diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 51aed389..416d4a26 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -134,6 +134,11 @@ jobs: source cosmosis-configure make + - name: Install likelihood python dependencies from pip + shell: bash -l {0} + run: | + pip install "act_dr6_lenslike>=1.0.2" + - name: Run Tests shell: bash -l {0} run: | @@ -229,6 +234,10 @@ jobs: pip install -v --no-cache-dir --no-binary=mpi4py,camb mpi4py camb pip install fitsio astropy fast-pt "Cython<3.0" jupyter + - name: Install likelihood python dependencies + run: | + pip install "act_dr6_lenslike>=1.0.2" + - name: Build run: | source .github/ci-setup.sh && make diff --git a/boltzmann/camb/camb_interface.py b/boltzmann/camb/camb_interface.py index 83fec043..6b24e0dc 100644 --- a/boltzmann/camb/camb_interface.py +++ b/boltzmann/camb/camb_interface.py @@ -72,6 +72,22 @@ def get_choice(options, name, valid, default=None, prefix=''): raise ValueError("Parameter setting '{}' in camb must be one of: {}. You tried: {}".format(name, valid, choice)) return prefix + choice + +def make_z_for_pk(more_config): + if "zmid" in more_config: + z = np.concatenate((np.linspace(more_config['zmin'], + more_config['zmid'], + more_config['nz_mid'], + endpoint=False), + np.linspace(more_config['zmid'], + more_config['zmax'], + more_config['nz']-more_config['nz_mid'])))[::-1] + else: + z = np.linspace(more_config['zmin'], more_config['zmax'], more_config["nz"])[::-1] + + return z + + def setup(options): mode = options.get_string(opt, 'mode', default="all") if not mode in MODES: @@ -162,7 +178,8 @@ def setup(options): more_config["transfer_params"]["kmax"] = options.get_double(opt, "kmax", default=10.0) # more_config["transfer_params"]["high_precision"] = options.get_bool(opt, "high_precision", default=True) - more_config['kmin'] = options.get_double(opt, "kmin", default=1e-5) + if options.has_value(opt, "kmin"): + warnings.warn("Option kmin does not have an effect.") more_config['kmax'] = options.get_double(opt, "kmax", more_config["transfer_params"]["kmax"]) more_config['kmax_extrapolate'] = options.get_double(opt, "kmax_extrapolate", default=more_config['kmax']) more_config['nk'] = options.get_int(opt, "nk", default=200) @@ -400,17 +417,7 @@ def extract_camb_params(block, config, more_config): p.set_accuracy(**more_config["accuracy_params"]) if want_perturbations: - if "zmid" in more_config: - z = np.concatenate((np.linspace(more_config['zmin'], - more_config['zmid'], - more_config['nz_mid'], - endpoint=False), - np.linspace(more_config['zmid'], - more_config['zmax'], - more_config['nz']-more_config['nz_mid'])))[::-1] - else: - z = np.linspace(more_config['zmin'], more_config['zmax'], more_config["nz"])[::-1] - + z = make_z_for_pk(more_config) p.set_matter_power(redshifts=z, nonlinear=config["NonLinear"] in ["NonLinear_both", "NonLinear_pk"], **more_config["transfer_params"]) return p @@ -530,8 +537,7 @@ def save_matter_power(r, block, more_config): # and the max one extrapolated out too. We output to the larger # of these kmax_power = max(more_config['kmax'], more_config['kmax_extrapolate']) - k = np.logspace(np.log10(more_config['kmin']), np.log10(kmax_power), more_config['nk']) - z = np.linspace(more_config['zmin'], more_config['zmax'], more_config['nz']) + z = make_z_for_pk(more_config)[::-1] P_tot = None @@ -547,6 +553,8 @@ def save_matter_power(r, block, more_config): extrap_kmax=more_config['kmax_extrapolate'] ) assert P.islog + k = np.logspace(np.log10(kcalc[0]), np.log10(kmax_power), more_config['nk']) + # P.P evaluates at k instead of logk p_k = P.P(z, k, grid=True) diff --git a/examples/bacco-values.ini b/examples/bacco-values.ini new file mode 100644 index 00000000..f9e82e5a --- /dev/null +++ b/examples/bacco-values.ini @@ -0,0 +1,24 @@ +[cosmological_parameters] +omega_m = 0.3 +h0 = 0.7 +omega_b = 0.048 +n_s = 0.97 +A_s = 2.19e-9 +w = -1.0 +wa = 0.0 +; New parametrization and names: +mnu = 0.0773 +num_massive_neutrinos = 3 +nnu = 3.046 + +omega_k = 0.0 +tau = 0.0697186 + +[baryon_parameters] +M_c = 9.0 14.0 15.0 +eta = -0.698 -0.3 0.698 +beta = -1.0 -0.22 0.698 +M1_z0_cen= 9.0 10.5 13.0 +theta_out= 0.0 0.25 0.477 +theta_inn = -2.0 -0.86 -0.522 +M_inn = 9.0 13.4 13.5 diff --git a/examples/bacco.ini b/examples/bacco.ini new file mode 100644 index 00000000..f3a74dae --- /dev/null +++ b/examples/bacco.ini @@ -0,0 +1,54 @@ +[runtime] +sampler = test +verbosity = debug + +[apriori] +nsample = 100 + +[output] +filename = output/bacco.txt + +[pipeline] +modules = consistency bbn_consistency camb extrapolate bacco_emulator + +timing=F +debug=F + +values = examples/bacco-values.ini +extra_output = + +[test] +save_dir=output/bacco +fatal_errors=T + +[consistency] +file = utility/consistency/consistency_interface.py + +[bbn_consistency] +file = utility/bbn_consistency/bbn_consistency.py + +[camb] +file = boltzmann/camb/camb_interface.py +mode = power +lmax = 2500 ;max ell to use for cmb calculation +feedback=0 ;amount of output to print +AccuracyBoost=1.1 ;CAMB accuracy boost parameter +do_tensors = T +do_lensing = T +NonLinear = none +zmin_background = 0. +zmax_background = 4. +nz_background = 401 +kmin=1e-4 +kmax = 50.0 +kmax_extrapolate = 500.0 +nk=700 +nz = 150 + +[extrapolate] +file = boltzmann/extrapolate/extrapolate_power.py +kmax = 500. + +[bacco_emulator] +file = structure/baccoemu/baccoemu_interface.py +mode = nonlinear diff --git a/examples/des-campaign.yml b/examples/des-campaign.yml index 79afc0a4..ef4fb03e 100644 --- a/examples/des-campaign.yml +++ b/examples/des-campaign.yml @@ -23,6 +23,35 @@ runs: params: - sampler = test + - name: bacco-nl + parent: fiducial + params: + - bacco.file = structure/baccoemu/baccoemu_interface.py + - bacco.mode = nonlinear + - camb.nonlinear = none + pipeline: + - after camb bacco + + - name: bacco-baryons + parent: fiducial + components: + - bacco_baryon_params + params: + - bacco.file = structure/baccoemu/baccoemu_interface.py + - bacco.mode = baryons + pipeline: + - after camb bacco + + - name: bacco-nl-baryons + parent: fiducial + components: + - bacco_baryon_params + params: + - bacco.file = structure/baccoemu/baccoemu_interface.py + - bacco.mode = nonlinear+baryons + pipeline: + - after camb bacco + # This run is based on the fiducial run above, with # additional changes applied to it on top of the ones above - name: class @@ -120,6 +149,15 @@ runs: # These components can be re-used in multiple runs above. components: + bacco_baryon_params: + values: + - baryon_parameters.M_c = 9.0 14.0 15.0 + - baryon_parameters.eta = -0.698 -0.3 0.698 + - baryon_parameters.beta = -1.0 -0.22 0.698 + - baryon_parameters.M1_z0_cen= 9.0 10.5 13.0 + - baryon_parameters.theta_out= 0.0 0.25 0.477 + - baryon_parameters.theta_inn = -2.0 -0.86 -0.522 + - baryon_parameters.M_inn = 9.0 13.4 13.5 maglim_cuts: params: - 2pt_like.angle_range_xip_1_1 = 2.475 999.0 diff --git a/examples/example.ipynb b/examples/example.ipynb index 20ec4421..53b80221 100644 --- a/examples/example.ipynb +++ b/examples/example.ipynb @@ -158,45 +158,13 @@ "* Running sampler 1/1: emcee\n", "* Running in serial mode.\n", "* Saving output -> output/pantheon.txt\n", - "* Note: You set resume=T but the file output/pantheon.txt does not exist so I will start a new one\n", + "* Note: You set resume=T so I will resume from file output/pantheon.txt\n", "****************************************************\n", "Generating starting positions in small ball around starting point\n", - "Begun sampling\n", - "Using likelihooods from first run:\n", - " - pantheon\n", - " - riess21\n", - "Done 10 iterations of emcee. Acceptance fraction 0.684\n", - "Done 20 iterations of emcee. Acceptance fraction 0.677\n", - "Done 30 iterations of emcee. Acceptance fraction 0.662\n", - "Done 40 iterations of emcee. Acceptance fraction 0.645\n", - "Done 50 iterations of emcee. Acceptance fraction 0.640\n", - "Done 60 iterations of emcee. Acceptance fraction 0.630\n", - "Done 70 iterations of emcee. Acceptance fraction 0.622\n", - "Done 80 iterations of emcee. Acceptance fraction 0.616\n", - "Done 90 iterations of emcee. Acceptance fraction 0.608\n", - "Done 100 iterations of emcee. Acceptance fraction 0.605\n", - "Done 110 iterations of emcee. Acceptance fraction 0.604\n", - "Done 120 iterations of emcee. Acceptance fraction 0.600\n", - "Done 130 iterations of emcee. Acceptance fraction 0.598\n", - "Done 140 iterations of emcee. Acceptance fraction 0.599\n", - "Done 150 iterations of emcee. Acceptance fraction 0.598\n", - "Done 160 iterations of emcee. Acceptance fraction 0.600\n", - "Done 170 iterations of emcee. Acceptance fraction 0.601\n", - "Done 180 iterations of emcee. Acceptance fraction 0.602\n", - "Done 190 iterations of emcee. Acceptance fraction 0.601\n", - "Done 200 iterations of emcee. Acceptance fraction 0.597\n", - "Done 210 iterations of emcee. Acceptance fraction 0.595\n", - "Done 220 iterations of emcee. Acceptance fraction 0.593\n", - "Done 230 iterations of emcee. Acceptance fraction 0.592\n", - "Done 240 iterations of emcee. Acceptance fraction 0.591\n", - "Done 250 iterations of emcee. Acceptance fraction 0.589\n", - "Done 260 iterations of emcee. Acceptance fraction 0.590\n", - "Done 270 iterations of emcee. Acceptance fraction 0.588\n", - "Done 280 iterations of emcee. Acceptance fraction 0.589\n", - "Done 290 iterations of emcee. Acceptance fraction 0.587\n", - "Done 300 iterations of emcee. Acceptance fraction 0.585\n", - "Total posterior evaluations = 8550 across all processes\n", - "Successful posterior evaluations = 8550 across all processes\n" + "You told me to resume the chain - it has already completed (with 9600 samples), so sampling will end.\n", + "Increase the 'samples' parameter to keep going.\n", + "Total posterior evaluations = 0 across all processes\n", + "Successful posterior evaluations = 0 across all processes\n" ] }, { @@ -300,38 +268,38 @@ "Using likelihooods from first run:\n", " - pantheon\n", " - riess21\n", - "Done 10 iterations of emcee. Acceptance fraction 0.728\n", - "Done 20 iterations of emcee. Acceptance fraction 0.700\n", - "Done 30 iterations of emcee. Acceptance fraction 0.671\n", - "Done 40 iterations of emcee. Acceptance fraction 0.659\n", - "Done 50 iterations of emcee. Acceptance fraction 0.641\n", - "Done 60 iterations of emcee. Acceptance fraction 0.630\n", - "Done 70 iterations of emcee. Acceptance fraction 0.621\n", - "Done 80 iterations of emcee. Acceptance fraction 0.621\n", - "Done 90 iterations of emcee. Acceptance fraction 0.612\n", - "Done 100 iterations of emcee. Acceptance fraction 0.608\n", - "Done 110 iterations of emcee. Acceptance fraction 0.602\n", - "Done 120 iterations of emcee. Acceptance fraction 0.601\n", - "Done 130 iterations of emcee. Acceptance fraction 0.596\n", - "Done 140 iterations of emcee. Acceptance fraction 0.593\n", - "Done 150 iterations of emcee. Acceptance fraction 0.593\n", - "Done 160 iterations of emcee. Acceptance fraction 0.591\n", - "Done 170 iterations of emcee. Acceptance fraction 0.592\n", - "Done 180 iterations of emcee. Acceptance fraction 0.590\n", - "Done 190 iterations of emcee. Acceptance fraction 0.588\n", - "Done 200 iterations of emcee. Acceptance fraction 0.587\n", - "Done 210 iterations of emcee. Acceptance fraction 0.584\n", - "Done 220 iterations of emcee. Acceptance fraction 0.585\n", - "Done 230 iterations of emcee. Acceptance fraction 0.583\n", - "Done 240 iterations of emcee. Acceptance fraction 0.584\n", - "Done 250 iterations of emcee. Acceptance fraction 0.585\n", - "Done 260 iterations of emcee. Acceptance fraction 0.586\n", - "Done 270 iterations of emcee. Acceptance fraction 0.587\n", - "Done 280 iterations of emcee. Acceptance fraction 0.587\n", - "Done 290 iterations of emcee. Acceptance fraction 0.586\n", - "Done 300 iterations of emcee. Acceptance fraction 0.583\n", - "Total posterior evaluations = 8557 across all processes\n", - "Successful posterior evaluations = 8557 across all processes\n" + "Done 10 iterations of emcee. Acceptance fraction 0.684\n", + "Done 20 iterations of emcee. Acceptance fraction 0.672\n", + "Done 30 iterations of emcee. Acceptance fraction 0.655\n", + "Done 40 iterations of emcee. Acceptance fraction 0.639\n", + "Done 50 iterations of emcee. Acceptance fraction 0.630\n", + "Done 60 iterations of emcee. Acceptance fraction 0.618\n", + "Done 70 iterations of emcee. Acceptance fraction 0.609\n", + "Done 80 iterations of emcee. Acceptance fraction 0.595\n", + "Done 90 iterations of emcee. Acceptance fraction 0.601\n", + "Done 100 iterations of emcee. Acceptance fraction 0.595\n", + "Done 110 iterations of emcee. Acceptance fraction 0.593\n", + "Done 120 iterations of emcee. Acceptance fraction 0.589\n", + "Done 130 iterations of emcee. Acceptance fraction 0.587\n", + "Done 140 iterations of emcee. Acceptance fraction 0.587\n", + "Done 150 iterations of emcee. Acceptance fraction 0.584\n", + "Done 160 iterations of emcee. Acceptance fraction 0.583\n", + "Done 170 iterations of emcee. Acceptance fraction 0.584\n", + "Done 180 iterations of emcee. Acceptance fraction 0.584\n", + "Done 190 iterations of emcee. Acceptance fraction 0.584\n", + "Done 200 iterations of emcee. Acceptance fraction 0.584\n", + "Done 210 iterations of emcee. Acceptance fraction 0.583\n", + "Done 220 iterations of emcee. Acceptance fraction 0.584\n", + "Done 230 iterations of emcee. Acceptance fraction 0.586\n", + "Done 240 iterations of emcee. Acceptance fraction 0.587\n", + "Done 250 iterations of emcee. Acceptance fraction 0.587\n", + "Done 260 iterations of emcee. Acceptance fraction 0.587\n", + "Done 270 iterations of emcee. Acceptance fraction 0.586\n", + "Done 280 iterations of emcee. Acceptance fraction 0.586\n", + "Done 290 iterations of emcee. Acceptance fraction 0.587\n", + "Done 300 iterations of emcee. Acceptance fraction 0.585\n", + "Total posterior evaluations = 8534 across all processes\n", + "Successful posterior evaluations = 8534 across all processes\n" ] } ], @@ -359,36 +327,36 @@ "data": { "text/html": [ "
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", 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" ] @@ -546,12 +514,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "[cosmological_parameters]\r\n", - "omega_m = 0.15 0.3 0.4\r\n", - "h0 = 0.6 0.7 0.8\r\n", - "w = -1.0\r\n", - "omega_b = 0.04\r\n", - "omega_k = -0.3 0.0 0.3\r\n" + "[cosmological_parameters]\n", + "omega_m = 0.15 0.3 0.4\n", + "h0 = 0.6 0.7 0.8\n", + "w = -1.0\n", + "omega_b = 0.04\n", + "omega_k = -0.3 0.0 0.3\n" ] } ], @@ -725,8 +693,8 @@ "Using likelihooods from first run:\n", " - pantheon\n", " - riess21\n", - "Total posterior evaluations = 43400 across all processes\n", - "Successful posterior evaluations = 43400 across all processes\n" + "Total posterior evaluations = 43600 across all processes\n", + "Successful posterior evaluations = 43600 across all processes\n" ] } ], @@ -752,7 +720,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "
\n", + "
\n", " name dtype \n", "-------------------------------- -------\n", "cosmological_parameters--omega_m float64\n", @@ -787,7 +755,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 14, @@ -796,7 +764,7 @@ }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -939,9 +907,31 @@ "****************************************************\n", "Using likelihooods from first run:\n", " - pantheon\n", - " - riess21\n", - "Total posterior evaluations = 49400 across all processes\n", - "Successful posterior evaluations = 49400 across all processes\n" + " - riess21\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/jzuntz/src/cosmosis/cosmosis-standard-library/background/astropy_background/astropy_background.py:110: RuntimeWarning: invalid value encountered in log10\n", + " mu[1:] = 5.0 * np.log10(D_L[1:]) + 25.0\n", + "/Users/jzuntz/src/cosmosis/env/lib/python3.11/site-packages/astropy/cosmology/flrw/base.py:1132: IntegrationWarning: The occurrence of roundoff error is detected, which prevents \n", + " the requested tolerance from being achieved. The error may be \n", + " underestimated.\n", + " return quad(self._inv_efunc_scalar, z1, z2, args=self._inv_efunc_scalar_args)[0]\n", + "/Users/jzuntz/src/cosmosis/env/lib/python3.11/site-packages/numpy/lib/function_base.py:2412: RuntimeWarning: invalid value encountered in _integral_comoving_distance_z1z2_scalar (vectorized)\n", + " outputs = ufunc(*inputs)\n", + "/Users/jzuntz/src/cosmosis/env/lib/python3.11/site-packages/astropy/cosmology/flrw/w0cdm.py:205: RuntimeWarning: invalid value encountered in sqrt\n", + " return sqrt(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total posterior evaluations = 49600 across all processes\n", + "Successful posterior evaluations = 49600 across all processes\n" ] } ], @@ -966,7 +956,7 @@ "outputs": [ { "data": { - "image/png": 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kSZO0e/fuLrfJyMjQAw88oK1btyozM1M1NTV68cUXdeONN571c5qbmzssfq6vr/e7dgAA0HP5fIfi//qv/9LYsWOVkJCgzz77TNLpmZdXXnmlW9sfOXJEbW1tio+P79AeHx+v6urqLrfJyMjQxo0blZWVpcjISA0ZMkSxsbF68sknz/o5+fn5crvdnhdPLQcAwGw+hZtVq1YpNzdXkydP1vHjxz1rbGJjY72+wd8/3un4zLqdruzfv19z5szRgw8+qL179+rVV1/VoUOHNGvWrLPuPy8vT3V1dZ5XRUWFV/UBAIDw4lO4efLJJ/XMM8/ogQceUEREhKd9zJgx+uCDD7q1j0GDBikiIqLTLE1NTU2n2Zwz8vPzNXbsWC1YsEDf+MY3dP3116uwsFDr169XVVVVl9u4XC7FxMR0eAEAAHP5FG4OHTqk0aNHd2p3uVxqbGzs1j4iIyOVlpamkpKSDu0lJSXKyMjocpsvv/xSvXp1LPlMuLIsq1ufCwAAzOZTuElOTlZZWVmn9t/+9rf6p3/6p27vJzc3V2vXrtX69et14MABzZs3T+Xl5Z7TTHl5ecrOzvb0nzJlijZv3qxVq1bp008/1VtvvaU5c+boiiuuUEJCgi9fBQAAGManq6UWLFigu+++WydPnpRlWXr33Xe1adMm5efna+3atd3eT1ZWlo4ePaolS5aoqqpKqamp2rp1q+dqrKqqKpWXl3v633bbbWpoaNDKlSs1f/58xcbGasKECfrZz37my9cAAAAGclg+ns955pln9PDDD3sW6CYmJmrRokXKyckJaIGBVl9fL7fbrbq6OtbfAEAX/lRZp28/+aZ+/eNvKTXRbXc5OI8L5f+XN7+/fZq5kaQ77rhDd9xxh44cOaL29nbFxcX5uisAAICA8WnNzYQJE3T8+HFJp696OhNs6uvrNWHChIAVBwAA4C2fws2OHTvU0tLSqf3kyZPnffAlAABAMHl1Wurvn/i9f//+DveoaWtr06uvvqrExMTAVQcAAOAlr8LNqFGj5HA45HA4ujz9FBUVdc5HIQAAAASbV+Hm0KFDsixLX/nKV/Tuu+9q8ODBnp9FRkYqLi6uwx2LAQAAQs2rcHPm/jPt7e1BKQYAAMBfPi0o/sUvfqHf/OY3nvf333+/YmNjlZGR4XlCOAAAgB18CjePPPKIoqKiJEl79uzRypUrtXTpUg0aNEjz5s0LaIEAAADe8OkmfhUVFRoxYoQkacuWLfr+97+vf//3f9fYsWN1zTXXBLI+AAAAr/g0cxMdHa2jR49Kkl577TVNnDhRktSnTx81NTUFrjoAAAAv+TRzc91112nmzJkaPXq0PvroI914442SpA8//FCXXHJJIOsDAADwik8zN0899ZTS09P1xRdf6KWXXtLAgQMlSXv37tWPfvSjgBYIAADgDZ9mbmJjY7Vy5cpO7YsXL/a7IAAAAH/4/FTw48ePa926dTpw4IAcDodSUlKUk5Mjt9vcx60DAICez6fTUqWlpbr00ku1YsUKHTt2TEeOHNGKFSt06aWX6o9//GOgawQAAOg2n2Zu5s2bp5tuuknPPPOMnM7Tuzh16pRmzpypuXPnateuXQEtEgAAoLt8CjelpaUdgo0kOZ1O3X///RozZkzAigMAAPCWT6elYmJiVF5e3qm9oqJC/fr187soAAAAX/kUbrKyspSTk6Pi4mJVVFTo888/1y9/+UvNnDmTS8EBAICtfDot9fjjj6tXr17Kzs7WqVOnJEm9e/fWXXfdpUcffTSgBQIAAHjDq3Dz5ZdfasGCBdqyZYtaW1v1ne98R/fcc4/cbrdGjBihiy66KFh1AgC6ofJ4k2obW/zax8GaEwGqBrCHV+HmoYceUlFRkaZNm6aoqCg9//zzam9v1wsvvBCs+gAA3VR5vEkTl+1UU2ub3/uK6h2h/n0jA1AVEHpehZvNmzdr3bp1+uEPfyhJmjZtmsaOHau2tjZFREQEpUAAQPfUNraoqbVNBVmjNCIu2q999e8bqcTYqABVBoSWV+GmoqJC48aN87y/4oor5HQ6dfjwYSUlJQW8OACA90bERSs1kbvF48Ll1dVSbW1tiozsOE3pdDo9i4oBAADs5tXMjWVZuu222+RyuTxtJ0+e1KxZs9S3b19P2+bNmwNXIQAAgBe8CjczZszo1Pav//qvASsGAADAX16Fmw0bNgSrDgAAgIDw6Q7FAAAAPRXhBgAAGIVwAwAAjEK4AQAARiHcAAAAoxBuAACAUQg3AADAKLaHm8LCQiUnJ6tPnz5KS0vTG2+8cc7+zc3NeuCBBzR8+HC5XC5deumlWr9+fYiqBQAAPZ1XN/ELtOLiYs2dO1eFhYUaO3as1qxZo8zMTO3fv1/Dhg3rcptbb71Vf/3rX7Vu3TqNGDFCNTU1PNsKAAB42Bpuli9frpycHM2cOVOSVFBQoG3btmnVqlXKz8/v1P/VV1/Vzp079emnn2rAgAGSpEsuuSSUJQMAgB7OttNSLS0t2rt3ryZNmtShfdKkSdq9e3eX2/z3f/+3xowZo6VLlyoxMVEjR47Ufffdp6amprN+TnNzs+rr6zu8AACAuWybuTly5Ija2toUHx/foT0+Pl7V1dVdbvPpp5/qzTffVJ8+ffTyyy/ryJEjmj17to4dO3bWdTf5+flavHhxwOsHAAA9k+0Lih0OR4f3lmV1ajujvb1dDodDGzdu1BVXXKHJkydr+fLlKioqOuvsTV5enurq6jyvioqKgH8HAADQc9g2czNo0CBFRER0mqWpqanpNJtzxtChQ5WYmCi32+1pS0lJkWVZ+vzzz/XVr3610zYul0sulyuwxQMAgB7LtpmbyMhIpaWlqaSkpEN7SUmJMjIyutxm7NixOnz4sE6cOOFp++ijj9SrVy9dfPHFQa0XAACEB1tPS+Xm5mrt2rVav369Dhw4oHnz5qm8vFyzZs2SdPqUUnZ2tqf/1KlTNXDgQN1+++3av3+/du3apQULFujf/u3fFBUVZdfXAAAAPYitl4JnZWXp6NGjWrJkiaqqqpSamqqtW7dq+PDhkqSqqiqVl5d7+kdHR6ukpEQ//vGPNWbMGA0cOFC33nqrHn74Ybu+AgAA6GFsDTeSNHv2bM2ePbvLnxUVFXVq+/rXv97pVBYAAMAZtocbALjQVR5vUm1ji9/7OVhz4vydgAsA4QYAbFR5vEkTl+1UU2tbQPYX1TtC/ftGBmRfQLgi3ACAjWobW9TU2qaCrFEaERft9/76941UYiwXWODCRrgBgB5gRFy0UhPd5+8I4Lxsv0MxAABAIBFuAACAUQg3AADAKIQbAABgFMINAAAwCuEGAAAYhXADAACMQrgBAABGIdwAAACjEG4AAIBRCDcAAMAohBsAAGAUwg0AADAK4QYAABiFcAMAAIxCuAEAAEYh3AAAAKMQbgAAgFEINwAAwCiEGwAAYBTCDQAAMArhBgAAGIVwAwAAjEK4AQAARiHcAAAAoxBuAACAUQg3AADAKIQbAABgFMINAAAwCuEGAAAYhXADAACMYnu4KSwsVHJysvr06aO0tDS98cYb3drurbfektPp1KhRo4JbIAAACCu2hpvi4mLNnTtXDzzwgPbt26dx48YpMzNT5eXl59yurq5O2dnZuvbaa0NUKQAACBdOOz98+fLlysnJ0cyZMyVJBQUF2rZtm1atWqX8/PyzbnfnnXdq6tSpioiI0JYtW0JULQB0VHm8SbWNLX7t42DNiQBVA+AM28JNS0uL9u7dq4ULF3ZonzRpknbv3n3W7TZs2KBPPvlEzz33nB5++OFglwkAXao83qSJy3aqqbXN731F9Y5Q/76RAagKgGRjuDly5Ija2toUHx/foT0+Pl7V1dVdbvPxxx9r4cKFeuONN+R0dq/05uZmNTc3e97X19f7XjQA/E1tY4uaWttUkDVKI+Ki/dpX/76RSoyNClBlAGw9LSVJDoejw3vLsjq1SVJbW5umTp2qxYsXa+TIkd3ef35+vhYvXux3nQDQlRFx0UpNdNtdBoC/Y9uC4kGDBikiIqLTLE1NTU2n2RxJamhoUGlpqe655x45nU45nU4tWbJE7733npxOp7Zv397l5+Tl5amurs7zqqioCMr3AQAAPYNtMzeRkZFKS0tTSUmJbrnlFk97SUmJbr755k79Y2Ji9MEHH3RoKyws1Pbt2/Xiiy8qOTm5y89xuVxyuVyBLR4AAPRYtp6Wys3N1fTp0zVmzBilp6fr6aefVnl5uWbNmiXp9KxLZWWlnn32WfXq1Uupqakdto+Li1OfPn06tQMAgAuXreEmKytLR48e1ZIlS1RVVaXU1FRt3bpVw4cPlyRVVVWd9543AAAAf89hWZZldxGhVF9fL7fbrbq6OsXExNhdDoAw9afKOn37yTf16x9/iwXFsNWFcix68/vb9scvAAAABBLhBgAAGIVwAwAAjEK4AQAARiHcAAAAoxBuAACAUQg3AADAKIQbAABgFMINAAAwCuEGAAAYhXADAACMQrgBAABGIdwAAACjEG4AAIBRCDcAAMAohBsAAGAUwg0AADCK0+4CACDUKo83qbaxxa99HKw5EaBqAAQa4QbABaXyeJMmLtupptY2v/cV1TtC/ftGBqAqAIFEuAFwQaltbFFTa5sKskZpRFy0X/vq3zdSibFRAaoMQKAQbgBckEbERSs10W13GQCCgAXFAADAKIQbAABgFMINAAAwCuEGAAAYhXADAACMQrgBAABGIdwAAACjEG4AAIBRCDcAAMAohBsAAGAUwg0AADAK4QYAABiFcAMAAIzCU8EBADDAwZoTfu+jf99IJcZGBaAaexFuAAAIY/37Riqqd4TmFpf5va+o3hH63fyrwz7g2B5uCgsL9dhjj6mqqkqXXXaZCgoKNG7cuC77bt68WatWrVJZWZmam5t12WWXadGiRbr++utDXDUAO1Qeb1JtY4tf+wjEv26BniQxNkq/m391QP5szC0uU21jC+HGH8XFxZo7d64KCws1duxYrVmzRpmZmdq/f7+GDRvWqf+uXbt03XXX6ZFHHlFsbKw2bNigKVOm6J133tHo0aNt+AYAQqXyeJMmLtupptY2v/cV1TtC/ftGBqAqoGdIjI0K+0ASSA7Lsiy7PvzKK6/UN7/5Ta1atcrTlpKSou985zvKz8/v1j4uu+wyZWVl6cEHH+xW//r6erndbtXV1SkmJsanugGE3p8q6/TtJ99UQdYojYiL9mtfpqwrAALpzJ+xX//4W0pNdNtdTife/P62beampaVFe/fu1cKFCzu0T5o0Sbt37+7WPtrb29XQ0KABAwactU9zc7Oam5s97+vr630rGECPMCIuukf+xQug57DtUvAjR46ora1N8fHxHdrj4+NVXV3drX0sW7ZMjY2NuvXWW8/aJz8/X2632/NKSkryq24AANCz2X6fG4fD0eG9ZVmd2rqyadMmLVq0SMXFxYqLiztrv7y8PNXV1XleFRUVftcMAAB6LttOSw0aNEgRERGdZmlqamo6zeb8o+LiYuXk5OiFF17QxIkTz9nX5XLJ5XL5XS8AAAgPts3cREZGKi0tTSUlJR3aS0pKlJGRcdbtNm3apNtuu03PP/+8brzxxmCXCQAAwoytl4Ln5uZq+vTpGjNmjNLT0/X000+rvLxcs2bNknT6lFJlZaWeffZZSaeDTXZ2tp544gldddVVnlmfqKgoud0sMAQAADaHm6ysLB09elRLlixRVVWVUlNTtXXrVg0fPlySVFVVpfLyck//NWvW6NSpU7r77rt19913e9pnzJihoqKiUJcPAAB6INvvUDx79mzNnj27y5/9Y2DZsWNH8AsCAABhzfarpQAAAAKJcAMAAIxCuAEAAEaxfc0NAPPxNG8AoUS4ARBUPM0bQKgRbgAEVW1ji5pa23iaN4CQIdwACAme5g0gVFhQDAAAjEK4AQAARiHcAAAAoxBuAACAUQg3AADAKIQbAABgFMINAAAwCuEGAAAYhXADAACMQrgBAABG4fELAM6Kp3kDCEeEGwBd4mneAMIV4QZAl3iaN4BwRbgBcE48zRtAuGFBMQAAMArhBgAAGIVwAwAAjMKaG8BAXMIN4EJGuAEMwyXcAC50hBvAMFzCDeBCR7gBDMUl3AAuVCwoBgAARmHmBuhBWAgMAP4j3AA9BAuBASAwCDdAD8FCYAAIDMINEACBPJ3EQmAA8A/hBvATp5MAoGch3AB+4nQSAPQshBsgQDidBAA9g+3hprCwUI899piqqqp02WWXqaCgQOPGjTtr/507dyo3N1cffvihEhISdP/992vWrFkhrBg9QSDWuAQKl14DQM9ia7gpLi7W3LlzVVhYqLFjx2rNmjXKzMzU/v37NWzYsE79Dx06pMmTJ+uOO+7Qc889p7feekuzZ8/W4MGD9b3vfc+GbwA7BHKNS6CwVgYAeg5bw83y5cuVk5OjmTNnSpIKCgq0bds2rVq1Svn5+Z36r169WsOGDVNBQYEkKSUlRaWlpXr88ccJN0HW02ZKArXGJVBYKwMAPYdt4aalpUV79+7VwoULO7RPmjRJu3fv7nKbPXv2aNKkSR3arr/+eq1bt06tra3q3bt3p22am5vV3NzseV9XVydJqq+v9/crdOmL+pP64kTz+TuGkWNftmruL/fpZGu73aV49OndS18f6FRCP4fdpfxNq+rrW+0uAgB8dqKhXu3NX+r9T6t0osG/35GDo10aHNMnQJWddub3tmVZ5+1rW7g5cuSI2traFB8f36E9Pj5e1dXVXW5TXV3dZf9Tp07pyJEjGjp0aKdt8vPztXjx4k7tSUlJflSPniDlMbsrAADzTCuwu4Jza2hokNt97os3bF9Q7HB0/Je3ZVmd2s7Xv6v2M/Ly8pSbm+t5397ermPHjmngwIHn/Bxf1NfXKykpSRUVFYqJiQnovvH/GOfQYJxDh7EODcY5NII1zpZlqaGhQQkJCefta1u4GTRokCIiIjrN0tTU1HSanTljyJAhXfZ3Op0aOHBgl9u4XC65XK4ObbGxsb4X3g0xMTH8wQkBxjk0GOfQYaxDg3EOjWCM8/lmbM7oFdBP9UJkZKTS0tJUUlLSob2kpEQZGRldbpOent6p/2uvvaYxY8Z0ud4GAABceGwLN5KUm5urtWvXav369Tpw4IDmzZun8vJyz31r8vLylJ2d7ek/a9YsffbZZ8rNzdWBAwe0fv16rVu3Tvfdd59dXwEAAPQwtq65ycrK0tGjR7VkyRJVVVUpNTVVW7du1fDhwyVJVVVVKi8v9/RPTk7W1q1bNW/ePD311FNKSEjQz3/+8x5zGbjL5dJDDz3U6TQYAotxDg3GOXQY69BgnEOjJ4yzw+rONVUAAABhwtbTUgAAAIFGuAEAAEYh3AAAAKMQbgAAgFEIN3666aabNGzYMPXp00dDhw7V9OnTdfjw4XNuY1mWFi1apISEBEVFRemaa67Rhx9+GKKKw89f/vIX5eTkKDk5WVFRUbr00kv10EMPqaXl3A/yvO222+RwODq8rrrqqhBVHX58HWeOZ+/99Kc/VUZGhi666KJu31SU49l7vowzx7NvamtrNX36dLndbrndbk2fPl3Hjx8/5zbBPKYJN34aP368fvWrX+l///d/9dJLL+mTTz7R97///XNus3TpUi1fvlwrV67UH/7wBw0ZMkTXXXedGhoaQlR1ePnzn/+s9vZ2rVmzRh9++KFWrFih1atX6yc/+cl5t73hhhtUVVXleW3dujUEFYcnX8eZ49l7LS0t+sEPfqC77rrLq+04nr3jyzhzPPtm6tSpKisr06uvvqpXX31VZWVlmj59+nm3C9oxbSGgXnnlFcvhcFgtLS1d/ry9vd0aMmSI9eijj3raTp48abndbmv16tWhKjPsLV261EpOTj5nnxkzZlg333xzaAoy1PnGmePZPxs2bLDcbne3+nI8+66748zx7Jv9+/dbkqy3337b07Znzx5LkvXnP//5rNsF85hm5iaAjh07po0bNyojI+Osj4M4dOiQqqurNWnSJE+by+XS1Vdfrd27d4eq1LBXV1enAQMGnLffjh07FBcXp5EjR+qOO+5QTU1NCKozx/nGmeM5tDieg4vj2Td79uyR2+3WlVde6Wm76qqr5Ha7zztuwTqmCTcB8B//8R/q27evBg4cqPLycr3yyitn7XvmwZ//+HDQ+Pj4Tg8FRdc++eQTPfnkk57HdJxNZmamNm7cqO3bt2vZsmX6wx/+oAkTJqi5uTlElYa37owzx3PocDwHH8ezb6qrqxUXF9epPS4u7pzjFsxjmnDThUWLFnVa5PSPr9LSUk//BQsWaN++fXrttdcUERGh7OxsWee58bPD4ejw3rKsTm2m83acJenw4cO64YYb9IMf/EAzZ8485/6zsrJ04403KjU1VVOmTNFvf/tbffTRR/rNb34TzK/V4wR7nCWOZ8m3cfYGx/NpwR5nieP5DG/GuqvxOd+4BfOYtvXZUj3VPffcox/+8Ifn7HPJJZd4/nvQoEEaNGiQRo4cqZSUFCUlJentt99Wenp6p+2GDBki6XTSHTp0qKe9pqam078WTOftOB8+fFjjx49Xenq6nn76aa8/b+jQoRo+fLg+/vhjr7cNZ8EcZ47n/+ftOPuL4/nsfB1njueOujvW77//vv761792+tkXX3zh1bgF8pgm3HThTFjxxZkZm7NNqyUnJ2vIkCEqKSnR6NGjJZ1e0b9z50797Gc/863gMOXNOFdWVmr8+PFKS0vThg0b1KuX95OOR48eVUVFRYe/tC4EwRxnjuf/58/fG77geA48jueOujvW6enpqqur07vvvqsrrrhCkvTOO++orq5OGRkZ3f68gB7TQVmmfIF45513rCeffNLat2+f9Ze//MXavn279a1vfcu69NJLrZMnT3r6fe1rX7M2b97sef/oo49abrfb2rx5s/XBBx9YP/rRj6yhQ4da9fX1dnyNHq+ystIaMWKENWHCBOvzzz+3qqqqPK+/9/fj3NDQYM2fP9/avXu3dejQIev111+30tPTrcTERMb5LHwZZ8viePbFZ599Zu3bt89avHixFR0dbe3bt8/at2+f1dDQ4OnD8ew/b8fZsjiefXXDDTdY3/jGN6w9e/ZYe/bssf75n//Z+va3v92hTyiPacKNH95//31r/Pjx1oABAyyXy2Vdcskl1qxZs6zPP/+8Qz9J1oYNGzzv29vbrYceesgaMmSI5XK5rH/5l3+xPvjggxBXHz42bNhgSery9ff+fpy//PJLa9KkSdbgwYOt3r17W8OGDbNmzJhhlZeX2/ANwoMv42xZHM++mDFjRpfj/Prrr3v6cDz7z9txtiyOZ18dPXrUmjZtmtWvXz+rX79+1rRp06za2toOfUJ5TDv+9oEAAABG4GopAABgFMINAAAwCuEGAAAYhXADAACMQrgBAABGIdwAAACjEG4AAIBRCDcAAMAohBsAAGAUwg2AsHPVVVdpxYoVnvdZWVlyOBxqbGyUdPrJ5pGRkTpw4IBdJQKwEeEGQNiJjY1VQ0ODJKmiokLbtm1Tv379VFtbK0l6+umnNWHCBKWkpNhZJgCbEG4AhJ3+/fvrxIkTkqSVK1dq2rRpGjx4sGpra9Xa2qqnn35a9957ryTp17/+tb72ta/pq1/9qtauXWtn2QBCxGl3AQDgrTMzN42NjVq7dq327Nmj3bt3q7a2Vi+//LL69eunG264QadOnVJubq5ef/11xcTE6Jvf/Ka++93vasCAAXZ/BQBBxMwNgLBzZubmF7/4hdLT0zVy5EjFxMSotrZWTz31lObMmSOHw6F3331Xl112mRITE9WvXz9NnjxZ27Zts7t8AEFGuAEQdmJjY1VfX68nnnhCc+fOlSTFxMTozTff1HvvvacZM2ZIOr2wODEx0bPdxRdfrMrKSjtKBhBChBsAYad///7avn27IiMjNXHiREmnw82qVauUk5Oj6OhoSZJlWZ22dTgcIa0VQOgRbgCEnTOnpc4sGpZOh5umpibdc889nrbExMQOMzWff/65hg4dGtJaAYSew+rqnzYAYIBTp04pJSVFO3bs8CwofvvttzVw4EC7SwMQRFwtBcBYTqdTy5Yt0/jx49Xe3q7777+fYANcAJi5AQAARmHNDQAAMArhBgAAGIVwAwAAjEK4AQAARiHcAAAAoxBuAACAUQg3AADAKIQbAABgFMINAAAwCuEGAAAYhXADAACMQrgBAABG+T8x0te8DuOfWAAAAABJRU5ErkJggg==", + "image/png": 