diff --git a/examples/03_pcac_example.ipynb b/examples/03_pcac_example.ipynb index 595a1be5..c5b5aecb 100644 --- a/examples/03_pcac_example.ipynb +++ b/examples/03_pcac_example.ipynb @@ -32,27 +32,46 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We can load data from preprocessed pickle files which contain a list of `pyerror` `Obs`:" + "We can load data from preprocessed files which contains lists of `pyerror` `Obs` and convert them to `Corr` objects. We use the parameters `padding_front` and `padding_back` to keep track of the fixed boundary conditions at both temporal ends of the lattice." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data has been written using pyerrors 2.0.0.\n", + "Format version 0.1\n", + "Written by fjosw on 2022-01-06 11:27:27 +0100 on host XPS139305, Linux-5.11.0-44-generic-x86_64-with-glibc2.29\n", + "\n", + "Description: SF correlation function f_A on a test ensemble\n", + "Data has been written using pyerrors 2.0.0.\n", + "Format version 0.1\n", + "Written by fjosw on 2022-01-06 11:27:34 +0100 on host XPS139305, Linux-5.11.0-44-generic-x86_64-with-glibc2.29\n", + "\n", + "Description: SF correlation function f_P on a test ensemble\n" + ] + } + ], "source": [ "p_obs_names = [r'f_A', r'f_P']\n", "\n", "p_obs = {}\n", "for i, item in enumerate(p_obs_names):\n", - " p_obs[item] = pe.load_object('./data/B1k2_' + item + '.p') " + " tmp_data = pe.input.json.load_json(\"./data/\" + item)\n", + " p_obs[item] = pe.Corr(tmp_data, padding_front=1, padding_back=1)\n", + " p_obs[item].tag = item" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We can now use the `pyerrors` function `plot_corrs` to have a quick look at the data we just read in " + "We can now use the method `Corr.show` to have a quick look at the data we just read in " ] }, { @@ -62,7 +81,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -74,23 +93,21 @@ } ], "source": [ - "pe.plot_corrs([p_obs['f_A'], p_obs['f_P']])" + "p_obs['f_A'].show(comp=p_obs['f_P'], y_range=[-0.8, 8])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Secondary observables" + "## Constructing the PCAC mass" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "One way of generating secondary observables is to write the desired math operations as for standard floats. `pyerrors` currently supports the basic arithmetic operations as well as numpy's basic trigonometric functions.\n", - "\n", - "We start by looking at the unimproved pcac mass $am=\\tilde{\\partial}_0 f_\\mathrm{A}/2 f_\\mathrm{P}$" + "For the PCAC mass we now need to obtain the first derivative of f_A and the second derivative of f_P" ] }, { @@ -99,16 +116,8 @@ "metadata": {}, "outputs": [], "source": [ - "uimpr_mass = []\n", - "for i in range(1, len(p_obs['f_A']) - 1):\n", - " uimpr_mass.append((p_obs['f_A'][i + 1] - p_obs['f_A'][i - 1]) / 2 / (2 * p_obs['f_P'][i]))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For more complicated secondary obsevables or secondary observables we use over and over again it is often useful to define a dedicated function for it. Here is an example for the improved pcac mass" + "first_deriv_fA = p_obs['f_A'].deriv()\n", + "first_deriv_fA.tag = r\"First derivative of f_A\"" ] }, { @@ -117,15 +126,15 @@ "metadata": {}, "outputs": [], "source": [ - "def pcac_mass(data, ca=0, **kwargs):\n", - " return ((data[1] - data[0]) / 2. + ca * (data[2] - 2 * data[3] + data[4])) / 2. / data[3]" + "second_deriv_fP = p_obs['f_P'].second_deriv()\n", + "second_deriv_fP.tag = r\"Second derivative of f_P\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Now we can construct the derived observable `pcac_mass` from the primary ones. Note the additional argument `ca` with which we can provide a value for the $\\mathrm{O}(a)$ improvement coefficient of the axial vector current." + "We can use these to obtain the unimproved PCAC mass:" ] }, { @@ -134,17 +143,15 @@ "metadata": {}, "outputs": [], "source": [ - "impr_mass = []\n", - "for i in range(1, len(p_obs['f_A']) - 1):\n", - " impr_mass.append(pcac_mass([p_obs['f_A'][i - 1], p_obs['f_A'][i + 1], p_obs['f_P'][i - 1],\n", - " p_obs['f_P'][i], p_obs['f_P'][i + 1]], ca=-0.03888694628624465))" + "am_pcac = first_deriv_fA / 2 / p_obs['f_P']\n", + "am_pcac.tag = \"Unimproved PCAC mass\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "To