Updated vimtex and snippets
This commit is contained in:
Minhazul Haque
parent
84a6b218fe
commit
10bf23a6ec
44 changed files with 4209 additions and 69 deletions
109
LuaSnip/python/docs.lua
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109
LuaSnip/python/docs.lua
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@ -0,0 +1,109 @@
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local helpers = require('personal.luasnip-helper-funcs')
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local get_visual = helpers.get_visual
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local line_begin = require("luasnip.extras.expand_conditions").line_begin
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return
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{
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-- FUNCTION PARAMETERS for use in docstrings, with heading
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s({trig="PP", snippetType="autosnippet"},
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fmta(
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[[
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Parameters
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----------
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<> : <>
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<>
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]],
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{
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i(1),
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i(2),
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i(3)
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}
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),
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{condition = line_begin}
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),
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-- FUNCTION RETURNS for use in docstrings, with heading
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s({trig="RR", snippetType="autosnippet"},
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fmta(
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[[
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Returns
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----------
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<> : <>
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<>
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]],
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{
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i(1),
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i(2),
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i(3)
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}
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),
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{condition = line_begin}
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),
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-- NOTES docstring section
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s({trig="NN", snippetType="autosnippet"},
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fmta(
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[[
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NOTES
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-----
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]],
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{ }
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),
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{condition = line_begin}
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),
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-- PRE-CONDITION docstring section
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s({trig="prr", snippetType="autosnippet"},
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fmta(
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[[
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Pre-Conditions
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--------------
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]],
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{ }
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),
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{condition = line_begin}
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),
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-- -- POST-CONDITION docstring section
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-- s({trig="pss", snippetType="autosnippet"},
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-- fmta(
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-- [[
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-- Post-Conditions
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-- ---------------
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-- ]],
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-- { }
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-- ),
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-- {condition = line_begin}
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-- ),
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-- FUNCTION PARAMETER for use in docstrings
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s({trig="::", snippetType="autosnippet"},
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fmta(
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[[
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<> : <>
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<>
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]],
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{
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i(1),
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i(2),
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i(3)
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}
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),
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{condition = line_begin}
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),
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-- LONG STRING OF DASHES FOR COMMENTS
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s({trig = "--", snippetType="autosnippet"},
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{t('# -------------------------------------------------------------------- #')},
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{condition = line_begin}
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),
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-- MULTILINE COMMENT
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s({trig = "cc", snippetType="autosnippet"},
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fmta(
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[[
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"""
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<>
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"""
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]],
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{
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d(1, get_visual),
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}
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),
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{condition = line_begin}
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),
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}
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125
LuaSnip/python/mpl.lua
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125
LuaSnip/python/mpl.lua
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@ -0,0 +1,125 @@
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local helpers = require('personal.luasnip-helper-funcs')
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local get_visual = helpers.get_visual
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local line_begin = require("luasnip.extras.expand_conditions").line_begin
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return
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{
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-- NEW FIGURE, AXES
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s({trig="fx", snippetType="autosnippet"},
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fmta(
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[[fig, ax = plt.subplots(<>)]],
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{
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d(1, get_visual),
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}
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),
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{condition = line_begin}
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),
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-- plt.
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s({trig=";p", snippetType="autosnippet"},
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{t("plt.")}
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),
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-- plt.plot()
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s({trig="pll", snippetType="autosnippet"},
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fmta(
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[[plt.plot(<>)]],
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{
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d(1, get_visual),
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}
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),
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{condition = line_begin}
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),
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-- plt.show()
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s({trig="pss", snippetType="autosnippet"},
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fmta(
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[[plt.show()]],
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{ }
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),
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{condition = line_begin}
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),
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-- AXIS PLOT
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s({trig="xp", snippetType="autosnippet"},
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fmta(
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[[ax.plot(<>)]],
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{
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d(1, get_visual),
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}
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),
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{condition = line_begin}
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),
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-- AXIS SET_XLABEL
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s({trig="xxl", snippetType="autosnippet"},
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fmta(
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[[ax.set_xlabel(<>)]],
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{
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d(1, get_visual),
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}
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),
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{condition = line_begin}
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),
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-- AXIS SET_YLABEL
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s({trig="xyl", snippetType="autosnippet"},
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fmta(
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[[ax.set_ylabel(<>)]],
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{
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d(1, get_visual),
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}
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),
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{condition = line_begin}
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),
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-- AXIS SET_TITLE
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s({trig="xt", snippetType="autosnippet"},
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fmta(
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[[ax.set_title(<>)]],
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{
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d(1, get_visual),
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}
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),
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{condition = line_begin}
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),
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-- TIGHT LAYOUT
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s({trig="ttl", snippetType="autosnippet"},
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{t("plt.tight_layout()")},
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{condition = line_begin}
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),
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-- STEM PLOT
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s({trig="stem", snippetType="autosnippet"},
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fmta(
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[[
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(markers, stemlines, baseline) = ax.stem(<>)
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plt.setp(markers, marker='o', markerfacecolor=<>, markeredgecolor="none", markersize=6)
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plt.setp(baseline, color=<>, linestyle="-")
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plt.setp(stemlines, linestyle="--", color=<>, linewidth=2)
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]],
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{
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i(1),
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i(2),
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i(3),
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i(4)
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}
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),
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{condition = line_begin}
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),
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-- REMOVE SPINE FUNCTION
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s({trig="spines"},
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fmta(
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[[
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def remove_spines(ax):
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"""
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Removes top and right spines from the inputted Matplotlib axis. This is for
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aesthetic purposes only and has no practical function.
