| Name | py2ls JSON |
| Version |
0.2.4.3
JSON |
| download |
| home_page | None |
| Summary | py(thon)2(too)ls |
| upload_time | 2024-10-20 08:50:49 |
| maintainer | None |
| docs_url | None |
| author | Jianfeng |
| requires_python | <4.0,>=3.5 |
| license | None |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Install
```python
pip install py2ls
```
# ips
### listdir, basename, dirname, newfolder, finfo
e.g.,
```python
fpath = "....../"
ips.listdir(fpath, kind='pdf', sort_by="size", ascending=0, output = 'df')
```
it filters the ‘.pdf’ files, and sort by the (file-size/name, length of name, create_time, mod_time, last_open_time …) it returns a DataFrame or BoxList (setting by ‘output’)
```python
dir_data, dir_fig = newfolder(fpath, {'data', 'fig'}) # create folder
```
```python
finfo(fpath) # get info: size, creation time, mod time, parent_path, fname, kind...
```
```python
dir_lib(lib_of_interest) # get the fpath
```
### list_func/func_list (same)
list functions in a package
### fload, fsave, figsave
e.g.,
```python
fload(fpath, kind=None, **kwargs)
```
load file (docx, pdf, image, md, json,csv,txt, html, yaml, xml, xlsx…) or save file.
```python
# figsave, as used in matlab.
figsave(dir_save, "fname.pdf", dpi=300)
```
### pdf2img, img2pdf, docx2pdf
extract images from a PDF, or merge images into a pdf file
```python
pdf2img(dir_pdf, dir_save=None, page=None, kind="png",verbose=True, **kws)
pdf2img(fpath, page=[None, None]) # means extract all pages
# processing page: 1
# processing page: 2
# processing page: 3
# processing page: 4
# processing page: 5
```
```python
img2pdf(dir_img, kind="jpeg",page=None, dir_save=None, page_size="a4", dpi=300)
```
```python
docx2pdf(dir_docx, dir_save) # convert docx to pdf
```
### paper_size
quickly get the size info
```python
paper_size('a4') # [210, 297]
paper_size('card') # [85.6, 53.98]
```
### str2num, num2str, str2list
```python
str2num(“123.345 dollers”,2)# => 123.35 (float)
```
```python
str2list("abcd") # ['a','b','c','d']
```
```python
list2str(['a','b','c','d']) # 'abcd'
```
### ssplit, sreplace
```python
sreplace(text, dict_replace=None, robust=True)
```
```python
ssplit(text, by="space", verbose=False, **kws) # by = "word", "sentence", ", ","num_strings","digital".....,"length", "upper followed lower", "lower followed upper"
```
```python
text = "The most pronounced physiological changes in sleep occur in the brain.[10] The brain uses significantly less energy during sleep than it does when awake, especially during non-REM sleep. In areas with reduced activity, the brain restores its supply of adenosine triphosphate (ATP), the molecule used for short-term storage and transport of energy.[11] In quiet waking, the brain is responsible for 20% of the body's energy use, thus this reduction has a noticeable effect on overall energy consumption.[12]"
ssplit(text, by=["[10]", "[11]", "[12]"])
# ['The most pronounced physiological changes in sleep occur in the brain.',
# ' The brain uses significantly less energy during sleep than it does when awake, especially during non-REM sleep. In areas with reduced activity, the brain restores its supply of adenosine triphosphate (ATP), the molecule used for short-term storage and transport of energy.',
# " In quiet waking, the brain is responsible for 20% of the body's energy use, thus this reduction has a noticeable effect on overall energy consumption.",
# '']
```
```python
ssplit(text[:30], by="len", length=5)
# ['The m', 'ost p', 'ronou', 'nced ', 'physi', 'ologi']
```
```python