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", 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", 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", 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" ] @@ -1053,7 +1043,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "ESS = 14865\n" + "ESS = 14976\n" ] } ], @@ -1074,7 +1064,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -1103,7 +1093,6 @@ "id": "8868f162", "metadata": { "heading_collapsed": true, - "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ @@ -1147,7 +1136,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Reading included ini file: `examples/des-y3-scale-cuts.ini'\n", + "Reading included ini file: examples/des-y3-scale-cuts.ini\n", "\n", "Setting up module consistency\n", "------------------------------\n", @@ -1326,7 +1315,7 @@ " - gammat 248 data points after cuts [using in likelihood]\n", " - wtheta 54 data points after cuts [using in likelihood]\n", "Total data points used = 529\n", - "Original covariance log(det): (1.0, -13340.21829668609)\n", + "Original covariance log(det): (1.0, -13340.218296686087)\n", "will get sigma_crit_inv factors from section sigma_crit_inv_lens_source\n", "using sigma_crit_inv factors to retain shear-ratio info\n", "setting up template matrix for pm-marginalization with shape: (5, 529)\n", @@ -1336,15 +1325,9 @@ "\n", "\n", "Setting up module shear_ratio_like\n", - "-----------------------------------\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "-----------------------------------\n", "9 4 3\n", - "Including -0.5*|C| normalization in shear_ratio likelihood where |C| = -65.05000501487132\n", + "Including -0.5*|C| normalization in shear_ratio likelihood where |C| = -65.0500050148713\n", "Setup all pipeline modules\n", "\n", "\n", @@ -1489,74 +1472,28 @@ "output_type": "stream", "text": [ "Om_b h^2 = 0.022853\n", - "Om_c h^2 = 0.119147\n", - "Om_nu h^2 = 0.000831\n", - "Om_darkenergy = 0.699946\n", - "Om_K = 0.000000\n", - "Om_m (inc Om_u) = 0.300002\n", - "100 theta (CosmoMC) = 1.043950\n", - "N_eff (total) = 3.046000\n", - " 3 nu, g= 3.0440 m_nu*c^2/k_B/T_nu0= 153.10 (m_nu= 0.026 eV)\n", - "Age of universe/GYr = 13.658\n", - "zstar = 1089.36\n", - "r_s(zstar)/Mpc = 144.28\n", - "100*theta = 1.044050\n", - "DA(zstar)/Gpc = 13.81899\n", - "zdrag = 1061.07\n", - "r_s(zdrag)/Mpc = 146.78\n", - "k_D(zstar) Mpc = 0.1414\n", - "100*theta_D = 0.160728\n", - "z_EQ (if v_nu=1) = 3393.12\n", - "k_EQ Mpc (if v_nu=1) = 0.010356\n", - "100*theta_EQ = 0.818631\n", - "100*theta_rs_EQ = 0.451897\n", - "tau_recomb/Mpc = 281.00 tau_now/Mpc = 14099.7\n", - "Om_b h^2 = 0.022853\n", - "Om_c h^2 = 0.119147\n", + "Om_c h^2 = 0.119146\n", "Om_nu h^2 = 0.000831\n", - "Om_darkenergy = 0.699946\n", + "Om_darkenergy = 0.699949\n", "Om_K = 0.000000\n", - "Om_m (inc Om_u) = 0.300002\n", - "100 theta (CosmoMC) = 1.043950\n", + "Om_m (inc Om_u) = 0.299999\n", + "100 theta (CosmoMC) = 1.043948\n", "N_eff (total) = 3.046000\n", " 3 nu, g= 3.0440 m_nu*c^2/k_B/T_nu0= 153.10 (m_nu= 0.026 eV)\n", "Age of universe/GYr = 13.658\n", "zstar = 1089.36\n", "r_s(zstar)/Mpc = 144.28\n", - "100*theta = 1.044050\n", - "DA(zstar)/Gpc = 13.81899\n", + "100*theta = 1.044049\n", + "DA(zstar)/Gpc = 13.81904\n", "zdrag = 1061.07\n", "r_s(zdrag)/Mpc = 146.78\n", "k_D(zstar) Mpc = 0.1414\n", - "100*theta_D = 0.160728\n", - "z_EQ (if v_nu=1) = 3393.12\n", + "100*theta_D = 0.160727\n", + "z_EQ (if v_nu=1) = 3393.09\n", "k_EQ Mpc (if v_nu=1) = 0.010356\n", - "100*theta_EQ = 0.818631\n", - "100*theta_rs_EQ = 0.451897\n", - "tau_recomb/Mpc = 281.00 tau_now/Mpc = 14099.7\n", - "Om_b h^2 = 0.022853\n", - "Om_c h^2 = 0.119147\n", - "Om_nu h^2 = 0.000831\n", - "Om_darkenergy = 0.699946\n", - "Om_K = 0.000000\n", - "Om_m (inc Om_u) = 0.300002\n", - "100 theta (CosmoMC) = 1.043950\n", - "N_eff (total) = 3.046000\n", - " 3 nu, g= 3.0440 m_nu*c^2/k_B/T_nu0= 153.10 (m_nu= 0.026 eV)\n", - "Age of universe/GYr = 13.658\n", - "zstar = 1089.36\n", - "r_s(zstar)/Mpc = 144.28\n", - "100*theta = 1.044050\n", - "DA(zstar)/Gpc = 13.81899\n", - "zdrag = 1061.07\n", - "r_s(zdrag)/Mpc = 146.78\n", - "k_D(zstar) Mpc = 0.1414\n", - "100*theta_D = 0.160728\n", - "z_EQ (if v_nu=1) = 3393.12\n", - "k_EQ Mpc (if v_nu=1) = 0.010356\n", - "100*theta_EQ = 0.818631\n", - "100*theta_rs_EQ = 0.451897\n", - "tau_recomb/Mpc = 281.00 tau_now/Mpc = 14099.7\n" + "100*theta_EQ = 0.818635\n", + "100*theta_rs_EQ = 0.451900\n", + "tau_recomb/Mpc = 281.00 tau_now/Mpc = 14099.8\n" ] }, { @@ -1626,13 +1563,13 @@ "text": [ "Parameter vector = [3.00e-01 6.90e-01 4.80e-02 9.70e-01 2.19e-09] ... \n", "\n", - "Likelihood = 6043.340736051251\n", + "Likelihood = 6043.372470380764\n", "Prior = 33.53219538473871\n", - "Posterior = 6076.87293143599\n", + "Posterior = 6076.904665765503\n", "\n", - "('COSMOLOGICAL_PARAMETERS', 'SIGMA_8') = 0.8256313000769074\n", - "('COSMOLOGICAL_PARAMETERS', 'SIGMA_12') = 0.8065433411789026\n", - "('DATA_VECTOR', '2PT_CHI2') = 1251.9736545758915\n" + "('COSMOLOGICAL_PARAMETERS', 'SIGMA_8') = 0.8256255577023566\n", + "('COSMOLOGICAL_PARAMETERS', 'SIGMA_12') = 0.8065377926764916\n", + "('DATA_VECTOR', '2PT_CHI2') = 1251.9059396597402\n" ] } ], @@ -1769,7 +1706,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -1838,93 +1775,93 @@ "Samples after cutting: 6600\n", "\n", "Marginalized mean, std-dev:\n", - " cosmological_parameters--omega_m = 0.302986 ± 0.0541066 \n", - " cosmological_parameters--h0 = 0.730551 ± 0.0131537 \n", - " cosmological_parameters--omega_k = -0.0183609 ± 0.13328 \n", - " supernova_params--m = -19.2596 ± 0.0408133 \n", - " cosmological_parameters--ommh2 = 0.161674 ± 0.029039 \n", + " cosmological_parameters--omega_m = 0.311077 ± 0.053731 \n", + " cosmological_parameters--h0 = 0.732183 ± 0.0123719 \n", + " cosmological_parameters--omega_k = -0.0403181 ± 0.14128 \n", + " supernova_params--m = -19.2558 ± 0.0389559 \n", + " cosmological_parameters--ommh2 = 0.166789 ± 0.029254 \n", " prior = 2.40795 ± 4.44089e-16 \n", - " post = -20.1041 ± 1.26664 \n", + " post = -19.9846 ± 1.23083 \n", "\n", "\n", "Marginalized 1D peak, 68% asymmetric error bars:\n", - " cosmological_parameters--omega_m = 0.322399 + 0.0503383 - 0.0631697 \n", - " cosmological_parameters--h0 = 0.727791 + 0.016366 - 0.00940575 \n", - " cosmological_parameters--omega_k = -0.0632906 + 0.157134 - 0.129546 \n", - " supernova_params--m = -19.2558 + 0.0373545 - 0.0413164 \n", - " cosmological_parameters--ommh2 = 0.176711 + 0.0197324 - 0.0403756 \n", + " cosmological_parameters--omega_m = 0.340243 + 0.0453693 - 0.0665746 \n", + " cosmological_parameters--h0 = 0.732042 + 0.0118437 - 0.0118437 \n", + " cosmological_parameters--omega_k = -0.109528 + 0.164378 - 0.123584 \n", + " supernova_params--m = -19.2654 + 0.0481099 - 0.0266019 \n", + " cosmological_parameters--ommh2 = 0.174925 + 0.0302846 - 0.0308784 \n", " prior = nan + nan - nan \n", - " post = -19.2547 + 0.637272 - 1.31703 \n", + " post = -19.183 + 0.596544 - 1.2357 \n", "\n", "\n", "Marginalized 1D peak, 95% asymmetric error bars:\n", - " cosmological_parameters--omega_m = 0.322399 + 0.0745204 - 0.120417 \n", - " cosmological_parameters--h0 = 0.727791 + 0.0282173 - 0.0235144 \n", - " cosmological_parameters--omega_k = -0.0632906 + 0.295076 - 0.189521 \n", - " supernova_params--m = -19.2558 + 0.0724452 - 0.0860286 \n", - " cosmological_parameters--ommh2 = 0.176711 + 0.0367327 - 0.0713403 \n", + " cosmological_parameters--omega_m = 0.340243 + 0.0596705 - 0.125259 \n", + " cosmological_parameters--h0 = 0.732042 + 0.0242796 - 0.0248718 \n", + " cosmological_parameters--omega_k = -0.109528 + 0.341955 - 0.166778 \n", + " supernova_params--m = -19.2654 + 0.0820698 - 0.0707498 \n", + " cosmological_parameters--ommh2 = 0.174925 + 0.0430516 - 0.0638352 \n", " prior = nan + nan - nan \n", - " post = -19.2547 + 0.934665 - 3.33506 \n", + " post = -19.183 + 0.852206 - 3.21708 \n", "\n", "Marginalized median, std-dev:\n", - " cosmological_parameters--omega_m = 0.309229 ± 0.0541066\n", - " cosmological_parameters--h0 = 0.730382 ± 0.0131537\n", - " cosmological_parameters--omega_k = -0.0243254 ± 0.13328\n", - " supernova_params--m = -19.2585 ± 0.0408133\n", - " cosmological_parameters--ommh2 = 0.164641 ± 0.029039\n", + " cosmological_parameters--omega_m = 0.316289 ± 0.053731\n", + " cosmological_parameters--h0 = 0.731947 ± 0.0123719\n", + " cosmological_parameters--omega_k = -0.0597501 ± 0.14128\n", + " supernova_params--m = -19.2564 ± 0.0389559\n", + " cosmological_parameters--ommh2 = 0.169724 ± 0.029254\n", " prior = 2.40795 ± 4.44089e-16\n", - " post = -19.8216 ± 1.26664\n", + " post = -19.706 ± 1.23083\n", "\n", "Best likelihood:\n", - " cosmological_parameters--omega_m = 0.327808\n", - " cosmological_parameters--h0 = 0.732015\n", - " cosmological_parameters--omega_k = -0.0845155\n", - " supernova_params--m = -19.2582\n", - " cosmological_parameters--ommh2 = 0.175654\n", + " cosmological_parameters--omega_m = 0.330906\n", + " cosmological_parameters--h0 = 0.730221\n", + " cosmological_parameters--omega_k = -0.0923922\n", + " supernova_params--m = -19.2637\n", + " cosmological_parameters--ommh2 = 0.176447\n", " prior = 2.40795\n", - " post = -18.3201\n", + " post = -18.3308\n", "\n", "95% lower limits:\n", - " cosmological_parameters--omega_m > 0.204332\n", - " cosmological_parameters--h0 > 0.708509\n", - " cosmological_parameters--omega_k > -0.22646\n", - " supernova_params--m > -19.3297\n", - " cosmological_parameters--ommh2 > 0.109382\n", + " cosmological_parameters--omega_m > 0.214598\n", + " cosmological_parameters--h0 > 0.711736\n", + " cosmological_parameters--omega_k > -0.240536\n", + " supernova_params--m > -19.3204\n", + " cosmological_parameters--ommh2 > 0.115689\n", " prior > 2.40795\n", - " post > -22.607\n", + " post > -22.3924\n", "\n", "95% upper limits:\n", - " cosmological_parameters--omega_m < 0.383011\n", - " cosmological_parameters--h0 < 0.751846\n", - " cosmological_parameters--omega_k < 0.214109\n", - " supernova_params--m < -19.196\n", - " cosmological_parameters--ommh2 < 0.205826\n", + " cosmological_parameters--omega_m < 0.390061\n", + " cosmological_parameters--h0 < 0.752029\n", + " cosmological_parameters--omega_k < 0.219731\n", + " supernova_params--m < -19.1937\n", + " cosmological_parameters--ommh2 < 0.209981\n", " prior < 2.40795\n", - " post < -18.636\n", + " post < -18.5961\n", "\n", "68% lower limits:\n", - " cosmological_parameters--omega_m > 0.277602\n", - " cosmological_parameters--h0 > 0.724813\n", - " cosmological_parameters--omega_k > -0.0877546\n", - " supernova_params--m > -19.2771\n", - " cosmological_parameters--ommh2 > 0.147944\n", + " cosmological_parameters--omega_m > 0.287044\n", + " cosmological_parameters--h0 > 0.726409\n", + " cosmological_parameters--omega_k > -0.124174\n", + " supernova_params--m > -19.2743\n", + " cosmological_parameters--ommh2 > 0.153704\n", " prior > 2.40795\n", - " post > -20.3849\n", + " post > -20.2366\n", "\n", "68% upper limits:\n", - " cosmological_parameters--omega_m < 0.334703\n", - " cosmological_parameters--h0 < 0.736342\n", - " cosmological_parameters--omega_k < 0.0431691\n", - " supernova_params--m < -19.2407\n", - " cosmological_parameters--ommh2 < 0.178058\n", + " cosmological_parameters--omega_m < 0.34328\n", + " cosmological_parameters--h0 < 0.73753\n", + " cosmological_parameters--omega_k < 0.0200835\n", + " supernova_params--m < -19.2386\n", + " cosmological_parameters--ommh2 < 0.184357\n", " prior < 2.40795\n", - " post < -19.3507\n", + " post < -19.2673\n", "\n", "\n", "#You should cite these papers in any publication based on this pipeline.\n", - " Riess et al, ApJLett, 908, 1\n", - " Scolnic et al, ApJ, 859, 28\n", " The Astropy Collaboration et al 2022 ApJ 935 167\n", + " Scolnic et al, ApJ, 859, 28\n", + " Riess et al, ApJLett, 908, 1\n", "\n", "Finalizing:\n" ] @@ -1933,7 +1870,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jzuntz/src/cosmosis/cosmosis/cosmosis/plotting/kde.py:29: RuntimeWarning: invalid value encountered in divide\n", + "/Users/jzuntz/src/cosmosis/env/lib/python3.11/site-packages/cosmosis/plotting/kde.py:29: RuntimeWarning: invalid value encountered in divide\n", " normalized_points.append((column-col_mean)/col_std)\n" ] } @@ -2014,7 +1951,7 @@ "outputs": [ { "data": { - "image/png": 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Table length=7\n", - "
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parameteru95data_set
str32float64str7
cosmological_parameters--omega_m0.38301120583904713chain_0
cosmological_parameters--h00.7518455907318123chain_0
cosmological_parameters--omega_k0.2141087565451413chain_0
supernova_params--m-19.196005540245203chain_0
cosmological_parameters--ommh20.20582640767777718chain_0
cosmological_parameters--omega_m0.39006076446005206chain_0
cosmological_parameters--h00.752029482180202chain_0
cosmological_parameters--omega_k0.21973082862542304chain_0
supernova_params--m-19.19366283841183chain_0
cosmological_parameters--ommh20.2099807519461205chain_0
prior2.407945608651871chain_0
post-18.63596685583259chain_0
post-18.596100604800164chain_0
" ], "text/plain": [ @@ -2056,13 +1993,13 @@ " parameter u95 data_set\n", " str32 float64 str7 \n", "-------------------------------- ------------------- --------\n", - "cosmological_parameters--omega_m 0.38301120583904713 chain_0\n", - " cosmological_parameters--h0 0.7518455907318123 chain_0\n", - "cosmological_parameters--omega_k 0.2141087565451413 chain_0\n", - " supernova_params--m -19.196005540245203 chain_0\n", - " cosmological_parameters--ommh2 0.20582640767777718 chain_0\n", + "cosmological_parameters--omega_m 0.39006076446005206 chain_0\n", + " cosmological_parameters--h0 0.752029482180202 chain_0\n", + "cosmological_parameters--omega_k 0.21973082862542304 chain_0\n", + " supernova_params--m -19.19366283841183 chain_0\n", + " cosmological_parameters--ommh2 0.2099807519461205 chain_0\n", " prior 2.407945608651871 chain_0\n", - " post -18.63596685583259 chain_0" + " post -18.596100604800164 chain_0" ] }, "execution_count": 31, @@ -2113,93 +2050,93 @@ "Samples after cutting: 6600\n", "\n", "Marginalized mean, std-dev:\n", - " cosmological_parameters--omega_m = 0.302986 ± 0.0541066 \n", - " cosmological_parameters--h0 = 0.730551 ± 0.0131537 \n", - " cosmological_parameters--omega_k = -0.0183609 ± 0.13328 \n", - " supernova_params--m = -19.2596 ± 0.0408133 \n", - " cosmological_parameters--ommh2 = 0.161674 ± 0.029039 \n", + " cosmological_parameters--omega_m = 0.311077 ± 0.053731 \n", + " cosmological_parameters--h0 = 0.732183 ± 0.0123719 \n", + " cosmological_parameters--omega_k = -0.0403181 ± 0.14128 \n", + " supernova_params--m = -19.2558 ± 0.0389559 \n", + " cosmological_parameters--ommh2 = 0.166789 ± 0.029254 \n", " prior = 2.40795 ± 4.44089e-16 \n", - " post = -20.1041 ± 1.26664 \n", + " post = -19.9846 ± 1.23083 \n", "\n", "\n", "Marginalized 1D peak, 68% asymmetric error bars:\n", - " cosmological_parameters--omega_m = 0.322399 + 0.0503383 - 0.0631697 \n", - " cosmological_parameters--h0 = 0.727791 + 0.016366 - 0.00940575 \n", - " cosmological_parameters--omega_k = -0.0632906 + 0.157134 - 0.129546 \n", - " supernova_params--m = -19.2558 + 0.0373545 - 0.0413164 \n", - " cosmological_parameters--ommh2 = 0.176711 + 0.0197324 - 0.0403756 \n", + " cosmological_parameters--omega_m = 0.340243 + 0.0453693 - 0.0665746 \n", + " cosmological_parameters--h0 = 0.732042 + 0.0118437 - 0.0118437 \n", + " cosmological_parameters--omega_k = -0.109528 + 0.164378 - 0.123584 \n", + " supernova_params--m = -19.2654 + 0.0481099 - 0.0266019 \n", + " cosmological_parameters--ommh2 = 0.174925 + 0.0302846 - 0.0308784 \n", " prior = nan + nan - nan \n", - " post = -19.2547 + 0.637272 - 1.31703 \n", + " post = -19.183 + 0.596544 - 1.2357 \n", "\n", "\n", "Marginalized 1D peak, 95% asymmetric error bars:\n", - " cosmological_parameters--omega_m = 0.322399 + 0.0745204 - 0.120417 \n", - " cosmological_parameters--h0 = 0.727791 + 0.0282173 - 0.0235144 \n", - " cosmological_parameters--omega_k = -0.0632906 + 0.295076 - 0.189521 \n", - " supernova_params--m = -19.2558 + 0.0724452 - 0.0860286 \n", - " cosmological_parameters--ommh2 = 0.176711 + 0.0367327 - 0.0713403 \n", + " cosmological_parameters--omega_m = 0.340243 + 0.0596705 - 0.125259 \n", + " cosmological_parameters--h0 = 0.732042 + 0.0242796 - 0.0248718 \n", + " cosmological_parameters--omega_k = -0.109528 + 0.341955 - 0.166778 \n", + " supernova_params--m = -19.2654 + 0.0820698 - 0.0707498 \n", + " cosmological_parameters--ommh2 = 0.174925 + 0.0430516 - 0.0638352 \n", " prior = nan + nan - nan \n", - " post = -19.2547 + 0.934665 - 3.33506 \n", + " post = -19.183 + 0.852206 - 3.21708 \n", "\n", "Marginalized median, std-dev:\n", - " cosmological_parameters--omega_m = 0.309229 ± 0.0541066\n", - " cosmological_parameters--h0 = 0.730382 ± 0.0131537\n", - " cosmological_parameters--omega_k = -0.0243254 ± 0.13328\n", - " supernova_params--m = -19.2585 ± 0.0408133\n", - " cosmological_parameters--ommh2 = 0.164641 ± 0.029039\n", + " cosmological_parameters--omega_m = 0.316289 ± 0.053731\n", + " cosmological_parameters--h0 = 0.731947 ± 0.0123719\n", + " cosmological_parameters--omega_k = -0.0597501 ± 0.14128\n", + " supernova_params--m = -19.2564 ± 0.0389559\n", + " cosmological_parameters--ommh2 = 0.169724 ± 0.029254\n", " prior = 2.40795 ± 4.44089e-16\n", - " post = -19.8216 ± 1.26664\n", + " post = -19.706 ± 1.23083\n", "\n", "Best likelihood:\n", - " cosmological_parameters--omega_m = 0.327808\n", - " cosmological_parameters--h0 = 0.732015\n", - " cosmological_parameters--omega_k = -0.0845155\n", - " supernova_params--m = -19.2582\n", - " cosmological_parameters--ommh2 = 0.175654\n", + " cosmological_parameters--omega_m = 0.330906\n", + " cosmological_parameters--h0 = 0.730221\n", + " cosmological_parameters--omega_k = -0.0923922\n", + " supernova_params--m = -19.2637\n", + " cosmological_parameters--ommh2 = 0.176447\n", " prior = 2.40795\n", - " post = -18.3201\n", + " post = -18.3308\n", "\n", "95% lower limits:\n", - " cosmological_parameters--omega_m > 0.204332\n", - " cosmological_parameters--h0 > 0.708509\n", - " cosmological_parameters--omega_k > -0.22646\n", - " supernova_params--m > -19.3297\n", - " cosmological_parameters--ommh2 > 0.109382\n", + " cosmological_parameters--omega_m > 0.214598\n", + " cosmological_parameters--h0 > 0.711736\n", + " cosmological_parameters--omega_k > -0.240536\n", + " supernova_params--m > -19.3204\n", + " cosmological_parameters--ommh2 > 0.115689\n", " prior > 2.40795\n", - " post > -22.607\n", + " post > -22.3924\n", "\n", "95% upper limits:\n", - " cosmological_parameters--omega_m < 0.383011\n", - " cosmological_parameters--h0 < 0.751846\n", - " cosmological_parameters--omega_k < 0.214109\n", - " supernova_params--m < -19.196\n", - " cosmological_parameters--ommh2 < 0.205826\n", + " cosmological_parameters--omega_m < 0.390061\n", + " cosmological_parameters--h0 < 0.752029\n", + " cosmological_parameters--omega_k < 0.219731\n", + " supernova_params--m < -19.1937\n", + " cosmological_parameters--ommh2 < 0.209981\n", " prior < 2.40795\n", - " post < -18.636\n", + " post < -18.5961\n", "\n", "68% lower limits:\n", - " cosmological_parameters--omega_m > 0.277602\n", - " cosmological_parameters--h0 > 0.724813\n", - " cosmological_parameters--omega_k > -0.0877546\n", - " supernova_params--m > -19.2771\n", - " cosmological_parameters--ommh2 > 0.147944\n", + " cosmological_parameters--omega_m > 0.287044\n", + " cosmological_parameters--h0 > 0.726409\n", + " cosmological_parameters--omega_k > -0.124174\n", + " supernova_params--m > -19.2743\n", + " cosmological_parameters--ommh2 > 0.153704\n", " prior > 2.40795\n", - " post > -20.3849\n", + " post > -20.2366\n", "\n", "68% upper limits:\n", - " cosmological_parameters--omega_m < 0.334703\n", - " cosmological_parameters--h0 < 0.736342\n", - " cosmological_parameters--omega_k < 0.0431691\n", - " supernova_params--m < -19.2407\n", - " cosmological_parameters--ommh2 < 0.178058\n", + " cosmological_parameters--omega_m < 0.34328\n", + " cosmological_parameters--h0 < 0.73753\n", + " cosmological_parameters--omega_k < 0.0200835\n", + " supernova_params--m < -19.2386\n", + " cosmological_parameters--ommh2 < 0.184357\n", " prior < 2.40795\n", - " post < -19.3507\n", + " post < -19.2673\n", "\n", "\n", "#You should cite these papers in any publication based on this pipeline.