From 4c9947cba7d339104e9fcdc01a007c8fe03cf88a Mon Sep 17 00:00:00 2001 From: Sam Duffield Date: Fri, 19 Jul 2024 10:26:50 +0100 Subject: [PATCH 1/8] Add matrix exponential simulations --- examples/matrix_exponentials/.gitignore | 2 + .../matrix_exponentials/matrix_generation.py | 13 +++ examples/matrix_exponentials/plot.py | 105 +++++++++++++++++ examples/matrix_exponentials/run.py | 107 ++++++++++++++++++ 4 files changed, 227 insertions(+) create mode 100644 examples/matrix_exponentials/.gitignore create mode 100644 examples/matrix_exponentials/matrix_generation.py create mode 100644 examples/matrix_exponentials/plot.py create mode 100644 examples/matrix_exponentials/run.py diff --git a/examples/matrix_exponentials/.gitignore b/examples/matrix_exponentials/.gitignore new file mode 100644 index 0000000..954b04c --- /dev/null +++ b/examples/matrix_exponentials/.gitignore @@ -0,0 +1,2 @@ +*.pdf +*.pkl \ No newline at end of file diff --git a/examples/matrix_exponentials/matrix_generation.py b/examples/matrix_exponentials/matrix_generation.py new file mode 100644 index 0000000..05d1ce8 --- /dev/null +++ b/examples/matrix_exponentials/matrix_generation.py @@ -0,0 +1,13 @@ +from jax import random, numpy as jnp +from scipy.stats import ortho_group + + +def wishart(d: int, key: random.PRNGKey) -> jnp.ndarray: + n = 2 * d # degrees of freedom + G = random.normal(key, shape=(d, n)) + A_wishart = (G @ G.T) / n + return A_wishart + + +def orthogonal(d: int, _) -> jnp.ndarray: + return ortho_group.rvs(d) diff --git a/examples/matrix_exponentials/plot.py b/examples/matrix_exponentials/plot.py new file mode 100644 index 0000000..11a1342 --- /dev/null +++ b/examples/matrix_exponentials/plot.py @@ -0,0 +1,105 @@ +import pickle +import numpy as np +import matplotlib.pyplot as plt +import argparse + + +parser = argparse.ArgumentParser() +parser.add_argument("--save_dir", type=str) +args = parser.parse_args() + +matrix_type = args.save_dir.split("/")[-1].split("_")[1].split(".")[0] + +# use latex for plots +plt.rc("text", usetex=True) +# set font +plt.rc("font", family="serif") +# set font size +plt.rcParams.update({"font.size": 10}) + +colors = [ + plt.cm.viridis(0.2), + plt.cm.viridis(0.4), + plt.cm.viridis(0.6), + plt.cm.viridis(0.8), +] + + +results = pickle.load(open(args.save_dir, "rb")) +ERR_abs = results["ERR_abs"] +dt = results["dt"] +NT = ERR_abs.shape[-1] +D = results["D"] +e0 = 8.0 if matrix_type == "wishart" else 2.1e3 +ylabel = ( + r"$|| \bar{C} - \exp(-A)||_F$" + if matrix_type == "wishart" + else r"$|| \bar{C} - \exp(-M)||_F$" +) + + +def plot(ERR, ylabel, e0, save_path, d_squared=True): + T = np.arange(NT) * dt + ERR_mean = ERR.mean(axis=0) + + # find time where error crosses threshold + TC = np.zeros(len(D)) + for i in range(len(D)): + TC[i] = np.min(T[10:][ERR_mean[i, 10:] < e0]) + + plt.figure(figsize=(7, 4.5)) + + for i in range(len(D)): + plt.plot(T, ERR_mean[i], color=colors[i]) + + # Add error bars + for i in range(len(D)): + plt.fill_between( + T, + ERR_mean[i] - ERR[:, i].std(axis=0), + ERR_mean[i] + ERR[:, i].std(axis=0), + color=colors[i], + alpha=0.3, + zorder=0, + ) + + plt.loglog() + plt.legend(["d = " + str(D[i]) for i in range(len(D))], loc="upper right") + plt.xlabel(r"Time ($\mu$s)", fontsize=18) + plt.ylabel(ylabel, fontsize=18) + + # show threshold as horizontal line + plt.axhline(e0, color="k", linestyle="--") + # show crossing times as vertical lines + for i in range(len(D)): + plt.axvline(TC[i], color=colors[i], linestyle="--") + + plt.xlim(30, T[-1]) + + # inset plot showing crossing time as a function of dimension + ax = plt.axes([0.16, 0.22, 0.3, 0.35]) + ax.tick_params(axis="y", direction="in", pad=-22) + ax.tick_params(axis="x", direction="in", pad=-15) + + for i in range(len(D)): + ax.scatter(D[i], TC[i], color=colors[i], zorder=10) + + if d_squared: + ts = np.array([10, 2000]) + plt.plot(ts, 0.3 * ts**2, color="black", linestyle="--") + plt.text(550, 1.7e5, s=r"$t_C = d^2$", rotation=25) + + plt.plot(D, TC, color="black", zorder=0) + plt.xlim(20, 1500) + + plt.loglog() + plt.xlabel(r"$d$", fontsize=15) + plt.ylabel(r"$t_C$", fontsize=15) + plt.minorticks_off() + + plt.tight_layout() + plt.savefig(save_path, dpi=300) + plt.show() + + +plot(ERR_abs, ylabel, e0, f"examples/matrix_exponentials/{matrix_type}_abs.pdf") diff --git a/examples/matrix_exponentials/run.py b/examples/matrix_exponentials/run.py new file mode 100644 index 0000000..b0d9901 --- /dev/null +++ b/examples/matrix_exponentials/run.py @@ -0,0 +1,107 @@ +from functools import partial +from jax import random, jit, config, numpy as jnp +from jax.scipy.linalg import expm +from jax.lax import scan +import numpy as np +import argparse +from tqdm import tqdm +import thermox +import pickle + +from examples.matrix_exponentials import matrix_generation + +# Set the precision of the computation +config.update("jax_enable_x64", True) + +np.random.seed(42) + + +# Load n_repeats, matrix_type and alpha from the command line +parser = argparse.ArgumentParser() +parser.add_argument("--n_repeats", type=int, default=1) +parser.add_argument("--matrix_type", type=str, default="wishart") +parser.add_argument("--alpha", type=float, default=0.0) +args = parser.parse_args() + + +sample = jit(partial(thermox.sample, associative_scan=False)) +get_matrix = getattr(matrix_generation, args.matrix_type) + + +NT = 10000 +dt = 12 +ts = jnp.arange(NT) * dt +N_burn = 0 +keys = random.split(random.PRNGKey(42), args.n_repeats) + + +gamma = 1 +beta = 1 +alpha = args.alpha + + +@jit +def samps_to_autocovs_errs(samps, true_exp): + def body_func(prev_mat, n): + new_mat = prev_mat * n / (n + 1) + jnp.outer(samps[n], samps[n - 1]) / (n + 1) + err = jnp.linalg.norm(new_mat * jnp.exp(alpha) - true_exp) + return new_mat, err + + return scan( + body_func, + jnp.zeros((samps.shape[1], samps.shape[1])), + jnp.arange(1, samps.shape[0]), + )[1] + + +D = [64, 128, 256, 512] +ERR_abs = np.zeros((args.n_repeats, len(D), NT)) +ERR_rel = np.zeros_like(ERR_abs) + +for repeat in tqdm(range(args.n_repeats)): + key = keys[repeat] + for i in range(len(D)): + d = D[i] + print(f"Repeat {repeat}/{args.n_repeats}, \t D = {d}") + + A = get_matrix(d, key) + + exact_exp_min_A = expm(-A) + + A_shifted = (A + alpha * jnp.eye(A.shape[0])) / dt + B = A_shifted + A_shifted.T + + A_shifted_lambda_min = jnp.min(jnp.linalg.eig(A_shifted / gamma)[0].real) + print("A Eig min: ", A_shifted_lambda_min) + + D_lambda_min = jnp.min(jnp.linalg.eig(B / (gamma * beta))[0].real) + print("D Eig min: ", D_lambda_min) + + x0 = np.zeros(d) + X = sample( + key, + ts, + x0, + A_shifted / gamma, + np.zeros(d), + B / (gamma * beta), + ) + + err_abs = samps_to_autocovs_errs(X, exact_exp_min_A) + + ERR_abs[repeat, i, 1:] = err_abs + ERR_rel[repeat, i, 1:] = err_abs / jnp.linalg.norm(exact_exp_min_A) + + with open( + f"examples/matrix_exponentials/results_{args.matrix_type}.pkl", "wb" + ) as f: + pickle.dump( + { + "D": D, + "dt": dt, + "alpha": alpha, + "ERR_abs": ERR_abs, + "ERR_rel": ERR_rel, + }, + f, + ) From 9e0690d3e41d94a6d74f956de955ada91ca309c3 Mon Sep 17 00:00:00 2001 From: Sam Duffield Date: Fri, 19 Jul 2024 14:30:01 +0100 Subject: [PATCH 2/8] Fix bug enforcing real eigen values --- examples/matrix_exponentials/plot.py | 41 +++++++++++++++++++++++----- examples/matrix_exponentials/run.py | 2 +- thermox/utils.py | 6 +--- 3 files changed, 36 insertions(+), 13 deletions(-) diff --git a/examples/matrix_exponentials/plot.py b/examples/matrix_exponentials/plot.py index 11a1342..39de119 100644 --- a/examples/matrix_exponentials/plot.py +++ b/examples/matrix_exponentials/plot.py @@ -8,8 +8,10 @@ parser.add_argument("--save_dir", type=str) args = parser.parse_args() + matrix_type = args.save_dir.split("/")[-1].split("_")[1].split(".")[0] + # use latex for plots plt.rc("text", usetex=True) # set font @@ -26,19 +28,24 @@ results = pickle.load(open(args.save_dir, "rb")) -ERR_abs = results["ERR_abs"] dt = results["dt"] -NT = ERR_abs.shape[-1] +NT = results["ERR_abs"].shape[-1] D = results["D"] -e0 = 8.0 if matrix_type == "wishart" else 2.1e3 -ylabel = ( +e0_abs = 8.0 if matrix_type == "wishart" else 19.0 +ylabel_abs = ( r"$|| \bar{C} - \exp(-A)||_F$" if matrix_type == "wishart" else r"$|| \bar{C} - \exp(-M)||_F$" ) +e0_rel = 0.9 +ylabel_rel = ( + r"$\frac{|| \bar{C} - \exp(-A)||_F}{||\exp(-A)||_F}$" + if matrix_type == "wishart" + else r"$\frac{|| \bar{C} - \exp(-M)||_F}{||\exp(-M)||_F}$" +) -def plot(ERR, ylabel, e0, save_path, d_squared=True): +def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False): T = np.arange(NT) * dt ERR_mean = ERR.mean(axis=0) @@ -84,8 +91,13 @@ def plot(ERR, ylabel, e0, save_path, d_squared=True): for i in range(len(D)): ax.scatter(D[i], TC[i], color=colors[i], zorder=10) + ts = np.array([10, 2000]) + + if d: + plt.plot(ts, 100 * ts, color="black", linestyle="--") + plt.text(600, 8e4, s=r"$t_C = d$", rotation=25) + if d_squared: - ts = np.array([10, 2000]) plt.plot(ts, 0.3 * ts**2, color="black", linestyle="--") plt.text(550, 1.7e5, s=r"$t_C = d^2$", rotation=25) @@ -102,4 +114,19 @@ def plot(ERR, ylabel, e0, save_path, d_squared=True): plt.show() -plot(ERR_abs, ylabel, e0, f"examples/matrix_exponentials/{matrix_type}_abs.pdf") +plot( + results["ERR_abs"], + ylabel_abs, + e0_abs, + f"examples/matrix_exponentials/{matrix_type}_abs.pdf", + d_squared=True, +) + + +plot( + results["ERR_rel"], + ylabel_rel, + e0_rel, + f"examples/matrix_exponentials/{matrix_type}_rel.pdf", + d=True, +) diff --git a/examples/matrix_exponentials/run.py b/examples/matrix_exponentials/run.py index b0d9901..d6f3c20 100644 --- a/examples/matrix_exponentials/run.py +++ b/examples/matrix_exponentials/run.py @@ -24,7 +24,7 @@ args = parser.parse_args() -sample = jit(partial(thermox.sample, associative_scan=False)) +sample = jit(thermox.sample) get_matrix = getattr(matrix_generation, args.matrix_type) diff --git a/thermox/utils.py b/thermox/utils.py index ffb4c08..c08e8a6 100644 --- a/thermox/utils.py +++ b/thermox/utils.py @@ -28,10 +28,6 @@ def preprocess_drift_matrix(A: Array) -> ProcessedDriftMatrix: """ A_eigvals, A_eigvecs = eig(A + 0.0j) - - A_eigvals = A_eigvals.real - A_eigvecs = A_eigvecs.real - A_eigvecs_inv = jnp.linalg.inv(A_eigvecs) symA = 0.5 * (A + A.T) @@ -39,7 +35,7 @@ def preprocess_drift_matrix(A: Array) -> ProcessedDriftMatrix: return ProcessedDriftMatrix( A, - A_eigvals.real, + A_eigvals, A_eigvecs, A_eigvecs_inv, symA_eigvals, From 111036f5ec2002f3a6af3db27b0bab4ddc2a0417 Mon Sep 17 00:00:00 2001 From: Sam Duffield Date: Fri, 19 Jul 2024 14:39:09 +0100 Subject: [PATCH 3/8] Add label to plots --- examples/matrix_exponentials/plot.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/examples/matrix_exponentials/plot.py b/examples/matrix_exponentials/plot.py index 39de119..b4f9d9d 100644 --- a/examples/matrix_exponentials/plot.py +++ b/examples/matrix_exponentials/plot.py @@ -43,9 +43,10 @@ if matrix_type == "wishart" else r"$\frac{|| \bar{C} - \exp(-M)||_F}{||\exp(-M)||_F}$" ) +fig_label = "(A)" if matrix_type == "wishart" else "(B)" -def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False): +def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False, fig_label=None): T = np.arange(NT) * dt ERR_mean = ERR.mean(axis=0) @@ -56,6 +57,9 @@ def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False): plt.figure(figsize=(7, 4.5)) + if fig_label is not None: + plt.gcf().text(0.02, 0.93, fig_label, fontsize=22) + for i in range(len(D)): plt.plot(T, ERR_mean[i], color=colors[i]) @@ -120,6 +124,7 @@ def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False): e0_abs, f"examples/matrix_exponentials/{matrix_type}_abs.pdf", d_squared=True, + fig_label=fig_label, ) @@ -129,4 +134,5 @@ def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False): e0_rel, f"examples/matrix_exponentials/{matrix_type}_rel.pdf", d=True, + fig_label=fig_label, ) From 96e2c5dd078cb1a90a562b60a8dceeb137cb80b9 Mon Sep 17 00:00:00 2001 From: Sam Duffield Date: Fri, 19 Jul 2024 14:56:27 +0100 Subject: [PATCH 4/8] Minor plot change --- examples/matrix_exponentials/plot.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/matrix_exponentials/plot.py b/examples/matrix_exponentials/plot.py index b4f9d9d..6a148f8 100644 --- a/examples/matrix_exponentials/plot.py +++ b/examples/matrix_exponentials/plot.py @@ -88,7 +88,7 @@ def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False, fig_label=None): plt.xlim(30, T[-1]) # inset plot showing crossing time as a function of dimension - ax = plt.axes([0.16, 0.22, 0.3, 0.35]) + ax = plt.axes([0.17, 0.22, 0.3, 