Added a plot checking how the background standard deviation of the covariance matrix decreases as the number of samples increases. The problem was that the theoretical estimate didn't have any background noise, whereas the measured one did. But it does go down as 1/sqrt(N), which corresponds to a standard sampling error convergence rate.
Multiple changes done here:

- Add: a way to enforce minimum distance stimuli. Closes #5

- Add: the indices of nontarget stimuli, used in the Sampler.

- Add: functions to plot specific datapoints. Handles multiple population code types.

Minors changes
Add: new datasets, for Cosyne.

Modified the plots slightly
- Add: functions to handle vectors, spherical coordinates and 3D rotations
- Add: 3D Plotting on a Sphere
- Add: 3D Plotting on a Torus
- Add: function wrapping angles into a specific range
Plots for Cosyne and PBS script

One example of the syntax for sending jobs through PBS.

Plots_cosyne contains all the functions needed to recreate the plots used in my poster, more or less.
Fisher Information computation and plots.

Script doing a few computations and plot to compute the Fisher Information, according to separable 2D Von Mises tuning curves, and assuming a Gaussian approximation to the recall process. First assume no covariance structure in the FI, then use the measured one.

We will then need to use the theoretical covariance derived using a KL projection (~Laplace) approximation for the whole recall model.

This contributes to issue #10, doesn't really close it yet, the whole thing has to be improved.
Big update, Wavelet code, new wrapping

- Add: Wavelet population code. fixes #7
- Add: New wrapping methods, playing around with many different possible circular tuning curves (Bivariate fisher, Von Mises-Fisher, Kent distribution). Helps for issue #13, but not completely finished.
- Add: multiple functions to handle spherical coordinates as well.
- Add: A function computing the theoretical covariance matrix found by minimizing the KL between the angle-marginalized-mixture object and its gaussian approximation.
- Add: Function to plot the network activity.
- Add: Functions to plot a neuron's response and the mean activity on a 3D space.
- Add/To modify: Function plotting the Fisher information (but a previous derivation, to be updated). Addresses #10
- Some added code in the main(), playing with the new functionality (specifically some plots about the KL approximation, to be moved somewhere else)
Time marginalization and Cosyne plots

- Add: Marginalization of time finalized. Does it numerically, nothing fancy here (computes the likelihood for all tc, then average). Checked with Charles, this seems like the correct thing to do, but might want to double-check the math. Closes #4.
- Add: Show nontargets stimuli when plotting the results, allows to see misbinding errors.
- Add: Plotting an histogram of the errors.
- Add: Writing the errors to a file.
- Add: Possibility to show the exponentiated likelihood, not just the log-likelihood.
- Add: Launcher to get full responses for a simultaneous presentation, for n=1..T objects. The responses are then used in Matlab to be fitted by Paul's model.
- Few modifications here and there, changed default parameters, and other tweaks.