\n", - " Riess et al, ApJLett, 908, 1\n", - " Scolnic et al, ApJ, 859, 28\n", " The Astropy Collaboration et al 2022 ApJ 935 167\n", + " Scolnic et al, ApJ, 859, 28\n", + " Riess et al, ApJLett, 908, 1\n", "\n", " - 1D plot cosmological_parameters--omega_m\n", " - 1D plot cosmological_parameters--h0\n", @@ -2214,7 +2151,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jzuntz/src/cosmosis/cosmosis/cosmosis/plotting/kde.py:29: RuntimeWarning: invalid value encountered in divide\n", + "/Users/jzuntz/src/cosmosis/env/lib/python3.11/site-packages/cosmosis/plotting/kde.py:29: RuntimeWarning: invalid value encountered in divide\n", " normalized_points.append((column-col_mean)/col_std)\n" ] }, @@ -2230,7 +2167,23 @@ " (making supernova_params--m vs cosmological_parameters--ommh2)\n", " (making cosmological_parameters--ommh2 vs cosmological_parameters--omega_m)\n", " (making cosmological_parameters--ommh2 vs cosmological_parameters--h0)\n", - " (making cosmological_parameters--ommh2 vs cosmological_parameters--omega_k)\n", + " (making cosmological_parameters--ommh2 vs cosmological_parameters--omega_k)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/jzuntz/src/cosmosis/env/lib/python3.11/site-packages/cosmosis/postprocessing/plots.py:734: UserWarning: The figure layout has changed to tight\n", + " fig.tight_layout()\n", + "/Users/jzuntz/src/cosmosis/env/lib/python3.11/site-packages/cosmosis/postprocessing/utils.py:42: RuntimeWarning: invalid value encountered in divide\n", + " x = (v-mu)/sigma\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ " - Trace plot cosmological_parameters--omega_m\n", " - Trace plot cosmological_parameters--h0\n", " - Trace plot cosmological_parameters--omega_k\n", @@ -2241,106 +2194,98 @@ "Samples after cutting: 3600\n", "\n", "Marginalized mean, std-dev:\n", - " cosmological_parameters--omega_m = 0.299763 ± 0.0550524 \n", - " cosmological_parameters--h0 = 0.7319 ± 0.0130927 \n", - " cosmological_parameters--omega_k = -0.010462 ± 0.134415 \n", - " supernova_params--m = -19.2552 ± 0.0403456 \n", - " cosmological_parameters--ommh2 = 0.160661 ± 0.0301993 \n", + " cosmological_parameters--omega_m = 0.306343 ± 0.0547416 \n", + " cosmological_parameters--h0 = 0.731609 ± 0.0120194 \n", + " cosmological_parameters--omega_k = -0.0292926 ± 0.141062 \n", + " supernova_params--m = -19.2576 ± 0.0386461 \n", + " cosmological_parameters--ommh2 = 0.163944 ± 0.0295061 \n", " prior = 2.40795 ± 4.44089e-16 \n", - " post = -20.0078 ± 1.16252 \n", + " post = -20.0116 ± 1.23014 \n", "\n", "\n", "Marginalized 1D peak, 68% asymmetric error bars:\n", - " cosmological_parameters--omega_m = 0.320919 + 0.0488578 - 0.0671178 \n", - " cosmological_parameters--h0 = 0.734608 + 0.0111377 - 0.0146815 \n", - " cosmological_parameters--omega_k = -0.0575368 + 0.161652 - 0.125729 \n", - " supernova_params--m = -19.2532 + 0.042828 - 0.0368646 \n", - " cosmological_parameters--ommh2 = 0.179443 + 0.0173038 - 0.0449292 \n", + " cosmological_parameters--omega_m = 0.344382 + 0.0352956 - 0.0790621 \n", + " cosmological_parameters--h0 = 0.731905 + 0.0119514 - 0.0112586 \n", + " cosmological_parameters--omega_k = -0.112908 + 0.188582 - 0.105033 \n", + " supernova_params--m = -19.2549 + 0.0349211 - 0.0387406 \n", + " cosmological_parameters--ommh2 = 0.159862 + 0.0415051 - 0.0197776 \n", " prior = nan + nan - nan \n", - " post = -19.3693 + 0.76971 - 1.10174 \n", + " post = -19.2642 + 0.677151 - 1.20789 \n", "\n", "\n", "Marginalized 1D peak, 95% asymmetric error bars:\n", - " cosmological_parameters--omega_m = 0.320919 + 0.0745204 - 0.124365 \n", - " cosmological_parameters--h0 = 0.734608 + 0.0221067 - 0.0295318 \n", - " cosmological_parameters--omega_k = -0.0575368 + 0.300552 - 0.187995 \n", - " supernova_params--m = -19.2532 + 0.0710186 - 0.0851139 \n", - " cosmological_parameters--ommh2 = 0.179443 + 0.0349112 - 0.078019 \n", + " cosmological_parameters--omega_m = 0.344382 + 0.0536493 - 0.138829 \n", + " cosmological_parameters--h0 = 0.731905 + 0.0228636 - 0.0254618 \n", + " cosmological_parameters--omega_k = -0.112908 + 0.359261 - 0.151582 \n", + " supernova_params--m = -19.2549 + 0.0714791 - 0.0829375 \n", + " cosmological_parameters--ommh2 = 0.159862 + 0.0562687 - 0.0523689 \n", " prior = nan + nan - nan \n", - " post = -19.3693 + 1.02628 - 2.9581 \n", + " post = -19.2642 + 0.93337 - 3.14784 \n", "\n", "Marginalized median, std-dev:\n", - " cosmological_parameters--omega_m = 0.305231 ± 0.0550524\n", - " cosmological_parameters--h0 = 0.732449 ± 0.0130927\n", - " cosmological_parameters--omega_k = -0.0195219 ± 0.134415\n", - " supernova_params--m = -19.254 ± 0.0403456\n", - " cosmological_parameters--ommh2 = 0.162955 ± 0.0301993\n", + " cosmological_parameters--omega_m = 0.310282 ± 0.0547416\n", + " cosmological_parameters--h0 = 0.731757 ± 0.0120194\n", + " cosmological_parameters--omega_k = -0.0483378 ± 0.141062\n", + " supernova_params--m = -19.2577 ± 0.0386461\n", + " cosmological_parameters--ommh2 = 0.164976 ± 0.0295061\n", " prior = 2.40795 ± 4.44089e-16\n", - " post = -19.7598 ± 1.16252\n", + " post = -19.7308 ± 1.23014\n", "\n", "Best likelihood:\n", - " cosmological_parameters--omega_m = 0.329177\n", - " cosmological_parameters--h0 = 0.730541\n", - " cosmological_parameters--omega_k = -0.077454\n", - " supernova_params--m = -19.2594\n", - " cosmological_parameters--ommh2 = 0.175679\n", + " cosmological_parameters--omega_m = 0.330906\n", + " cosmological_parameters--h0 = 0.730221\n", + " cosmological_parameters--omega_k = -0.0923922\n", + " supernova_params--m = -19.2637\n", + " cosmological_parameters--ommh2 = 0.176447\n", " prior = 2.40795\n", - " post = -18.343\n", + " post = -18.3308\n", "\n", "95% lower limits:\n", - " cosmological_parameters--omega_m > 0.200721\n", - " cosmological_parameters--h0 > 0.710179\n", - " cosmological_parameters--omega_k > -0.216103\n", - " supernova_params--m > -19.3257\n", - " cosmological_parameters--ommh2 > 0.107069\n", + " cosmological_parameters--omega_m > 0.209502\n", + " cosmological_parameters--h0 > 0.711149\n", + " cosmological_parameters--omega_k > -0.228182\n", + " supernova_params--m > -19.3251\n", + " cosmological_parameters--ommh2 > 0.111196\n", " prior > 2.40795\n", - " post > -22.3247\n", + " post > -22.4296\n", "\n", "95% upper limits:\n", - " cosmological_parameters--omega_m < 0.381794\n", - " cosmological_parameters--h0 < 0.752818\n", - " cosmological_parameters--omega_k < 0.219644\n", - " supernova_params--m < -19.1918\n", - " cosmological_parameters--ommh2 < 0.207129\n", + " cosmological_parameters--omega_m < 0.385896\n", + " cosmological_parameters--h0 < 0.750671\n", + " cosmological_parameters--omega_k < 0.226591\n", + " supernova_params--m < -19.1947\n", + " cosmological_parameters--ommh2 < 0.208213\n", " prior < 2.40795\n", - " post < -18.6145\n", + " post < -18.6034\n", "\n", "68% lower limits:\n", - " cosmological_parameters--omega_m > 0.27265\n", - " cosmological_parameters--h0 > 0.726193\n", - " cosmological_parameters--omega_k > -0.0835794\n", - " supernova_params--m > -19.2712\n", - " cosmological_parameters--ommh2 > 0.145614\n", + " cosmological_parameters--omega_m > 0.278962\n", + " cosmological_parameters--h0 > 0.726398\n", + " cosmological_parameters--omega_k > -0.117368\n", + " supernova_params--m > -19.2745\n", + " cosmological_parameters--ommh2 > 0.14937\n", " prior > 2.40795\n", - " post > -20.2736\n", + " post > -20.3062\n", "\n", "68% upper limits:\n", - " cosmological_parameters--omega_m < 0.331442\n", - " cosmological_parameters--h0 < 0.737853\n", - " cosmological_parameters--omega_k < 0.0552775\n", - " supernova_params--m < -19.2365\n", - " cosmological_parameters--ommh2 < 0.178276\n", + " cosmological_parameters--omega_m < 0.341307\n", + " cosmological_parameters--h0 < 0.736894\n", + " cosmological_parameters--omega_k < 0.0377531\n", + " supernova_params--m < -19.242\n", + " cosmological_parameters--ommh2 < 0.181439\n", " prior < 2.40795\n", - " post < -19.3268\n", + " post < -19.2851\n", "\n", "NOT saving more than one covariance matrix - just using first ini file\n", "NOT saving more than one proposal matrix - just using first ini file\n", "\n", "#You should cite these papers in any publication based on this pipeline.\n", - " Riess et al, ApJLett, 908, 1\n", - " Scolnic et al, ApJ, 859, 28\n", " The Astropy Collaboration et al 2022 ApJ 935 167\n", + " Scolnic et al, ApJ, 859, 28\n", + " Riess et al, ApJLett, 908, 1\n", "\n", "Finalizing:\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jzuntz/src/cosmosis/cosmosis/cosmosis/postprocessing/utils.py:42: RuntimeWarning: invalid value encountered in divide\n", - " x = (v-mu)/sigma\n" - ] } ], "source": [ @@ -2356,7 +2301,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -2372,7 +2317,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 39, "id": "b13ccf1e", "metadata": {}, "outputs": [ @@ -2380,53 +2325,59 @@ "data": { "text/html": [ "
Table length=14\n", - "\n", + "
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parametermodessigmadata_set
str32float64float64str8
cosmological_parameters--omega_m0.322399383087727860.05410661160232988Emcee
cosmological_parameters--h00.72779127139843150.013153718017527035Emcee
cosmological_parameters--omega_k-0.063290603889114280.1332801929562442Emcee
supernova_params--m-19.2558152968542270.040813306515946855Emcee
cosmological_parameters--ommh20.176710602918255220.02903896496405144Emcee
cosmological_parameters--omega_m0.34024275723846270.05373096344172164Emcee
cosmological_parameters--h00.73204202338830730.012371948908432618Emcee
cosmological_parameters--omega_k-0.10952828321617960.14128048885744773Emcee
supernova_params--m-19.2653683633333340.03895585152058654Emcee
cosmological_parameters--ommh20.17492543581324760.02925395538623886Emcee
priornan4.440892098500626e-16Emcee
post-19.2547397859174971.2666418795087506Emcee
cosmological_parameters--omega_m0.32091884437545560.05505239073474754Nautilus
cosmological_parameters--h00.73460848448442560.013092732514922002Nautilus
cosmological_parameters--omega_k-0.0575368258882873740.13441452473640203Nautilus
supernova_params--m-19.2532407024500040.040345642878508954Nautilus
cosmological_parameters--ommh20.179442785800466350.030199321294975524Nautilus
post-19.182988077585621.2308295100168705Emcee
cosmological_parameters--omega_m0.34438158347111220.05474162234416896Nautilus
cosmological_parameters--h00.73190488335583660.012019369775189798Nautilus
cosmological_parameters--omega_k-0.112908151817911720.14106162618011311Nautilus
supernova_params--m-19.254853892579510.03864605903118181Nautilus
cosmological_parameters--ommh20.159861961791974230.02950605207317032Nautilus
priornan4.440892098500626e-16Nautilus
post-19.369307474561851.1625172113135325Nautilus
post-19.2641519891996321.230135087851152Nautilus
" ], "text/plain": [ "\n", - " parameter modes sigma data_set\n", - " str32 float64 float64 str8 \n", - "-------------------------------- --------------------- --------------------- --------\n", - "cosmological_parameters--omega_m 0.32239938308772786 0.05410661160232988 Emcee\n", - " cosmological_parameters--h0 0.7277912713984315 0.013153718017527035 Emcee\n", - "cosmological_parameters--omega_k -0.06329060388911428 0.1332801929562442 Emcee\n", - " supernova_params--m -19.255815296854227 0.040813306515946855 Emcee\n", - " cosmological_parameters--ommh2 0.17671060291825522 0.02903896496405144 Emcee\n", - " prior nan 4.440892098500626e-16 Emcee\n", - " post -19.254739785917497 1.2666418795087506 Emcee\n", - "cosmological_parameters--omega_m 0.3209188443754556 0.05505239073474754 Nautilus\n", - " cosmological_parameters--h0 0.7346084844844256 0.013092732514922002 Nautilus\n", - "cosmological_parameters--omega_k -0.057536825888287374 0.13441452473640203 Nautilus\n", - " supernova_params--m -19.253240702450004 0.040345642878508954 Nautilus\n", - " cosmological_parameters--ommh2 0.17944278580046635 0.030199321294975524 Nautilus\n", - " prior nan 4.440892098500626e-16 Nautilus\n", - " post -19.36930747456185 1.1625172113135325 Nautilus" + " parameter modes sigma data_set\n", + " str32 float64 float64 str8 \n", + "-------------------------------- -------------------- --------------------- --------\n", + "cosmological_parameters--omega_m 0.3402427572384627 0.05373096344172164 Emcee\n", + " cosmological_parameters--h0 0.7320420233883073 0.012371948908432618 Emcee\n", + "cosmological_parameters--omega_k -0.1095282832161796 0.14128048885744773 Emcee\n", + " supernova_params--m -19.265368363333334 0.03895585152058654 Emcee\n", + " cosmological_parameters--ommh2 0.1749254358132476 0.02925395538623886 Emcee\n", + " prior nan 4.440892098500626e-16 Emcee\n", + " post -19.18298807758562 1.2308295100168705 Emcee\n", + "cosmological_parameters--omega_m 0.3443815834711122 0.05474162234416896 Nautilus\n", + " cosmological_parameters--h0 0.7319048833558366 0.012019369775189798 Nautilus\n", + "cosmological_parameters--omega_k -0.11290815181791172 0.14106162618011311 Nautilus\n", + " supernova_params--m -19.25485389257951 0.03864605903118181 Nautilus\n", + " cosmological_parameters--ommh2 0.15986196179197423 0.02950605207317032 Nautilus\n", + " prior nan 4.440892098500626e-16 Nautilus\n", + " post -19.264151989199632 1.230135087851152 Nautilus" ] }, - "execution_count": 34, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "results.outputs['modes'].value.to_astropy()" + "if 'maxpost' in results.outputs:\n", + " # Newer versions of cosmosis call this \"maxpost\" to distinguish from \"maxlike\"\n", + " r = results.outputs['maxpost'].value.to_astropy()\n", + "else:\n", + " # Slightly older versions call it \"mode\"\n", + " r = results.outputs['modes'].value.to_astropy()\n", + "r" ] }, { @@ -2454,7 +2405,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.3" + "version": "3.11.4" } }, "nbformat": 4, diff --git a/examples/planck.ini b/examples/planck.ini index 40256587..e20e5adb 100644 --- a/examples/planck.ini +++ b/examples/planck.ini @@ -26,7 +26,7 @@ timing=F ;Planck 2018 high ell TT,TE and EE + low ell TT + low ell EE (in Planck notations = TT+lowE) ;without CMB lensing file = likelihood/planck2018/planck_interface.so -data_1 = %(planck_path)s/hi_l/plik/plik_rd12_HM_v22b_TTTEEE.clik +data_1 = %(planck_path)s/hi_l/plik_lite/plik_lite_v22_TTTEEE.clik data_2 = %(planck_path)s/low_l/commander/commander_dx12_v3_2_29.clik data_3 = %(planck_path)s/low_l/simall/simall_100x143_offlike5_EE_Aplanck_B.clik diff --git a/examples/planck_class.ini b/examples/planck_class.ini index f30f1d63..676a81e1 100644 --- a/examples/planck_class.ini +++ b/examples/planck_class.ini @@ -26,9 +26,13 @@ timing=F ;Planck 2018 high ell TT,TE and EE + low ell TT + low ell EE (in Planck notations = TT+lowE) ;without CMB lensing file = likelihood/planck2018/planck_interface.so -data_1 = %(planck_path)s/hi_l/plik/plik_rd12_HM_v22b_TTTEEE.clik -data_2 = %(planck_path)s/low_l/commander/commander_dx12_v3_2_29.clik -data_3 = %(planck_path)s/low_l/simall/simall_100x143_offlike5_EE_Aplanck_B.clik +; It would be nice to use the same likelihood files as the main planck (camb) test here, +; but the planck 2018 likelihood cannot cope with using the same file again in the same process, +; so when I run the automatic test program it crashes. +; This is not encouraging. +; data_1 = %(planck_path)s/hi_l/plik/plik_rd12_HM_v22b_TTTEEE.clik +data_1 = %(planck_path)s/low_l/commander/commander_dx12_v3_2_29.clik +data_2 = %(planck_path)s/low_l/simall/simall_100x143_offlike5_EE_Aplanck_B.clik ; The consistency module translates between our chosen parameterization diff --git a/examples/planck_values.ini b/examples/planck_values.ini index e39a85ce..60f75aef 100644 --- a/examples/planck_values.ini +++ b/examples/planck_values.ini @@ -29,51 +29,3 @@ wa = 0.0 ;equation of state of dark energy (redshift dependency) [planck] a_planck = 0.9 1.0 1.1 ; Total Planck calibration (relative to 1) at map level, scales all channels -;adapted from cosmomc where param[paramname] = center min max start_width propose_width -;comments for parameters are taken from cosmomc file -a_cib_217 = 0. 67. 200. ;Spectral index of the CIB -cib_index = -1.3 ;Spectral index of the CIB -xi_sz_cib = 0. 0. 1. ;TSZ-CIB template amplitude (positive is negative) -a_sz = 0. 7. 10. ;Thermal SZ amplitude at 143 GH -ps_a_100_100 = 0. 257. 400. ;Point source amplitude at 100 GHz -ps_a_143_143 = 0. 47. 400. ;Point source amplitude at 143 GHz -ps_a_143_217 = 0. 40. 400. ;Point source amplitude at 143x217 GHz -ps_a_217_217 = 0. 104. 400. ;Point source amplitude at 217 GHz -ksz_norm = 0. 0. 10. ;Kinetic SZ amplitude at 143 GHz -gal545_a_100 = 0. 7. 50. ;Dust amplitude at 100 GHz -gal545_a_143 = 0. 9. 50. ;Dust amplitude at 143 GHz -gal545_a_143_217 = 0. 21. 100. ;Dust amplitude at 143x217 GHz -gal545_a_217 = 0. 80. 400. ;Dust amplitude at 217 GHz -a_sbpx_100_100_tt = 1. ;Subpix noise multiplicative factor at 100 GHz -a_sbpx_143_143_tt = 1. ;Subpix noise multiplicative factor at 143 GHz -a_sbpx_143_217_tt = 1. ;Subpix noise multiplicative factor at 143x217 GHz -a_sbpx_217_217_tt = 1. ;Subpix noise multiplicative factor at 217 GHz -calib_100t = 0. 1.0002 3. ;Relative power spectrum calibration factor 100/143 -calib_217t = 0. 0.99805 3. ;Relative power spectrum calibration factor 217/143 -calib_100p = 1.021 -calib_143p = 0.966 -calib_217p = 1.04 -galf_ee_a_100 = 0.055 -galf_ee_a_100_143 = 0.040 -galf_ee_a_100_217 = 0.094 -galf_ee_a_143 = 0.086 -galf_ee_a_143_217 = 0.21 -galf_ee_a_217 = 0.70 -galf_ee_index = -2.4 -galf_te_a_100 = 0 0.13 10 -galf_te_a_100_143 = 0 0.13 10 -galf_te_a_100_217 = 0 0.46 10 -galf_te_a_143 = 0 0.207 10 -galf_te_a_143_217 = 0 0.69 10 -galf_te_a_217 = 0 1.938 10 -galf_te_index = -2.4 -a_cnoise_e2e_100_100_ee = 1. -a_cnoise_e2e_143_143_ee = 1. -a_cnoise_e2e_217_217_ee = 1. -a_sbpx_100_100_ee = 1. -a_sbpx_100_143_ee = 1. -a_sbpx_100_217_ee = 1. -a_sbpx_143_143_ee = 1. -a_sbpx_143_217_ee = 1. -a_sbpx_217_217_ee = 1. -a_pol = 1. diff --git a/examples/priors_tdcosmo.ini b/examples/priors_tdcosmo.ini new file mode 100644 index 00000000..c4bbc615 --- /dev/null +++ b/examples/priors_tdcosmo.ini @@ -0,0 +1,3 @@ +[cosmological_parameters] + +omega_m = gaussian 0.298 0.022 diff --git a/examples/tdcosmo.ini b/examples/tdcosmo.ini new file mode 100644 index 00000000..5fdde9cb --- /dev/null +++ b/examples/tdcosmo.ini @@ -0,0 +1,84 @@ +[runtime] +sampler = test +verbosity = standard + +[grid] +; The number of samples to take in each +; dimension in which the parameters vary +nsample_dimension = 5 + +[pipeline] +modules = consistency camb tdcosmo +values = examples/values_tdcosmo.ini +priors = examples/priors_tdcosmo.ini + + +[output] +format=text +filename=output/tdcosmo_camb.txt + +; We have a single likelihood module here - BICEP2. +[tdcosmo] +file = likelihood/tdcosmo/tdcosmo_likelihood.py +;distances_computation_module = "CosmoInterp" +distances_computation_module = "camb" +num_distribution_draws = 200 +data_sets = 'tdcosmo7' + +; The consistency module translates between our chosen parameterization +; and any other that modules in the pipeline may want (e.g. camb) +[consistency] +file = utility/consistency/consistency_interface.py + +[camb] +; For background-only data we do not need a full +; Boltzmann evaluation, just D(z), etc. +; Setting mode=background means we get this. +file = boltzmann/camb/camb_interface.py +mode = background +feedback = 0 + +; We need quite fine redshift spacing, because the supernovae +; go down to low z where things are pretty sensitive +nz_background = 200 +zmin_background = 0.0 +zmax_background = 3.0 + + +;[camb] +;; For background-only data we do not need a full +;; Boltzmann evaluation, just D(z), etc. +;; Setting mode=background means we get this. +;file = boltzmann/camb/camb_interface.py +;mode = background +;feedback = 0 +; +;; We need quite fine redshift spacing, because the supernovae +;; go down to low z where things are pretty sensitive +;nz_background = 200 +;zmin_background = 0.0 +;zmax_background = 2.0 + +[polychord] +base_dir = output/y3-polychord-checkpoints +polychord_outfile_root = tdcosmo +resume = F +feedback = 3 +fast_fraction = 0.1 + +;Minimum settings +live_points = 250 +num_repeats = 30 +tolerance = 0.1 + +;Settings for paper runs +; live_points = 500 +; num_repeats=60 +; tolerance=0.01 +; boost_posteriors=10.0 + +[emcee] +walkers = 80 +samples = 10000 +nsteps = 5 + diff --git a/examples/values_tdcosmo.ini b/examples/values_tdcosmo.ini new file mode 100644 index 00000000..d580c9b1 --- /dev/null +++ b/examples/values_tdcosmo.ini @@ -0,0 +1,30 @@ +[cosmological_parameters] +; Listing all these three numbers is how to specify +; that a parameter should vary. The numbers are: +; lower limit, starting value, upper limit + +omega_m = 0.05 0.3 0.5 +h0 = 0. 0.72 1.5 +omega_b = 0.04 +omega_k = 0.0 +w = -1.0 +wa = 0.0 +mnu = 0.06 +nnu = 3.046 + +; CAMB requires these parameters to be set even +; if they are not used +A_s = 2.0e-9 +n_s = 1.0 +tau = 0.08 + +[nuisance_strong_lensing] +; kinematics and Mass-Sheet Degeneracy parameters +lambda_mst = 0.5 1.0 1.5 +;lambda_mst_sigma = 0 0.04 0.2 +log_lambda_mst_sigma = -3 -1.398 -0.301 +alpha_lambda = -1. 0.0 1. +;a_ani = 0.1 1.5 5. +;a_ani_sigma = 0. 0.3 1. +log_a_ani = -1 0.176 0.699 +log_a_ani_sigma = -2 -0.523 0. \ No newline at end of file diff --git a/likelihood/2pt/cosebis/simple_like.py b/likelihood/2pt/cosebis/simple_like.py index acc52bcd..3c65c9e9 100644 --- a/likelihood/2pt/cosebis/simple_like.py +++ b/likelihood/2pt/cosebis/simple_like.py @@ -66,7 +66,6 @@ def setup(options): return config def execute(block, config): - print('Gathering theory outputs to calculate the likelihood') ## Check that the theory has been calculated ## For cosebis this requires the cl_to_cosebis_interface to be run @@ -80,7 +79,6 @@ def execute(block, config): nbTomo_max = 1000 for i in range(nbTomo_max): if not block.has_value(section_name, 'bin_%d_%d' % (i+1, i+1)): - print('%s stops at bin %d' % (section_name, i)) break for j in range(i, nbTomo_max): diff --git a/likelihood/act-dr6-lens/act_dr6_lenslike.py b/likelihood/act-dr6-lens/act_dr6_lenslike.py deleted file mode 100644 index 077408c0..00000000 --- a/likelihood/act-dr6-lens/act_dr6_lenslike.py +++ /dev/null @@ -1,490 +0,0 @@ -__author__ = "Mathew Madhavacheril" -__version__ = "1.0.0" - -import numpy as np -import warnings -from scipy.interpolate import interp1d -InstallableLikelihood = object -import os -file_dir = os.path.abspath(os.path.dirname(__file__)) -data_dir = f"{file_dir}/data/v1.1/" - -variants =[x.strip() for x in ''' -act_baseline, -act_extended, -actplanck_baseline, -actplanck_extended, -act_polonly, -act_cibdeproj, -act_cinpaint -'''.strip().replace('\n','').split(',')] - - -# ================ -# HELPER FUNCTIONS -# ================ - -def pp_to_kk(clpp,ell): - return clpp * (ell*(ell+1.))**2. / 4. - -def get_corrected_clkk(data_dict,clkk,cltt,clte,clee,clbb,suff=''): - clkk_fid = data_dict['fiducial_cl_kk'] - cl_dict = {'tt':cltt,'te':clte,'ee':clee,'bb':clbb} - N1_kk_corr = data_dict[f'dN1_kk{suff}'] @ (clkk-clkk_fid) - dNorm = data_dict[f'dAL_dC{suff}'] - fid_norm = data_dict[f'fAL{suff}'] - N1_cmb_corr = 0. - norm_corr = 0. - for i,s in enumerate(['tt','ee','bb','te']): - cldiff = (cl_dict[s]-data_dict[f'fiducial_cl_{s}']) - N1_cmb_corr = N1_cmb_corr + (data_dict[f'dN1_{s}{suff}']@cldiff) - c = - 2. * (dNorm[i] @ cldiff) - if i==0: - ls = np.arange(c.size) - c[ls>=2] = c[ls>=2] / fid_norm[ls>=2] - norm_corr = norm_corr + c - nclkk = clkk + norm_corr*clkk_fid + N1_kk_corr + N1_cmb_corr - return nclkk - -def standardize(ls,cls,trim_lmax,lbuffer=2,extra_dims="y"): - cstart = int(ls[0]) - diffs = np.diff(ls) - if not(np.all(np.isclose(diffs,1.))): raise ValueError("Multipoles are not spaced by 1") - if not(cstart<=2): raise ValueError("Multipoles start at value greater than 2") - nlen = trim_lmax+lbuffer - cend = nlen - cstart - if extra_dims=="xyy": - out = np.zeros((cls.shape[0],nlen,nlen)) - out[:,cstart:,cstart:] = cls[:,:cend,:cend] - elif extra_dims=="yy": - out = np.zeros((nlen,nlen)) - out[cstart:,cstart:] = cls[:cend,:cend] - elif extra_dims=="xy": - out = np.zeros((cls.shape[0],nlen)) - out[:,cstart:] = cls[:,:cend] - elif extra_dims=="y": - out = np.zeros(nlen) - out[cstart:] = cls[:cend] - else: - raise ValueError - return out - -def get_limber_clkk_flat_universe(results,Pfunc,lmax,kmax,nz,zsrc=None): - # Adapting code from Antony Lewis' CAMB notebook - if zsrc is None: - chistar = results.conformal_time(0)- results.tau_maxvis - else: - chistar = results.comoving_radial_distance(zsrc) - chis = np.linspace(0,chistar,nz) - zs=results.redshift_at_comoving_radial_distance(chis) - dchis = (chis[2:]-chis[:-2])/2 - chis = chis[1:-1] - zs = zs[1:-1] - - #Get lensing window function (flat universe) - win = ((chistar-chis)/(chis**2*chistar))**2 - #Do integral over chi - ls = np.arange(0,lmax+2, dtype=np.float64) - cl_kappa=np.zeros(ls.shape) - w = np.ones(chis.shape) #this is just used to set to zero k values out of range of interpolation - for i, l in enumerate(ls[2:]): - k=(l+0.5)/chis - w[:]=1 - w[k<1e-4]=0 - w[k>=kmax]=0 - cl_kappa[i+2] = np.dot(dchis, w*Pfunc.P(zs, k, grid=False)*win/k**4) - cl_kappa*= (ls*(ls+1))**2 - return cl_kappa - -def get_camb_lens_obj(nz,kmax,zmax=None): - import camb - pars = camb.CAMBparams() - # This cosmology is purely to go from chis->zs for limber integration; - # the details do not matter - pars.set_cosmology(H0=67.5, ombh2=0.022, omch2=0.122) - pars.InitPower.set_params(ns=0.965) - results= camb.get_background(pars) - nz = nz - if zmax is None: - chistar = results.conformal_time(0)- results.tau_maxvis - else: - chistar = results.comoving_radial_distance(zmax) - chis = np.linspace(0,chistar,nz) - zs=results.redshift_at_comoving_radial_distance(chis) - cobj = {"CAMBdata": None, - "Pk_interpolator": { "z": zs, - "k_max": kmax, - "nonlinear": True, - "vars_pairs": ([["Weyl", "Weyl"]])}} - return cobj - - -def parse_variant(variant): - - variant = variant.lower().strip() - if variant not in variants: raise ValueError - - v = None - if '_extended' in variant: - baseline = False - else: - baseline = True - if '_baseline' not in variant: - v = variant.split('_')[-1] - - include_planck = True if 'actplanck' in variant else False - return v,baseline,include_planck - - -# ================== -# Generic likelihood -# ================== - -""" -data_dict = load_data(data_directory) # pre-load data -# for each predicted spectra in chain -# cl_kk is CMB lensing convergence power spectrum (dimensionless, -# no ell or 2pi factors) -# cl_tt, cl_ee, cl_te, cl_bb are lensed CMB power spectra -# (muK^2 units, no ell or 2pi factors) -lnlike = generic_lnlike(data_dict,cl_kk,cl_tt,cl_ee,cl_te,cl_bb) -This returns ln(Likelihood) -so for example, -chi_square = -2 lnlike -""" - -def load_data(variant,lens_only=False, - apply_hartlap=True,like_corrections=True,mock=False, - nsims_act=796,nsims_planck=400,trim_lmax=2998,scale_cov=None): - """ - Given a data directory path, this function loads into a dictionary - the data products necessary for evaluating the DR6 lensing likelihood. - This includes: - 1. the ACT lensing bandpowers. Planck lensing bandpowers will be - appended if include_planck is True. - 2. the associated binning matrix to be applied to a theory curve - 3. the associated covariance matrix - 4. data products associated with applying likelihood corrections - - All these products will be standardized so that they apply - to theory curves specified from L=0 to trim_lmax. - - A Hartlap correction will be applied to the covariance matrix - corresponding to the lower of the number of simulations involved. - - """ - # TODO: review defaults - - - v,baseline,include_planck = parse_variant(variant) - - - # output data - d = {} - - if lens_only and like_corrections: raise ValueError("Likelihood corrections should not be used in lens_only runs.") - if not(lens_only) and not(like_corrections): - warnings.warn("Neither using CMB-marginalized covariance matrix nor including likelihood corrections. Effective covariance may be underestimated.") - - d['include_planck'] = include_planck - d['likelihood_corrections'] = like_corrections - - # Fiducial spectra - if like_corrections: - f_ls, f_tt, f_ee, f_bb, f_te = np.loadtxt(f"{data_dir}/like_corrs/cosmo2017_10K_acc3_lensedCls.dat",unpack=True) - f_tt = f_tt / (f_ls * (f_ls+1.)) * 2. * np.pi - f_ee = f_ee / (f_ls * (f_ls+1.)) * 2. * np.pi - f_bb = f_bb / (f_ls * (f_ls+1.)) * 2. * np.pi - f_te = f_te / (f_ls * (f_ls+1.)) * 2. * np.pi - - fd_ls, f_dd = np.loadtxt(f"{data_dir}/like_corrs/cosmo2017_10K_acc3_lenspotentialCls.dat",unpack=True,usecols=[0,5]) - f_kk = f_dd * 2. * np.pi / 4. - d['fiducial_cl_tt'] = standardize(f_ls,f_tt,trim_lmax) - d['fiducial_cl_te'] = standardize(f_ls,f_te,trim_lmax) - d['fiducial_cl_ee'] = standardize(f_ls,f_ee,trim_lmax) - d['fiducial_cl_bb'] = standardize(f_ls,f_bb,trim_lmax) - d['fiducial_cl_kk'] = standardize(fd_ls,f_kk,trim_lmax) - - - # Return data bandpowers, covariance matrix and binning matrix - ddir = data_dir - if baseline: - start = 2 - end = -6 - else: - start = 2 - end = -3 - - if v is None: - y = np.loadtxt(f'{ddir}/clkk_bandpowers_act.txt') - elif v=='cinpaint': - y = np.loadtxt(f'{ddir}/clkk_bandpowers_act_cinpaint.txt') - elif v=='polonly': - y = np.loadtxt(f'{ddir}/clkk_bandpowers_act_polonly.txt') - elif v=='cibdeproj': - y = np.loadtxt(f'{ddir}/clkk_bandpowers_act_cibdeproj.txt') - nbins_tot_act = y.size - d['full_data_binned_clkk_act'] = y.copy() - data_act = y[start:end].copy() - d['data_binned_clkk'] = data_act - nbins_act = data_act.size - - binmat = np.loadtxt(f'{ddir}/binning_matrix_act.txt') - d['full_binmat_act'] = binmat.copy() - pells = np.arange(binmat.shape[1]) - bcents = binmat@pells - ls = np.arange(binmat.shape[1]) - d['binmat_act'] = standardize(ls,binmat[start:end,:],trim_lmax,extra_dims="xy") - d['bcents_act'] = bcents.copy() - - if lens_only: - if include_planck: - if v not in [None,'cinpaint']: raise ValueError(f"Combination of {v} with Planck is not available") - fcov = np.loadtxt(f'{ddir}/covmat_actplanck_cmbmarg.txt') - else: - if v=='cibdeproj': - fcov = np.loadtxt(f"{ddir}/covmat_act_cibdeproj_cmbmarg.txt") - elif v=='pol': - fcov = np.loadtxt(f"{ddir}/covmat_act_polonly_cmbmarg.txt") - else: - fcov = np.loadtxt(f"{ddir}/covmat_act_cmbmarg.txt") - else: - if v not in [None,'cinpaint']: raise ValueError(f"Covmat for {v} without CMB marginalization is not available") - if include_planck: - fcov = np.loadtxt(f'{ddir}/covmat_actplanck.txt') - else: - fcov = np.loadtxt(f'{ddir}/covmat_act.txt') - - d['full_act_cov'] = fcov.copy() - # Remove trailing bins from ACT part - sel = np.s_[nbins_tot_act+end:nbins_tot_act] - cov = np.delete(np.delete(fcov,sel,0),sel,1) - # Remove leading bins from ACT part - sel = np.s_[:start] - cov = np.delete(np.delete(cov,sel,0),sel,1) - - # Test - covmat = np.loadtxt(f'{ddir}/covmat_act.txt') - covmat1 = covmat[start:end,start:end] - cdiff = cov[:nbins_act,:nbins_act] - covmat1 - if not(np.all(np.isclose(cdiff,0))): raise ValueError - - if include_planck: - data_planck = np.loadtxt(f'{ddir}/clkk_bandpowers_planck.txt') - d['data_binned_clkk'] = np.append(d['data_binned_clkk'],data_planck) - binmat = np.loadtxt(f'{ddir}/binning_matrix_planck.txt') - pells = np.arange(binmat.shape[1]) - bcents = binmat@pells - ls = np.arange(binmat.shape[1]) - d['binmat_planck'] = standardize(ls,binmat,trim_lmax,extra_dims="xy") - d['bcents_planck'] = bcents.copy() - - if like_corrections: - # Load matrices - cmat = np.load(f"{ddir}/like_corrs/norm_correction_matrix_Lmin0_Lmax4000.npy") - ls = np.arange(cmat.shape[1]) - d['dAL_dC'] = standardize(ls,cmat,trim_lmax,extra_dims="xyy") - if include_planck: - cmat = np.load(f"{ddir}/like_corrs/P18_norm_correction_matrix_Lmin0_Lmax3000.npy") - ls = np.arange(cmat.shape[1]) - d['dAL_dC_planck'] = standardize(ls,cmat,trim_lmax,extra_dims="xyy") - - - fAL_ls,fAL = np.loadtxt(f"{ddir}/like_corrs/n0mv_fiducial_lmin600_lmax3000_Lmin0_Lmax4000.txt") - d['fAL'] = standardize(fAL_ls,fAL,trim_lmax,extra_dims="y") - if include_planck: - fAL_ls,fAL = np.loadtxt(f"{ddir}/like_corrs/PLANCK_n0mv_fiducial_lmin600_lmax3000_Lmin0_Lmax3000.txt") - d['fAL_planck'] = standardize(fAL_ls,fAL,trim_lmax,extra_dims="y") - - for spec in ['kk','tt','ee','bb','te']: - n1mat = np.loadtxt(f"{ddir}/like_corrs/N1der_{spec.upper()}_lmin600_lmax3000_full.txt") - d[f'dN1_{spec}'] = standardize(fAL_ls,n1mat,trim_lmax,extra_dims="yy") - if include_planck: - n1mat = np.loadtxt(f"{ddir}/like_corrs/N1_planck_der_{spec.upper()}_lmin100_lmax2048.txt") - d[f'dN1_{spec}_planck'] = standardize(fAL_ls,n1mat,trim_lmax,extra_dims="yy") - - nbins = d['data_binned_clkk'].size - nsims = min(nsims_act,nsims_planck) if include_planck else nsims_act - hartlap_correction = (nsims-nbins-2.)