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"""
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ax.spines['top'].set_visible(False)
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ax.spines['right'].set_visible(False)
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ax.get_xaxis().tick_bottom()
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ax.get_yaxis().tick_left()
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]],
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{
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}
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),
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{condition = line_begin}
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),
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}
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19
LuaSnip/python/numpy.lua
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19
LuaSnip/python/numpy.lua
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@ -0,0 +1,19 @@
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local helpers = require('personal.luasnip-helper-funcs')
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local get_visual = helpers.get_visual
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local line_begin = require("luasnip.extras.expand_conditions").line_begin
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return
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{
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-- NP.LOADTXT
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s({trig="nlt", snippetType="autosnippet"},
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fmta(
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[[
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np.loadtxt(<>)
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]],
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{
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d(1, get_visual),
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}
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)
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),
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}
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163
LuaSnip/python/python.lua
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163
LuaSnip/python/python.lua
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@ -0,0 +1,163 @@
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local helpers = require('personal.luasnip-helper-funcs')
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local get_visual = helpers.get_visual
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local line_begin = require("luasnip.extras.expand_conditions").line_begin
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return
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{
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-- PRINT STATEMENT
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s({trig="pp", snippetType="autosnippet"},
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fmta(
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[[print(<>)]],
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{
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d(1, get_visual),
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}
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),
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{condition = line_begin}
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),
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-- MAIN FUNCTION
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s({trig="main", snippetType="autosnippet"},
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fmta(
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[[
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if __name__ == "__main__":
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<>
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]],
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{
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d(1, get_visual),
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}
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),
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{condition = line_begin}
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),
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-- CLASS
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s({trig="class"},
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fmta(
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[[
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class <>(<>):
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def __init__(self<>):
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<>
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]],
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{
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i(1),
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i(2),
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i(3),
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i(4),
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}
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),
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{condition = line_begin}
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),
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-- EXIT MAIN FUNCTION with sys.exit()
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s({trig="XX", snippetType="autosnippet"},
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{ t("sys.exit()") },
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{condition = line_begin}
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),
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-- FUNCTION DEFINITION WITH CHOICE NODE DOCSTRING
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-- The idea is to let you choose if you want to use the docstring or not
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s({trig="ff", snippetType="autosnippet"},
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fmta(
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[[
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def <>(<>):
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<><>
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]],
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{
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i(1),
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i(2),
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c(3, {sn(nil, {t({"\"\"\"", ""}), t(" "), i(1, ""), t({"", " \"\"\"", " "})}), t("")}),
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-- t(" "),
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d(4, get_visual),
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}
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),
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{condition = line_begin}
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),
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-- TIME, i.e. snippet for timing code execution
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s({trig="time"},
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fmta(
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[[
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start = time.time()
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<>
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end = time.time()
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]],
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{
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d(1, get_visual),
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}
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)
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),
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-- for _ in range()
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s({trig="frr", snippetType = "autosnippet"},
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fmta(
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[[
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for <> in range(<>):
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<>
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]],
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{
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i(1),
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i(2),
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i(3)
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}
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),
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{condition = line_begin}
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),
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-- IF STATEMENT
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s({trig="iff", snippetType = "autosnippet"},
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fmta(
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[[
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if <>:
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<>
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]],
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{
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i(1),
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d(2, get_visual),
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}
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),
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{condition = line_begin}
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),
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-- with open(filename) as file
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s({trig="wof", snippetType = "autosnippet"},
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fmta(
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[[
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with open(<>) as <>:
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<>
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]],
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{
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i(1),
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i(2, 'file'),
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i(0),
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}
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),
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{condition = line_begin}
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),
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-- RETURN STATEMENT
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s({trig = ";r", snippetType = "autosnippet"},