0.35]) ax.tick_params(axis="y", direction="in", pad=-22) ax.tick_params(axis="x", direction="in", pad=-15) From a55ed086e17fc8e2ca666001cdb40d2c588e475f Mon Sep 17 00:00:00 2001 From: Sam Duffield Date: Fri, 19 Jul 2024 14:56:46 +0100 Subject: [PATCH 5/8] Remove import --- examples/matrix_exponentials/run.py | 1 - 1 file changed, 1 deletion(-) diff --git a/examples/matrix_exponentials/run.py b/examples/matrix_exponentials/run.py index d6f3c20..40f8ebb 100644 --- a/examples/matrix_exponentials/run.py +++ b/examples/matrix_exponentials/run.py @@ -1,4 +1,3 @@ -from functools import partial from jax import random, jit, config, numpy as jnp from jax.scipy.linalg import expm from jax.lax import scan From a36cc1a7ebc5f3b634c45a54b85ac23de872f7bd Mon Sep 17 00:00:00 2001 From: Sam Duffield Date: Fri, 19 Jul 2024 15:38:08 +0100 Subject: [PATCH 6/8] Add figures --- examples/matrix_exponentials/.gitignore | 1 - .../matrix_exponentials/orthogonal_abs.pdf | Bin 0 -> 925896 bytes .../matrix_exponentials/orthogonal_rel.pdf | Bin 0 -> 996355 bytes examples/matrix_exponentials/wishart_abs.pdf | Bin 0 -> 926203 bytes examples/matrix_exponentials/wishart_rel.pdf | Bin 0 -> 997399 bytes 5 files changed, 1 deletion(-) create mode 100644 examples/matrix_exponentials/orthogonal_abs.pdf create mode 100644 examples/matrix_exponentials/orthogonal_rel.pdf create mode 100644 examples/matrix_exponentials/wishart_abs.pdf create mode 100644 examples/matrix_exponentials/wishart_rel.pdf diff --git a/examples/matrix_exponentials/.gitignore b/examples/matrix_exponentials/.gitignore index 954b04c..f2a723b 100644 --- a/examples/matrix_exponentials/.gitignore +++ b/examples/matrix_exponentials/.gitignore @@ -1,2 +1 @@ -*.pdf *.pkl \ No newline at end of file diff --git a/examples/matrix_exponentials/orthogonal_abs.pdf b/examples/matrix_exponentials/orthogonal_abs.pdf new file mode 100644 index 0000000000000000000000000000000000000000..6640e0278ebf67914bca1d024cf71844b0e2a8fe GIT binary patch literal 925896 zcmZU4cTiJN)3<_j1nD4Mx-?Rtq=y=6kS@JRZ_=eBMFN4)I|LEw0Ro|y zgdQN2&*yvIZ|0r(=KgVJ&+eK1?cO=(?(W&k_4bXbpoq{*Vy+rETXj3J2-^!b_fJm5 za&m0K@B9IFY{JUc-qtSe4s612tsU&V*hK#c7_ccQ5Zk%g{zp*ie=SgTck^Zw`@aIh zAM`#s+1YrrN&c5q@$*(Q^tSf4V|)4EiMQ6?-gcgDY~ueRiG>Y6TiZIiIj~9m57*P( z#?a22&Fr7rH>&@j*!g+032V6igYf!)M&uCMj-S3~q7ylmd7cbewL|?L55DP2+GwR<;FE;7_N-DXz zx&Na?{v-Ck9q}Lb|MQ%-otuOAXEu@l(WdI?^3PT_VO5uZ4tQf{<8EvBAIM(bo_5x* z#C~}}`D1mT$J{coSiV`37lw3mwG6K`6<_*2pvKXEg~NGreTj8VVvv#kBja2bGI#c) zdd&CgMDqTa^$s0!FMNN53BjQ6Z=&zd=2ma+_PcHhyRHjEP89DiD{ilN?oWk7t_!

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zG#rT{c}`#fuB(Lb39{310NRRr5m*3Siw+v?l5h|Tc}2Sj4wAS5GA9IpsZ%N$CjsxG z1~88DkJ~H^D6pE&YfQq;fKSbW#aniY0oW6eNR5FJfycp-P`oF>nEYciJivznLn8Q= zm_k1^1@)YXNco`|5l@?nNCOekpi}(PX_7A(@r*cYC1=E0P}dppdls=R$K6$gBUtiX zL;&Cl@Um!8*H0Vu8H8P4|~jZQ~M zL@;Hv&1f(c5OuK{4gO9;i0E#c>kB}@piEee2KMS~4ecXfDKQ#^?