ssplit(text, by="non_alphanumeric")
# ['The most pronounced physiological changes in sleep occur in the brain.[',
# '10',
# '] The brain uses significantly less energy during sleep than it does when awake, especially during non-REM sleep. In areas with reduced activity, the brain restores its supply of adenosine triphosphate (ATP), the molecule used for short-term storage and transport of energy.[',
# '11',
# '] In quiet waking, the brain is responsible for ',
# '20',
# "% of the body's energy use, thus this reduction has a noticeable effect on overall energy consumption.[",
# '12',
# ']']
```
```python
ssplit(text, by="sent")
#['The most pronounced physiological changes in sleep occur in the brain.',
#'[10] The brain uses significantly less energy during sleep than it does when awake, especially during non-REM sleep.',
#'In areas with reduced activity, the brain restores its supply of adenosine triphosphate (ATP), the molecule used for short-term storage and transport of energy.',
#"[11] In quiet waking, the brain is responsible for 20% of the body's energy use, thus this reduction has a noticeable effect on overall energy consumption.",
#'[12]']
```
```python
ssplit(text, by="lowup")
# ["The most pronounced physiological changes in sleep occur in the brain.[10] The brain uses significantly less energy during sleep than it does when awake, especially during non-REM sleep. In areas with reduced activity, the brain restores its supply of adenosine triphosphate (ATP), the molecule used for short-term storage and transport of energy.[11] In quiet waking, the brain is responsible for 20% of the body's energy use, thus this reduction has a noticeable effect on overall energy consumption.[12]"]
```
```python
sreplace(text, dict_replace=None, robust=True)
```
```python
text= 'The most pronounced physiological changes in sleep occur in the brain.[10] '
'The brain uses significantly less energy during sleep than it does when '
'awake, especially during non-REM sleep. In areas with reduced activity, the '
'brain restores its supply of adenosine triphosphate (ATP), the molecule used '
'for short-term storage and transport of energy.[11] In quiet waking, the '
"brain is responsible for 20% of the body's energy use, thus this reduction "
'has a noticeable effect on overall energy consumption.[12]'
sreplace(text)
"The most pronounced physiological changes in sleep occur in the brain"
sreplace(text,{"sleep":"wakewake"}) # sreplace(text,dict(sleep="wakewake"))
"The most pronounced physiological changes in wakewake occur in the brain."
```
### stats
#### **FuncCmpt** ( two groups cmp)
```python
FuncCmpt(X1, X2, pmc='auto', pair='unpaired')
e.g.,
X1 = [19, 22, 16, 29, 24]
X2 = [20, 11, 17, 12, 22]
p, res = FumcCmpt(X1,X2, pmc='pmc', pair = 'unpair')
# normally distributed
# normally distributed
# unpaired t text
# t(8) = 1.81117, p=0.1077
p,res = FuncCmpt(x1,x2, pmc='pmc',pair='pair')
# paired t test
# t(4)=1.55556,p=0.19479
```
#### FuncMultiCmpt ( multiple groups cmp)
```python
FuncMultiCmpt(pmc='pmc', pair='unpair', data=None, dv=None, factor=None,
ss_type=2, detailed=True, effsize='np2',
correction='auto', between=None, within=None,
subject=None, group=None
)
```
```python
df = pd.DataFrame({'score': [64, 66, 68, 75, 78, 94, 98, 79, 71, 80,
91, 92, 93, 90, 97, 94, 82, 88, 95, 96,
79, 78, 88, 94, 92, 85, 83, 85, 82, 81],
'group': np.repeat(['strat1', 'strat2', 'strat3'],repeats=10)})
res = FuncMultiCmpt(pmc='auto',pair='unpaired',data=df, dv='score', factor='group', group='group')
res["APA"]