/(nsims-1.) - if apply_hartlap: - pass - #warnings.warn("Hartlap correction to cinv: ", hartlap_correction) - else: - warnings.warn(f"Disabled Hartlap correction to cinv: {hartlap_correction}") - hartlap_correction = 1.0 - if scale_cov is not None: - warnings.warn(f"Covariance has been artificially scaled by: {scale_cov}") - cov = cov * scale_cov - d['cov'] = cov - cinv = np.linalg.inv(cov) * hartlap_correction - d['cinv'] = cinv - - if mock: - mclpp = np.loadtxt(f"{self.ddir}/cls_default_dr6_accuracy.txt",usecols=[5]) - ls = np.arange(mclpp.size) - mclkk = mclpp * 2. * np.pi / 4. - self.clkk_data = self.binning_matrix @ mclkk[:self.kLmax] - - return d - - -def generic_lnlike(data_dict,ell_kk,cl_kk,ell_cmb,cl_tt,cl_ee,cl_te,cl_bb,trim_lmax = 2998): - - cl_kk = standardize(ell_kk,cl_kk,trim_lmax) - cl_tt = standardize(ell_cmb,cl_tt,trim_lmax) - cl_ee = standardize(ell_cmb,cl_ee,trim_lmax) - cl_bb = standardize(ell_cmb,cl_bb,trim_lmax) - cl_te = standardize(ell_cmb,cl_te,trim_lmax) - - d = data_dict - cinv = d['cinv'] - clkk_act = get_corrected_clkk(data_dict,cl_kk,cl_tt,cl_te,cl_ee,cl_bb) if d['likelihood_corrections'] else cl_kk - bclkk = d['binmat_act'] @ clkk_act - if d['include_planck']: - clkk_planck = get_corrected_clkk(data_dict,cl_kk,cl_tt,cl_te,cl_ee,cl_bb,'_planck') if d['likelihood_corrections'] else cl_kk - bclkk = np.append(bclkk, d['binmat_planck'] @ clkk_planck) - delta = d['data_binned_clkk'] - bclkk - lnlike = -0.5 * np.dot(delta,np.dot(cinv,delta)) - return lnlike, bclkk - - -# ================= -# Cobaya likelihood -# ================= - -class GenericLimberCosmicShear(InstallableLikelihood): - - zsrc: float - ngal_arcmin2: float - fsky: float - glmin = 10 - lmin = 10 - lmax = 500 - nell = 20 - shape_std = 0.3 - draw_noise = False - nz = 40 - trim_lmax = 599 - kmax = 10 - cmb_noise = None - - def initialize(self): - from orphics import stats - import pyfisher - bin_edges = np.geomspace(self.glmin,self.lmax,self.nell) - bin_edges = bin_edges[bin_edges>self.lmin] - self.binner = stats.bin1D(bin_edges) - self.ls = np.arange(0,self.trim_lmax+2) - if self.cmb_noise is None: - nls_dict = {'kk': lambda x: x*0+self.shape_std**2/(2.*self.ngal_arcmin2*1.18e7)} - else: - import pyfisher - ls,nls = pyfisher.get_lensing_nl(self.cmb_noise) - nls_dict = {'kk': interp1d(ls,nls,bounds_error=True)} - cl_kk = self.get_mock_theory() - cls_dict = {'kk': interp1d(self.ls,cl_kk)} - self.d = {} - self.d['data_binned_clkk'] = self.binner.bin(self.ls,cl_kk)[1] - cov = pyfisher.gaussian_band_covariance(bin_edges,['kk'],cls_dict,nls_dict,interpolate=False)[:,0,0] / self.fsky - cinv = np.diag(1./cov) - self.d['cinv'] = cinv - - def get_mock_theory(self): - import camb - from camb import model - pars = camb.CAMBparams() - pars.set_cosmology(H0=67.5, ombh2=0.022, omch2=0.122) - pars.InitPower.set_params(ns=0.965) - results = camb.get_background(pars) - PK = camb.get_matter_power_interpolator(pars, nonlinear=True, - hubble_units=False, k_hunit=False, kmax=self.kmax, - var1=model.Transfer_Weyl,var2=model.Transfer_Weyl, zmax=self.zsrc) - return get_limber_clkk_flat_universe(results,PK,self.trim_lmax,self.kmax,self.nz,zsrc=self.zsrc) - - - def get_requirements(self): - cobj = get_camb_lens_obj(self.nz,self.kmax,self.zsrc) - return cobj - - def logp(self, **params_values): - cl_kk = self.get_limber_clkk( **params_values) - bclkk = self.binner.bin(self.ls,cl_kk)[1] - delta = self.d['data_binned_clkk'] - bclkk - logp = -0.5 * np.dot(delta,np.dot(self.d['cinv'],delta)) - self.log.debug( - f"Generic Cosmic Shear lnLike value = {logp} (chisquare = {-2 * logp})") - return logp - - def get_limber_clkk(self,**params_values): - Pfunc = self.theory.get_Pk_interpolator(var_pair=("Weyl", "Weyl"), nonlinear=True, extrap_kmax=30.) - results = self.provider.get_CAMBdata() - return get_limber_clkk_flat_universe(results,Pfunc,self.trim_lmax,self.kmax,self.nz,zsrc=self.zsrc) - -class ACTDR6LensLike(InstallableLikelihood): - - lmax: int - mock = False - nsims_act = 792. # Number of sims used for covmat; used in Hartlap correction - nsims_planck = 400. # Number of sims used for covmat; used in Hartlap correction - no_like_corrections = False - lens_only = False - # Any ells above this will be discarded; likelihood must at least request ells up to this - trim_lmax = 2998 - variant = "act_baseline" - apply_hartlap = True - # Limber integral parameters - limber = False - nz = 100 - kmax = 10 - scale_cov = None - alens = False # Whether to divide the theory spectrum by Alens - - def initialize(self): - if self.lens_only: self.no_like_corrections = True - if self.lmax 0, "Data not found ! Add at least one of those 3 data sets 'tdcosmo7', 'SLACS_SDSS' or 'SLACS_IFU'" + # choose which likelihood you want here: + self._likelihood = LensSampleLikelihood(lens_list) + + # choose if you want the full astropy distance calculation or a interpolated version of it (for speed-up) + self._interpolate_distances_type = 'None' + + def cosmosis_cosmo_2_astropy_cosmo(self, block): + """ + + :param cosmosis_cosmo: cosmosis cosmology object + :return ~astropy.cosmology equivalent cosmology object + """ + H0 = block['cosmological_parameters', 'h0'] * 100 #in km/s/Mpc + om = block['cosmological_parameters', 'omega_m'] + ok = block['cosmological_parameters', 'omega_k'] + ob = block['cosmological_parameters', 'omega_b'] + w0 = block['cosmological_parameters', 'w'] + wa = block['cosmological_parameters', 'wa'] + mnu = block['cosmological_parameters', 'mnu'] + nnu = block['cosmological_parameters', 'nnu'] + + ol = 1 - om - ok + + if self._distances_computation_module == 'astropy': + # we are using standard astropy cosmology for distance compuation + cosmo = w0waCDM(H0=H0, Om0=om, Ode0=ol, Ob0=ob, w0=w0, wa=wa, m_nu=mnu, Neff=nnu) + elif self._distances_computation_module == 'CosmoInterp': + # we are using an interpolated version of the standard astropy cosmology (for speed-up) + cosmo = w0waCDM(H0=H0, Om0=om, Ode0=ol, Ob0=ob, w0=w0, wa=wa, m_nu=mnu, Neff=nnu) + cosmo = CosmoInterp(cosmo=cosmo, z_stop=5, num_interp=100) + elif self._distances_computation_module == 'camb': + # we use the camb distances + z_bg = block['distances', 'z'] + D_A = block['distances', 'd_A'] + K = ok * c.to('km/s').value * H0 #in Mpc^-2 + cosmo = CosmoInterp(ang_dist_list=D_A, z_list=z_bg, Ok0=ok, K=K) + else: + raise ValueError() + + return cosmo + + def likelihood(self, block): + cosmo = self.cosmosis_cosmo_2_astropy_cosmo(block) + + # here the additional parameters required to evaluate the likelihood in accordance with TDCOSMO IV Table 3 + lambda_mst = block['nuisance_strong_lensing', 'lambda_mst'] + log_lambda_mst_sigma = block['nuisance_strong_lensing', 'log_lambda_mst_sigma'] + lambda_mst_sigma = 10**log_lambda_mst_sigma + + alpha_lambda = block['nuisance_strong_lensing', 'alpha_lambda'] + + # We will define this parameter in the block in log space because the prior is uniform in log_ space. + # a_ani = block['nuisance_strong_lensing', 'a_ani'] + # a_ani_sigma = block['nuisance_strong_lensing', 'a_ani_sigma'] + + log_a_ani = block['nuisance_strong_lensing', 'log_a_ani'] + a_ani = 10**log_a_ani + + log_a_ani_sigma = block['nuisance_strong_lensing', 'log_a_ani_sigma'] + a_ani_sigma = 10**log_a_ani_sigma + + + kwargs_lens_test = {'lambda_mst': lambda_mst, # mean in the internal MST distribution + 'lambda_mst_sigma': lambda_mst_sigma, # Gaussian sigma of the distribution of lambda_mst + 'alpha_lambda': alpha_lambda, # slope of lambda_mst with r_eff/theta_E + } + kwargs_kin_test = {'a_ani': a_ani, # mean a_ani anisotropy parameter in the OM model + 'a_ani_sigma': a_ani_sigma, # sigma(a_ani)⟨a_ani⟩ is the 1-sigma Gaussian scatter in a_ani + } + + logl = self._likelihood.log_likelihood(cosmo=cosmo, kwargs_lens=kwargs_lens_test, kwargs_kin=kwargs_kin_test) + + return float(logl) + + +def setup(options): + options = SectionOptions(options) + return TDCOSMOlenses(options) + + +def execute(block, config): + like = config.likelihood(block) + block[names.likelihoods, "TDCOSMO_like"] = like + return 0 + diff --git a/number_density/correlated_priors/module.yaml b/number_density/correlated_priors/module.yaml index a121a3a3..9f73a2d7 100644 --- a/number_density/correlated_priors/module.yaml +++ b/number_density/correlated_priors/module.yaml @@ -11,43 +11,45 @@ assumptions: The matrix must be ordered to match the order of the input parameter list" explanation: - " We may have a set of nuisance parameters for each tomographic bin that we know to be - correlated. Examples include the mean redshift uncertainties, shear calibration errors - or slowly-evolving galaxy bias. This module allows us to include known - correlations between the parameters when sampling. - This module reads the estimated covariance between a set of parameters. Through a Cholesky - decomposition, it then returns a set of correlated parameter values for - a given input set of uncorrelated parameters. - " + This module converts a set of uncorrelated parameters into a set of correlated ones following + a covariance matrix. The covariance matrix is provided in block ascii format. The matrix must be + ordered to match the order of the input parameter list. The output parameters are updated with the + cholesky decomposition of the covariance matrix multiplied by the values of the input parameters. + The output parameters are then passed to the downstream modules. + + A typical example usage is converting from uncorrelated nuisance parameters following normal distributions + to multivariate normal ones. + + In future this functionality should be included in the cosmosis core. + params: uncorrelated_parameters: - meaning: The list of parameter names for the uncorrelated parameters that the sampler will vary + meaning: The list of parameter names for the uncorrelated parameters that the sampler will vary. The parameters should be in the form "section1/param1 section2/param2 ..." type: str default: + output_parameters: meaning: The list of parameter names for the output sample of correlated parameters. These must be named following the relevant expectation of the downstream modules. - For example the parameter for photo-z bias in bin i is expected to be called bias_i + For example the parameter for photo-z bias in bin i is expected to be called bias_i. + The parameters should be in the form "section1/param1 section2/param2 ..." type: str default: + covariance: meaning: Location of the covariance matrix defining the correlation between the parameters type: str default: inputs: - cov: - meaning: The covariance matrix read from the covariance file, ordered in the same sense - as the parameter list - type: real - default: - block[input_parameters]: - meaning: The values of the input paramaters in the block - type: real - default: + input_parameters_sections: + names: + meaning: The input parameter. The sections and names are defined in the uncorrelated_parameters parameter. + type: real + default: outputs: - block[output_parameters]: - meaning: The values of the output paramaters in the block are updated with the cholesky - decomposition of cov multipled by the values of the input parameters in the block. - type: real - default: + section1: + name1: + meaning: The values of the output paramaters, which have the appropriate correlations. The sections and names are defined in the output_parameters parameter. + type: real + default: diff --git a/shear/cosebis/modules/tostring.cc b/shear/cosebis/modules/tostring.cc index 4fd0995c..b114ad93 100644 --- a/shear/cosebis/modules/tostring.cc +++ b/shear/cosebis/modules/tostring.cc @@ -1,4 +1,6 @@ #include "tostring.h" +#include +#include void noBlanks(string& str) { @@ -8,32 +10,24 @@ void noBlanks(string& str) } string toString(const int i){ - ostrstream ost; - ost << i << '\0'; - return ost.str(); + return to_string(i); } string toString(const long l){ - ostrstream ost; - ost << l << '\0'; - return ost.str(); + return to_string(l); } string toString(const int short us){ - ostrstream ost; - ost << us << '\0'; - return ost.str(); + return to_string(us); } string toString(const int unsigned ui){ - ostrstream ost; - ost << ui << '\0'; - return ost.str(); + return to_string(ui); } string toString(const float f,int precision){ - ostrstream ost; + ostringstream ost; if (precision) ost.precision(precision); @@ -41,12 +35,12 @@ string toString(const float f,int precision){ ost.precision(0); ost.setf(ios::fixed,ios::floatfield); - ost << f << '\0'; + ost << f; return ost.str(); } string toString(const double d,int precision){ - ostrstream ost; + ostringstream ost; if (precision) ost.precision(precision); @@ -54,7 +48,7 @@ string toString(const double d,int precision){ ost.precision(0); ost.setf(ios::fixed,ios::floatfield); - ost << d << '\0'; + ost << d; return ost.str(); } diff --git a/shear/cosebis/modules/tostring.h b/shear/cosebis/modules/tostring.h index cceb6071..3d06a439 100644 --- a/shear/cosebis/modules/tostring.h +++ b/shear/cosebis/modules/tostring.h @@ -2,7 +2,6 @@ #define TOSTRING_H #include -#include using namespace std; diff --git a/structure/EuclidEmulator2/euclid_emulator2_interface.py b/structure/EuclidEmulator2/euclid_emulator2_interface.py index 46878d7e..78370d73 100644 --- a/structure/EuclidEmulator2/euclid_emulator2_interface.py +++ b/structure/EuclidEmulator2/euclid_emulator2_interface.py @@ -46,11 +46,12 @@ def execute(block, config): # Get z and k from the NL power section z, k, P = block.get_grid(input_section, "z", "k_h", "P_k") - _, b = ee2.get_boost(params, z, k) if len(z) > 100: raise ValueError("EuclidEmulator2 only allows up to 100 redshift values") + _, b = ee2.get_boost(params, z, k) + # Not sure why but b comes back as a dictionary of arrays # instead of a 2D array P_boosted = P.copy() diff --git a/structure/baccoemu/LICENSE b/structure/baccoemu/LICENSE new file mode 100644 index 00000000..1227a037 --- /dev/null +++ b/structure/baccoemu/LICENSE @@ -0,0 +1,20 @@ +Copyright (c) 2020 The Python Packaging Authority + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + diff --git a/structure/baccoemu/baccoemu_interface.py b/structure/baccoemu/baccoemu_interface.py new file mode 100644 index 00000000..a7e86387 --- /dev/null +++ b/structure/baccoemu/baccoemu_interface.py @@ -0,0 +1,207 @@ +from cosmosis.datablock import option_section, names +from scipy.interpolate import RectBivariateSpline +import numpy as np +import baccoemu_vendored as baccoemu +import traceback + + +def setup(options): + mode = options.get_string(option_section, "mode", default="nonlinear") + + # do this only once in the setup phase + emulator = baccoemu.Matter_powerspectrum() + + allowed_modes = ["nonlinear", "baryons", "nonlinear+baryons"] + if mode not in allowed_modes: + raise ValueError(f"unrecognised value of 'mode' parameter in baccoemu: {mode}") + + return mode, emulator + + +def check_params(params): + ranges = { + "omega_cold": [0.15, 0.6], + "omega_baryon": [0.03, 0.07], + "ns": [0.92, 1.01], + "hubble": [0.6, 0.8], + "neutrino_mass": [0.0, 0.4], + } + + for key, (vmin, vmax) in ranges.items(): + if not (params[key] > vmin) and (params[key] < vmax): + raise ValueError(f"BaccoEmu: {key} must be in range [{vmin},{vmax}]") + + +def execute(block, config): + mode, emulator = config + + try: + if mode == "nonlinear": + emulate_nonlinear_power(block, emulator) + elif mode == "nonlinear+baryons": + emulate_boosted_nonlinear_power(block, emulator) + elif mode == "baryons": + emulate_baryonic_boost(block, emulator) + else: + raise RuntimeError("This should not happen") + except ValueError as error: + # print traceback from exception + print(traceback.format_exc()) + return 1 + + return 0 + + +def emulate_nonlinear_power(block, emulator): + z_lin, k_lin, P_lin = block.get_grid("matter_power_lin", "z", "k_h", "p_k") + + # bacco specific stuff + # This is required to avoid a bounds error + zmask = z_lin < 1.5 + a_lin = 1 / (1 + z_lin[zmask]) + + kmask = (k_lin < 4.69) & (k_lin > 0.0001) + cosmo = names.cosmological_parameters + + omega_cold = block[cosmo, "omega_c"] + block[cosmo, "omega_b"] + Omb = block[cosmo, "omega_b"] + + params = { + "omega_cold": omega_cold, + "A_s": block[cosmo, "a_s"], + "omega_baryon": Omb, + "ns": block[cosmo, "n_s"], + "hubble": block[cosmo, "h0"], + "neutrino_mass": block[cosmo, "mnu"], + "w0": block.get_double(cosmo, "w", -1.0), + "wa": 0.0, + "expfactor": a_lin, + } + + # check we're within the allowed bounds for the emulator + check_params(params) + + # evaluate the nonlinear growth factor as a function of k and z + k_bacco, F = emulator.get_nonlinear_boost(k=k_lin[kmask], cold=False, **params) + k_nl = k_lin + z_nl = z_lin + + # interpolate it to the same sampling as the linear matter power spectrum + I = RectBivariateSpline(np.log10(k_bacco), z_lin[zmask], np.log10(F).T) + F_interp = 10 ** I(np.log10(k_nl), z_nl).T + + # apply the factor + P_nl = F_interp * P_lin + + # save everything + block.put_grid("matter_power_nl", "z", z_nl, "k_h", k_nl, "p_k", P_nl) + + return 0 + + +def emulate_boosted_nonlinear_power(block, emulator): + z_lin, k_lin, P_lin = block.get_grid("matter_power_lin", "z", "k_h", "p_k") + + # This is required to avoid a bounds error + zmask = z_lin < 1.5 + a_lin = 1 / (1 + z_lin[zmask]) + + kmask = (k_lin < 4.69) & (k_lin > 0.0001) + + cosmo = names.cosmological_parameters + + # In BACCO omega_cold refers to baryons + CDM + omega_cold = block[cosmo, "omega_c"] + block[cosmo, "omega_b"] + + params = { + "omega_cold": omega_cold, + "A_s": block[cosmo, "a_s"], + "omega_baryon": block[cosmo, "omega_b"], + "ns": block[cosmo, "n_s"], + "hubble": block[cosmo, "h0"], + "neutrino_mass": block[cosmo, "mnu"], + "w0": block.get_double(cosmo, "w", -1.0), + "wa": block.get_double(cosmo, "wa", 0.0), + "expfactor": a_lin, + "M_c": block["baryon_parameters", "m_c"], + "eta": block["baryon_parameters", "eta"], + "beta": block["baryon_parameters", "beta"], + "M1_z0_cen": block["baryon_parameters", "m1_z0_cen"], + "theta_out": block["baryon_parameters", "theta_out"], + "theta_inn": block["baryon_parameters", "theta_inn"], + "M_inn": block["baryon_parameters", "m_inn"], + } + + # check we're within the allowed bounds for the emulator + check_params(params) + + k_nl = k_lin + z_nl = z_lin + + # evaluate the nonlinear growth factor as a function of k and z + k_bacco, F = emulator.get_nonlinear_boost(k=k_lin[kmask], cold=False, **params) + I_nl = RectBivariateSpline(np.log10(k_bacco), z_lin[zmask], np.log10(F).T) + F_interp = 10 ** I_nl(np.log10(k_nl), z_nl).T + + # same thing for baryons + k_bacco, S = emulator.get_baryonic_boost(k=k_lin[kmask], **params) + I_baryon = RectBivariateSpline(np.log10(k_bacco), z_lin[zmask], S.T) + S_interp = I_baryon(np.log10(k_nl), z_nl).T + + # apply the factor + P_nl = F_interp * S_interp * P_lin + + # save everything + block.put_grid("matter_power_nl", "z", z_nl, "k_h", k_nl, "p_k", P_nl) + + return 0 + + +def emulate_baryonic_boost(block, emulator): + z_nl, k_nl, P_nl = block.get_grid("matter_power_nl", "z", "k_h", "p_k") + + # This is required to avoid a bounds error + zmask = z_nl < 1.5 + a_lin = 1 / (1 + z_nl[zmask]) + + kmask = (k_nl < 4.69) & (k_nl > 0.0001) + + cosmo = names.cosmological_parameters + + # In BACCO omega_cold refers to baryons + CDM + omega_cold = block[cosmo, "omega_c"] + block[cosmo, "omega_b"] + + params = { + "omega_cold": omega_cold, + "A_s": block[cosmo, "a_s"], + "omega_baryon": block[cosmo, "omega_b"], + "ns": block[cosmo, "n_s"], + "hubble": block[cosmo, "h0"], + "neutrino_mass": block[cosmo, "mnu"], + "w0": block.get_double(cosmo, "w", -1.0), + "wa": block.get_double(cosmo, "wa", 0.0), + "expfactor": a_lin, + "M_c": block["baryon_parameters", "m_c"], + "eta": block["baryon_parameters", "eta"], + "beta": block["baryon_parameters", "beta"], + "M1_z0_cen": block["baryon_parameters", "m1_z0_cen"], + "theta_out": block["baryon_parameters", "theta_out"], + "theta_inn": block["baryon_parameters", "theta_inn"], + "M_inn": block["baryon_parameters", "m_inn"], + } + + # check we're within the allowed bounds for the emulator + check_params(params) + + # just get the boost factor from bacco + k_bacco, S = emulator.get_baryonic_boost(k=k_nl[kmask], **params) + I_baryon = RectBivariateSpline(np.log10(k_bacco), z_nl[zmask], S.T) + S_interp = I_baryon(np.log10(k_nl), z_nl).T + + # apply the factor + P_nl *= S_interp + + # save everything + block.put_grid("matter_power_nl", "z", z_nl, "k_h", k_nl, "p_k", P_nl) + + return 0 diff --git a/structure/baccoemu/baccoemu_vendored/.gitignore b/structure/baccoemu/baccoemu_vendored/.gitignore new file mode 100644 index 00000000..e4e943ec --- /dev/null +++ b/structure/baccoemu/baccoemu_vendored/.gitignore @@ -0,0 +1,6 @@ +baryon_emu_* +cold_matter_linear_emu_* +no_wiggles_emu_* +sigma8_emu_* +nonlinear_emu_* +total_matter_linear_emu_* diff --git a/structure/baccoemu/baccoemu_vendored/__init__.py b/structure/baccoemu/baccoemu_vendored/__init__.py new file mode 100644 index 00000000..18c66e88 --- /dev/null +++ b/structure/baccoemu/baccoemu_vendored/__init__.py @@ -0,0 +1,16 @@ +import numpy as np +import copy +import pickle +import tqdm +import hashlib +from ._version import __version__ +from .utils import * +from .matter_powerspectrum import * +from .baryonic_boost import * +from .lbias_expansion import * + +import tensorflow +from packaging import version +required_tf_version = '2.6.0' +if version.parse(tensorflow.__version__) < version.parse(required_tf_version): + raise ImportError(f'tensorflow={tensorflow.