Return correct shapes from Correlator

doc/tutorials/01-lennard_jones/01-lennard_jones.ipynb

@@ -549,9 +549,9 @@
    "source": [
     "fig3 = plt.figure(num=None, figsize=(10, 6), dpi=80, facecolor='w', edgecolor='k')\n",
     "fig3.set_tight_layout(False)\n",
-    "lag_time = msd[:, 0]\n",
+    "lag_time = msd_corr.lag_times()\n",
     "for i in range(0, N_PART, 30):\n",
-    "    msd_particle_i = msd[:, 2+i*3] + msd[:, 3+i*3] + msd[:, 4+i*3]\n",
+    "    msd_particle_i = msd[:, i, 0] + msd[:, i, 1] + msd[:, i, 2]\n",
     "    plt.plot(lag_time, msd_particle_i,\n",
     "             'o-', linewidth=2, label=\"particle id =\" + str(i))\n",
     "plt.xlabel(r'Lag time $\\tau$ [$\\delta t$]', fontsize=20)\n",

doc/tutorials/04-lattice_boltzmann/04-lattice_boltzmann_part2.ipynb

@@ -87,6 +87,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import numpy as np\n",
     "import logging\n",
     "import sys\n",
     "\n",
@@ -138,7 +139,9 @@
     "    for i in range(LOOPS):\n",
     "        system.integrator.run(STEPS)\n",
     "    correlator.finalize()\n",
-    "    msd_results.append(correlator.result())\n",
+    "    msd_results.append(np.column_stack((correlator.lag_times(),\n",
+    "                                        correlator.sample_sizes(),\n",
+    "                                        correlator.result().reshape([-1, 3]))))\n",
     "\n",
     "logging.info(\"Sampling finished.\")"
    ]

doc/tutorials/04-lattice_boltzmann/04-lattice_boltzmann_part3.ipynb

@@ -147,8 +147,8 @@
     "correlator.finalize()\n",
     "corrdata = correlator.result()\n",
     "\n",
-    "tau = corrdata[:, 0]\n",
-    "msd = corrdata[:, 2] + corrdata[:, 3] + corrdata[:, 4]\n",
+    "tau = correlator.lag_times()\n",
+    "msd = corrdata[:, 0] + corrdata[:, 1] + corrdata[:, 2]\n",
     "\n",
     "rh = system.analysis.calc_rh(chain_start=0, number_of_chains=1, chain_length=N_MONOMERS)[0]"
    ]

doc/tutorials/04-lattice_boltzmann/scripts/04-lattice_boltzmann_part3_solution.py

@@ -119,8 +119,8 @@
     corrdata = correlator.result()
 
     rh_results[index] = np.average(rhs)
-    tau = corrdata[1:, 0]
-    msd = corrdata[1:, 2] + corrdata[1:, 3] + corrdata[1:, 4]
+    tau = correlator.lag_times()[1:]
+    msd = corrdata[1:, 0] + corrdata[1:, 1] + corrdata[1:, 2]
     np.save('msd_{}'.format(N), np.c_[tau, msd])
 
 np.save('rh.npy', rh_results)

doc/tutorials/06-active_matter/06-active_matter.ipynb

@@ -385,7 +385,10 @@
     "# Finalize the correlator and write to disk\n",
     "system.auto_update_accumulators.remove(msd)\n",
     "msd.finalize()\n",
-    "numpy.savetxt(\"output.dat\", msd.result())\n",
+    "numpy.savetxt(\"output.dat\",\n",
+    "              numpy.column_stack((msd.lag_times(),\n",
+    "                                  msd.sample_sizes(),\n",
+    "                                  msd.result().reshape([-1, 3]))))\n",
     "```\n",
     "\n",
     "Here, the observable `pos_id` is set to the particle positions of the\n",