# ['group:F(2, 17)=9.71719,p=0.0016']
```
#### FuncStars
```python
FuncStars(ax,
pval=None,
Ylim=None,
Xlim=None,
symbol='*',
yscale=0.95,
x1=0,
x2=1,
alpha=0.05,
fontsize=14,
fontsize_note=6,
rotation=0,
fontname='Arial',
values_below=None,
linego=True,
linestyle='-',
linecolor='k',
linewidth=.8,
nsshow='off',
symbolcolor='k',
tailindicator=[0.06, 0.06],
report=None,
report_scale=-0.1,
report_loc=None)
```
### plots
#### stdshade
```python
stdshade(ax=None,*args, **kwargs)
```
#### add_colorbar
```python
add_colorbar(im, width=None, pad=None, **kwargs)
```
#### get_color
```python
get_color(n=1, cmap='auto')
```
```python
get_color(12)
# ['#474747',
# '#FF2C00',
# '#0C5DA5',
# '#845B97',
# '#58BBCC',
# '#FF9500',
# '#D57DBE',
# '#474747',
# '#FF2C00',
# '#0C5DA5',
# '#845B97',
# '#58BBCC']
```
```python
get_color(5, cmap="jet") # ['#000080', '#000084', '#000089', '#00008d', '#000092']
get_color(5,cmap="rainbow") #['#8000ff', '#7e03ff', '#7c06ff', '#7a09ff', '#780dff']
```
#### img appearance
#### imgsets
```python
imgsets(
img,
sets=None,
show=True,
show_axis=False,
size=None,
dpi=100,
figsize=None,
auto=False,
filter_kws=None,
)
```
```python
img = imgsets(
fpath,
sets={"rota": -5, "sharp": 10},
dpi=200,
# show_axis=True,
)
figsave(dir_save, "test1_sharp.pdf")
img2 = imgsets(
fpath,
sets={"rota": -5, "crop": [100, 100, 300, 400], "sharp": 10},
dpi=200,
filter_kws={
"sharpen": 10,
},
# show_axis=True,
)
figsave(dir_save, "test2_crop.pdf")
```
```python
fload(dir_img)
```
```python
imgsets(img, sets={"color": 1.5}, show=0)
```
```python
imgsets(img, sets={"pad": (300, 300), "bgcolor": (73, 162, 127)}, show=0)
```
```python
imgsets(
img,
sets={"contrast": 1.3, "color": 1.5, "pad": (300, 300)},
show=0,
filter_kws=dict(sh=1050, EDG=10, gaus=5),
)
```
```python
imgsets(
img,
sets={"color": 10.5},
show=0,
filter_kws=dict(EDGE_ENHANCE=50, EDGE_NHANCEmore=50),
)
```
```python
imgsets(
img,
sets=dict(contr=1.5, rm="default"),
show=0,
# filter_kws=dict(sharp=1),
)
```
```python
imgsets(
img,
sets=dict(contr=0, rm="default"),
show=0,
filter_kws=dict(sharp=1),
)
```
#### figsets
```python
figsets(*args)
```
```python
cm = 1 / 2.54
# plt.style.use("paper")
plt.figure(figsize=[8 * cm, 5 * cm])
for i in range(2, 4):
plt.plot(x, y * i, ls="-")
figsets(
plt.gca(),
{
"xlabel": f"time([{x[0]}:{x[-1]}])",
"ylabel": "Amplitude (signals)",
# "titel": "paper",
"xlim": [0, 600],
"xtick": np.arange(0, 620, 150),
"xlabel": "test xticklabel",
# "ylim": [-2.5, 2.5],
"sp": "go",
# "style": "paper",
"box": ":",
"grid": "on",
"minorticks": "on",
"ticks": {"c": "k"},
},
)
figsets('style','paper')
```
```python
cm = 1/2.54 # centimeters in inches
fig, ax = plt.subplots(1, 1, figsize=(7*cm, 5*cm))
x = np.linspace(0, 2 * np.pi, 50) * 100
y = np.sin(x)
c=get_color(7)
for i in range(2,7):
plt.plot(x, y*i,c=c[i])
figsets(
ax,
{
"xlim": [0, 450],
# "ylim": [-1.5, 1.5],
"xlabel": "2222",
# "style":"paper",
"yticks": np.arange(-5,5, 2),
"ylabel": "ylabelsssss",
"xtkbel": range(0, 800, 100),
# "spine": 5,
"suptitle": "supertitle",
# "minorticks": "y",
# "ticksloc":"lt",
# "ticks": {"direction": "out",'c':'b'},
"rotation":45,
# 'box':"lt",
# "labellocation":'r',
# "ax_color":'b',
# 'grid':{"which":'minor','lw':1,"ls":'-.','c':'b','al':0.3},
},
)
```
Raw data
{
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"name": "py2ls",
"maintainer": null,
"docs_url": null,
"requires_python": "<4.0,>=3.5",
"maintainer_email": null,
"keywords": null,
"author": "Jianfeng",
