Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Energy distr #269

Open
wants to merge 18 commits into
base: develop
Choose a base branch
from
Open

Energy distr #269

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
18 commits
Select commit Hold shift + click to select a range
6b4e22e
update
Dec 23, 2022
ac4b97a
update
Dec 26, 2022
6fec4e4
update
Dec 29, 2022
0520928
update
Jan 16, 2023
10b4d20
update
Jan 23, 2023
45310f6
read MCNP table 126 (#250)
luca-fiorito-11 Feb 2, 2023
79f3727
Update unit_test.yml
luca-fiorito-11 Feb 13, 2023
8cfb432
update
Feb 13, 2023
6b07ba6
Merge branch 'v1.0' of https://github.com/luca-fiorito-11/sandy into …
Feb 13, 2023
a5d6191
Fix sampling unit tests (#252)
luca-fiorito-11 Feb 17, 2023
f369b91
Expanding the use for the energy distribution data
May 10, 2023
84ce2f6
Comments added
May 10, 2023
8bdf93f
Input for specific incident energy
May 11, 2023
b457c75
Test for efmean for mf 35
May 11, 2023
1722047
test for chi covariance matrix added
May 11, 2023
7b4b45e
Test for chi data added
May 11, 2023
5a05d45
Option to use ifissp without incident mean energy
May 11, 2023
b6b3d5f
Better approach to efmean plus relative test and info added
May 12, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions .github/workflows/unit_test.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6,9 +6,9 @@ name: CI
on:
# Triggers the workflow on push or pull request events but only for the develop branch
push:
branches: [ develop ]
branches: [ develop, v1.0 ]
pull_request:
branches: [ develop ]
branches: [ develop, v1.0 ]

