d, x, y = arp.cv2d(data, x, y, bw=5, c1=0.001, c2=0.001, w='default')
+cv2d = arp.cv2d(data, x, y, bw=5, c1=0.001, c2=0.001, w='default')
 ```
 
 Calculates two-dimensional curvature. The details about the curvature method can
@@ -49,10 +49,8 @@ features in image plots*, [Review of Scientific Instruments **82**, 043712
 - `w` : scaling weight (optional).
 
 **Outputs:**
-- `cv2d` : 2D array of curvature. Output array has different shape than the
-input array as the edges are removed due to smoothing artifacts.
-- `x` : cropped input `x` array to match `cv2d` dimension.
-- `y` : cropped input `y` array to match `cv2d` dimension.
+- `cv2d` : 2D array of curvature. Output array has the same shape as the input
+array.
 
 
 ## export_itx
@@ -169,7 +167,7 @@ the slit, and perpendicular to the slit directions, respectively.
 ## laplacian
 
 ```python
-diff2, x, y = arp.laplacian(data, x, y, bw=5, w='default')
+diff2 = arp.laplacian(data, x, y, bw=5, w='default')
 ```
 
 Laplacian (second order partial derivatives with respect to both energy and
@@ -185,10 +183,7 @@ angle) of the spectra.
 
 **Outputs:**
 - `diff2` : 2D array of spectra after taking second order partial derivative
-w.r.t. both energy and angle. This array has different shape than the input
-array as the edges are removed due to smoothing artifacts.
-- `x` : cropped input `x` array to match `diff2` dimension.
-- `y` : cropped input `y` array to match `diff2` dimension.
+w.r.t. both energy and angle. This array has the same shape as input array.
 
 
 ## line_profile

src/cv2d.py

@@ -10,17 +10,12 @@ def cv2d(data, x, y, bw=5, c1=0.001, c2=0.001, w='default'):
     import numpy as np
     from astropy.convolution import convolve, Box2DKernel
     # https://docs.astropy.org/en/latest/api/astropy.convolution.Box2DKernel.html
+    # https://docs.astropy.org/en/latest/api/astropy.convolution.convolve.html#astropy.convolution.convolve
 
     if (w=='default'):
         w = data.shape[0]/data.shape[1]
 
-    data_smth = convolve(data, Box2DKernel(bw))
-
-    # crop the edges
-    bo = int(bw/2 + 1)
-    data_smth = data_smth[bo:-bo, bo:-bo]
-    x = x[bo:-bo]
-    y = y[bo:-bo]
+    data_smth = convolve(data, Box2DKernel(bw), boundary='extend')
 
     dE   = np.gradient(data_smth, axis=0)
     dT   = np.gradient(data_smth, axis=1)*w
@@ -39,4 +34,4 @@ def cv2d(data, x, y, bw=5, c1=0.001, c2=0.001, w='default'):
     #             jj <= bo+1 or jj >= data.shape[1]-bo-1):
     #             diff2[ii][jj] = np.nan
 
-    return cv2d, x, y
+    return cv2d

src/laplacian.py

@@ -9,17 +9,11 @@ def laplacian(data, x, y, bw=5, w='default'):
     import numpy as np
     from astropy.convolution import convolve, Box2DKernel
     # https://docs.astropy.org/en/latest/api/astropy.convolution.Box2DKernel.html
-
+    # https://docs.astropy.org/en/latest/api/astropy.convolution.convolve.html#astropy.convolution.convolve
     if (w=='default'):
         w = data.shape[0]/data.shape[1]
 
-    data_smth = convolve(data, Box2DKernel(bw))
-
-    # crop the edges
-    bo = int(bw/2 + 1)
-    data_smth = data_smth[bo:-bo, bo:-bo]
-    x = x[bo:-bo]
-    y = y[bo:-bo]
+    data_smth = convolve(data, Box2DKernel(bw), boundary='extend')
 
     # Laplacian
     diff2 = np.gradient(np.gradient(data_smth, axis=0), axis=0) + \
@@ -32,4 +26,4 @@ def laplacian(data, x, y, bw=5, w='default'):
     #             jj <= bo+1 or jj >= data.shape[1]-bo-1):
     #             diff2[ii][jj] = np.nan
 
-    return diff2, x, y
+    return diff2