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{ t("return") },
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{ condition = line_begin }
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),
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-- KWARGS STATEMENT
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s({trig = ";k", snippetType = "autosnippet", wordTrig=false},
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{ t("kwargs") }
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),
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-- KWARGS.GET
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s({trig="kgg", snippetType = "autosnippet"},
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fmta(
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[[
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kwargs.get('<>', '<>')
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]],
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{
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d(1, get_visual),
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i(2)
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}
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)
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),
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-- SELF (for use in classes)
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s({trig = ";s", snippetType = "autosnippet"},
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{ t("self.") }
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),
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-- SELF (for use in classes) without dot
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s({trig = ";S", snippetType = "autosnippet"},
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{ t("self") }
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),
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-- TRACEBACK
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s({trig = "tbb", snippetType = "autosnippet"},
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{ t("print(traceback.format_exc())") },
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{ condition = line_begin }
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),
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}
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131
LuaSnip/python/torch.lua
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131
LuaSnip/python/torch.lua
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@ -0,0 +1,131 @@
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local helpers = require('personal.luasnip-helper-funcs')
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local get_visual = helpers.get_visual
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local line_begin = require("luasnip.extras.expand_conditions").line_begin
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return
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{
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-- COMMON IMPORTS
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s({trig="itorch"},
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fmt(
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[[
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import torch
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from torch import nn
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from torch.utils.data import Dataset, DataLoader
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]],
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{
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}
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),
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{condition = line_begin}
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),
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-- NETWORK MODEL TEMPLATE
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s({trig="model"},
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fmta(
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[[
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class FooNet(nn.Module):
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def __init__(self):
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super(FooNet, self).__init__()
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<>
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def forward(self, x):
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<>
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]],
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{
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i(1),
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i(2)
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}
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),
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{condition = line_begin}
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),
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-- CUSTOM DATASET TEMPLATE
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s({trig="dataset"},
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fmta(
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[[
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class FooDataset(Dataset):
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def __init__(self, ...):
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<>
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def __getitem__(self, index):
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# Returns the (feature vector, label) tuple at index `index`
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<>
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def __len__(self):
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# Return number of instances in dataset
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<>
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]],
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{
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i(1),
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i(2),
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i(3)
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}
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),
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{condition = line_begin}
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),
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-- SGD OPTIMIZER
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s({trig="optim"},
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fmta(
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[[
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optim = torch.optim.SGD(model.parameters(), lr=<>)
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]],
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{
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i(1),
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}
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),
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{condition = line_begin}
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),
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-- TRAINING LOOP TEMPLATE
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s({trig="train"},
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fmta(
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[[
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def train_loop(dataloader, model, loss_fn, optim):
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N = len(dataloader.dataset)
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# Loop over all minibatches in dataset
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for mb, (X, y) in enumerate(dataloader):
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# Compute prediction and loss
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pred = model(X)
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loss = loss_fn(pred, y)
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# Backpropagation
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optimizer.zero_grad()
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loss.backward()
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optimizer.step()
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# Log loss and number of instances trained
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if mb % <> == 0:
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loss, n = loss.item(), mb * len(X)
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print("loss: {:.7f} [{:5d}/{:5d}]".format(loss, n, N))
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]],
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{
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i(1, "100"),
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}
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),
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{condition = line_begin}
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),
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-- TEST LOOP TEMPLATE
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s({trig="test"},
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fmta(
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[[
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def test_loop(dataloader, model, loss_fn):
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N = len(dataloader.dataset)
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num_batches = len(dataloader)
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test_loss = 0
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correct_preds = 0
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with torch.no_grad():
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for X, y in dataloader:
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pred = model(X)
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test_loss += loss_fn(pred, y).item()
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correct_preds += (pred.argmax(1) == y).type(torch.float).sum().item()
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test_loss /= num_batches
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print("Test Error: \n Accuracy: {:.1f}%\n Avg loss per minibatch: {:8f} \n".format((100*correct_preds/N), test_loss))
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]],
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{ }
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),
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{condition = line_begin}
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),
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}
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