diff --git a/talks/matlab_vs_python/bloch/bloch.ipynb b/talks/matlab_vs_python/bloch/bloch.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..a96717a06ac7f261330974fdc39c8e68b2348208
--- /dev/null
+++ b/talks/matlab_vs_python/bloch/bloch.ipynb
@@ -0,0 +1,127 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Imports"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "from scipy.integrate import ode\n",
+ "import matplotlib.pyplot as plt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Define bloch and B_eff functions"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def bloch_ode(t,M,T1,T2):\n",
+ " B = B_eff(t)\n",
+ " return np.array([M[1]*B[2] - M[2]*B[1] - M[0]/T2,\n",
+ " M[2]*B[0] - M[0]*B[2] - M[1]/T2,\n",
+ " M[0]*B[1] - M[1]*B[0] - (M[2]-1)/T1])\n",
+ "\n",
+ "def B_eff(t):\n",
+ " if t < 0.25:\n",
+ " return np.array([0, 0, 0])\n",
+ " elif t < 1.25:\n",
+ " return np.array([1.8*np.sinc(t-0.75), 0, 0])\n",
+ " elif t < 1.50:\n",
+ " return np.array([0, 0, 0])\n",
+ " elif t < 3.00:\n",
+ " return np.array([0, 0, 2*np.pi])\n",
+ " else:\n",
+ " return np.array([0, 0, 0])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Integrate ODE"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "t = np.array([0])\n",
+ "M = np.array([[0, 0, 1]])\n",
+ "dt= 0.005\n",
+ "r = ode(bloch_ode)\n",
+ "r.set_integrator('dopri5')\n",
+ "r.set_initial_value(M[0],t[0])\n",
+ "r.set_f_params(1500, 50)\n",
+ "while r.successful() and r.t < 5:\n",
+ " t = np.append(t,r.t+dt)\n",
+ " M = np.append(M, np.array([r.integrate(t[-1])]),axis=0)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot Results"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "_, ax = plt.subplots(figsize=(12,12))\n",
+ "ax.plot(t,M[:,0], label='Mx')\n",
+ "ax.plot(t,M[:,1], label='My')\n",
+ "ax.plot(t,M[:,2], label='Mz')\n",
+ "ax.legend()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/talks/matlab_vs_python/bloch/bloch.m b/talks/matlab_vs_python/bloch/bloch.m
new file mode 100644
index 0000000000000000000000000000000000000000..324fcc85ebf9ff8bd6ea0631f50fca34b6c761e2
--- /dev/null
+++ b/talks/matlab_vs_python/bloch/bloch.m
@@ -0,0 +1,32 @@
+%% Imports
+
+%% Integrate ODE
+[t, M] = ode45(@(t,M)bloch_ode(t,M,1500,50),linspace(0,5,1000),[0;0;1]);
+
+%% Plot Results
+clf();hold on;
+plot(t,M(:,1));
+plot(t,M(:,2));
+plot(t,M(:,3));
+
+%% Define bloch and b_eff functions
+function dM = bloch_ode(t,M,T1,T2)
+ B = B_eff(t); % B-effective
+ dM = [M(2)*B(3) - M(3)*B(2) - M(1)/T2; % dMx/dt
+ M(3)*B(1) - M(1)*B(3) - M(2)/T2; % dMy/dt
+ M(1)*B(2) - M(2)*B(1) - (M(3)-1)/T1]; % dMz/dt
+end
+
+function b = B_eff(t)
+ if t < 0.25 % No B-field
+ b = [0, 0, 0];
+ elseif t < 1.25 % 1-ms excitation around x-axis
+ b = [1.8*sinc(t-0.75), 0, 0];
+ elseif t < 1.50 % No B-field
+ b = [0, 0, 0];
+ elseif t < 3.00 % Gradient in y-direction
+ b = [0, 0, 2*pi];
+ else % No B-field
+ b = [0, 0, 0];
+ end
+end
\ No newline at end of file