calculate the error of an observable we use the `gamma_method`. Let us have a look at the docstring" + "And with the inclusion of the improvement coefficient $c_\\mathrm{A}$ also the $\\mathrm{O}(a)$ improved PCAC mass:" ] }, { @@ -153,42 +160,26 @@ "metadata": {}, "outputs": [], "source": [ - "?pe.Obs.gamma_method" + "cA = -0.03888694628624465\n", + "am_pcac_impr = (first_deriv_fA + cA * second_deriv_fP) / 2 / p_obs['f_P']\n", + "am_pcac_impr.tag = \"Improved PCAC mass\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We can apply the `gamma_method` to the pcac mass on every time slice for both the unimproved and the improved mass." + "We can take a look at the time dependence of the PCAC mass with the method `Corr.show`:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, - "outputs": [], - "source": [ - "masses = [uimpr_mass, impr_mass]\n", - "for i, item in enumerate(masses):\n", - " [o.gamma_method() for o in item]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can now have a look at the result by plotting the two lists of `Obs`" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -200,109 +191,64 @@ } ], "source": [ - "pe.plot_corrs([impr_mass, uimpr_mass], xrange=[0.5, 18.5], label=['Improved pcac mass', 'Unimproved pcac mass'])" + "am_pcac_impr.show(comp=am_pcac)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Tertiary observables" + "## Plateau values" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We can now construct a plateau as (tertiary) derived observable from the masses. At this point the distinction between primary and secondary observables becomes blurred. We can again and again resample objects into new observables which allows us to modulize the analysis. Note that `np.mean` and similar functions can be applied to the `Obs` as if they were real numbers." + "We can now construct a plateau as a derived observable from the masses." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fit with 1 parameters\n", + "Method: Levenberg-Marquardt\n", + "`ftol` termination condition is satisfied.\n", + "chisquare/d.o.f.: 0.2704765091136813\n", + "Result\t 5.03431904e-03 +/- 5.38835422e-04 +/- 8.24919899e-05 (10.703%)\n", + " t_int\t 5.15384615e-01 +/- 1.25000000e-01 S = 3.00\n", + "64 samples in 1 ensemble:\n", + " · Ensemble 'test_ensemble' : 64 configurations (from 1 to 64)\n" + ] + } + ], + "source": [ + "pcac_plateau = am_pcac_impr.plateau([7, 16]) # We manually specify the plateau range here\n", + "pcac_plateau.gamma_method()\n", + "pcac_plateau.details()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can now plot the data with the two plateaus" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Result\t 4.79208242e-03 +/- 2.09091228e-04 +/- 1.90500140e-05 (4.363%)\n", - " t_int\t 1.09826949e+00 +/- 1.84087104e-01 S = 2.00\n" - ] - } - ], - "source": [ - "pcac_plateau = np.mean(impr_mass[6:15])\n", - "pcac_plateau.gamma_method()\n", - "pcac_plateau.print()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can also use a weighted average with given `plateau_range` (passed to the function as kwarg)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "def weighted_plateau(data, **kwargs):\n", - " if 'plateau_range' in kwargs:\n", - " plateau_range = kwargs.get('plateau_range')\n", - " else:\n", - " raise Exception('No range given.')\n", - " \n", - " num = 0\n", - " den = 0\n", - " for i in range(plateau_range[0], plateau_range[1]):\n", - " if data[i].dvalue == 0.0:\n", - " raise Exception('Run gamma_method for input first')\n", - " num += 1 / data[i].dvalue * data[i]\n", - " den += 1 / data[i].dvalue\n", - " return num / den" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Result\t 4.78698515e-03 +/- 2.04149923e-04 +/- 1.85998184e-05 (4.265%)\n", - " t_int\t 1.06605715e+00 +/- 1.79069383e-01 S = 2.00\n" - ] - } - ], - "source": [ - "w_pcac_plateau = weighted_plateau(impr_mass, plateau_range=[6, 15])\n", - "w_pcac_plateau.gamma_method()\n", - "w_pcac_plateau.print()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this case the two variants of the plateau are almost identical\n", - "\n", - "We can now plot the data with the two plateaus" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -314,8 +260,7 @@ } ], "source": [ - "pe.plot_corrs([impr_mass, uimpr_mass], plateau=[pcac_plateau, w_pcac_plateau], xrange=[0.5, 18.5],\n", - " label=['Improved pcac mass', 'Unimproved pcac mass'])" + "am_pcac_impr.show(comp=am_pcac, plateau=pcac_plateau)" ] }, { @@ -334,22 +279,24 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Result\t 4.79208242e-03 +/- 2.02509166e-04 +/- 2.05063968e-05 (4.226%)\n", - " t_int\t 1.03021214e+00 +/- 1.94552148e-01 S = 3.00\n" + "Result\t 5.03431904e-03 +/- 5.38835422e-04 +/- 8.24919899e-05 (10.703%)\n", + " t_int\t 5.15384615e-01 +/- 1.25000000e-01 S = 3.00\n", + "64 samples in 1 ensemble:\n", + " · Ensemble 'test_ensemble' : 64 configurations (from 1 to 64)\n" ] } ], "source": [ "pe.Obs.S_global = 3.0\n", "pcac_plateau.gamma_method()\n", - "pcac_plateau.print()" + "pcac_plateau.details()" ] }, { @@ -361,70 +308,23 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Result\t 4.79208242e-03 +/- 2.04669865e-04 +/- 1.97135904e-05 (4.271%)\n", - " t_int\t 1.05231340e+00 +/- 1.88061498e-01 S = 2.50\n" + "Result\t 5.03431904e-03 +/- 5.38835422e-04 +/- 8.24919899e-05 (10.703%)\n", + " t_int\t 5.15384615e-01 +/- 1.25000000e-01 S = 2.50\n", + "64 samples in 1 ensemble:\n", + " · Ensemble 'test_ensemble' : 64 configurations (from 1 to 64)\n" ] } ], "source": [ "pcac_plateau.gamma_method(S=2.5)\n", - "pcac_plateau.print()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can have a look at the respective normalized autocorrelation function (rho) and the integrated autocorrelation time" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pcac_plateau.plot_rho()\n", - "pcac_plateau.plot_tauint()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Critical slowing down" + "pcac_plateau.details()" ] }, { @@ -436,90 +336,23 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Result\t 4.79208242e-03 +/- 2.28649024e-04 +/- 1.67571716e-05 (4.771%)\n", - " t_int\t 1.31333644e+00 +/- 5.19554793e-01 tau_exp = 10.00, N_sigma = 1\n" + "Result\t 5.03431904e-03 +/- 7.82447810e-04 +/- 1.19787368e-04 (15.542%)\n", + " t_int\t 1.08675071e+00 +/- 1.63643098e+00 tau_exp = 10.00, N_sigma = 1\n", + "64 samples in 1 ensemble:\n", + " · Ensemble 'test_ensemble' : 64 configurations (from 1 to 64)\n" ] } ], "source": [ - "pcac_plateau.gamma_method(tau_exp=10, N_sigma=1)\n", - "pcac_plateau.print()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The attached tail, which takes into account long range autocorrelations, is shown in the plots for rho and tauint" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pcac_plateau.plot_rho()\n", - "pcac_plateau.plot_tauint()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Additional information on the ensembles and replicas can be printed with print level 2 (In this case there is only one ensemble with one replicum.)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Result\t 4.79208242e-03 +/- 2.28649024e-04 +/- 1.67571716e-05 (4.771%)\n", - " t_int\t 1.31333644e+00 +/- 5.19554793e-01 tau_exp = 10.00, N_sigma = 1\n", - "1024 samples in 1 ensembles:\n", - " : ['B1k2r2']\n" - ] - } - ], - "source": [ - "pcac_plateau.print(2)" + "pcac_plateau.gamma_method(tau_exp=10)\n", + "pcac_plateau.details()" ] }, { @@ -531,12 +364,12 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -560,11 +393,11 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ - "pcac_plateau.dump('B1k2_pcac_plateau')" + "pe.input.json.dump_to_json(pcac_plateau, \"pcac_plateau_test_ensemble\")" ] }, { @@ -577,7 +410,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -591,7 +424,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.8.10" } }, "nbformat": 4, diff --git a/examples/data/B1k2_f_A.p b/examples/data/B1k2_f_A.p deleted file mode 100644 index 48c52af6..00000000 Binary files a/examples/data/B1k2_f_A.p and /dev/null differ diff --git a/examples/data/B1k2_f_P.p b/examples/data/B1k2_f_P.p deleted file mode 100644 index 748b6b30..00000000 Binary files a/examples/data/B1k2_f_P.p and /dev/null differ diff --git a/examples/data/f_A.json.gz b/examples/data/f_A.json.gz new file mode 100644 index 00000000..be30ce31 Binary files /dev/null and b/examples/data/f_A.json.gz differ diff --git a/examples/data/f_P.json.gz b/examples/data/f_P.json.gz new file mode 100644 index 00000000..60f31ad0 Binary files /dev/null and b/examples/data/f_P.json.gz differ