__version__} is not supported by baccoemu. Please update tensorflow >= 2.6.0') diff --git a/structure/baccoemu/baccoemu_vendored/_version.py b/structure/baccoemu/baccoemu_vendored/_version.py new file mode 100644 index 00000000..9aa3f903 --- /dev/null +++ b/structure/baccoemu/baccoemu_vendored/_version.py @@ -0,0 +1 @@ +__version__ = "2.1.0" diff --git a/structure/baccoemu/baccoemu_vendored/baryonic_boost.py b/structure/baccoemu/baccoemu_vendored/baryonic_boost.py new file mode 100644 index 00000000..3892f0de --- /dev/null +++ b/structure/baccoemu/baccoemu_vendored/baryonic_boost.py @@ -0,0 +1,271 @@ +import numpy as np +import copy +import pickle +from .utils import _transform_space, MyProgressBar + +__all__ = ["get_baryon_fractions"] + +def load_baryonic_emu(fold_name=None, detail_name=None, verbose=True): + """Loads in memory the baryonic boost emulator, described in Aricò et al. 2020c. + + :param verbose: whether to activate the verbose mode, defaults to True. + :type verbose: boolean, optional + + :return: a dictionary containing the emulator object + :rtype: dict + """ + import os + if verbose: + print('Loading Baryonic Emulator...') + basefold = os.path.dirname(os.path.abspath(__file__)) + + from tensorflow.keras.models import load_model + + old_emulator_names = [(basefold + '/' + + "NN_emulator_sg_0.99_15000_PCA6_BNFalse_DO0.0_NL2_data_midmfcorr_10k")] + for old_emulator_name in old_emulator_names: + if os.path.exists(old_emulator_name): + import shutil + shutil.rmtree(old_emulator_name) + + if fold_name is not None: + emulator_name = fold_name + else: + emulator_name = (basefold + '/' + + "baryon_emu_1.0.0") + + if (not os.path.exists(emulator_name)): + import urllib.request + import tarfile + import ssl + ssl._create_default_https_context = ssl._create_unverified_context + print('Downloading Emulator data (5 Mb)...') + urllib.request.urlretrieve( + 'https://bacco.dipc.org/baryon_emu_1.0.0.tar', + emulator_name + '.tar', + MyProgressBar()) + tf = tarfile.open(emulator_name+'.tar', 'r') + tf.extractall(path=basefold) + tf.close() + os.remove(emulator_name + '.tar') + + emulator = {} + emulator['emu_type'] = 'nn' + emulator['model'] = load_model(emulator_name, compile=False) + detail_name = 'k_scaler_bounds.pkl' if detail_name is None else detail_name + with open(emulator_name + '/' +detail_name, 'rb') as f: + emulator['scaler'] = pickle.load(f) + emulator['pca'] = pickle.load(f) + emulator['k'] = pickle.load(f) + emulator['values'] = pickle.load(f) + if fold_name == None: + emulator['rotation'] = pickle.load(f) + emulator['bounds'] = pickle.load(f) + + if fold_name == None: + emulator['keys'] = ['omega_cold', 'sigma8_cold', 'omega_baryon', + 'ns', 'hubble', 'neutrino_mass', 'w0', 'wa', 'M_c', 'eta', 'beta', 'M1_z0_cen', + 'theta_inn', 'M_inn', 'theta_out', 'expfactor'] + else: + emulator['keys'] = ['omega_cold', 'sigma8_cold', 'omega_baryon', + 'hubble', 'M_c', 'eta', 'beta', 'M1_z0_cen', + 'theta_inn','M_inn','theta_out', 'expfactor'] + if verbose: + print('Baryonic Emulator loaded in memory.') + return emulator + +def get_baryon_fractions(M_200c, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, M_c=None, eta=None, beta=None, + M1_z0_cen=None, theta_out=None, theta_inn=None, M_inn=None): + """Compute the mass fraction of the different baryonic components, following the + baryonic correction model described in Aricò et al 2020b (see also Aricò et al 2020a). + + :param M_200: Halo mass inside a sphere which encompass a density 200 times larger than the critical density of the Universe. + :type array_like + :param omega_cold: omega cold matter (cdm + baryons), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_cold: float or array + :param omega_matter: omega total matter (cdm + baryons + neutrinos), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_matter: float or array + :param sigma8_cold: rms of cold (cdm + baryons) linear perturbations, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type sigma8_cold: float or array + :param A_s: primordial scalar amplitude at k=0.05 1/Mpc, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type A_s: float or array + :param hubble: adimensional Hubble parameters, h=H0/(100 km/s/Mpc) + :type hubble: float or array + :param ns: scalar spectral index + :type ns: float or array + :param neutrino_mass: total neutrino mass + :type neutrino_mass: float or array + :param w0: dark energy equation of state redshift 0 parameter + :type w0: float or array + :param wa: dark energy equation of state redshift dependent parameter + :type wa: float or array + :param expfactor: expansion factor a = 1 / (1 + z) + :type expfactor: float or array + :param M_c: mass fraction of hot gas in haloes + :type M_c: float or array + :param eta: extent of ejected gas + :type eta: float or array + :param beta: mass fraction of hot gas in haloes + :type beta: float or array + :param M1_z0_cen: characteristic halo mass scale for central galaxy + :type M1_z0_cen: float or array + :param theta_out: density profile of hot gas in haloes + :type theta_out: float or array + :param theta_inn: density profile of hot gas in haloes + :type theta_inn: float or array + :param M_inn: density profile of hot gas in haloes + :type M_inn: float or array + + :return: a dictionary containing the baryonic components mass fractions, with the following keywords: + + #. 'ej_gas' -> ejected gas + #. 'cen_galaxy' -> central galaxy + #. 'sat_galaxy' -> satellite galaxy + #. 'bo_gas' -> bound gas + #. 're_gas' -> reaccreted gas + #. 'dark_matter' -> dark matter + #. 'gas' -> total gas + #. 'stellar' -> total stars + #. 'baryon' -> total baryons + + :rtype: dict + """ + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + + coord = copy.deepcopy(kwargs) + for par in ['M_c','eta','beta','M1_z0_cen','theta_out','theta_inn','M_inn']: + coord[par] = 10**(coord[par]) + + stellar_pars = _SMHM_relation(coord) + frac_cg = _galaxy_fraction(stellar_pars, M_200c, 'centrals') + frac_sg = _galaxy_fraction(stellar_pars, M_200c, 'satellites') + frac_stars = frac_cg + frac_sg + + + o_m = coord['omega_matter'] if coord['omega_matter'] is not None else coord['omega_cold'] + coord['neutrino_mass'] / 93.14 / coord['hubble']**2 + + baryon_matter_ratio = coord['omega_baryon']/o_m + + if np.any(frac_stars > baryon_matter_ratio): + raise ValueError(""" Your stellar fraction is larger than the baryon fraction! + Please use meaningful stellar parameters""") + + frac_bg = (baryon_matter_ratio-frac_stars)/(1+(coord['M_c']/M_200c)**coord['beta']) + frac_bar = frac_bg + frac_stars + + M_r = 1e16 + beta_r = 2. + frac_re = (baryon_matter_ratio-frac_bar)/(1+(M_r/M_200c)**beta_r) + frac_bg -= frac_re #fraction of reaccreted gas is taken from the bound gas + frac_eg = baryon_matter_ratio - frac_bar + frac_dm = 1 - baryon_matter_ratio + + frac_gas = frac_bg + frac_eg + frac_re + return {'ej_gas': np.array(frac_eg, dtype=np.float32), + 'cen_galaxy': np.array(frac_cg, dtype=np.float32), + 'sat_galaxy': np.array(frac_sg, dtype=np.float32), + 'bo_gas': np.array(frac_bg, dtype=np.float32), + 're_gas': np.array(frac_re, dtype=np.float32), + 'dark_matter': np.array(frac_dm, dtype=np.float32), + 'gas': np.array(frac_gas, dtype=np.float32), + 'stellar': np.array(frac_stars, dtype=np.float32), + 'baryon': np.array(baryon_matter_ratio, dtype=np.float32), + } + +def _SMHM_relation(coordinates): + """ + Internal function which evolve the Stellar Mass to Halo Mass (SMHM) relation parameters + at the correct redshift, following Behroozi et al. 2013. + + :param coordinates: a set of coordinates in parameter space + :type coordinates: dict + :param a: expansion factor + :type a: float + :return: dictionary with the evolved SHAM parameters. + :rtype: dictionary + """ + a = coordinates['expfactor'] + z = 1/a -1 + nu = np.exp(-4*a**2) #Exponential cutoff of evolution of M ∗ (M h ) with scale factor + + pars = {} + pars['M1_z0_cen'] = np.float64(coordinates['M1_z0_cen']) + pars['epsilon_z0_cen'] = np.float32(0.023) + pars['alpha_z0_cen'] = np.float32(-1.779) + pars['gamma_z0_cen'] = np.float32(0.547) + pars['delta_z0_cen'] = np.float32(4.394) + + pars['M1_fsat'] = np.float32(1.59) + pars['epsilon_fsat'] = np.float32(0.2) + pars['alpha_fsat'] = np.float32(0.16) + pars['gamma_fsat'] = np.float32(1.67) + pars['delta_fsat'] = np.float32(0.99) + + ini = {'a':0,'a2':0,'z':0} + stellar_pars = { + 'M1': copy.deepcopy(ini), # Charactheristic halo mass Msolar/h + 'epsilon':copy.deepcopy(ini), # Characteristic stellar mass to halo mass ratio + 'alpha':copy.deepcopy(ini), # Faint-end slope of SMHM relation + 'delta':copy.deepcopy(ini), #Index of subpower law at massive end of SMHM relation + 'gamma':copy.deepcopy(ini) #Strength of subpower law at massive end of SMHM relation + } + + stellar_pars['M1']['a'] = -1.793; stellar_pars['M1']['z'] = -0.251 + stellar_pars['alpha']['a'] = 0.731; + stellar_pars['gamma']['a'] = 1.319; stellar_pars['gamma']['z'] = 0.279 + stellar_pars['delta']['a'] = 2.608; stellar_pars['delta']['a'] = -0.043 + stellar_pars['epsilon']['a'] = -0.006; stellar_pars['epsilon']['a2'] = -0.119; + + #for central galaxies: + for p in stellar_pars.keys(): + p0_cen = np.log10(pars[p+'_z0_cen']) if p in ['M1','epsilon'] else pars[p+'_z0_cen'] + pcen_z = p0_cen + nu*(stellar_pars[p]['a']*(a-1) + stellar_pars[p]['z']*z) + stellar_pars[p]['a2']*(a-1) + pars[p+'_cen'] = 10**(pcen_z) if p in ['M1','epsilon'] else pcen_z + + #for satellites: + for p in stellar_pars.keys(): + pars[p+'_sat'] = pars[p+'_cen'] * pars[p+'_fsat'] + return pars + +def _galaxy_fraction(pars, M_200, type='centrals'): + """ + Function which compute the galaxy mass fractions. + :param pars: set of SHAM parameters + :type pars: dict + :param M_200: Halo mass inside a sphere which encompass a density 200 times larger than the critical density of the Universe. + :type array_like + :param type: 'centrals' to select central galaxies, 'satellites' to select satellites galaxies. + :type string + :return: galaxy mass fractions. + :rtype: array_like + """ + t = '_cen' if type == 'centrals' else '_sat' + return _stellar_fraction(M_200, M1=pars['M1'+t], alpha=pars['alpha'+t], + gamma=pars['gamma'+t],delta=pars['delta'+t],epsilon=pars['epsilon'+t]) + +def _stellar_fraction(M_200, M1=1.526e11, alpha= -1.779, gamma = 0.547, delta = 4.394, epsilon=0.023): + """ + Internal function which compute the galaxy mass fractions. + + :param M_200: Halo mass inside a sphere which encompass a density 200 times larger than the critical density of the Universe. + :type array_like + :return: galaxy mass fractions. + :rtype: array_like + """ + fact = 10**( _g(np.log10(M_200/M1), alpha, gamma, delta) - _g(0, alpha, gamma, delta)) + return epsilon * (M1/M_200) * fact + +def _g(x, alpha= -1.779, gamma = 0.547, delta = 4.394): + return -np.log10( 10**(alpha*x) + 1) + \ + delta * ( (np.log10( 1+np.exp(x) ))**gamma ) / ( 1 + np.exp(10**(-x)) ) diff --git a/structure/baccoemu/baccoemu_vendored/lbias_expansion.py b/structure/baccoemu/baccoemu_vendored/lbias_expansion.py new file mode 100644 index 00000000..5af3f43b --- /dev/null +++ b/structure/baccoemu/baccoemu_vendored/lbias_expansion.py @@ -0,0 +1,748 @@ +import numpy as np +import copy +import pickle +import os +from .utils import _transform_space, MyProgressBar, mean_absolute_exp_percentage_error, accuracy_exp_01, accuracy_exp_005 +from scipy import interpolate +import tensorflow +tensorflow.compat.v1.logging.set_verbosity(tensorflow.compat.v1.logging.ERROR) +from tensorflow.keras.models import load_model +gpus = tensorflow.config.experimental.list_physical_devices('GPU') +if gpus: + for gpu in gpus: + tensorflow.config.experimental.set_memory_growth(gpu, True) +from .matter_powerspectrum import load_smeared_bao_emu + + +__all__ = ["Lbias_expansion"] + +class Lbias_expansion(object): + """ + A class to load and call the baccoemu for the Lagrangian bias expansion terms. + By default, the nonlinear Lagrangian bias expansion terms emulator (described + in Zennaro et al, 2021) and LPT lagrangian bias expansion terms emulator + (described in Aricò et al, 2021) are loaded. + Another emulator loaded by deafult is the IR-resummed linear power spectrum. + + :param lpt: whether to load the LPT emulator, defaults to True + :type lpt: boolean, optional + :param compute_sigma8: whether to load the sigma8 emulator, defaults to True + :type compute_sigma8: boolean, optional + :param smeared_bao: whether to load the smeared bao, defaults to True + :type smeared_bao: boolean, optional + :param nonlinear_boost: whether to load the nonlinear boost emulator, defaults to True + :type nonlinear_boost: boolean, optional + :param compute_sigma8: whether to load the sigma8 emulator, defaults to True + :type compute_sigma8: boolean, optional + :param verbose: whether to activate the verbose mode, defaults to True + :type verbose: boolean, optional + + """ + def __init__(self, lpt=True, smeared_bao=True, nonlinear_boost=True, compute_sigma8=True, verbose=True): + + self.verbose = verbose + + self.compute_lpt = True if lpt else False + self.compute_smeared_bao = True if smeared_bao else False + + self.cosmo_keys = np.array(['omega_cold', 'sigma8_cold', 'omega_baryon', 'ns', + 'hubble', 'neutrino_mass', 'w0', 'wa', 'expfactor']) + + self.lb_term_labels = [r'$1 1$', r'$1 \delta$', r'$1 \delta^2$', r'$1 s^2$', + r'$ 1 \nabla^2\delta$', r'$\delta \delta$', + r'$\delta \delta^2$', r'$\delta s^2$', + r'$\delta \nabla^2\delta$', r'$\delta^2 \delta^2$', + r'$\delta^2 s^2$', r'$\delta^2 \nabla^2\delta$', + r'$s^2 s^2$', r'$s^2 \nabla^2\delta$', + r'$\nabla^2\delta \nabla^2\delta$'] + + self.emulator = {} + if self.compute_lpt: + self.emulator['lpt'] = load_lpt_emu() + + if self.compute_smeared_bao: + self.emulator['smeared_bao'] = load_smeared_bao_emu() + + self.compute_nonlinear_boost = True if nonlinear_boost else False + if self.compute_nonlinear_boost: + self.emulator['nonlinear'] = load_nonlinear_lbias_emu() + + self.compute_sigma8 = True if compute_sigma8 else False + + if self.compute_sigma8: + from .matter_powerspectrum import Matter_powerspectrum + self.matter_powerspectrum_emulator = Matter_powerspectrum(linear=False, smeared_bao=False, + nonlinear_boost=False, baryonic_boost=False, + compute_sigma8=True, verbose=verbose) + + def _get_parameters(self, coordinates, which_emu, grid=None): + """ + Function that returns a dictionary of cosmological parameters, + computing derived cosmological parameters, if not + already present in the given coordinates, and checking the relevant boundaries. + :param coordinates: a set of coordinates in parameter space + :type coordinates: dict + :param which_emu: kind of emulator: options are 'linear', 'nonlinear','baryon','smeared_bao','sigma8' + :type which_emu: str + :param grid: dictionary with parameter and vector of values where to evaluate the emulator, defaults to None + :type grid: array_like, optional + :return: coordinates with derived parameters + :rtype: dict + """ + coordinates = {key: np.atleast_1d(coordinates[key]) for key in set(list(coordinates.keys())) - set(['k', 'k_lin', 'pk_lin'])} + + avail_pars = [coo for coo in coordinates.keys() if coordinates[coo][0] is not None] #parameters currently available + eva_pars = self.emulator[which_emu]['keys'] #parameters strictly needed to evaluate the emulator + req_pars = self.emulator[which_emu]['keys'] #parameters needed for a computation + comp_pars = list(set(req_pars)-set(avail_pars)) #parameters to be computed + deriv_pars = ['omega_cold','sigma8_cold', 'A_s'] #derived parameters that can be computed + miss_pars = list(set(comp_pars)-set(deriv_pars)) #parameters missing from coordinates + extra_pars = list(set(req_pars)-set(eva_pars)) #requested parameters not needed for evaluation + if miss_pars: + print(f"{which_emu} emulator:") + print(f" Please add the parameter(s) {miss_pars} to your coordinates!") + raise KeyError(f"{which_emu} emulator: coordinates need the following parameters: ", miss_pars) + + if ('omega_cold' in avail_pars) & ('omega_matter' in avail_pars): + assert len(coordinates['omega_cold']) == len(coordinates['omega_matter']), 'Both omega_cold and omega_matter were provided, but they have different len' + om_from_oc = coordinates['omega_cold'] + coordinates['neutrino_mass'] / 93.14 /coordinates['hubble']**2 + assert np.all(np.abs(coordinates['omega_matter'] - om_from_oc) < 1e-4), 'Both omega_cold and omega_matter were provided, but they are inconsistent among each other' + + if 'omega_cold' in comp_pars: + if 'omega_matter' not in avail_pars: + raise KeyError('One parameter between omega_matter and omega_cold must be provided!') + + omega_nu = coordinates['neutrino_mass'] / 93.14 /coordinates['hubble']**2 + coordinates['omega_cold'] = coordinates['omega_matter'] - omega_nu + + if ('sigma8_cold' not in avail_pars) & ('A_s' not in avail_pars): + raise KeyError('One parameter between sigma8_cold and A_s must be provided!') + + if ('sigma8_cold' in avail_pars) & ('A_s' in avail_pars): + #commented for the cases where one is computed and same value is repeated + #assert len(np.atleast_1d(coordinates['sigma8_cold'])) == len(atleast_1d(coordinates['A_s'])), 'Both sigma8_cold and A_s were provided, but they have different len' + + ignore_s8_pars = copy.deepcopy(coordinates) + del ignore_s8_pars['sigma8_cold'] + s8_from_A_s = self.matter_powerspectrum_emulator.get_sigma8(**ignore_s8_pars) + assert np.all(np.abs(coordinates['sigma8_cold'] - s8_from_A_s) < 1e-4), 'Both sigma8_cold and A_s were provided, but they are inconsistent among each other' + + if 'sigma8_cold' in comp_pars: + tmp_coords = copy.deepcopy(coordinates) + tmp_coords['cold']=True + coordinates['sigma8_cold'] = np.atleast_1d(self.matter_powerspectrum_emulator.get_sigma8(**tmp_coords)) + + if 'A_s' in comp_pars: + tmp_coords = copy.deepcopy(coordinates) + del tmp_coords['sigma8_cold'] + tmp_coords['A_s'] = 2e-9 + tmp_coords['cold'] = True + coordinates['A_s'] = np.atleast_1d((coordinates['sigma8_cold'] / self.matter_powerspectrum_emulator.get_sigma8(**tmp_coords))**2 * tmp_coords['A_s']) + + + pp = np.squeeze([coordinates[p][0] for p in eva_pars]) + coords_out = copy.deepcopy(coordinates) + + grid = {} + for key in coordinates.keys(): + if len(np.atleast_1d(coordinates[key])) > 1: + grid[key] = np.array(coordinates[key]) + + if len(list(grid.keys()))==0: + grid = None + else: + grid_structure = [] + for key in grid.keys(): + grid_structure.append(len(grid[key])) + grid_structure = np.array(grid_structure) + values, counts = np.unique(grid_structure, return_counts=True) + counts_but_highest = np.delete(counts, np.argmax(counts)) + assert np.all(counts == counts[0]) | np.all(counts_but_highest == 1), 'When passing multiple coordinate sets you should either vary only on parameter, or all parameters should have the same len' + + if grid is not None: + grid_pars = list(grid.keys()) # list of parameters that are varyied in a grid + N = len(grid[grid_pars[0]]) + pp = np.tile(pp, (N, 1)) + for par in grid_pars: + if par in eva_pars: + index = eva_pars.index(par) + pp[:,index] = np.float64(grid[par]) + if par in req_pars: + coords_out[par] = grid[par] + pp = np.float64(pp) + + for i,par in enumerate(eva_pars): + val = pp[i] if grid is None else pp[:,i] + message = 'Param {}={} out of bounds [{}, {}]'.format( + par, val, self.emulator[which_emu]['bounds'][i][0], self.emulator[which_emu]['bounds'][i][1]) + + assert np.all(val >= self.emulator[which_emu]['bounds'][i][0]) & np.all(val <= self.emulator[which_emu]['bounds'][i][1]), message + + if extra_pars: + cc = np.squeeze([coords_out[p] for p in extra_pars]) + if None in cc: + raise ValueError(f'None in parameters: {extra_pars} = {cc}!') + + return coords_out, pp, grid + + def get_galaxy_real_pk(self, bias=None, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, k=None, **kwargs): + """Compute the predicted galaxy auto pk and galaxy-matter cross pk given a set of bias parameters + + :param bias: a list of bias parameters, including b1, b2, bs2, blaplacian + :type bias: array-like + :param omega_cold: omega cold matter (cdm + baryons), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_cold: float or array + :param omega_matter: omega total matter (cdm + baryons + neutrinos), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_matter: float or array + :param sigma8_cold: rms of cold (cdm + baryons) linear perturbations, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type sigma8_cold: float or array + :param A_s: primordial scalar amplitude at k=0.05 1/Mpc, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type A_s: float or array + :param hubble: adimensional Hubble parameters, h=H0/(100 km/s/Mpc) + :type hubble: float or array + :param ns: scalar spectral index + :type ns: float or array + :param neutrino_mass: total neutrino mass + :type neutrino_mass: float or array + :param w0: dark energy equation of state redshift 0 parameter + :type w0: float or array + :param wa: dark energy equation of state redshift dependent parameter + :type wa: float or array + :param expfactor: expansion factor a = 1 / (1 + z) + :type expfactor: float or array + :param k: a vector of wavemodes in h/Mpc at which the nonlinear boost will be computed, if None + the default wavemodes of the nonlinear emulator will be used, defaults to None + :type k: array_like, optional + :return: k and P(k), a list of the emulated 15 LPT Lagrangian bias expansion terms + :rtype: tuple + """ + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + + import itertools + + assert len(bias) == 4, 'Please, pass a valid bias array, with b1, b2, bs2, blaplacian' + + k, pnn = self.get_nonlinear_pnn(**kwargs) + bias = np.concatenate(([1], bias)) + prod = np.array(list(itertools.combinations_with_replacement(np.arange(len(bias)), r=2))) + + pgal_auto = 0 + for i in range(len(pnn)): + fac = 2 if prod[i, 0] != prod[i,1] else 1 + pgal_auto += bias[prod[i, 0]] * bias[prod[i,1]] * fac * pnn[i] + pgal_cross = np.dot(bias, pnn[:5]) + + return k, pgal_auto, pgal_cross + + + def get_nonlinear_pnn(self, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, k=None, **kwargs): + """Compute the prediction of the nonlinear cold matter power spectrum. + + :param omega_cold: omega cold matter (cdm + baryons), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_cold: float or array + :param omega_matter: omega total matter (cdm + baryons + neutrinos), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_matter: float or array + :param sigma8_cold: rms of cold (cdm + baryons) linear perturbations, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type sigma8_cold: float or array + :param A_s: primordial scalar amplitude at k=0.05 1/Mpc, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type A_s: float or array + :param hubble: adimensional Hubble parameters, h=H0/(100 km/s/Mpc) + :type hubble: float or array + :param ns: scalar spectral index + :type ns: float or array + :param neutrino_mass: total neutrino mass + :type neutrino_mass: float or array + :param w0: dark energy equation of state redshift 0 parameter + :type w0: float or array + :param wa: dark energy equation of state redshift dependent parameter + :type wa: float or array + :param expfactor: expansion factor a = 1 / (1 + z) + :type expfactor: float or array + :param k: a vector of wavemodes in h/Mpc at which the nonlinear boost will be computed, if None + the default wavemodes of the nonlinear emulator will be used, defaults to None + :type k: array_like, optional + :return: k and P(k), a list of the emulated 15 LPT Lagrangian bias expansion terms + :rtype: tuple + """ + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + + if not self.compute_nonlinear_boost: + raise ValueError("Please enable the l-bias nonlinear boost!") + + coordinates, pp, grid = self._get_parameters(kwargs, 'nonlinear') + emulator = self.emulator['nonlinear'] + + n_log = [0,1,5,9,12,14] + n_switch = [10 , 11] + + _pp = _transform_space(np.array([pp]), space_rotation=False, bounds=emulator['bounds']) + + tmp_coords = copy.deepcopy(kwargs) + tmp_coords['k'] = emulator['k'] + _, pk_lpt = self.get_lpt_pk(**tmp_coords) + _, pk_bao = self.get_smeared_bao_pk(**tmp_coords) + + pk_lpt[0] = pk_bao + pk_lpt[1] = pk_bao + pk_lpt[5] = pk_bao + pk_lpt[4] = -pk_bao * emulator['k']**2 + pk_lpt[8] = -pk_bao * emulator['k']**2 + pk_lpt[14] = pk_bao * emulator['k']**4 + + P_nn = [] + for n in range(15): + prediction = emulator['model'][n](_pp.reshape(-1,9), training=False) + # import pdb; pdb.set_trace() + if n in n_switch: + lpt_term = pk_lpt[n + 2] + else: + lpt_term = pk_lpt[n] + if n in n_log: + _this_P_nn = np.squeeze(np.exp(emulator['scaler'][n].inverse_transform(prediction)) * lpt_term) + else: + _this_P_nn = np.squeeze(emulator['scaler'][n].inverse_transform(prediction) * lpt_term) + if n in n_switch: + if len(pk_lpt.shape) == 2: + _this_P_nn[:25] = _this_P_nn[:25] * pk_lpt[n][:25] / lpt_term[:25] + else: + _this_P_nn[:,:25] = _this_P_nn[:,:25] * pk_lpt[n,:,:25] / lpt_term[:,:25] + P_nn.append(_this_P_nn) + + if k is not None: + if max(k) > 0.75: + raise ValueError(f""" + The maximum k of the l-bias nonlinear emulator must be 0.75 h/Mpc: + the current value is {max(k)} h/Mpc""") + if (min(k) <= 1e-2)&(self.verbose): + print("WARNING: the nonlinear emulator is extrapolating to k < 0.01 h/Mpc!") + + new_P_nn = [] + for n in range(15): + unexpected_negative = np.any(P_nn[n] <= 0.0) # can happen when allowing extrapolation + if (n in n_log) & (unexpected_negative is False): + new_P_nn.append(np.exp(interpolate.interp1d(np.log(emulator['k']), np.log(P_nn[n]), kind='cubic', axis=0 if grid is None else 1, fill_value='extrapolate')(np.log(k)))) + else: + new_P_nn.append(interpolate.interp1d(np.log(emulator['k']), P_nn[n], kind='cubic', axis=0 if grid is None else 1, fill_value='extrapolate')(np.log(k))) + P_nn = np.array(new_P_nn) + else : + k = emulator['k'] + + return k, P_nn + + def get_lpt_pk(self, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, k=None, **kwargs): + """Compute the prediction of the 15 LPT