diff --git a/talks/matlab_vs_python/bloch/bloch.py b/talks/matlab_vs_python/bloch/bloch.py
new file mode 100644
index 0000000000000000000000000000000000000000..873798d44709e21eb70e3294ede8aee10b118705
--- /dev/null
+++ b/talks/matlab_vs_python/bloch/bloch.py
@@ -0,0 +1,40 @@
+#%% Imports
+import numpy as np
+from scipy.integrate import ode
+import matplotlib.pyplot as plt
+
+#%% Define bloch and B_eff functions
+def bloch_ode(t,M,T1,T2):
+ B = B_eff(t)
+ return np.array([M[1]*B[2] - M[2]*B[1] - M[0]/T2,
+ M[2]*B[0] - M[0]*B[2] - M[1]/T2,
+ M[0]*B[1] - M[1]*B[0] - (M[2]-1)/T1])
+
+def B_eff(t):
+ if t < 0.25:
+ return np.array([0, 0, 0])
+ elif t < 1.25:
+ return np.array([1.8*np.sinc(t-0.75), 0, 0])
+ elif t < 1.50:
+ return np.array([0, 0, 0])
+ elif t < 3.00:
+ return np.array([0, 0, 2*np.pi])
+ else:
+ return np.array([0, 0, 0])
+
+#%% Integrate ODE
+t = np.array([0])
+M = np.array([[0, 0, 1]])
+dt= 0.005
+r = ode(bloch_ode)\
+ .set_integrator('dopri5')\
+ .set_initial_value(M[0],t[0])\
+ .set_f_params(1500, 50)
+while r.successful() and r.t < 5:
+ t = np.append(t,r.t+dt)
+ M = np.append(M, np.array([r.integrate(t[-1])]),axis=0)
+
+#%% Plot Results
+plt.plot(t,M[:,0])
+plt.plot(t,M[:,1])
+plt.plot(t,M[:,2])
\ No newline at end of file
diff --git a/talks/matlab_vs_python/partial_fourier/data.mat b/talks/matlab_vs_python/partial_fourier/data.mat
new file mode 100644
index 0000000000000000000000000000000000000000..c63c984d088a3280bafb2a681a3a8a50853531cf
Binary files /dev/null and b/talks/matlab_vs_python/partial_fourier/data.mat differ
diff --git a/talks/matlab_vs_python/partial_fourier/partial_fourier.ipynb b/talks/matlab_vs_python/partial_fourier/partial_fourier.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..ea2bb3e782730d4a5ad488077d4ba7a330f35e65
--- /dev/null
+++ b/talks/matlab_vs_python/partial_fourier/partial_fourier.ipynb
@@ -0,0 +1,136 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Imports"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import h5py\n",
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Load Data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "h = h5py.File('data.mat','r')\n",
+ "img = np.transpose(h.get('img')['real']+1j*h.get('img')['imag'])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "6/8 Partial Fourier sampling"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "n = np.random.randn(96,96) + 1j*np.random.randn(96,96)\n",
+ "y = np.fft.fftshift(np.fft.fft2(img),axes=0) + n\n",
+ "y[72:,:] = 0"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Estimate phase"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "pad = np.pad(np.hanning(48),24,'constant')[:,None]\n",
+ "phs = np.exp(1j*np.angle(np.fft.ifft2(np.fft.ifftshift(y*pad,axes=0))))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "POCS reconstruction"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "est = np.zeros((96,96))\n",
+ "iters = 10\n",
+ "for i in range(iters):\n",
