Merge remote-tracking branch 'origin/development' into feature-fast-p…

…oisson

@chebcolloc/fred.m

@@ -24,4 +24,4 @@
     F = kernel(X, Y) * spdiags(s.', 0, sum(n), sum(n));
 end
 
-end
+end

@chebcolloc/volt.m

@@ -30,5 +30,4 @@
 
 V = V .* matrix(disc, n); 
 
-end
-
+end

@chebfun/besseli.m

@@ -11,14 +11,14 @@
 %
 %   The relationship between I_NU(Z) and J_NU(Z) = BESSELJ(NU, Z) is
 %
-%        I_NU(Z) = 1i^NU * J_NU(1i*Z).
+%        I_NU(Z) = 1i^-NU * J_NU(1i*Z).
 %
 % See also AIRY, BESSELH, BESSLJ, BESSELK, BESSELY.
 
 % Copyright 2017 by The University of Oxford and The Chebfun Developers.
 % See http://www.chebfun.org/ for Chebfun information.
 
-scl = 1i.^nu;
+scl = 1i.^-nu;
 g = scl*besselj(nu, 1i*f, varargin{:});
 
 end

@chebguiController/plotEigenmodes.m

@@ -40,7 +40,15 @@ function plotEigenmodes(handles, selection, h1, h2)
 C = get(0, 'DefaultAxesColorOrder');
 C = repmat(C, ceil(length(D)/size(C, 1)), 1);
 
-% Number of unknown variables in the problem
+% Usually, we end up solving for more than 1 eigenfunctions/values, which means
+% that the solution V is a CHEBMATRIX, rather than a simple CHEBFUN. The
+% plotting below assumes we're working with a CHEBMATRIX for various
+% functionality, so cast a single CHEBFUN to a CHEBMATRIX:
+if ( ~isa(V, 'chebmatrix') )
+    V = chebmatrix(V);
+end
+
+% Number of unknown variables in the problem:
 numVar = size(V, 1);
 
 % Need to trim the data we are plotting if user has made a selection

@chebmatrix/plot.m

@@ -37,6 +37,16 @@
     % call CHEBFUN/PLOT():
     A.blocks = reshape(A.blocks, 1, numel(A.blocks));
     A = quasimatrix(A.blocks);
+
+    % Repeat for other CHEBMATRIX types in varargin.
+    for k = 1:numel(varargin)
+        if ( isa(varargin{k}, 'chebmatrix') )
+            tmp = varargin{k};
+            tmp = reshape(tmp.blocks, 1, numel(tmp.blocks));
+            varargin{k} = quasimatrix(tmp);
+        end
+    end
+
     [varargout{1:nargout}] = plot(A, varargin{:});
 
 end

@chebop/eig.m

@@ -1,4 +1,4 @@
-function eig(varargin)
+function varargout = eig(varargin)
 %   EIG(N) is not supported. Use EIGS(N) to find selected eigenvalues of a
 %   linear operator.
 %