"author_email": "Jianfeng.Liu0413@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/01/cf/7289c233bb2425b3882cb743d0631f8e9f26bfbf9190a34b99ce2481c33e/py2ls-0.2.4.3.tar.gz",
"platform": null,
"description": "# Install\n\n```python\npip install py2ls\n```\n\n\n\n# ips\n\n### listdir, basename, dirname, newfolder, finfo\n\ne.g., \n\n```python\nfpath = \"....../\"\nips.listdir(fpath, kind='pdf', sort_by=\"size\", ascending=0, output = 'df')\n```\n\nit filters the \u2018.pdf\u2019 files, and sort by the (file-size/name, length of name, create_time, mod_time, last_open_time \u2026) it returns a DataFrame or BoxList (setting by \u2018output\u2019)\n\n```python\ndir_data, dir_fig = newfolder(fpath, {'data', 'fig'}) # create folder\n```\n\n```python\nfinfo(fpath) # get info: size, creation time, mod time, parent_path, fname, kind...\n```\n\n```python\ndir_lib(lib_of_interest) # get the fpath\n```\n\n\n\n### list_func/func_list (same)\n\nlist functions in a package\n\n### fload, fsave, figsave\n\ne.g., \n\n```python\nfload(fpath, kind=None, **kwargs)\n```\n\nload file (docx, pdf, image, md, json,csv,txt, html, yaml, xml, xlsx\u2026) or save file.\n\n```python\n# figsave, as used in matlab. \nfigsave(dir_save, \"fname.pdf\", dpi=300)\n```\n\n\n\n### pdf2img, img2pdf, docx2pdf\n\nextract images from a PDF, or merge images into a pdf file\n\n```python\npdf2img(dir_pdf, dir_save=None, page=None, kind=\"png\",verbose=True, **kws)\npdf2img(fpath, page=[None, None]) # means extract all pages\n# processing page: 1\n# processing page: 2\n# processing page: 3\n# processing page: 4\n# processing page: 5\n\n```\n\n```python\nimg2pdf(dir_img, kind=\"jpeg\",page=None, dir_save=None, page_size=\"a4\", dpi=300)\n```\n\n```python\ndocx2pdf(dir_docx, dir_save) # convert docx to pdf\n```\n\n### paper_size\n\nquickly get the size info\n\n```python\npaper_size('a4') # [210, 297]\npaper_size('card') # [85.6, 53.98]\n```\n\n\n\n### str2num, num2str, str2list\n\n```python\nstr2num(\u201c123.345 dollers\u201d,2)# => 123.35 (float) \n```\n\n```python\nstr2list(\"abcd\") # ['a','b','c','d']\n```\n\n```python\nlist2str(['a','b','c','d']) # 'abcd'\n```\n\n### ssplit, sreplace\n\n```python\nsreplace(text, dict_replace=None, robust=True)\n```\n\n```python\nssplit(text, by=\"space\", verbose=False, **kws) # by = \"word\", \"sentence\", \", \",\"num_strings\",\"digital\".....,\"length\", \"upper followed lower\", \"lower followed upper\"\n```\n\n```python\ntext = \"The most pronounced physiological changes in sleep occur in the brain.[10] The brain uses significantly less energy during sleep than it does when awake, especially during non-REM sleep. In areas with reduced activity, the brain restores its supply of adenosine triphosphate (ATP), the molecule used for short-term storage and transport of energy.[11] In quiet waking, the brain is responsible for 20% of the body's energy use, thus this reduction has a noticeable effect on overall energy consumption.[12]\"\nssplit(text, by=[\"[10]\", \"[11]\", \"[12]\"])\n# ['The most pronounced physiological changes in sleep occur in the brain.',\n# ' The brain uses significantly less energy during sleep than it does when awake, especially during non-REM sleep. In areas with reduced activity, the brain restores its supply of adenosine triphosphate (ATP), the molecule used for short-term storage and transport of energy.',\n# \" In quiet waking, the brain is responsible for 20% of the body's energy use, thus this reduction has a noticeable effect on overall energy consumption.