Lagrangian bias expansion terms. + + + :param omega_cold: omega cold matter (cdm + baryons), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_cold: float or array + :param omega_matter: omega total matter (cdm + baryons + neutrinos), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_matter: float or array + :param sigma8_cold: rms of cold (cdm + baryons) linear perturbations, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type sigma8_cold: float or array + :param A_s: primordial scalar amplitude at k=0.05 1/Mpc, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type A_s: float or array + :param hubble: adimensional Hubble parameters, h=H0/(100 km/s/Mpc) + :type hubble: float or array + :param ns: scalar spectral index + :type ns: float or array + :param neutrino_mass: total neutrino mass + :type neutrino_mass: float or array + :param w0: dark energy equation of state redshift 0 parameter + :type w0: float or array + :param wa: dark energy equation of state redshift dependent parameter + :type wa: float or array + :param expfactor: expansion factor a = 1 / (1 + z) + :type expfactor: float or array + :param k: a vector of wavemodes in h/Mpc at which the nonlinear boost will be computed, if None + the default wavemodes of the nonlinear emulator will be used, defaults to None + :type k: array_like, optional + :return: k and P(k), a list of the emulated 15 LPT Lagrangian bias expansion terms + :rtype: tuple + """ + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + + if not self.compute_lpt: + raise ValueError("Please enable the lpt emulator!") + + emulator = self.emulator['lpt'] + coordinates, pp, grid = self._get_parameters(kwargs, 'lpt') + + sub = emulator['sub'] + scaler = emulator['scaler'] + + P_nn = [] + for n in range(15): + pred = emulator['model'][n](pp.reshape(-1,9), training=False) + prediction = np.squeeze(scaler[n].inverse_transform(pred)) + P_nn.append(prediction) + + if k is not None: + if max(k) > 0.75: + raise ValueError(f""" + The maximum k of the l-bias lpt emulator must be 0.75 h/Mpc: + the current value is {max(k)} h/Mpc""") + if (min(k) <= 1e-2)&(self.verbose): + print("WARNING: the l-bias lpt emulator is extrapolating to k < 0.01 h/Mpc!") + + for n in range(15): + p_interp = interpolate.interp1d(np.log(emulator['k']), P_nn[n], kind='cubic', axis=0 if grid is None else 1, fill_value='extrapolate', + assume_sorted=True) + P_nn[n] = p_interp(np.log(k)) + else : + k = emulator['k'] + + P_nn = np.array([np.exp(P_nn[n])-sub[n] for n in range(15)]) + return k, P_nn + + def get_smeared_bao_pk(self, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, k=None, **kwargs): + """Evaluate the smeared bao emulator at a set of coordinates in parameter space. + + :param omega_cold: omega cold matter (cdm + baryons), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_cold: float or array + :param omega_matter: omega total matter (cdm + baryons + neutrinos), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_matter: float or array + :param sigma8_cold: rms of cold (cdm + baryons) linear perturbations, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type sigma8_cold: float or array + :param A_s: primordial scalar amplitude at k=0.05 1/Mpc, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type A_s: float or array + :param hubble: adimensional Hubble parameters, h=H0/(100 km/s/Mpc) + :type hubble: float or array + :param ns: scalar spectral index + :type ns: float or array + :param neutrino_mass: total neutrino mass + :type neutrino_mass: float or array + :param w0: dark energy equation of state redshift 0 parameter + :type w0: float or array + :param wa: dark energy equation of state redshift dependent parameter + :type wa: float or array + :param expfactor: expansion factor a = 1 / (1 + z) + :type expfactor: float or array + :param k: a vector of wavemodes in h/Mpc at which the nonlinear boost will be computed, if None + the default wavemodes of the nonlinear emulator will be used, defaults to None + :type k: array_like, optional + :return: k and P(k), a list of the emulated 15 LPT Lagrangian bias expansion terms + :rtype: tuple + """ + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + + if not self.compute_smeared_bao: + raise ValueError("Please enable the smeared bao emulator!") + + emulator = self.emulator['smeared_bao'] + coordinates, pp, grid = self._get_parameters(kwargs, 'smeared_bao') + + ypred = emulator['model'](pp.reshape(-1,9), training=False) + pk_bao = np.squeeze(np.exp(emulator['scaler'].inverse_transform(ypred))) + if k is not None: + if (max(k) > 30.)|(min(k) < 1e-3): + raise ValueError(f""" + A minimum k > 0.001 h/Mpc and a maximum k < 30 h/Mpc + are required for the linear emulator: + the current values are {min(k)} h/Mpc and {max(k)} h/Mpc + """) + + else: + pk_bao = np.exp(interpolate.interp1d(np.log(emulator['k']),np.log(pk_bao), kind='cubic', axis=0 if grid is None else 1, fill_value='extrapolate')(np.log(k))) + else: + k = emulator['k'] + return k, pk_bao + + def _vector_eval_lpt_pk(self, coordinates): + """Get the lpt pk in a fast vectorized way + + Note: no checks are performed to increase speed, be aware of what you do + + :param coordinates: 2D array with a grid of cooordinates + :type coordinates: array + """ + emulator = self.lpt_emulator + sub = emulator['sub'] + scaler = emulator['scaler'] + + P_nn = [] + for n in range(15): + pred = emulator['model'][n](coordinates, training=False) + prediction = np.exp(scaler[n].inverse_transform(pred)) - sub[n] + P_nn.append(prediction) + return np.array(P_nn) + + def _vector_eval_smeared_bao_pk(self, coordinates): + """Get the nonlinear pk in a fast vectorized way + + Note: no checks are performed to increase speed, be aware of what you do + + :param coordinates: 2D array with a grid of cooordinates + :type coordinates: array + """ + emulator = self.smeared_bao_emulator + ypred = emulator['model'](coordinates, training=False) + pk_bao = np.exp(emulator['scaler'].inverse_transform(ypred)) + return pk_bao + + + def _vector_eval_nonlinear_pnn(self, coordinates): + """Get the nonlinear pk in a fast vectorized way + + Note: no checks are performed to increase speed, be aware of what you do + + :param coordinates: 2D array with a grid of cooordinates + :type coordinates: array + """ + from scipy.interpolate import interp1d + emulator = self.nonlinear_emulator + _pp = _transform_space(coordinates, space_rotation=False, bounds=emulator['bounds']) + + pk_lpt = self._vector_eval_lpt_pk(coordinates) + pk_bao = self._vector_eval_smeared_bao_pk(coordinates) + pk_bao_interp = np.exp(interp1d(np.log(self.smeared_bao_emulator['k']), np.log(pk_bao), kind='cubic')(np.log(emulator['k']))) + + pk_lpt[0,:,:] = pk_bao_interp + pk_lpt[1,:,:] = pk_bao_interp + pk_lpt[5,:,:] = pk_bao_interp + pk_lpt[4,:,:] = -pk_bao_interp * emulator['k']**2 + pk_lpt[8,:,:] = -pk_bao_interp * emulator['k']**2 + pk_lpt[14,:,:] = pk_bao_interp * emulator['k']**4 + + P_nn = [] + n_log = [0,1,5,9,12,14] + n_switch = [10 , 11] + for n in range(15): + prediction = emulator['model'][n](_pp, training=False) + if n in n_switch: + lpt_term = pk_lpt[n + 2,:,:] + else: + lpt_term = pk_lpt[n,:,:] + if n in n_log: + _this_P_nn = np.exp(emulator['scaler'][n].inverse_transform(prediction)) * lpt_term + else: + _this_P_nn = emulator['scaler'][n].inverse_transform(prediction) * lpt_term + if n in n_switch: + _this_P_nn[:,:25] = _this_P_nn[:,:25] * pk_lpt[n,:,:25] / lpt_term[:,:25] + P_nn.append(_this_P_nn) + + return np.array(P_nn) + + def _vector_eval_galaxy_real_pk(self, coordinates, bias): + """Get the galaxy pk in a fast vectorized way + + Note: no checks are performed to increase speed, be aware of what you do + + :param coordinates: 2D array with a grid of cooordinates + :type coordinates: array + :param bias: 2D array with a grid of bias + :type bias: array + """ + import itertools + + pnn = self._vector_eval_nonlinear_pnn(coordinates) + bias = np.hstack([np.full((len(coordinates), 1), 1), bias]) + prod = np.array(list(itertools.combinations_with_replacement(np.arange(bias.shape[1]), r=2))) + + pgal_auto = np.zeros((pnn.shape[1], pnn.shape[2])) + pgal_cross = np.zeros((pnn.shape[1], pnn.shape[2])) + for i in range(len(pnn)): + fac = 2 if prod[i, 0] != prod[i, 1] else 1 + pgal_auto += (bias[:, prod[i, 0]] * bias[:, prod[i, 1]] * fac * pnn[i, :, :].T).T + if i < 5: + pgal_cross += (bias[:, i] * pnn[i, :, :].T).T + + return self.nonlinear_emulator['k'], pgal_auto, pgal_cross + + def Hubble(self, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, k=None, **kwargs): + """Hubble function in km / s / Mpc + + Warning: neutrino and dynamical dark energy not yet implemented + Warning: no radiation included + """ + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + O_m = kwargs['omega_matter'] if kwargs['omega_matter'] is not None else kwargs['omega_cold'] + O_Lambda = 1 - O_m + return kwargs['hubble'] * 100 * np.sqrt(O_m / expfactor**3 + O_Lambda) + + def comoving_radial_distance(self, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, k=None, **kwargs): + """Comoving radial distance in Mpc/h + + Warning: neutrino and dynamical dark energy not yet implemented + Warning: no radiation included + """ + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + hpars = copy.deepcopy(kwargs) + del hpars['expfactor'] + + nz = int(1e4) + z_in = 0 + z_fin = 1 / kwargs['expfactor'] - 1 + z_vector = np.linspace(z_in, z_fin, nz) + a_vector = 1 / (1 + z_vector) + H_vector = self.Hubble(expfactor=a_vector, **hpars) + return 3e3 * hpars['hubble']*100 / np.trapz(H_vector, x=z_vector) + + +def load_lpt_emu(verbose=True): + """Loads in memory the lpt emulator described in Aricò et al. 2021. + + :return: a dictionary containing the emulator object + :rtype: dict + """ + + if verbose: + print('Loading l-bias lpt emulator...') + + basefold = os.path.dirname(os.path.abspath(__file__)) + + old_names = [(basefold + '/' + "lpt_emulator")] + for old_name in old_names: + if os.path.exists(old_name): + import shutil + shutil.rmtree(old_name) + + emulator_name = (basefold + '/' + + "lpt_emulator_v2.0.0") + + if (not os.path.exists(emulator_name)): + import urllib.request + import tarfile + import ssl + ssl._create_default_https_context = ssl._create_unverified_context + print('Downloading emulator data (34 Mb)...') + urllib.request.urlretrieve( + 'https://bacco.dipc.org/lpt_emulator_v2.0.0.tar', + emulator_name + '.tar', + MyProgressBar()) + tf = tarfile.open(emulator_name+'.tar', 'r') + tf.extractall(path=basefold) + tf.close() + os.remove(emulator_name + '.tar') + + customs={"accuracy_01": accuracy_exp_01, + "accuracy_005": accuracy_exp_005, + "mean_absolute_exp_percentage_error":mean_absolute_exp_percentage_error} + + emulator = {} + emulator['emu_type'] = 'nn' + + emulator['model'] = [] + emulator['sub'] = [] + emulator['scaler'] = [] + for n in range(15): + i_emulator_name = f'{emulator_name}/lpt_emu_field{n}' + + file_to_read = open(f"{i_emulator_name}/details.pickle", "rb") + nn_details = pickle.load(file_to_read) + + emulator['model'].append(load_model(i_emulator_name, custom_objects=customs)) + emulator['scaler'].append(nn_details['scaler']) + emulator['sub'].append(nn_details['subtract']) + + emulator['k'] = nn_details['kk'] + emulator['keys'] = ['omega_cold', 'sigma8_cold', 'omega_baryon', 'ns', + 'hubble', 'neutrino_mass', 'w0', 'wa', 'expfactor'] + emulator['bounds'] = nn_details['bounds'] + + if verbose: + print('L-bias lpt emulator loaded in memory.') + + return emulator + +def load_nonlinear_lbias_emu(emu_type='nn', verbose=True): + """Loads in memory the nonlinear emulator described in Zennaro et al. 2021. + + :param emu_type: type of emulator, can be 'gp' for the gaussian process, ot + 'nn' for the neural network + :type emu_type: str + + :return: a dictionary containing the emulator object + :rtype: dict + """ + if verbose: + print('Loading non-linear l-bias emulator...') + + basefold = os.path.dirname(os.path.abspath(__file__)) + + emulator_name = (basefold + '/' + + "lbias_emulator") + + if (not os.path.exists(emulator_name)): + import urllib.request + import tarfile + import ssl + ssl._create_default_https_context = ssl._create_unverified_context + print('Downloading emulator data (34Mb)...') + urllib.request.urlretrieve( + 'https://bacco.dipc.org/lbias_emulator.tar', + emulator_name + '.tar', + MyProgressBar()) + tf = tarfile.open(emulator_name+'.tar', 'r') + tf.extractall(path=basefold) + tf.close() + os.remove(emulator_name + '.tar') + emulator = {} + emulator['emu_type'] = 'nn' + emulator['model'] = [] + for n in range(15): + i_emulator_name = f'{emulator_name}/lbias_emu_field{n}' + emulator['model'].append(load_model(i_emulator_name)) + + with open(emulator_name + '/lbias_emu.pickle', 'rb') as f: + emulator['scaler'] = pickle.load(f) + emulator['npca'] = pickle.load(f) + emulator['k'] = pickle.load(f) + _ = pickle.load(f) # components + emulator['rotation'] = pickle.load(f) + emulator['bounds'] = pickle.load(f) + emulator['keys'] = ['omega_cold', 'sigma8_cold', 'omega_baryon', 'ns', + 'hubble', 'neutrino_mass', 'w0', 'wa', 'expfactor'] + + if verbose: + print('Nonlinear l-bias emulator loaded in memory.') + return emulator diff --git a/structure/baccoemu/baccoemu_vendored/matter_powerspectrum.py b/structure/baccoemu/baccoemu_vendored/matter_powerspectrum.py new file mode 100644 index 00000000..ab1d84b6 --- /dev/null +++ b/structure/baccoemu/baccoemu_vendored/matter_powerspectrum.py @@ -0,0 +1,1595 @@ +import numpy as np +import copy +import pickle +import os + +from numpy.core.shape_base import atleast_1d +from scipy.sparse import coo +from .utils import _transform_space, MyProgressBar, mean_absolute_exp_percentage_error, accuracy_exp_002, accuracy_exp_005 + +import tensorflow +tensorflow.compat.v1.logging.set_verbosity(tensorflow.compat.v1.logging.ERROR) +from tensorflow.keras.models import load_model +from .baryonic_boost import load_baryonic_emu +from scipy import interpolate +gpus = tensorflow.config.experimental.list_physical_devices('GPU') +if gpus: + for gpu in gpus: + tensorflow.config.experimental.set_memory_growth(gpu, True) + +__all__ = ["Matter_powerspectrum"] + +class Matter_powerspectrum(object): + """ + A class to load and call the baccoemu for the matter powerspectrum. + By default, the linear power spectrum (described in Aricò et al. 2021), the nonlinear boost + (described in Angulo et al. 2020), and the baryonic boost (described in Aricò et al. 2020c) are loaded. + + The emulators for A_s, sigma8, sigma12, and the smearing and removing of the BAO are also available. + + At large scales, i.e. k<0.01, the ratios between non-linear/linear and baryonic/non-linear spectra is considered to be 1. + + :param linear: whether to load the linear emulator, defaults to True + :type linear: boolean, optional + :param smeared_bao: whether to load the smeared-BAO emulator, defaults to False + :type smeared_bao: boolean, optional + :param no_wiggles: whether to load the no-wiggles emulator, defaults to True + :type no_wiggles: boolean, optional + :param nonlinear_boost: whether to load the nonlinear boost emulator, defaults to True + :type nonlinear_boost: boolean, optional + :param baryonic_boost: whether to load the baryonic boost emulator, defaults to True + :type baryonic_boost: boolean, optional + :param compute_sigma8: whether to load the sigma8 emulator, defaults to True + :type compute_sigma8: boolean, optional + :param verbose: whether to activate the verbose mode, defaults to True + :type verbose: boolean, optional + + """ + def __init__(self, linear=True, smeared_bao=False, no_wiggles=True, nonlinear_boost = True, + baryonic_boost=True, compute_sigma8=True, + nonlinear_emu_path=None, nonlinear_emu_details=None, + baryonic_emu_path=None, baryonic_emu_details=None, verbose=True): + + self.verbose = verbose + + self.compute_linear = True if linear else False + self.compute_smeared_bao = True if smeared_bao else False + self.compute_no_wiggles = True if no_wiggles else False + self.compute_nonlinear_boost = True if nonlinear_boost else False + self.compute_baryonic_boost = True if baryonic_boost else False + self.compute_sigma8 = True if compute_sigma8 else False + + if self.compute_smeared_bao and self.compute_no_wiggles: + print("""Provide only one between the smeared BAO and the non-wiggles emulators!""") + raise ValueError("""Set either compute_smeared_bao=False (default) or no_wiggles=False!""") + + self.emulator = {} + if self.compute_sigma8: + self.emulator['sigma8'] = load_sigma8_emu(verbose=verbose) + + if self.compute_linear: + self.emulator['linear'] = load_linear_emu(verbose=verbose) + + if self.compute_smeared_bao: + self.emulator['smeared_bao'] = load_smeared_bao_emu(verbose=verbose) + + if self.compute_no_wiggles: + self.emulator['no_wiggles'] = load_no_wiggles_emu(verbose=verbose) + + if self.compute_nonlinear_boost: + self.emulator['nonlinear'] = load_nonlinear_emu(fold_name=nonlinear_emu_path, detail_name=nonlinear_emu_details, verbose=verbose) + + if self.compute_baryonic_boost: + self.emulator['baryon'] = load_baryonic_emu(fold_name=baryonic_emu_path, detail_name=baryonic_emu_details, verbose=verbose) + + def _get_parameters(self, coordinates, which_emu): + """ + Function that returns a dictionary of cosmological parameters, + computing derived cosmological parameters, if not + already present in the given coordinates, and checking the relevant boundaries. + :param coordinates: a set of coordinates in parameter space + :type coordinates: dict + :param which_emu: kind of emulator: options are 'linear', 'nonlinear','baryon','smeared_bao','sigma8' + :type which_emu: str + :return: coordinates with derived parameters + :rtype: dict + """ + coordinates = {key: np.atleast_1d(coordinates[key]) for key in set(list(coordinates.keys())) - set(['k', 'k_lin', 'pk_lin'])} + + avail_pars = [coo for coo in coordinates.keys() if coordinates[coo][0] is not None] #parameters currently available + eva_pars = self.emulator[which_emu]['keys'] #parameters strictly needed to evaluate the emulator + req_pars = self.emulator[which_emu]['keys'] if which_emu != 'linear' else self.emulator[which_emu]['full_keys'] #parameters needed for a computation + comp_pars = list(set(req_pars)-set(avail_pars)) #parameters to be computed + deriv_pars = ['omega_cold','sigma8_cold', 'A_s'] #derived parameters that can be computed + miss_pars = list(set(comp_pars)-set(deriv_pars)) #parameters missing from coordinates + extra_pars = list(set(req_pars)-set(eva_pars)) #requested parameters not needed for evaluation + if miss_pars: + print(f"{which_emu} emulator:") + print(f" Please add the parameter(s) {miss_pars} to your coordinates!") + raise KeyError(f"{which_emu} emulator: coordinates need the following parameters: ", miss_pars) + + if ('omega_cold' in avail_pars) & ('omega_matter' in avail_pars): + assert len(coordinates['omega_cold']) == len(coordinates['omega_matter']), 'Both omega_cold and omega_matter were provided, but they have different len' + om_from_oc = coordinates['omega_cold'] + coordinates['neutrino_mass'] / 93.14 /coordinates['hubble']**2 + assert np.all(np.abs(coordinates['omega_matter'] - om_from_oc) < 1e-4), 'Both omega_cold and omega_matter were provided, but they are inconsistent among each other' + + if 'omega_cold' in comp_pars: + if 'omega_matter' not in avail_pars: + raise KeyError('One parameter between omega_matter and omega_cold must be provided!') + + omega_nu = coordinates['neutrino_mass'] / 93.14 /coordinates['hubble']**2 + coordinates['omega_cold'] = coordinates['omega_matter'] - omega_nu + + if ('sigma8_cold' not in avail_pars) & ('A_s' not in avail_pars): + raise KeyError('One parameter between sigma8_cold and A_s must be provided!') + + if ('sigma8_cold' in avail_pars) & ('A_s' in avail_pars): + #commented for the cases where one is computed and same value is repeated + #assert len(np.atleast_1d(coordinates['sigma8_cold'])) == len(atleast_1d(coordinates['A_s'])), 'Both sigma8_cold and A_s were provided, but they have different len' + + ignore_s8_pars = copy.deepcopy(coordinates) + del ignore_s8_pars['sigma8_cold'] + ignore_s8_pars['cold'] = True + s8_from_A_s = self.get_sigma8(**ignore_s8_pars) + assert np.all(np.abs(coordinates['sigma8_cold'] - s8_from_A_s) < 1e-4), 'Both sigma8_cold and A_s were provided, but they are inconsistent among each other' + + if 'sigma8_cold' in comp_pars: + tmp_coords = copy.deepcopy(coordinates) + tmp_coords['cold']=True + coordinates['sigma8_cold'] = np.atleast_1d(self.get_sigma8(**tmp_coords)) + + if 'A_s' in comp_pars: + tmp_coords = copy.deepcopy(coordinates) + del tmp_coords['sigma8_cold'] + tmp_coords['A_s'] = 2e-9 + tmp_coords['cold'] = True + coordinates['A_s'] = np.atleast_1d((coordinates['sigma8_cold'] / self.get_sigma8(**tmp_coords))**2 * tmp_coords['A_s']) + + pp = np.squeeze([coordinates[p][0] for p in eva_pars]) + coords_out = copy.deepcopy(coordinates) + + grid = {} + for key in coordinates.keys(): + if len(np.atleast_1d(coordinates[key])) > 1: + grid[key] = np.array(coordinates[key]) + + if len(list(grid.keys()))==0: + grid = None + else: + grid_structure = [] + for key in grid.keys(): + grid_structure.append(len(grid[key])) + grid_structure = np.array(grid_structure) + values, counts = np.unique(grid_structure, return_counts=True) + counts_but_highest = np.delete(counts, np.argmax(counts)) + assert np.all(counts == counts[0]) | np.all(counts_but_highest == 1), 'When passing multiple coordinate sets you should either vary only on parameter, or all parameters should have the same len' + + if grid is not None: + grid_pars = list(grid.keys()) # list of parameters that are varyied in a grid + N = len(grid[grid_pars[0]]) + pp = np.tile(pp, (N, 1)) + for par in grid_pars: + if par in eva_pars: + index = eva_pars.index(par) + pp[:,index] = np.float64(grid[par]) + if par in req_pars: + coords_out[par] = grid[par] + pp = np.float64(pp) + + for i,par in enumerate(eva_pars): + val = pp[i] if grid is None else pp[:,i] + message = 'Param {}={} out of bounds [{}, {}]'.format( + par, val, self.emulator[which_emu]['bounds'][i][0], self.emulator[which_emu]['bounds'][i][1]) + + assert np.all(val >= self.emulator[which_emu]['bounds'][i][0]) & np.all(val <= self.emulator[which_emu]['bounds'][i][1]), message + + if extra_pars: + cc = np.squeeze([coords_out[p] for p in extra_pars]) + if None in cc: + raise ValueError(f'None in parameters: {extra_pars} = {cc}!') + + return coords_out, pp, grid + + + def _evaluate_nonlinear(self, **kwargs): + """Evaluate the given emulator at a set of coordinates in parameter space. + + The coordinates must be specified as a dictionary with the following + keywords: + + #. 'omega_cold' + #. 'omega_baryon' + #. 'sigma8_cold' + #. 'hubble' + #. 'ns' + #. 'neutrino_mass' + #. 'w0' + #. 'wa' + #. 'expfactor' + #. 'k' : a vector of wavemodes in h/Mpc at which the nonlinear boost will be computed, if None + the default wavemodes of the nonlinear emulator will be used, defaults to None + #. 'k_lin': a vector of wavemodes in h/Mpc, if None the wavemodes used by + the linear emulator are returned, defaults to None + #. 'pk_lin': a vector of linear matter power spectrum computed at k_lin, either cold or total depending + on the key "cold". If None the linear emulator will be called, defaults to None + #. 