&;YYl}IF`n|rnf z`eY&|FKUM_-E2ElgE78Th=Rc1+fnIYU(EF-5y{vb5QR#^#zW``VCByBg`%VCM$xXxO>Yh%gbstS|6I z0J(WiUK*7QCWp}=ItjbxG>DFpo3XwKHV2&u!6?)lZPWXYMukX#E{)YF*s%a#1YnEj z*wG;hiH4~&9n=L|KcG>*+v5-gLhoO+O^=0+z~J0rG>AgO?jbq^6RDW>0KO1FYR`>F zhY=8cu7<$iSYtJW1hCC>?Z8fxq&#c@ literal 0 HcmV?d00001 From 7c791706bf3527a1b4c0c35b05fefc107b6ba1e2 Mon Sep 17 00:00:00 2001 From: Sam Duffield Date: Mon, 22 Jul 2024 12:31:36 +0100 Subject: [PATCH 7/8] Add comments to run --- examples/matrix_exponentials/run.py | 28 ++++++++++++++++++---------- 1 file changed, 18 insertions(+), 10 deletions(-) diff --git a/examples/matrix_exponentials/run.py b/examples/matrix_exponentials/run.py index 40f8ebb..d020cc1 100644 --- a/examples/matrix_exponentials/run.py +++ b/examples/matrix_exponentials/run.py @@ -12,33 +12,33 @@ # Set the precision of the computation config.update("jax_enable_x64", True) +# Set seed for orthogonal matrix generation np.random.seed(42) - # Load n_repeats, matrix_type and alpha from the command line parser = argparse.ArgumentParser() parser.add_argument("--n_repeats", type=int, default=1) parser.add_argument("--matrix_type", type=str, default="wishart") parser.add_argument("--alpha", type=float, default=0.0) args = parser.parse_args() - - -sample = jit(thermox.sample) get_matrix = getattr(matrix_generation, args.matrix_type) +alpha = args.alpha +# Jit for speed (avoid recompilation) +sample = jit(thermox.sample) +# Hyperparameters shared across all experiments NT = 10000 dt = 12 ts = jnp.arange(NT) * dt N_burn = 0 keys = random.split(random.PRNGKey(42), args.n_repeats) - - gamma = 1 beta = 1 -alpha = args.alpha +D = [64, 128, 256, 512] +# Function to compute array of autocovariance errors from samples @jit def samps_to_autocovs_errs(samps, true_exp): def body_func(prev_mat, n): @@ -53,10 +53,11 @@ def body_func(prev_mat, n): )[1] -D = [64, 128, 256, 512] +# Initialize arrays to store errors ERR_abs = np.zeros((args.n_repeats, len(D), NT)) ERR_rel = np.zeros_like(ERR_abs) +# Loop over repeats and dimensions for repeat in tqdm(range(args.n_repeats)): key = keys[repeat] for i in range(len(D)): @@ -64,19 +65,23 @@ def body_func(prev_mat, n): print(f"Repeat {repeat}/{args.n_repeats}, \t D = {d}") A = get_matrix(d, key) - exact_exp_min_A = expm(-A) + # Shift and scale A and compute symmetrized B A_shifted = (A + alpha * jnp.eye(A.shape[0])) / dt B = A_shifted + A_shifted.T + # Print eigenvalues A_shifted_lambda_min = jnp.min(jnp.linalg.eig(A_shifted / gamma)[0].real) print("A Eig min: ", A_shifted_lambda_min) D_lambda_min = jnp.min(jnp.linalg.eig(B / (gamma * beta))[0].real) print("D Eig min: ", D_lambda_min) + # Initialize at zeros x0 = np.zeros(d) + + # Run the sampler X = sample( key, ts, @@ -86,11 +91,14 @@ def body_func(prev_mat, n): B / (gamma * beta), ) + # Compute absolute error err_abs = samps_to_autocovs_errs(X, exact_exp_min_A) - ERR_abs[repeat, i, 1:] = err_abs + + # Compute relative error ERR_rel[repeat, i, 1:] = err_abs / jnp.linalg.norm(exact_exp_min_A) + # Save results (overwrites after each repeat) with open( f"examples/matrix_exponentials/results_{args.matrix_type}.pkl", "wb" ) as f: From 3b33c7e580d289cb99daaeddeb4e899e13fa93f6 Mon Sep 17 00:00:00 2001 From: Sam Duffield Date: Mon, 22 Jul 2024 12:36:04 +0100 Subject: [PATCH 8/8] Better casing --- examples/matrix_exponentials/plot.py | 18 +++++++++--------- examples/matrix_exponentials/run.py | 12 ++++++------ 2 files changed, 15 