\",\n # '']\n```\n\n```python\nssplit(text[:30], by=\"len\", length=5)\n# ['The m', 'ost p', 'ronou', 'nced ', 'physi', 'ologi']\n```\n\n```python\nssplit(text, by=\"non_alphanumeric\")\n# ['The most pronounced physiological changes in sleep occur in the brain.[',\n# '10',\n# '] The brain uses significantly less energy during sleep than it does when awake, especially during non-REM sleep. In areas with reduced activity, the brain restores its supply of adenosine triphosphate (ATP), the molecule used for short-term storage and transport of energy.[',\n# '11',\n# '] In quiet waking, the brain is responsible for ',\n# '20',\n# \"% of the body's energy use, thus this reduction has a noticeable effect on overall energy consumption.[\",\n# '12',\n# ']']\n```\n\n```python\nssplit(text, by=\"sent\")\n#['The most pronounced physiological changes in sleep occur in the brain.',\n #'[10] The brain uses significantly less energy during sleep than it does when awake, especially during non-REM sleep.',\n #'In areas with reduced activity, the brain restores its supply of adenosine triphosphate (ATP), the molecule used for short-term storage and transport of energy.',\n #\"[11] In quiet waking, the brain is responsible for 20% of the body's energy use, thus this reduction has a noticeable effect on overall energy consumption.\",\n #'[12]']\n```\n\n```python\nssplit(text, by=\"lowup\")\n# [\"The most pronounced physiological changes in sleep occur in the brain.[10] The brain uses significantly less energy during sleep than it does when awake, especially during non-REM sleep. In areas with reduced activity, the brain restores its supply of adenosine triphosphate (ATP), the molecule used for short-term storage and transport of energy.[11] In quiet waking, the brain is responsible for 20% of the body's energy use, thus this reduction has a noticeable effect on overall energy consumption.[12]\"]\n\n```\n\n```python\nsreplace(text, dict_replace=None, robust=True)\n```\n\n```python\ntext= 'The most pronounced physiological changes in sleep occur in the brain.[10] '\n 'The brain uses significantly less energy during sleep than it does when '\n 'awake, especially during non-REM sleep. In areas with reduced activity, the '\n 'brain restores its supply of adenosine triphosphate (ATP), the molecule used '\n 'for short-term storage and transport of energy.[11] In quiet waking, the '\n \"brain is responsible for 20% of the body's energy use, thus this reduction \"\n 'has a noticeable effect on overall energy consumption.[12]'\nsreplace(text)\n\"The most pronounced physiological changes in sleep occur in the brain\"\nsreplace(text,{\"sleep\":\"wakewake\"}) # sreplace(text,dict(sleep=\"wakewake\"))\n\"The most pronounced physiological changes in wakewake occur in the brain.\"\n```\n\n### stats\n\n#### **FuncCmpt** ( two groups cmp)\n\n```python\nFuncCmpt(X1, X2, pmc='auto', pair='unpaired')\ne.g., \nX1 = [19, 22, 16, 29, 24]\nX2 = [20, 11, 17, 12, 22]\np, res = FumcCmpt(X1,X2, pmc='pmc', pair = 'unpair')\n# normally distributed\n# normally distributed\n# unpaired t text\n# t(8) = 1.81117, p=0.1077\np,res = FuncCmpt(x1,x2, pmc='pmc',pair='pair')\n# paired t test\n# t(4)=1.55556,p=0.19479\n```\n\n#### FuncMultiCmpt ( multiple groups cmp)\n\n```python\nFuncMultiCmpt(pmc='pmc', pair='unpair', data=None, dv=None, factor=None,\n ss_type=2, detailed=True, effsize='np2',\n correction='auto', between=None, within=None,\n subject=None, group=None\n )\n```\n\n```python\ndf = pd.DataFrame({'score': [64, 66, 68, 75, 78, 94, 98, 79, 71, 80,\n 91, 92, 93, 90, 97, 94, 82, 88, 95, 96,\n 79, 78, 88, 94, 92, 85, 83, 85, 