'cold': whether to return the cold matter power spectrum or the total one. Default to True + """ + if not self.compute_nonlinear_boost: + raise ValueError("Please enable the nonlinear boost!") + + k = kwargs['k'] if 'k' in kwargs.keys() else None + k_lin = kwargs['k_lin'] if 'k_lin' in kwargs.keys() else None + pk_lin = kwargs['pk_lin'] if 'pk_lin' in kwargs.keys() else None + cold = kwargs['cold'] if 'cold' in kwargs.keys() else True + + emulator = self.emulator['nonlinear'] + + coords, pp, grid = self._get_parameters(kwargs, 'nonlinear') + + _pp = _transform_space(pp, space_rotation=False, bounds=emulator['bounds']) + + yrec = emulator['model'](_pp.reshape(-1,9), training=False) + Q = np.squeeze(np.exp(emulator['scaler'].inverse_transform(yrec))) + + if pk_lin is None: + pk_lin_kwargs = copy.deepcopy(kwargs) + pk_lin_kwargs['k'] = None + k_lin, pk_lin = self.get_linear_pk(**pk_lin_kwargs) + else: + k_lin = np.squeeze(k_lin) + pk_lin = np.squeeze(pk_lin) + if k_lin is None: + raise ValueError("""If the linear power spectrum pk_lin is provided, + also the wavenumbers k_lin at which is computed must be provided """) + elif (np.amin(k_lin)>1e-3) | (np.amax(k_lin) < 10): + raise ValueError(f""" + A minimum k <= 0.001 h/Mpc and a maximum k >= 10 h/Mpc + are required in the linear power spectrum for the calculation + of the non linear boost: + the current values are {np.amin(k_lin)}) h/Mpc and {np.amax(k_lin)} h/Mpc + """) + if cold: + k_lin_cold = k_lin + pk_lin_cold = pk_lin + else: + k_lin_tot = k_lin + pk_lin_tot = pk_lin + total_kwargs = copy.deepcopy(kwargs) + total_kwargs['cold'] = True + k_lin_cold, pk_lin_cold = self.get_linear_pk(**total_kwargs) + + pklin_interp_cold = interpolate.interp1d(np.log(k_lin_cold), np.log(pk_lin_cold), + kind='linear', axis = -1 if grid is None else 1, fill_value='extrapolate') + pk_lin_emu_cold = np.exp(pklin_interp_cold(np.log(emulator['k']))) + + if not cold: + pklin_interp_tot = interpolate.interp1d(np.log(k_lin_tot), np.log(pk_lin_tot), + kind='linear', axis = -1 if grid is None else 1, fill_value='extrapolate') + pk_lin_emu_tot = np.exp(pklin_interp_tot(np.log(emulator['k']))) + pk_lin_emu = pk_lin_emu_tot + else: + pk_lin_emu = pk_lin_emu_cold + + if self.compute_smeared_bao: + smeared_bao_kwargs = copy.deepcopy(kwargs) + smeared_bao_kwargs['k'] = emulator['k'] + _, pk_smeared = self.get_smeared_bao_pk(**smeared_bao_kwargs) + + elif self.compute_no_wiggles: + no_wiggles_kwargs = copy.deepcopy(kwargs) + no_wiggles_kwargs['k'] = emulator['k'] + no_wiggles_kwargs['k_lin'] = k_lin_cold + no_wiggles_kwargs['pk_lin'] = pk_lin_cold + _, pk_no_wiggles = self.get_no_wiggles_pk(**no_wiggles_kwargs) + pk_smeared = _smeared_bao_pk(k_lin=k_lin_cold, pk_lin=pk_lin_cold, k_emu=emulator['k'], pk_lin_emu=pk_lin_emu_cold, pk_nw=pk_no_wiggles, grid=grid) + else: + pk_smeared = _smeared_bao_pk(k_lin=k_lin_cold, pk_lin=pk_lin_cold, k_emu=emulator['k'], pk_lin_emu=pk_lin_emu_cold, grid=grid) + + if cold: + nonlinear_boost = Q * pk_smeared / pk_lin_emu_cold + else: + omega_nu = kwargs['neutrino_mass'] / 93.14 / kwargs['hubble']**2 + omega_matter = kwargs['omega_cold'] + omega_nu if kwargs['omega_cold'] is not None else kwargs['omega_matter'] + f_nu = omega_nu/omega_matter + if grid is None: + add = pk_lin_emu_tot - (1-f_nu)**2 * pk_lin_emu_cold + else: + add = pk_lin_emu_tot - ((1-f_nu)**2 * pk_lin_emu_cold.T).T + + if grid is None: + nonlinear_boost = (Q*pk_smeared*(1-f_nu)**2 + add)/pk_lin_emu_tot + else: + nonlinear_boost = (((Q*pk_smeared).T*(1-f_nu)**2).T + add)/pk_lin_emu_tot + + if k is not None: + k_max = max(k) + kemu_max = self.emulator['nonlinear']['k'].max() + kemu_min = self.emulator['nonlinear']['k'].min() + + if (k_max > kemu_max): + raise ValueError(f"""The nonlinear emulator must be {kemu_max} h/Mpc: the current value is {k_max} h/Mpc""") + + nl_interp = interpolate.interp1d(np.log(emulator['k']), nonlinear_boost, + kind='linear', axis = -1 if grid is None else 1, fill_value='extrapolate', bounds_error=False, + assume_sorted=True) + nonlinear_boost = np.squeeze(nl_interp(np.log(k))) + if grid is None: + nonlinear_boost[k kemu_max) & (self.verbose): + print(f""" WARNING: + The maximum k of the baryonic boost emulator is {kemu_max} h/Mpc: + the baryonic emulator is currently extrapolating to {k_max} h/Mpc; + the extrapolation will likely be not accurate. + """) + + baryonic_interp = interpolate.interp1d(np.log(emulator['k']), baryonic_boost, + kind='linear', axis = 0 if grid is None else 1, fill_value='extrapolate', bounds_error=False, + assume_sorted=True) + baryonic_boost = baryonic_interp(np.log(k)) + if grid is None: + baryonic_boost[k max(emulator['k']))|(min(k) < min(emulator['k'])): + raise ValueError(f""" + A minimum k > {min(emulator['k'])} h/Mpc and a maximum k < {max(emulator['k'])} h/Mpc + are required for the linear emulator: + the current values are {min(k)} h/Mpc and {max(k)} h/Mpc + """) + + else: + if np.any(pk_lin < 0): + pklin_interp = interpolate.interp1d(np.log(emulator['k']), pk_lin, + kind='linear', axis = 0 if grid is None else 1, fill_value='extrapolate', + assume_sorted=True) + pk_lin = pklin_interp(np.log(k)) + else: + pklin_interp = interpolate.interp1d(np.log(emulator['k']), np.log(pk_lin), + kind='linear', axis = 0 if grid is None else 1, fill_value='extrapolate', + assume_sorted=True) + pk_lin = np.exp(pklin_interp(np.log(k))) + else: + k = emulator['k'] + return k, pk_lin + + + def get_smeared_bao_pk(self, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, k=None, **kwargs): + """Evaluate the cold matter power spectrum with smeared bao, calling an emulator + at a set of coordinates in parameter space. + + :param omega_cold: omega cold matter (cdm + baryons), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_cold: float or array + :param omega_matter: omega total matter (cdm + baryons + neutrinos), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_matter: float or array + :param sigma8_cold: rms of cold (cdm + baryons) linear perturbations, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type sigma8_cold: float or array + :param A_s: primordial scalar amplitude at k=0.05 1/Mpc, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type A_s: float or array + :param hubble: adimensional Hubble parameters, h=H0/(100 km/s/Mpc) + :type hubble: float or array + :param ns: scalar spectral index + :type ns: float or array + :param neutrino_mass: total neutrino mass + :type neutrino_mass: float or array + :param w0: dark energy equation of state redshift 0 parameter + :type w0: float or array + :param wa: dark energy equation of state redshift dependent parameter + :type wa: float or array + :param expfactor: expansion factor a = 1 / (1 + z) + :type expfactor: float or array + :param k: a vector of wavemodes in h/Mpc at which the nonlinear boost will be computed, if None + the default wavemodes of the linear emulator will be used, defaults to None + :type k: array_like, optional + :param k_lin: a vector of wavemodes in h/Mpc, if None the wavemodes used by + the linear emulator are returned, defaults to None + :type k_lin: array_like, optional + :param pk_lin: a vector of linear power spectrum computed at k_lin, if None + the linear emulator will be called, defaults to None + :type pk_lin: array_like, optional + :param grid: dictionary with parameters and vectors of values where to evaluate the emulator, defaults to None + :type grid: array_like, optional + + :return: k and the linear P(k) + :rtype: tuple + """ + + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + + if not self.compute_smeared_bao: + raise ValueError("Please enable the smeared bao emulator!") + + emulator = self.emulator['smeared_bao'] + coordinates, pp, grid = self._get_parameters(kwargs, 'smeared_bao') + + ypred = emulator['model'](pp.reshape(-1,9), training=False) + pk_bao = np.squeeze(np.exp(emulator['scaler'].inverse_transform(ypred))) + + if k is not None: + if (max(k) > max(emulator['k']))|(min(k) < min(emulator['k'])): + raise ValueError(f""" + A minimum k > 0.001 h/Mpc and a maximum k < 30 h/Mpc + are required for the smeared-BAO emulator: + the current values are {min(k)} h/Mpc and {max(k)} h/Mpc + """) + else: + pk_bao_interp = interpolate.interp1d(np.log(emulator['k']), np.log(pk_bao), + kind='linear', axis = 0 if grid is None else 1, fill_value='extrapolate', + assume_sorted=True) + pk_bao = np.exp(pk_bao_interp(np.log(k))) + else: + k = emulator['k'] + return k, pk_bao + + def get_no_wiggles_pk(self, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, k=None, k_lin=None, pk_lin=None, **kwargs): + """Evaluate the cold matter power spectrum with no wiggles (no bao), calling an emulator + at a set of coordinates in parameter space. + + :param omega_cold: omega cold matter (cdm + baryons), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_cold: float or array + :param omega_matter: omega total matter (cdm + baryons + neutrinos), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_matter: float or array + :param sigma8_cold: rms of cold (cdm + baryons) linear perturbations, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type sigma8_cold: float or array + :param A_s: primordial scalar amplitude at k=0.05 1/Mpc, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type A_s: float or array + :param hubble: adimensional Hubble parameters, h=H0/(100 km/s/Mpc) + :type hubble: float or array + :param ns: scalar spectral index + :type ns: float or array + :param neutrino_mass: total neutrino mass + :type neutrino_mass: float or array + :param w0: dark energy equation of state redshift 0 parameter + :type w0: float or array + :param wa: dark energy equation of state redshift dependent parameter + :type wa: float or array + :param expfactor: expansion factor a = 1 / (1 + z) + :type expfactor: float or array + :param k: a vector of wavemodes in h/Mpc at which the nonlinear boost will be computed, if None + the default wavemodes of the linear emulator will be used, defaults to None + :type k: array_like, optional + :param k_lin: a vector of wavemodes in h/Mpc, if None the wavemodes used by + the linear emulator are returned, defaults to None + :type k_lin: array_like, optional + :param pk_lin: a vector of linear power spectrum computed at k_lin, if None + the linear emulator will be called, defaults to None + :type pk_lin: array_like, optional + :param grid: dictionary with parameters and vectors of values where to evaluate the emulator, defaults to None + :type grid: array_like, optional + + :return: k and the linear P(k) + :rtype: tuple + """ + + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + + if not self.compute_no_wiggles: + raise ValueError("Please enable the no_wiggles emulator!") + + emulator = self.emulator['no_wiggles'] + coordinates, pp, grid = self._get_parameters(kwargs, 'no_wiggles') + + ypred = emulator['model'](pp.reshape(-1,7), training=False) + ypred = emulator['scaler'].inverse_transform(ypred) + ypred[:,emulator['k']>0.8] = 0. + ypred = np.squeeze(ypred) + + if k is not None: + if (min(k) < min(emulator['k'])) and (self.verbose): + print(f"""The no-wiggles emulator is extrapolating from {min(k)} to {min(emulator['k'])} h/Mpc!""") + + pk_no_wiggles_interp = interpolate.interp1d(np.log(emulator['k']), ypred, + kind='linear', axis = 0 if grid is None else 1, fill_value=0., bounds_error=False, + assume_sorted=True) + pk_no_wiggles_plin_ratio = np.exp(pk_no_wiggles_interp(np.log(k))) + else: + k = emulator['k'] + pk_no_wiggles_plin_ratio = np.squeeze(np.exp(ypred)) + + if (k_lin is not None) & (pk_lin is not None): + do_interp = False + if len(k_lin) != len(k): + do_interp = True + else: + if np.any(k_lin != k): + do_interp = True + if do_interp: + pk_lin_interp = interpolate.interp1d(np.log(k_lin), np.log(pk_lin), + kind='linear', axis = 0 if grid is None else 1, fill_value='extrapolate', + assume_sorted=True) + pk_lin = np.exp(pk_lin_interp(np.log(k))) + + else: + linear_kwargs = copy.deepcopy(kwargs) + linear_kwargs['k'] = k + k_lin, pk_lin = self.get_linear_pk(**linear_kwargs) + + pk_no_wiggles = pk_no_wiggles_plin_ratio * pk_lin + + return k, pk_no_wiggles + + def get_sigma8(self, cold=True, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, **kwargs): + """Return sigma8, calling an emulator + at a set of coordinates in parameter space. + + :param cold: whether to return sigma8_cold (cdm+baryons) or total matter + :type cold: bool + :param omega_cold: omega cold matter (cdm + baryons), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_cold: float or array + :param omega_matter: omega total matter (cdm + baryons + neutrinos), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_matter: float or array + :param sigma8_cold: rms of cold (cdm + baryons) linear perturbations, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type sigma8_cold: float or array + :param A_s: primordial scalar amplitude at k=0.05 1/Mpc, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type A_s: float or array + :param hubble: adimensional Hubble parameters, h=H0/(100 km/s/Mpc) + :type hubble: float or array + :param ns: scalar spectral index + :type ns: float or array + :param neutrino_mass: total neutrino mass + :type neutrino_mass: float or array + :param w0: dark energy equation of state redshift 0 parameter + :type w0: float or array + :param wa: dark energy equation of state redshift dependent parameter + :type wa: float or array + :param expfactor: expansion factor a = 1 / (1 + z) + :type expfactor: float or array + + :return: sigma8 + :rtype: float or array + """ + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + + if self.compute_sigma8: + emulator = self.emulator['sigma8'] + else: + raise ValueError("Please enable the sigma8 emulator!") + + coordinates, pp, grid = self._get_parameters(kwargs, 'sigma8') + ypred = np.squeeze(emulator['model'](pp.reshape(-1,7), training=False)) + if hasattr(coordinates['A_s'], '__len__'): + ypred = (ypred.T * np.sqrt(coordinates['A_s']/1.e-9)).T + else: + ypred = ypred * np.sqrt(coordinates['A_s']/1.e-9) + s8_index = 0 if cold else 1 + res = ypred[...,s8_index] + res = float(res) if res.ndim==0 else res + return res + + + def get_sigma12(self, cold=True, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, **kwargs): + """Return sigma12, calling an emulator + at a set of coordinates in parameter space. + + :param cold: whether to return sigma8_cold (cdm+baryons) or total matter + :type cold: bool + :param omega_cold: omega cold matter (cdm + baryons), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_cold: float or array + :param omega_matter: omega total matter (cdm + baryons + neutrinos), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_matter: float or array + :param sigma8_cold: rms of cold (cdm + baryons) linear perturbations, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type sigma8_cold: float or array + :param A_s: primordial scalar amplitude at k=0.05 1/Mpc, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type A_s: float or array + :param hubble: adimensional Hubble parameters, h=H0/(100 km/s/Mpc) + :type hubble: float or array + :param ns: scalar spectral index + :type ns: float or array + :param neutrino_mass: total neutrino mass + :type neutrino_mass: float or array + :param w0: dark energy equation of state redshift 0 parameter + :type w0: float or array + :param wa: dark energy equation of state redshift dependent parameter + :type wa: float or array + :param expfactor: expansion factor a = 1 / (1 + z) + :type expfactor: float or array + + :return: sigma12 + :rtype: float or array + """ + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + + if self.compute_sigma8: + emulator = self.emulator['sigma8'] + else: + raise ValueError("Please enable the sigma8 emulator!") + + coordinates, pp, grid = self._get_parameters(kwargs, 'sigma8') + ypred = np.squeeze(emulator['model'](pp.reshape(-1,7), training=False)) + ypred = ypred * np.sqrt(coordinates['A_s']/1.e-9) + s8_index = 2 if cold else 3 + res = ypred[...,s8_index] + res = float(res) if res.ndim==0 else res + return res + + + def get_A_s(self, omega_cold=None, omega_matter=None, omega_baryon=None, + sigma8_cold=None, A_s=None, hubble=None, ns=None, neutrino_mass=None, + w0=None, wa=None, expfactor=None, **kwargs): + """Return A_s, corresponding to a given sigma8_cold + at a set of coordinates in parameter space. + + :param omega_cold: omega cold matter (cdm + baryons), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_cold: float or array + :param omega_matter: omega total matter (cdm + baryons + neutrinos), either omega_cold + or omega_matter should be specified, if both are specified + they should be consistent + :type omega_matter: float or array + :param sigma8_cold: rms of cold (cdm + baryons) linear perturbations, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type sigma8_cold: float or array + :param A_s: primordial scalar amplitude at k=0.05 1/Mpc, either sigma8_cold + or A_s should be specified, if both are specified they should be + consistent + :type A_s: float or array + :param hubble: adimensional Hubble parameters, h=H0/(100 km/s/Mpc) + :type hubble: float or array + :param ns: scalar spectral index + :type ns: float or array + :param neutrino_mass: total neutrino mass + :type neutrino_mass: float or array + :param w0: dark energy equation of state redshift 0 parameter + :type w0: float or array + :param wa: dark energy equation of state redshift dependent parameter + :type wa: float or array + :param expfactor: expansion factor a = 1 / (1 + z) + :type expfactor: float or array + + :return: A_s + :rtype: float or array + """ + _kwargs = locals() + kwargs = {key: _kwargs[key] for key in set(list(_kwargs.keys())) - set(['self'])} + + coordinates, pp, grid = self._get_parameters(kwargs, 'linear') + + res = np.squeeze(coordinates['A_s']) + + return float(res) if res.ndim == 0 else res + + +def load_linear_emu(verbose=True): + """Loads in memory the linear emulator described in Aricò et al. 2021. + + :return: a dictionary containing the emulator object + :rtype: dict + """ + + if verbose: + print('Loading linear emulator...') + + basefold = os.path.dirname(os.path.abspath(__file__)) + emulator_cold_name = (basefold + '/' + + "cold_matter_linear_emu_1.0.0") + emulator_tot_name = (basefold + '/' + + "total_matter_linear_emu_1.0.0") + + old_names = [(basefold + '/' + "linear_emulator")] + for old_name in old_names: + if os.path.exists(old_name): + import shutil + shutil.rmtree(old_name) + + if (not os.path.exists(emulator_cold_name)): + import urllib.request + import tarfile + import ssl + ssl._create_default_https_context = ssl._create_unverified_context + print('Downloading emulator data (2 Mb)...') + urllib.request.urlretrieve( + 'https://bacco.dipc.org/cold_matter_linear_emu_1.0.0.tar', + emulator_cold_name + '.tar', + MyProgressBar()) + tf = tarfile.open(emulator_cold_name+'.tar', 'r') + tf.extractall(path=basefold) + tf.close() + os.remove(emulator_cold_name + '.tar') + + if (not os.path.exists(emulator_tot_name)): + import urllib.request + import tarfile + import ssl + ssl._create_default_https_context = ssl._create_unverified_context + print('Downloading emulator data (2 Mb)...') + urllib.request.urlretrieve( + 'https://bacco.dipc.org/total_matter_linear_emu_1.0.0.tar', + emulator_tot_name + '.tar', + MyProgressBar()) + tf = tarfile.open(emulator_tot_name+'.tar', 'r') + tf.extractall(path=basefold) + tf.close() + os.remove(emulator_tot_name + '.tar') + + customs = { + "accuracy_exp_002": accuracy_exp_002, + "accuracy_exp_005": accuracy_exp_005, + "mean_absolute_exp_percentage_error":mean_absolute_exp_percentage_error + } + metrics_list = ["accuracy",accuracy_exp_002, accuracy_exp_005] + + emulator = {} + emulator['emu_type'] = 'nn' + emulator['model_cold'] = load_model(emulator_cold_name, custom_objects=customs, compile=False) + emulator['model_cold'].compile(optimizer='adam', loss=mean_absolute_exp_percentage_error, metrics=metrics_list) + + file_to_read = open(f"{emulator_cold_name}/details.pickle", "rb") + nn_cold_details = pickle.load(file_to_read) + + emulator['k'] = nn_cold_details['kk'] + emulator['scaler_cold'] = nn_cold_details['scaler'] + + emulator['model_tot'] = load_model(emulator_tot_name, custom_objects=customs, compile=False) + emulator['model_tot'].compile(optimizer='adam', loss=mean_absolute_exp_percentage_error, metrics=metrics_list) + + file_to_read = open(f"{emulator_tot_name}/details.pickle", "rb") + nn_tot_details = pickle.load(file_to_read) + + emulator['scaler_tot'] = nn_tot_details['scaler'] + emulator['keys'] = ['omega_cold', 'omega_baryon', + 'hubble', 'neutrino_mass', 'w0', 'wa', 'expfactor'] + emulator['full_keys'] = ['omega_cold', 'omega_baryon', 'A_s', 'ns', + 'hubble', 'neutrino_mass', 'w0', 'wa', 'expfactor'] + + emulator['bounds'] = nn_tot_details['bounds']#{key: nn_cold_details['bounds'][i] for i, key in enumerate(emulator['keys'])} + + if verbose: + print('Linear emulator loaded in memory.') + + return emulator + +def load_sigma8_emu(verbose=True): + """Loads in memory an emulator to quickly pass from A_s to sigma8. + + :return: a dictionary containing the emulator object + :rtype: dict + """ + + if verbose: + print('Loading sigma8 emulator...') + + basefold = os.path.dirname(os.path.abspath(__file__)) + + old_names = [(basefold + '/' + "sigma8_emu_1.0.0"),] + for old_name in old_names: + if os.path.exists(old_name): + import shutil + shutil.rmtree(old_name) + + emulator_name = (basefold + '/' + + "sigma8_emu_2.0.0") + + if (not os.path.exists(emulator_name)): + import urllib.request + import tarfile + import ssl + ssl._create_default_https_context = ssl._create_unverified_context + print('Downloading emulator data (141 Kb)...') + urllib.request.urlretrieve( + 'https://bacco.dipc.org/sigma8_emu_2.0.0.tar', + emulator_name + '.tar', + MyProgressBar()) + tf = tarfile.open(emulator_name+'.tar', 'r') + tf.extractall(path=basefold) + tf.close() + os.remove(emulator_name + '.tar') + + + customs = { + "accuracy_exp_002": accuracy_exp_002, + "accuracy_exp_005": accuracy_exp_005, + "mean_absolute_exp_percentage_error":mean_absolute_exp_percentage_error + } + metrics_list = ["accuracy",accuracy_exp_002, accuracy_exp_005] + + emulator = {} + emulator['emu_type'] = 'nn' + emulator['model'] = load_model(emulator_name, custom_objects=customs, compile=False) + emulator['model'].compile(optimizer='adam', loss=mean_absolute_exp_percentage_error, metrics=metrics_list) + + file_to_read = open(f"{emulator_name}/details.pickle", "rb") + nn_details = pickle.load(file_to_read) + emulator['bounds'] = nn_details['bounds'] + emulator['keys'] = ['omega_cold', 'omega_baryon', 'ns', 'hubble', 'neutrino_mass', 'w0', 'wa'] + + if verbose: + print('Sigma8 emulator loaded in memory.') + + return emulator + +def load_smeared_bao_emu(verbose=True): + """Loads in memory the smeared bao emulator. + + :return: a dictionary containing the emulator object + :rtype: dict + """ + + if verbose: + print('Loading smeared bao emulator...') + + basefold = os.path.dirname(os.path.abspath(__file__)) + + old_names = [(basefold + '/' + "smeared_bao_emu"), + (basefold + '/' + "smeared_bao_emu_1")] + for old_name in old_names: + if os.path.exists(old_name): + import shutil + shutil.rmtree(old_name) + + emulator_name = (basefold + '/' + + "smeared_bao_emu_1.0.0") + + if (not os.path.exists(emulator_name)): + import urllib.request + import tarfile + import ssl + ssl._create_default_https_context = ssl._create_unverified_context + print('Downloading emulator data (1.2 Mb)...') + urllib.request.urlretrieve( + 'https://bacco.dipc.org/smeared_bao_emu_1.0.0.tar', + emulator_name + '.tar', + MyProgressBar()) + tf = tarfile.open(emulator_name+'.tar', 'r') + tf.extractall(path=basefold) + tf.close() + os.remove(emulator_name + '.tar') + + customs = { + "accuracy_exp_002": accuracy_exp_002, + "accuracy_exp_005": accuracy_exp_005, + "mean_absolute_exp_percentage_error":mean_absolute_exp_percentage_error + } + metrics_list = ["accuracy",accuracy_exp_002, accuracy_exp_005] + + emulator = {} + emulator['emu_type'] = 'nn' + emulator['model'] = load_model(emulator_name, custom_objects=customs, compile=False) + emulator['model'].compile(optimizer='adam', loss=mean_absolute_exp_percentage_error, metrics=metrics_list) + + file_to_read = open(f"{emulator_name}/details.pickle", "rb") + nn_details = pickle.load(file_to_read) + emulator['k'] = nn_details['kk'] + emulator['scaler'] = nn_details['scaler'] + emulator['bounds'] = nn_details['bounds'] + emulator['keys'] = ['omega_cold', 'sigma8_cold', 'omega_baryon', 'ns', + 'hubble', 'neutrino_mass', 'w0', 'wa', 'expfactor'] + + if verbose: + print('Smeared bao emulator loaded in memory.') + + return emulator + +def load_no_wiggles_emu(verbose=True): + """Loads in memory the no-wiggles emulator. + + :return: a dictionary containing the emulator object + :rtype: dict + """ + + if verbose: + print('Loading no-wiggles emulator...') + import deepdish as dd + + basefold = os.path.dirname(os.path.abspath(__file__)) + + emulator_name = (basefold + '/' + + "no_wiggles_emu_1.0.0") + + if (not os.path.exists(emulator_name)): + import urllib.request + import tarfile + import ssl + ssl._create_default_https_context = ssl._create_unverified_context + print('Downloading emulator data (6.7 Mb)...') + urllib.request.urlretrieve( + 'https://bacco.dipc.org/no_wiggles_emu_1.0.0.tar', + emulator_name + '.tar', + MyProgressBar()) + tf = tarfile.open(emulator_name+'.tar', 'r') + tf.extractall(path=basefold) + tf.close() + os.remove(emulator_name + '.tar') + + customs = { + "accuracy_exp_002": accuracy_exp_002, + "accuracy_exp_005": accuracy_exp_005, + "mean_absolute_exp_percentage_error":mean_absolute_exp_percentage_error + } + metrics_list = ["accuracy",accuracy_exp_002, accuracy_exp_005] + + emulator = {} + emulator['emu_type'] = 'nn' + emulator['model'] = load_model(emulator_name, custom_objects=customs, compile=False) + emulator['model'].compile(optimizer='adam', loss=mean_absolute_exp_percentage_error, metrics=metrics_list) + + file_to_read = open(f"{emulator_name}/details.pickle", "rb") + nn_details = pickle.load(file_to_read) + + emulator['k'] = nn_details['kk'] + emulator['scaler'] = nn_details['scaler'] + emulator['bounds'] = nn_details['bounds'] + emulator['keys'] = nn_details['keys'] + + if verbose: + print('No-wiggles emulator loaded in memory.') + + return emulator + +def load_nonlinear_emu(verbose=True, fold_name=None, detail_name=None): + """Loads in memory the nonlinear emulator described in Angulo et al. 2020. + + :return: a dictionary containing the emulator object + :rtype: dict + """ + if verbose: + print('Loading non-linear emulator...') + + if fold_name is None: + basefold = os.path.dirname(os.path.abspath(__file__)) + + old_emulator_names = [(basefold + '/' + + "NN_emulator_data_iter4_big_160.pickle_sg_0.95_2000_rot_bao"), + (basefold + '/' + + "NN_emulator_data_iter4_big_160.pickle_sg_0.99_2000_PCA5_BNFalse_DO0rot_bao"), + (basefold + '/' + + "NN_emulator_data_iter4_big_160.pickle_sg_0.99_2000_PCA6_BNFalse_DO0rot_bao")] + for old_emulator_name in old_emulator_names: + if os.path.exists(old_emulator_name): + import shutil + shutil.rmtree(old_emulator_name) + + emulator_name = (basefold + '/' + + "nonlinear_emu_1.0.1") + detail_name = 'details.pickle' + + if (not os.path.exists(emulator_name)): + import urllib.request + import tarfile + import ssl + ssl._create_default_https_context = ssl._create_unverified_context + print('Downloading emulator data (3Mb)...') + urllib.request.urlretrieve( + 'https://bacco.dipc.org/nonlinear_emu_1.0.1.tar', + emulator_name + '.tar', + MyProgressBar()) + tf = tarfile.open(emulator_name+'.tar', 'r') + tf.extractall(path=basefold) + tf.close() + os.remove(emulator_name + '.tar') + else: + emulator_name = fold_name + emulator = {} + emulator['emu_type'] = 'nn' + emulator['model'] = load_model(emulator_name, compile=False) + with open(os.path.join(emulator_name, detail_name), 'rb') as f: + emulator['scaler'] = pickle.load(f) + _pca = pickle.load(f) + emulator['k'] = pickle.load(f) + _trcoords = pickle.load(f) + emulator['bounds'] = pickle.load(f) + + emulator['keys'] = ['omega_cold', 'sigma8_cold', 'omega_baryon', 'ns', + 'hubble', 'neutrino_mass', 'w0', 'wa', 'expfactor'] + if verbose: + print('Nonlinear emulator loaded in memory.') + return emulator + +def _compute_camb_spectrum(params, kmax=50, k_per_logint=0, cold=True): + """ + Calls camb with the current cosmological parameters and returns a + dictionary with the following keys: + kk, pk + :param cold: whether to return the cold matter power spectrum or the total one. Default to cold. + :type cold: bool, optional + + Through the species keyword the following power spectra can be obtained: + matter, cdm, baryons, neutrinos, cold matter (cdm+baryons), photons, + divergence of the cdm velocity field, divergence of the baryon velocity + field, divergence of the cdm-baryon relative velocity field + """ + import camb + + if 'tau' not in params.keys(): + params['tau'] = 0.0952 + if 'num_massive_neutrinos' not in params.keys(): + params['num_massive_neutrinos'] = 3 if params['neutrino_mass'] != 0.0 else 0 + if 'Neffective' not in params.keys(): + params['Neffective'] = 3.046 + if 'omega_k' not in params.keys(): + params['omega_k'] = 0 + if 'omega_cdm' not in params.keys(): + if 'omega_cold' in params.keys(): + params['omega_cdm'] = params['omega_cold'] - params['omega_baryon'] + elif 'omega_matter' in params.keys(): + params['omega_cdm'] = params['omega_matter'] - params['omega_baryon'] - params['neutrino_mass'] / 93.14 / params['hubble']**2 + else: + raise ValueError('At least one among omega_matter and omega_cold should be specified') + + assert params['omega_k'] == 0, 'Non flat geometries are not supported' + + expfactor = params['expfactor'] + + # Set up a new set of parameters for CAMB + pars = camb.CAMBparams() + + # This function sets up CosmoMC-like settings, with one massive neutrino and helium set using BBN consistency + # Set neutrino-related parameters + # camb.nonlinear.Halofit('takahashi') + pars.set_cosmology( + H0=100 * params['hubble'], + ombh2=(params['omega_baryon'] * params['hubble']**2), + omch2=(params['omega_cdm'] * params['hubble']**2), + omk=params['omega_k'], + neutrino_hierarchy='degenerate', + num_massive_neutrinos=params['num_massive_neutrinos'], + mnu=params['neutrino_mass'], + standard_neutrino_neff=params['Neffective'], + tau=params['tau']) + + + if 'A_s' in params.keys(): + if params['A_s'] is not None: + A_s = params['A_s'] + ReNormalizeInputSpectrum = False + else: + A_s = 2.e-9 + ReNormalizeInputSpectrum = True + else: + A_s = 2.e-9 + ReNormalizeInputSpectrum = True + + pars.set_dark_energy( + w=params['w0'], + wa=params['wa']) + + redshifts = [(1 / expfactor - 1)] + if expfactor < 1: + redshifts.append(0) + + pars.InitPower.set_params(ns=params['ns'], As=A_s) + pars.YHe = 0.24 + pars.set_matter_power( + redshifts=redshifts, + kmax=kmax, + k_per_logint=k_per_logint) + + pars.WantCls = False + pars.WantScalars = False + pars.Want_CMB = False + pars.DoLensing = False + + # calculate results for these parameters + results = camb.get_results(pars) + + if cold: + index = 7 # cdm + baryons + else: + index = 6 + kh, z, pk = results.get_linear_matter_power_spectrum(var1=(1 + index), + var2=(1 + index), + hubble_units=True, + have_power_spectra=False, + params=None) + pk = pk[-1, :] + + if ReNormalizeInputSpectrum: + sigma8 = results.get_sigmaR(8, z_indices=-1, var1=(1 + index), var2=(1 + index)) + if cold: + Normalization = (params['sigma8_cold'] / sigma8)**2 + else: + Normalization = (params['sigma8'] / sigma8)**2 + pk *= Normalization + + mask = (kh > 1e-4) + + return {'k': kh[mask], 'pk': pk[mask]} + +def compute_camb_pk(coordinates, k=None, cold=True): + """Compute the linear prediction of the matter power spectrum using camb + + The coordinates must be specified as a dictionary with the following + keywords: + + #. 'omega_cold' + #. 'omega_baryon' + #. 'sigma8' + #. 'hubble' + #. 'ns' + #. 'neutrino_mass' + #. 'w0' + #. 'wa' + #. 'expfactor' + + :param coordinates: a set of coordinates in parameter space + :type coordinates: dict + :param k: a vector of wavemodes in h/Mpc, if None the wavemodes used by + camb are returned, defaults to None + :type k: array_like, optional + :param cold: whether to return the cold matter power spectrum or the total one. Default to cold. + :type cold: bool, optional + :return: k and linear pk + :rtype: tuple + """ + _pk_dict = _compute_camb_spectrum(coordinates, cold=cold) + if k is not None: + _k = k + _interp = interpolate.interp1d(np.log(_pk_dict['k']), np.log(_pk_dict['pk']), kind='cubic') + _pk = np.exp(_interp(np.log(_k))) + else: + _k = _pk_dict['k'] + _pk = _pk_dict['pk'] + return _k, _pk + +def _nowiggles_pk(k_lin=None, pk_lin=None, k_emu=None): + """De-wiggled linear prediction of the cold matter power spectrum + + The BAO feature is removed by identifying and removing its corresponding + bump in real space, by means of a DST, and consequently transforming + back to Fourier space. + See: + - Baumann et al 2018 (https://arxiv.org/pdf/1712.08067.pdf) + - Giblin et al 2019 (https://arxiv.org/pdf/1906.02742.pdf) + + :param k_lin: a vector of wavemodes in h/Mpc, if None the wavemodes used by + camb are returned, defaults to None + :type k_lin: array_like, optional + :param pk_lin: a vector of linear power spectrum computed at k_lin, if None + camb will be called, defaults to None + :type pk_lin: array_like, optional + + :param k_emu: a vector of wavemodes in h/Mpc, if None the wavemodes used by + the emulator are returned, defaults to None + :type k_emu: array_like, optional + + :return: dewiggled pk computed at k_emu + :rtype: array_like + """ + + from scipy.fftpack import dst, idst + + nk = int(2**15) + kmin = k_lin.min() + kmax = 10 + klin = np.linspace(kmin, kmax, nk) + + pkcamb_cs = interpolate.splrep(np.log(k_lin), np.log(pk_lin), s=0) + pklin = np.exp(interpolate.splev(np.log(klin), pkcamb_cs, der=0, ext=0)) + + f = np.log10(klin * pklin) + + dstpk = dst(f, type=2) + + even = dstpk[0::2] + odd = dstpk[1::2] + + i_even = np.arange(len(even)).astype(int) + i_odd = np.arange(len(odd)).astype(int) + + even_cs = interpolate.splrep(i_even, even, s=0) + odd_cs = interpolate.splrep(i_odd, odd, s=0) + + even_2nd_der = interpolate.splev(i_even, even_cs, der=2, ext=0) + odd_2nd_der = interpolate.splev(i_odd, odd_cs, der=2, ext=0) + + # these indexes have been fudged for the k-range considered + # [~1e-4, 10], any other choice would require visual inspection + imin_even = i_even[100:300][np.argmax(even_2nd_der[100:300])] - 20 + imax_even = i_even[100:300][np.argmin(even_2nd_der[100:300])] + 70 + imin_odd = i_odd[100:300][np.argmax(odd_2nd_der[100:300])] - 20 + imax_odd = i_odd[100:300][np.argmin(odd_2nd_der[100:300])] + 75 + + i_even_holed = np.concatenate((i_even[:imin_even], i_even[imax_even:])) + i_odd_holed = np.concatenate((i_odd[:imin_odd], i_odd[imax_odd:])) + + even_holed = np.concatenate((even[:imin_even], even[imax_even:])) + odd_holed = np.concatenate((odd[:imin_odd], odd[imax_odd:])) + + even_holed_cs = interpolate.splrep(i_even_holed, even_holed * (i_even_holed+1)**2, s=0) + odd_holed_cs = interpolate.splrep(i_odd_holed, odd_holed * (i_odd_holed+1)**2, s=0) + + even_smooth = interpolate.splev(i_even, even_holed_cs, der=0, ext=0) / (i_even + 1)**2 + odd_smooth = interpolate.splev(i_odd, odd_holed_cs, der=0, ext=0) / (i_odd + 1)**2 + + dstpk_smooth = [] + for ii in range(len(i_even)): + dstpk_smooth.append(even_smooth[ii]) + dstpk_smooth.append(odd_smooth[ii]) + dstpk_smooth = np.array(dstpk_smooth) + + pksmooth = idst(dstpk_smooth, type=2) / (2 * len(dstpk_smooth)) + pksmooth = 10**(pksmooth) / klin + + k_highk = k_lin[k_lin > 5] + p_highk = pk_lin[k_lin > 5] + + k_extended = np.concatenate((klin[klin < 5], k_highk)) + p_extended = np.concatenate((pksmooth[klin < 5], p_highk)) + + pksmooth_cs = interpolate.splrep(np.log(k_extended), np.log(p_extended), s=0) + pksmooth_interp = np.exp(interpolate.splev(np.log(k_emu), pksmooth_cs, der=0, ext=0)) + + return pksmooth_interp + +def _smeared_bao_pk(k_lin=None, pk_lin=None, k_emu=None, pk_lin_emu=None, pk_nw=None, grid=None): + """Prediction of the cold matter power spectrum using a Boltzmann solver with smeared BAO feature + + :param k_lin: a vector of wavemodes in h/Mpc, if None the wavemodes used by + camb are returned, defaults to None + :type k_lin: array_like, optional + :param pk_lin: a vector of linear power spectrum computed at k_lin, if None + camb will be called, defaults to None + :type pk_lin: array_like, optional + + :param k_emu: a vector of wavemodes in h/Mpc, if None the wavemodes used by + the emulator are returned, defaults to None + :type k_emu: array_like, optional + :param pk_emu: a vector of linear power spectrum computed at k_emu, defaults to None + :type pk_emu: array_like, optional + :param pk_nw: a vector of no-wiggles power spectrum computed at k_emu, defaults to None + :type pk_nw: array_like, optional + :param grid: dictionary with parameter and vector of values where to evaluate the emulator, defaults to None + :type grid: array_like, optional + + :return: smeared BAO pk computed at k_emu + :rtype: array_like + """ + from scipy.integrate import trapz + + if grid is None: + sigma_star_2 = trapz(k_lin * pk_lin, x=np.log(k_lin)) / (3 * np.pi**2) + k_star_2 = 1 / sigma_star_2 + G = np.exp(-0.5 * (k_emu**2 / k_star_2)) + if pk_nw is None: + pk_nw = _nowiggles_pk(k_lin=k_lin, pk_lin=pk_lin, k_emu=k_emu) + else: + sigma_star_2 = trapz(k_lin[None,:] * pk_lin, x=np.log(k_lin[None:,]), axis=1) / (3 * np.pi**2) + k_star_2 = 1 / sigma_star_2 + G = np.exp(-0.5 * (k_emu**2 / k_star_2[:,None])) + if pk_nw is None: + pk_nw = np.array([_nowiggles_pk(k_lin=k_lin, pk_lin=pkl, k_emu=k_emu) for pkl in pk_lin]) + return pk_lin_emu * G + pk_nw * (1 - G) diff --git a/structure/baccoemu/baccoemu_vendored/tqdm.patch b/structure/baccoemu/baccoemu_vendored/tqdm.patch new file mode 100644 index 00000000..f612b6e1 --- /dev/null +++ b/structure/baccoemu/baccoemu_vendored/tqdm.patch @@ -0,0 +1,41 @@ +diff --git a/structure/baccoemu/baccoemu_vendored/__init__.py b/structure/baccoemu/baccoemu_vendored/__init__.py +index 85b3d19..18c66e8 100644 +--- a/structure/baccoemu/baccoemu_vendored/__init__.py ++++ b/structure/baccoemu/baccoemu_vendored/__init__.py +@@ -1,7 +1,7 @@ + import numpy as np + import copy + import pickle +-import progressbar ++import tqdm + import hashlib + from ._version import __version__ + from .utils import * +diff --git a/structure/baccoemu/baccoemu_vendored/utils.py b/structure/baccoemu/baccoemu_vendored/utils.py +index 9b448a1..4e6cd65 100644 +--- a/structure/baccoemu/baccoemu_vendored/utils.py ++++ b/structure/baccoemu/baccoemu_vendored/utils.py +@@ -1,7 +1,7 @@ + import numpy as np + import copy + import pickle +-import progressbar ++import tqdm + import hashlib + from ._version import __version__ + +@@ -68,11 +68,10 @@ class MyProgressBar(): + + def __call__(self, block_num, block_size, total_size): + if not self.pbar: +- self.pbar=progressbar.ProgressBar(maxval=total_size) +- self.pbar.start() +- ++ self.pbar=tqdm.trange(total_size) ++ self.pbar.set_description("Downloading") + downloaded = block_num * block_size + if downloaded < total_size: + self.pbar.update(downloaded) + else: +- self.pbar.finish() ++ self.pbar.close() diff --git a/structure/baccoemu/baccoemu_vendored/utils.py b/structure/baccoemu/baccoemu_vendored/utils.py new file mode 100644 index 00000000..4e6cd65e --- /dev/null +++ b/structure/baccoemu/baccoemu_vendored/utils.py @@ -0,0 +1,77 @@ +import numpy as np +import copy +import pickle +import tqdm +import hashlib +from ._version import __version__ + +def _md5(fname): + hash_md5 = hashlib.md5() + with open(fname, "rb") as f: + for chunk in iter(lambda: f.read(4096), b""): + hash_md5.update(chunk) + return hash_md5.hexdigest() + +def _transform_space(x, space_rotation=False, rotation=None, bounds=None): + """Normalize coordinates to [0,1] intervals and if necessary apply a rotation + + :param x: coordinates in parameter space + :type x: ndarray + :param space_rotation: whether to apply the rotation matrix defined through + the rotation keyword, defaults to False + :type space_rotation: bool, optional + :param rotation: rotation matrix, defaults to None + :type rotation: ndarray, optional + :param bounds: ranges within which the emulator hypervolume is defined, + defaults to None + :type bounds: ndarray, optional + :return: normalized and (if required) rotated coordinates + :rtype: ndarray + """ + if space_rotation: + #Get x into the eigenbasis + R = rotation['rotation_matrix'].T + xR = copy.deepcopy(np.array([np.dot(R, xi) + for xi in x])) + xR = xR - rotation['rot_points_means'] + xR = xR/rotation['rot_points_stddevs'] + return xR + else: + return (x - bounds[:, 0])/(bounds[:, 1] - bounds[:, 0]) + +def accuracy_exp_002(y_true, y_pred): + dataset = K.abs(K.exp(y_pred)/K.exp(y_true)-1) + tot = dataset >= 0 + sel = dataset <= 0.002 + return K.shape(dataset[sel])[0] /K.shape(dataset[tot])[0] + +def accuracy_exp_005(y_true, y_pred): + dataset = K.abs(K.exp(y_pred)/K.exp(y_true)-1) + tot = dataset >= 0 + sel = dataset <= 0.005 + return K.shape(dataset[sel])[0] /K.shape(dataset[tot])[0] + +def accuracy_exp_01(y_true, y_pred): + dataset = K.abs(K.exp(y_pred)/K.exp(y_true)-1) + tot = dataset >= 0 + sel = dataset <= 0.01 + return K.shape(dataset[sel])[0] /K.shape(dataset[tot])[0] + +def mean_absolute_exp_percentage_error(y_true, y_pred): + diff = K.abs((K.exp(y_true) - K.exp(y_pred)) / K.clip(K.exp(y_true), + K.epsilon(),None)) + return K.mean(diff, axis=-1) + +class MyProgressBar(): + def __init__(self): + self.pbar = None + + def __call__(self, block_num, block_size, total_size): + if not self.pbar: + self.pbar=tqdm.trange(total_size) + self.pbar.set_description("Downloading") + downloaded = block_num * block_size + if downloaded < total_size: + self.pbar.update(downloaded) + else: + self.pbar.close() diff --git a/structure/baccoemu/module.yaml b/structure/baccoemu/module.yaml new file mode 100644 index 00000000..ff4ce4b3 --- /dev/null +++ b/structure/baccoemu/module.yaml @@ -0,0 +1,142 @@ +#This is a template for module description files +name: "bacco_emulator" +version: "7e0ca8b556da6ad8e11168026078b1d29920adcf" +purpose: "Emulate the non-linear, baryonified, matter power spectrum" +url: "https://bitbucket.org/rangulo/baccoemu" +interface: "baccoemu_interface.py" +attribution: [Giovanni Aricò, Raul E. Angulo, Sergio Contreras, Lurdes Ondaro-Mallea, Marcos Pellejero-Ibañez, Matteo Zennaro, Jens Stücker, Simon Samuroff] +rules: + Please cite the papers below if you use this code in your research" +cite: + - "https://doi.org/10.1093/mnras/stab1911" + - "https://doi.org/10.1093/mnras/stab2018" + - "https://doi.org/10.12688/openreseurope.14310.2" + +assumptions: + - "Neural network emulation of NL baryonic power effcts" + - "w0waCDM cosmology" + +explanation: | + Baccoemu is a collection of cosmological neural-network emulators for large-scale structure statistics + in a wide cosmological parameter space, including dynamical dark energy and massive neutrinos. + These emulators were developed as part of the Bacco project. + + We imported the Bacco Emulator code into this directory because the PyPI version of the code is not recent, + and it has some dependencies that we would like to install from conda-forge rather than PyPI (tensorflow). + We have to make one change to it to make it work on python 3.8 and 3.9 - replacing the progressbar2 + library with TQDM. A patch file with this change is included. + + The license for this package says copyright belongs to the python packaging authority, but that seems unlikely. + +# List of parameters that can go in the params.ini file in the section for this module +params: + mode: + meaning: + What to emulate; the NL DM-only power, the baryonic boost, or both. Choose from 'nonlinear', 'baryons', 'nonlinear+baryons'. If 'baryons' is chosen then the NL power is read from the block (e.g. from camb). Otherwise the NL power is emulated. + type: str + default: pk_nl_only + +#Inputs for a given choice of a parameter, from the values.ini or from other modules +#If no such choices, just do one of these omitting mode=something part: +inputs: + matter_power_lin: + z: + meaning: Redshifts of samples. + type: real 1d + default: + k_h: + meaning: Wavenumbers k of samples in Mpc/h. + type: real 1d + default: + p_k: + meaning: Linear power spectrum at samples in (Mpc/h)^-3. + type: real 2d + default: + matter_power_nl: + z: + meaning: Redshifts of samples. Only if mode = = "baryons". + type: real 1d + default: + k_h: + meaning: Wavenumbers k of samples in Mpc/h. Only if mode = = "baryons". + type: real 1d + default: + p_k: + meaning: Linear power spectrum at samples in (Mpc/h)^-3. Only if mode = = "baryons". + type: real 2d + default: + cosmological_parameters: + A_s: + meaning: Amplitude of the primordial power spectrum. + type: real + default: + omega_c: + meaning: Cold dark matter density parameter + type: real + default: + omega_b: + meaning: Baryon density parameter + type: real + default: + n_s: + meaning: Primordial power spectrum spectral index. + type: real + default: + h0: + meaning: Hubble parameter. + type: real + default: + mnu: + meaning: Sum of neutrino masses in eV. + type: real + default: + w0: + meaning: Dark energy equation of state parameter at z=0 + type: real + default: -1.0 + wa: + meaning: Dark energy equation of state rate of change with scale factor + type: real + default: 0.0 + baryon_parameters: + M_c: + meaning: Gas mass parameter; log scale in Msun/h. Range 9.0 to 15.0 + type: real + default: + eta: + meaning: Ejected gas density exponential cut-off scale, in range -0.698 to 0.698 + type: real + default: + beta: + meaning: Gas mass index parameter; log scale, in range -1.0 to 0.698 + type: real + default: + M1_z0_cen: + meaning: characteristic halo mass scale for central galaxies, in range 9.0 to 13.0; log scale in Msun/h + type: real + default: + theta_out: + meaning: Scaling of r200 to give outer power-law profile scale of hot gas radius. Range 0.0 to 0.477 + type: real + default: + theta_inn: + meaning: Scaling of r200 to give inner power-law profile scale of hot gas radius. Range -2.0 to -0.522 + type: real + default: + M_inn: + meaning: Characteristic mass of inner hot gas; log scale in Msun/h. Range 9.0 to 13.5. + type: real + default: + + +outputs: + matter_power_nl: + z: + meaning: Redshifts of samples. + type: real 1d + k_h: + meaning: Wavenumbers k of samples in Mpc/h. + type: real 1d + p_k: + meaning: Non-linear power spectrum at samples in (Mpc/h)^-3, potentially including baryon corrections. + type: real 2d diff --git a/structure/projection/project_2d.py b/structure/projection/project_2d.py index 7f78f343..45fa3627 100644 --- a/structure/projection/project_2d.py +++ b/structure/projection/project_2d.py @@ -1507,6 +1507,7 @@ def load_distance_splines(self, block): self.chi_max = chi_distance.max() self.a_of_chi = interp.InterpolatedUnivariateSpline(chi_distance, a_distance) self.chi_of_z = interp.InterpolatedUnivariateSpline(z_distance, chi_distance) + self.max_z_for_chi = z_distance.max() self.dchidz = self.chi_of_z.derivative() self.chi_distance = chi_distance @@ -1537,6 +1538,8 @@ def load_kernels(self, block): dchi=self.shear_kernel_dchi) elif kernel_type == 'K' and sample_name == 'cmb': + if self.max_z_for_chi < 1000.0: + raise ValueError("To get CMB lensing you need to compute distances to very high z. Consider setting the zmax_logz and n_logz parameters if using CAMB.") chi_star = block['distances','chistar'] h0 = block[names.cosmological_parameters, "h0"] self.kernels[sample_name].set_cmblensing_splines(self.chi_of_z, self.a_of_chi, chi_star*h0, clip = self.clip_chi_kernels) diff --git a/tests/test_cosmosis_standard_library.py b/tests/test_cosmosis_standard_library.py index b215a188..dedc4cc3 100644 --- a/tests/test_cosmosis_standard_library.py +++ b/tests/test_cosmosis_standard_library.py @@ -32,11 +32,15 @@ def test_bao(capsys): check_no_camb_warnings(capsys) def test_planck(capsys): + if not os.path.exists("likelihood/planck2018/baseline/plc_3.0/hi_l/plik_lite/plik_lite_v22_TT.clik"): + pytest.skip("Planck data not found") run_cosmosis("examples/planck.ini") - check_likelihood(capsys, "-1441.14", "-1441.30", "-1441.46") + check_likelihood(capsys, "-1441.14", "-1441.30", "-1441.46", "-502.5") check_no_camb_warnings(capsys) def test_planck_class(capsys): + if not os.path.exists("likelihood/planck2018/baseline/plc_3.0/hi_l/plik_lite/plik_lite_v22_TT.clik"): + pytest.skip("Planck data not found") run_cosmosis("examples/planck_class.ini", override={("class","mpk"):"T"}) check_no_camb_warnings(capsys) @@ -102,6 +106,10 @@ def test_des_y3_mead(capsys): check_no_camb_warnings(capsys) def test_act_dr6_lensing(capsys): + try: + import act_dr6_lenslike + except ImportError: + pytest.skip("ACT likelihood code not found") run_cosmosis("examples/act-dr6-lens.ini") check_likelihood(capsys, "-9.89", "-9.86", "-9.90") check_no_camb_warnings(capsys) @@ -133,3 +141,21 @@ def test_kids(capsys): run_cosmosis("examples/kids-1000.ini") check_likelihood(capsys, "-47.6") check_no_camb_warnings(capsys) + +def test_bacco(): + # The baseline version just does non-linear matter power + run_cosmosis("examples/bacco.ini") + + # This variant emulates NL power with baryonic effects + run_cosmosis("examples/bacco.ini", + override={ + ("bacco_emulator", "mode"): "nonlinear+baryons", + }) + + # This variant uses camb to get the NL power and only emulates the baryonic effects + run_cosmosis("examples/bacco.ini", + override={ + ("bacco_emulator", "mode"): "baryons", + ("camb", "nonlinear"): "pk", + ("camb", "halofit_version"): "takahashi", + }) diff --git a/tests/test_demos.py b/tests/test_demos.py index 9e3e3967..70fb1b66 100644 --- a/tests/test_demos.py +++ b/tests/test_demos.py @@ -1,7 +1,7 @@ import os from cosmosis import run_cosmosis from cosmosis.postprocessing import run_cosmosis_postprocess - +import pytest def run_demo(i, args=None, variables=None): if args is None: @@ -45,12 +45,16 @@ def test_demo1(): run_demo(1) def test_demo2(): + if not os.path.exists("likelihood/planck2018/baseline/plc_3.0/hi_l/plik_lite/plik_lite_v22_TT.clik"): + pytest.skip("Planck data not found") run_demo(2) def test_demo3(): run_demo(3, ["grid.nsample_dimension=10"]) def test_demo4(): + if not os.path.exists("likelihood/planck2018/baseline/plc_3.0/hi_l/plik_lite/plik_lite_v22_TT.clik"): + pytest.skip("Planck data not found") run_demo(4, variables=[ "cosmological_parameters.n_s=0.962", "cosmological_parameters.h0=0.680", diff --git a/utility/consistency/module.yaml b/utility/consistency/module.yaml index 6935492f..55db2c1c 100644 --- a/utility/consistency/module.yaml +++ b/utility/consistency/module.yaml @@ -23,63 +23,14 @@ explanation: | then an error status is returned. You can set an option to also calculate the Hubble parameter from the CosmoMC theta - parameter, and vice versa. This is off by default as it's a little slow. - It matches the CosmoMC version to about 0.2%, which is enough for testing the - effects of changing prior but not for precision comparison of the value itself. + parameter, and vice versa. This is off by default as it's a little slower. + It uses the camb code directly so should match up. - The below relations are used by default. These can either be replaced entirely by - those in a file given by the relations_file setup parameter or added to as a comma - separated list using the extra_relations setup parameter. + The standard set of relations is in consistency.py and relates the standard LCDM + parameters, including massive neutrinos. - omega_m=ommh2/h/h + It also converts log1e10As or A_s_1e9 to A_s, and (S_8, Omega_m) to (sigma_8, Omega_m). - omega_b=ombh2/h/h - - omega_c=omch2/h/h - - omega_nu=omnuh2/h/h - - ommh2=omega_m*h*h - - ombh2=omega_b*h*h - - omch2=omega_c*h*h - - omnuh2=omega_nu*h*h - - omch2=ommh2-ombh2 - - ommh2=omch2+ombh2 - - baryon=omega_b/omega_m - - omega_b=omega_m*baryon_fraction - - omega_m=omega_b/baryon_fraction - - baryon_fraction=ombh2/ommh2 - - ombh2=ommh2*baryon_fraction - - ommh2=ombh2/baryon_fraction - - omega_m=omega_b+omega_c - - h=hubble/100 - - hubble=h*100 - - omega_lambda=1-omega_m-omega_k-omega_nu - - omega_m=1-omega_lambda-omega_k-omega_nu - - omega_k=1-omega_m-omega_lambda-omega_nu - - omega_nu=1-omega_m-omega_lambda-omega_k - - mnu=omnuh2*93.14 - - omnuh2=mnu/93.14 params: verbose: @@ -158,6 +109,18 @@ inputs: meaning: Dimensionless Hubble h = H_0 / 100 km/s/Mpc type: real default: + log1e10As: + meaning: log (10**10 * A_s) parameter. Ignored if not present + type: real + default: + A_s_1e9: + meaning: 10**9 * A_s parameter. Ignored if not present + type: real + default: + S_8: + meaning: sigma_8 * (omega_m/0.3)**0.5 parameter. Ignored if not present. + type: real + default: outputs: cosmological_parameters: omega_m: @@ -199,3 +162,9 @@ outputs: h: meaning: Dimensionless Hubble h = H_0 / 100 km/s/Mpc type: real + A_s: + meaning: Amplitude of primordial fluctuations. Only if log1e10As or A_s_1e9 is present on input. + type: real + sigma_8: + meaning: RMS mass fluctuation in 8 Mpc/h spheres. Only if S_8 is present on input. + type: real