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Add 3D sp graph

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Joshua Coles 2023-03-17 21:45:33 +00:00
parent efcd6c0099
commit 1155064306
6 changed files with 1220 additions and 36 deletions
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figures/sp-fd.svg
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notebooks/lib.py
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@ -68,6 +68,16 @@ def read_load(load_dir: str, reader=read_xy_alt):
return pd.concat([reader(path) for path in paths])
def augment_read_with_sp(inner_reader):
def hoc(path: str):
probability = float(Path(path).parent.name)
df = inner_reader(path)
df['probability'] = probability
return df
return hoc
def read_sp_xy(specific_probability_dir: str):
probability = float(Path(specific_probability_dir).name)
df = read_load(specific_probability_dir)
@ -76,11 +86,16 @@ def read_sp_xy(specific_probability_dir: str):
return df
def read_sp(sp_dir: str):
def read_sp(sp_dir: str, inner_reader=read_xy_alt):
if not Path(sp_dir).exists():
raise Exception("Root does not exist")
return pd.concat([read_sp_xy(specific_probability_dir) for specific_probability_dir in glob(f'{sp_dir}/*')])
reader = augment_read_with_sp(inner_reader)
return pd.concat([
read_load(specific_probability_dir, reader)
for specific_probability_dir in glob(f'{sp_dir}/*')
])
def convergent_tail_index(series, tol):
@ -126,3 +141,20 @@ def mean_across(df):
.replace([np.inf, -np.inf], np.nan)
return data
def aggregate_sp_fd(df):
by_run = df.groupby(['probability', 'N'])
by_probability = by_run.agg(
overall_fd=('fd', lambda fd: np.mean(fd[-100:])),
overall_fd_std=('fd', 'std')
).reset_index().groupby('probability')
data = by_probability.agg(
fd=('overall_fd', 'mean'),
# TODO Check stats
fd_std=('overall_fd_std', lambda std: np.sqrt(np.mean(np.square(std))))
)
return data

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notebooks/sp-fd-3d.py Normal file
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@ -0,0 +1,18 @@
from matplotlib import pyplot as plt
from notebooks.lib import read_sp, read_xyz_alt, aggregate_sp_fd
data_3d_sp = read_sp("../data/rust-3d-offaxis-sp", read_xyz_alt)
sp_fd_data = aggregate_sp_fd(data_3d_sp)
# %%
plt.fill_between(sp_fd_data.index, sp_fd_data.fd - sp_fd_data.fd_std, sp_fd_data.fd + sp_fd_data.fd_std, alpha=0.2, label=f"Standard error band")
plt.plot(sp_fd_data.index, sp_fd_data.fd, color='tab:blue', label='fd mean, seeds = 100')
plt.xlabel("$p_{stick}$")
plt.ylabel("$fd$")
plt.legend()
plt.savefig('../figures/sp-fd-3d.svg')
plt.savefig('../figures/sp-fd-3d.png')
plt.show()

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notebooks/sp-fd.py
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@ -1,25 +1,13 @@
import numpy as np
from matplotlib import pyplot as plt
from notebooks.lib import read_sp
from notebooks.lib import read_sp, aggregate_sp_fd
c_sp = read_sp("../data/stick-probability")
by_run = c_sp.groupby(['probability', 'N'])
by_probability = by_run.agg(
overall_fd=('fd', lambda fd: np.mean(fd[-100:])),
overall_fd_std=('fd', 'std')
).reset_index().groupby('probability')
ggg = by_probability.agg(
fd=('overall_fd', 'mean'),
# TODO Check stats
fd_std=('overall_fd_std', lambda std: np.sqrt(np.mean(np.square(std))))
)
data_2d_sp = read_sp("../data/stick-probability")
sp_fd_data = aggregate_sp_fd(data_2d_sp)
# %%
plt.fill_between(ggg.index, ggg.fd - ggg.fd_std, ggg.fd + ggg.fd_std, alpha=0.2, label=f"Standard error band")
plt.plot(ggg.index, ggg.fd, color='tab:blue', label='fd mean, seeds = 100')
plt.fill_between(sp_fd_data.index, sp_fd_data.fd - sp_fd_data.fd_std, sp_fd_data.fd + sp_fd_data.fd_std, alpha=0.2, label=f"Standard error band")
plt.plot(sp_fd_data.index, sp_fd_data.fd, color='tab:blue', label='fd mean, seeds = 100')
plt.xlabel("$p_{stick}$")
plt.ylabel("$fd$")