+ " est = np.fft.fftshift(np.fft.fft2(est*phs),axes=0)\n",
+ " est[:72,:] = y[:72,:]\n",
+ " est = np.maximum(np.real(np.fft.ifft2(np.fft.ifftshift(est,axes=0))*np.conj(phs)),0)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Plot reconstruction"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "_, ax = plt.subplots(1,2,figsize=(16,16))\n",
+ "ax[0].imshow(np.abs(np.fft.ifft2(np.fft.ifftshift(y,axes=0))), vmin=0, vmax=1)\n",
+ "ax[0].set_title('Zero-filled')\n",
+ "ax[1].imshow(est, vmin=0, vmax=1)\n",
+ "ax[1].set_title('POCS recon')"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/talks/matlab_vs_python/partial_fourier/partial_fourier.m b/talks/matlab_vs_python/partial_fourier/partial_fourier.m
new file mode 100644
index 0000000000000000000000000000000000000000..b364ab7a192beafbeac83d9dba59ac0fbd655425
--- /dev/null
+++ b/talks/matlab_vs_python/partial_fourier/partial_fourier.m
@@ -0,0 +1,32 @@
+%% Imports
+
+%% Load Data
+h = matfile('data.mat');
+img = h.img;
+
+%% 6/8 Partial Fourier sampling
+n = randn(96) + 1j*randn(96);
+y = fftshift(fft2(img),1) + 0*n;
+%y(73:end,:) = 0;
+
+%% Estimate phase
+pad = padarray(hann(48),24);
+phs = exp(1j*angle(ifft2(ifftshift(y.*pad,1))));
+
+%% POCS reconstruction
+est = zeros(96);
+iters = 10;
+for i = 1:iters
+ est = fftshift(fft2(est.*phs),1);
+ est(1:72,:) = y(1:72,:);
+ est = max(real(ifft2(ifftshift(est,1)).*conj(phs)),0);
+end
+
+%% Plot reconstruction
+figure();
+subplot(1,2,1);
+imshow(abs(ifft2(ifftshift(y,1))),[0 1],'colormap',jet);
+title('Zero-Filled');
+subplot(1,2,2);
+imshow(est,[0 1],'colormap',jet);
+title('POCS recon');
\ No newline at end of file
diff --git a/talks/matlab_vs_python/partial_fourier/partial_fourier.py b/talks/matlab_vs_python/partial_fourier/partial_fourier.py
new file mode 100644
index 0000000000000000000000000000000000000000..2ceb7ece4f5a288fba11ae2345cb225cc2e1642b
--- /dev/null
+++ b/talks/matlab_vs_python/partial_fourier/partial_fourier.py
@@ -0,0 +1,32 @@
+#%% Imports
+import h5py
+import matplotlib.pyplot as plt
+import numpy as np
+
+#%% Load Data
+h = h5py.File('data.mat','r')
+img = np.transpose(h.get('img')['real']+1j*h.get('img')['imag'])
+
+#%% 6/8 Partial Fourier sampling
+n = np.random.randn(96,96) + 1j*np.random.randn(96,96)
+y = np.fft.fftshift(np.fft.fft2(img),axes=0) + n
+y[72:,:] = 0
+
+#%% Estimate phase
+pad = np.pad(np.hanning(48),24,'constant')[:,None]
+phs = np.exp(1j*np.angle(np.fft.ifft2(np.fft.ifftshift(y*pad,axes=0))))
+
+#%% POCS reconstruction
+est = np.zeros((96,96))
+iters = 10
+for i in range(iters):
+ est = np.fft.fftshift(np.fft.fft2(est*phs),axes=0)
+ est[:72,:] = y[:72,:]
+ est = np.maximum(np.real(np.fft.ifft2(np.fft.ifftshift(est,axes=0))*np.conj(phs)),0)
+
+#%% Plot reconstruction
+_, ax = plt.subplots(1,2)
+ax[0].imshow(np.abs(np.fft.ifft2(np.fft.ifftshift(y,axes=0))),vmin=0,vmax=1)
+ax[0].set_title('Zero-filled')
+ax[1].imshow(est, vmin=0, vmax=1)
+ax[1].set_title('POCS recon')
\ No newline at end of file