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nomad-lab
analytics-toolkit-tutorials
Commits
e50370af
Commit
e50370af
authored
8 years ago
by
Ankit Kariryaa
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Add the latest query example tutorial
parent
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query_example_v1_1.bkr
+78
-30
78 additions, 30 deletions
query_example_v1_1.bkr
with
78 additions
and
30 deletions
query_example_v1.bkr
→
query_example_v1
_1
.bkr
+
78
−
30
View file @
e50370af
...
...
@@ -18,12 +18,35 @@
"mode": "javascript",
"background": "#FFE0F0"
}
},
"languageVersion": "ES2015"
},
{
"name": "IPython",
"plugin": "IPython",
"setup": "%matplotlib inline\nimport numpy\nimport matplotlib\nfrom matplotlib import pylab, mlab, pyplot\nnp = numpy\nplt = pyplot\nfrom IPython.display import display\nfrom IPython.core.pylabtools import figsize, getfigs\nfrom pylab import *\nfrom numpy import *\n",
"view": {
"cm": {
"mode": "python"
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}
}
],
"cells": [
{
"id": "sectionVN8BXw",
"id": "markdownT9rKmh",
"type": "markdown",
"body": [
"Warning: running the first cell of this notebook can take a long time(hours).",
"",
"One can run safely the second and third cell, that will analyze a precomputed result of the first cell (queryMgO.out).",
"",
"A more documented version of this notebook will be uploaded soon."
],
"evaluatorReader": false
},
{
"id": "sectionQ3dZWh",
"type": "section",
"title": "Query Example",
"level": 1,
...
...
@@ -31,7 +54,19 @@
"collapsed": false
},
{
"id": "sectionWfNm4q",
"id": "markdownKIKNEj",
"type": "markdown",
"body": [
"*Warning*: running the first cell of this notebook can take a long time(hours), we are working to integrate the (much faster) flink query.",
"",
"One can run safely the second and third cell, that will analyze a precomputed result of the first cell (queryMgO.out).",
"",
"A more documented version of this notebook will be uploaded soon."
],
"evaluatorReader": false
},
{
"id": "sectionzKgCDS",
"type": "section",
"title": "Scan the whole NOMAD Archive",
"level": 2,
...
...
@@ -39,20 +74,14 @@
"collapsed": false
},
{
"id": "markdownwxOAJP",
"type": "markdown",
"body": [
"Try to filter whole archives based on the summary data.",
"Extract not just the data you want to plot but also its identifiers (provenance)"
],
"evaluatorReader": false
},
{
"id": "codesNXl6E",
"id": "codecJWYiO",
"type": "code",
"evaluator": "IPython",
"input": {
"body": [
"from nomad_structure_tools import query",
"percentageOfArchives = 5",
"",
"def hasMgO(stats):",
" els = set(stats.get(\"elements\",{}).keys())",
" return stats and \"Mg\" in els and \"O\" in els and ((stats.get(\"nEigenvalues\", 0) > 0) or stats.get(\"nBands\", 0) > 0)",
...
...
@@ -93,7 +122,7 @@
" else:",
" return None",
"",
"def methodToFile(outPath, archiveGroupIndexRange = query.archiveSplit(0
,
1), calculationGroupIndexRange = query.calculationSplit(0,1)):",
"def methodToFile(outPath, archiveGroupIndexRange = query.archiveSplit(
percentageOfArchives,1
01), calculationGroupIndexRange = query.calculationSplit(0,1)):",
" \"\"\"perform query, stores result to file\"\"\"",
" with open(outPath, \"w\", encoding=\"utf-8\") as outF:",
" nomadArch.queryCalcs(",
...
...
@@ -114,10 +143,10 @@
"state": {}
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"evaluatorReader": true,
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LNKIwc
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"type": "section",
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"level": 2,
...
...
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"collapsed": false
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"id": "markdown
qcviza
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"body": [
"Organize results in a table, convert units (from SI)"
...
...
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ih6a8T
",
"id": "code
CSQ8CP
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"type": "code",
"evaluator": "IPython",
"input": {
"body": [
"import json",
"from ipywidgets import *",
"import pandas as pd",
"#from nomadcore.unit_conversion.unit_conversion import convert_unit_function",
"def convert_unit_function(sourceUnits, targetUnits):",
...
...
@@ -177,7 +205,7 @@
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"barsOnColumn": {},
"heatmapOnColumn": {},
"tableFilter": "",
"showFilter": false,
"columnSearchActive": false,
"columnFilter": [],
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"result": {
...
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"title": "Plot results",
"level": 2,
...
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"id": "code
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...
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"payload": {
"type": "OutputContainer",
"psubtype": "OutputContainer",
"items": [
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"Having kept reference we can get extra features of the data whe have."
...
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