# Allows you to run this workflow manually from the Actions tab
workflow_dispatch:
Expand Down
Binary file added librwfortra.QHHCXIBOJA55O3WWC5YSNGHAWGL2BYRO.gfortran-win_amd64.dll
View file
Open in desktop
Binary file not shown.
263 changes: 263 additions & 0 deletions notebooks/notebook_shapiro.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,263 @@
{
"cells": [
{
"cell_type": "markdown",
"id": "cfc7bba9",
"metadata": {},
"source": [
"# Shapiro-Wilk test for normal and lognormal distributions"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8e456eaf",
"metadata": {},
"outputs": [],
"source": [
"import sandy"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "35fae75e",
"metadata": {},
"outputs": [],
"source": [
"import logging\n",
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8e08433c",
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import seaborn as sns"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c57f6407",
"metadata": {},
"outputs": [],
"source": [
"logging.getLogger().setLevel(logging.WARN)"
]
},
{
"cell_type": "markdown",
"id": "8d1ddd57",
"metadata": {},
"source": [
"Generate 5000 xs samples normally and log-normally distributed"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fa73bbbc",
"metadata": {},
"outputs": [],
"source": [
"tape = sandy.get_endf6_file(\"jeff_33\", \"xs\", 10010)\n",
"njoy_kws = dict(err=1, errorr33_kws=dict(mt=102))\n",
"nsmp = 5000\n",
"seed = 5\n",
"\n",
"smp_norm = tape.get_perturbations(nsmp, njoy_kws=njoy_kws, smp_kws=dict(seed33=seed, pdf=\"normal\"))[33]\n",
"smp_lognorm = tape.get_perturbations(nsmp, njoy_kws=njoy_kws, smp_kws=dict(seed33=seed, pdf=\"lognormal\"))[33]\n",
"smp_uniform = tape.get_perturbations(nsmp, njoy_kws=njoy_kws, smp_kws=dict(seed33=seed, pdf=\"uniform\"))[33]"
]
},
{
"cell_type": "markdown",
"id": "08f12802",
"metadata": {},
"source": [
"## Shapiro-Wilk test normal samples and normal distribution"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4cf664f6",
"metadata": {},
"outputs": [],
"source": [
"stat_norm = []\n",
"stat_lognorm = []\n",
"for n in [10, 50, 100, 500, 1000, 5000]:\n",
" df = smp_norm.test_shapiro(pdf=\"normal\", size=n)\n",
" idx = df.statistic.idxmin()\n",
" stat_norm.append(df.loc[idx].rename(n))\n",
"\n",
" df = smp_norm.test_shapiro(pdf=\"lognormal\", size=n)\n",
" idx = df.statistic.idxmin()\n",
" stat_lognorm.append(df.loc[idx].rename(n))\n",
"\n",
"opts = dict(left_index=True, right_index=True, suffixes=(\"_norm\", \"_lognorm\"))\n",
"pd.DataFrame(stat_norm).merge(pd.DataFrame(stat_lognorm), **opts).rename_axis(\"# SMP\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "449bdf7d",
"metadata": {},
"outputs": [],
"source": [
"test = smp_norm.test_shapiro(pdf=\"normal\", size=5000)\n",
"\n",
"fig, ax = plt.subplots(figsize=(7, 4), dpi=100)\n",
"\n",
"idx = test.statistic.idxmin()\n",
"w = test.loc[idx]\n",
"sns.histplot(data=smp_norm.data.loc[idx], label=f\"W:stat={w.statistic:.2e}, p-value={w.pvalue:.2e}\", color=\"dodgerblue\")\n",
"\n",
"idx = test.statistic.idxmax()\n",
"w = test.loc[idx]\n",
"sns.histplot(data=smp_norm.data.loc[idx], label=f\"W:stat={w.statistic:.2e}, p-value={w.pvalue:.2e}\", color=\"tomato\")\n",
"\n",
"ax.set(xlabel=\"W\")\n",
"ax.legend()\n",
"fig.tight_layout()"
]
},
{
"cell_type": "markdown",
"id": "78c3e97d",
"metadata": {},
"source": [
"## Shapiro-Wilk test for lognormal samples and lognormal distribution"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "be16d4f1",
"metadata": {},
"outputs": [],
"source": [
"stat_norm = []\n",
"stat_lognorm = []\n",
"for n in [10, 50, 100, 500, 1000, 5000]:\n",
" df = smp_lognorm.test_shapiro(pdf=\"normal\", size=n)\n",
" idx = df.statistic.idxmin()\n",
" stat_norm.append(df.loc[idx].rename(n))\n",
"\n",
" df = smp_lognorm.test_shapiro(pdf=\"lognormal\", size=n)\n",
" idx = df.statistic.idxmin()\n",
" stat_lognorm.append(df.loc[idx].rename(n))\n",
"\n",
"opts = dict(left_index=True, right_index=True, suffixes=(\"_norm\", \"_lognorm\"))\n",
"pd.DataFrame(stat_norm).merge(pd.DataFrame(stat_lognorm), **opts).rename_axis(\"# SMP\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8fa36199",
"metadata": {},
"outputs": [],
"source": [
"test = smp_lognorm.test_shapiro(pdf=\"lognormal\", size=5000)\n",
"\n",
"fig, ax = plt.subplots(figsize=(7, 4), dpi=100)\n",
"\n",
"idx = test.statistic.idxmin()\n",
"w = test.loc[idx]\n",
"sns.histplot(data=smp_lognorm.data.loc[idx], label=f\"W:stat={w.statistic:.2e}, p-value={w.pvalue:.2e}\", color=\"dodgerblue\")\n",
"\n",
"idx = test.statistic.idxmax()\n",
"w = test.loc[idx]\n",
"sns.histplot(data=smp_lognorm.data.loc[idx], label=f\"W:stat={w.statistic:.2e}, p-value={w.pvalue:.2e}\", color=\"tomato\")\n",
"\n",
"ax.set(xlabel=\"W\")\n",
"ax.legend()\n",
"fig.tight_layout()"
]
},
{
"cell_type": "markdown",
"id": "975dbaa1",
"metadata": {},
"source": [
"## Shapiro-Wilk test for uniform samples and normal distribution"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bded2114",
"metadata": {},
"outputs": [],
"source": [
"stat_norm = []\n",
"stat_lognorm = []\n",
"for n in [10, 50, 100, 500, 1000, 5000]:\n",
" df = smp_uniform.test_shapiro(pdf=\"normal\", size=n)\n",
" idx = df.statistic.idxmin()\n",
" stat_norm.append(df.loc[idx].rename(n))\n",
"\n",
" df = smp_uniform.test_shapiro(pdf=\"lognormal\", size=n)\n",
" idx = df.statistic.idxmin()\n",
" stat_lognorm.append(df.loc[idx].rename(n))\n",
"\n",
"opts = dict(left_index=True, right_index=True, suffixes=(\"_norm\", \"_lognorm\"))\n",
"pd.DataFrame(stat_norm).merge(pd.DataFrame(stat_lognorm), **opts).rename_axis(\"# SMP\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b6e1d4ee",
"metadata": {},
"outputs": [],
"source": [
"test = smp_uniform.test_shapiro(pdf=\"uniform\", size=5000)\n",
"\n",
"fig, ax = plt.subplots(figsize=(7, 4), dpi=100)\n",
"\n",
"idx = test.statistic.idxmin()\n",
"w = test.loc[idx]\n",
"sns.histplot(data=smp_uniform.data.loc[idx], label=f\"W:stat={w.statistic:.2e}, p-value={w.pvalue:.2e}\", color=\"dodgerblue\")\n",
"\n",
"idx = test.statistic.idxmax()\n",
"w = test.loc[idx]\n",
"sns.histplot(data=smp_uniform.data.loc[idx], label=f\"W:stat={w.statistic:.2e}, p-value={w.pvalue:.2e}\", color=\"tomato\")\n",
"\n",
"ax.set(xlabel=\"W\")\n",
"ax.legend()\n",
"fig.tight_layout()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python3 (sandy-devel)",
"language": "python",
"name": "sandy-devel"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
2 changes: 1 addition & 1 deletion requirements_conda.txt
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,4 +11,4 @@ scipy
sphinx
seaborn >= 0.9
statsmodels
pytables
pytables
Binary file added rwf.cp310-win_amd64.pyd
View file
Open in desktop
Binary file not shown.
3 changes: 2 additions & 1 deletion sandy/__init__.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
from .decay import *
from .energy_grids import *
from .errorr import *
from .groupr import *
from .gendf import *
from .fy import *
from .tsl import *
from .gls import *
Expand All @@ -23,6 +23,7 @@
from .utils import *
from .core import *
from .sampling import *
from .spectra import *
import sandy.mcnp
import sandy.aleph2
import sandy.tools
Expand Down
Loading