insertions(+), 15 deletions(-) diff --git a/examples/matrix_exponentials/plot.py b/examples/matrix_exponentials/plot.py index 6a148f8..2f7b94a 100644 --- a/examples/matrix_exponentials/plot.py +++ b/examples/matrix_exponentials/plot.py @@ -29,7 +29,7 @@ results = pickle.load(open(args.save_dir, "rb")) dt = results["dt"] -NT = results["ERR_abs"].shape[-1] +NT = results["err_abs"].shape[-1] D = results["D"] e0_abs = 8.0 if matrix_type == "wishart" else 19.0 ylabel_abs = ( @@ -46,14 +46,14 @@ fig_label = "(A)" if matrix_type == "wishart" else "(B)" -def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False, fig_label=None): +def plot(err, ylabel, e0, save_path, d=False, d_squared=False, fig_label=None): T = np.arange(NT) * dt - ERR_mean = ERR.mean(axis=0) + err_mean = err.mean(axis=0) # find time where error crosses threshold TC = np.zeros(len(D)) for i in range(len(D)): - TC[i] = np.min(T[10:][ERR_mean[i, 10:] < e0]) + TC[i] = np.min(T[10:][err_mean[i, 10:] < e0]) plt.figure(figsize=(7, 4.5)) @@ -61,14 +61,14 @@ def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False, fig_label=None): plt.gcf().text(0.02, 0.93, fig_label, fontsize=22) for i in range(len(D)): - plt.plot(T, ERR_mean[i], color=colors[i]) + plt.plot(T, err_mean[i], color=colors[i]) # Add error bars for i in range(len(D)): plt.fill_between( T, - ERR_mean[i] - ERR[:, i].std(axis=0), - ERR_mean[i] + ERR[:, i].std(axis=0), + err_mean[i] - err[:, i].std(axis=0), + err_mean[i] + err[:, i].std(axis=0), color=colors[i], alpha=0.3, zorder=0, @@ -119,7 +119,7 @@ def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False, fig_label=None): plot( - results["ERR_abs"], + results["err_abs"], ylabel_abs, e0_abs, f"examples/matrix_exponentials/{matrix_type}_abs.pdf", @@ -129,7 +129,7 @@ def plot(ERR, ylabel, e0, save_path, d=False, d_squared=False, fig_label=None): plot( - results["ERR_rel"], + results["err_rel"], ylabel_rel, e0_rel, f"examples/matrix_exponentials/{matrix_type}_rel.pdf", diff --git a/examples/matrix_exponentials/run.py b/examples/matrix_exponentials/run.py index d020cc1..88ad020 100644 --- a/examples/matrix_exponentials/run.py +++ b/examples/matrix_exponentials/run.py @@ -54,8 +54,8 @@ def body_func(prev_mat, n): # Initialize arrays to store errors -ERR_abs = np.zeros((args.n_repeats, len(D), NT)) -ERR_rel = np.zeros_like(ERR_abs) +err_abs = np.zeros((args.n_repeats, len(D), NT)) +err_rel = np.zeros_like(err_abs) # Loop over repeats and dimensions for repeat in tqdm(range(args.n_repeats)): @@ -93,10 +93,10 @@ def body_func(prev_mat, n): # Compute absolute error err_abs = samps_to_autocovs_errs(X, exact_exp_min_A) - ERR_abs[repeat, i, 1:] = err_abs + err_abs[repeat, i, 1:] = err_abs # Compute relative error - ERR_rel[repeat, i, 1:] = err_abs / jnp.linalg.norm(exact_exp_min_A) + err_rel[repeat, i, 1:] = err_abs / jnp.linalg.norm(exact_exp_min_A) # Save results (overwrites after each repeat) with open( @@ -107,8 +107,8 @@ def body_func(prev_mat, n): "D": D, "dt": dt, "alpha": alpha, - "ERR_abs": ERR_abs, - "ERR_rel": ERR_rel, + "err_abs": err_abs, + "err_rel": err_rel, }, f, )

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