doc/tutorials/06-active_matter/solutions/enhanced_diffusion.py

@@ -119,12 +119,21 @@
     # Finalize the accumulators and write to disk
     system.auto_update_accumulators.remove(msd)
     msd.finalize()
-    np.savetxt("{}/msd_{}_{}.dat".format(outdir, vel, run), msd.result())
+    np.savetxt("{}/msd_{}_{}.dat".format(outdir, vel, run),
+               np.column_stack((msd.lag_times(),
+                                msd.sample_sizes(),
+                                msd.result().reshape([-1, 3]))))
 
     system.auto_update_accumulators.remove(vacf)
     vacf.finalize()
-    np.savetxt("{}/vacf_{}_{}.dat".format(outdir, vel, run), vacf.result())
+    np.savetxt("{}/vacf_{}_{}.dat".format(outdir, vel, run),
+               np.column_stack((vacf.lag_times(),
+                                vacf.sample_sizes(),
+                                vacf.result().reshape([-1, 1]))))
 
     system.auto_update_accumulators.remove(avacf)
     avacf.finalize()
-    np.savetxt("{}/avacf_{}_{}.dat".format(outdir, vel, run), avacf.result())
+    np.savetxt("{}/avacf_{}_{}.dat".format(outdir, vel, run),
+               np.column_stack((avacf.lag_times(),
+                                avacf.sample_sizes(),
+                                avacf.result().reshape([-1, 1]))))

samples/diffusion_coefficient.py

@@ -55,27 +55,30 @@
 c_pos.finalize()
 c_vel.finalize()
 
-np.savetxt("msd.dat", c_pos.result())
-np.savetxt("vacf.dat", c_vel.result())
+msd = np.column_stack((c_pos.lag_times(),
+                       c_pos.sample_sizes(),
+                       c_pos.result().reshape([-1, 3])))
+vacf = np.column_stack((c_vel.lag_times(),
+                        c_vel.sample_sizes(),
+                        c_vel.result().reshape([-1, 1])))
+np.savetxt("msd.dat", msd)
+np.savetxt("vacf.dat", vacf)
 
 # Integral of vacf via Green-Kubo
 # D= 1/3 int_0^infty <v(t_0)v(t_0+t)> dt
 
-vacf = c_vel.result()
 # Integrate with trapezoidal rule
 I = np.trapz(vacf[:, 2], vacf[:, 0])
 ratio = 1. / 3. * I / (kT / gamma)
 print("Ratio of measured and expected diffusion coefficients from Green-Kubo:",
       ratio)
 
-# Check MSD
-msd = c_pos.result()
-
 
 def expected_msd(x):
     return 2. * kT / gamma * x
 
 
+# Check MSD
 print("Ratio of expected and measured msd")
 print("#time ratio_x ratio_y ratio_z")
 for i in range(4, msd.shape[0], 4):

samples/observables_correlators.py

@@ -69,6 +69,10 @@
 
 # Finalize the correlation calculation and write the results to a file
 c.finalize()
-np.savetxt("res.dat", c.result())
+np.savetxt("res.dat", np.column_stack((c.lag_times(),
+                                       c.sample_sizes(),
+                                       c.result().reshape([-1, 3]))))
 fcs.finalize()
-np.savetxt("fcs.dat", fcs.result())
+np.savetxt("fcs.dat", np.column_stack((fcs.lag_times(),
+                                       fcs.sample_sizes(),
+                                       fcs.result().reshape([-1, 1]))))

src/core/accumulators/AccumulatorBase.hpp

@@ -19,6 +19,9 @@
 #ifndef CORE_ACCUMULATORS_ACCUMULATORBASE
 #define CORE_ACCUMULATORS_ACCUMULATORBASE
 
+#include <cstddef>
+#include <vector>
+
 namespace Accumulators {
 
 class AccumulatorBase {
@@ -28,6 +31,8 @@ class AccumulatorBase {
   virtual ~AccumulatorBase() = default;
 
   virtual void update() = 0;
+  /** Dimensions needed to reshape the flat array returned by the accumulator */
+  virtual std::vector<size_t> shape() const = 0;
 
 private:
   // Number of timesteps between automatic updates.