82, 81],\n 'group': np.repeat(['strat1', 'strat2', 'strat3'],repeats=10)})\nres = FuncMultiCmpt(pmc='auto',pair='unpaired',data=df, dv='score', factor='group', group='group')\nres[\"APA\"] \n# ['group:F(2, 17)=9.71719,p=0.0016']\n```\n\n#### FuncStars\n\n```python\nFuncStars(ax,\n pval=None,\n Ylim=None,\n Xlim=None,\n symbol='*',\n yscale=0.95,\n x1=0,\n x2=1,\n alpha=0.05,\n fontsize=14,\n fontsize_note=6,\n rotation=0,\n fontname='Arial',\n values_below=None,\n linego=True,\n linestyle='-',\n linecolor='k',\n linewidth=.8,\n nsshow='off',\n symbolcolor='k',\n tailindicator=[0.06, 0.06],\n report=None,\n report_scale=-0.1,\n report_loc=None)\n\n\n\n```\n\n### plots\n\n#### stdshade\n\n```python\nstdshade(ax=None,*args, **kwargs)\n```\n\n#### add_colorbar\n\n```python\nadd_colorbar(im, width=None, pad=None, **kwargs)\n```\n\n#### get_color\n\n```python\nget_color(n=1, cmap='auto')\n```\n\n```python\nget_color(12)\n# ['#474747',\n# '#FF2C00',\n# '#0C5DA5',\n# '#845B97',\n# '#58BBCC',\n# '#FF9500',\n# '#D57DBE',\n# '#474747',\n# '#FF2C00',\n# '#0C5DA5',\n# '#845B97',\n# '#58BBCC']\n```\n\n```python\nget_color(5, cmap=\"jet\") # ['#000080', '#000084', '#000089', '#00008d', '#000092']\nget_color(5,cmap=\"rainbow\") #['#8000ff', '#7e03ff', '#7c06ff', '#7a09ff', '#780dff']\n```\n\n#### img appearance\n\n#### imgsets\n\n```python\nimgsets(\n img,\n sets=None,\n show=True,\n show_axis=False,\n size=None,\n dpi=100,\n figsize=None,\n auto=False,\n filter_kws=None,\n)\n```\n\n```python\nimg = imgsets(\n fpath,\n sets={\"rota\": -5, \"sharp\": 10},\n dpi=200,\n # show_axis=True,\n)\nfigsave(dir_save, \"test1_sharp.pdf\")\n\n\nimg2 = imgsets(\n fpath,\n sets={\"rota\": -5, \"crop\": [100, 100, 300, 400], \"sharp\": 10},\n dpi=200,\n filter_kws={\n \"sharpen\": 10,\n },\n # show_axis=True,\n)\nfigsave(dir_save, \"test2_crop.pdf\")\n```\n\n```python\nfload(dir_img)\n```\n\n\n\n```python\nimgsets(img, sets={\"color\": 1.5}, show=0)\n```\n\n\n\n```python\nimgsets(img, sets={\"pad\": (300, 300), \"bgcolor\": (73, 162, 127)}, show=0)\n```\n\n\n\n```python\nimgsets(\n img,\n sets={\"contrast\": 1.3, \"color\": 1.5, \"pad\": (300, 300)},\n show=0,\n filter_kws=dict(sh=1050, EDG=10, gaus=5),\n)\n```\n\n\n\n```python\nimgsets(\n img,\n sets={\"color\": 10.5},\n show=0,\n filter_kws=dict(EDGE_ENHANCE=50, EDGE_NHANCEmore=50),\n)\n```\n\n\n\n```python\nimgsets(\n img,\n sets=dict(contr=1.5, rm=\"default\"),\n show=0,\n # filter_kws=dict(sharp=1),\n)\n```\n\n\n\n```python\nimgsets(\n img,\n sets=dict(contr=0, rm=\"default\"),\n show=0,\n filter_kws=dict(sharp=1),\n)\n```\n\n\n\n#### figsets\n\n```python\nfigsets(*args)\n```\n\n```python\ncm = 1 / 2.54\n# plt.style.use(\"paper\")\nplt.figure(figsize=[8 * cm, 5 * cm])\nfor i in range(2, 4):\n plt.plot(x, y * i, ls=\"-\")\nfigsets(\n plt.gca(),\n {\n \"xlabel\": f\"time([{x[0]}:{x[-1]}])\",\n \"ylabel\": \"Amplitude (signals)\",\n # \"titel\": \"paper\",\n \"xlim\": [0, 600],\n \"xtick\": np.arange(0, 620, 150),\n \"xlabel\": \"test xticklabel\",\n # \"ylim\": [-2.5, 2.5],\n \"sp\": \"go\",\n # \"style\": \"paper\",\n \"box\": \":\",\n \"grid\": \"on\",\n \"minorticks\": \"on\",\n \"ticks\": {\"c\": \"k\"},\n },\n)\nfigsets('style','paper')\n```\n\n```python\ncm = 1/2.54 # centimeters in inches\nfig, ax = plt.subplots(1, 1, figsize=(7*cm, 5*cm))\nx = np.linspace(0, 2 * np.pi, 50) * 100\ny = np.sin(x)\nc=get_color(7)\n\nfor i in range(2,7):\n plt.plot(x, y*i,c=c[i])\nfigsets(\n ax,\n {\n \"xlim\": [0, 450],\n # 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