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Merge pull request #18 from Naereen/patch-3

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Typo: alohabetically → alphabetically on Gesture Typing.ipynb
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Peter Norvig 2017-12-03 10:25:56 -08:00 committed by GitHub
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ipynb/Gesture Typing.ipynb
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@ -400,7 +400,7 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"And the longest ten paths? Including the lengths? We'll use a helper function, `print_top`, which prints the top *n* items in a seqence according to some key function:" "And the ten longest paths? Including the lengths? We'll use a helper function, `print_top`, which prints the top *n* items in a seqence according to some key function:"
] ]
}, },
{ {
@ -490,7 +490,7 @@
"===\n", "===\n",
"\n", "\n",
"What is the average segment length for a typical typing work load? To answer that, we need to know what a typical work load is. We will read a file of \"typical\" text, and count how many times each segment is used. A `Workload` is a `dict` of the form `{segment: proportion, ...},` e.g. `{'AB': 0.02}`, where each key is a two-letter string (or *bigram*) representing a segment, and each value is the proportion of time that segment appears in the workload. Since the distance from `A` to `B` on a keyboard is the same as the distance from `B` to `A`, we can combine them together into one count;\n", "What is the average segment length for a typical typing work load? To answer that, we need to know what a typical work load is. We will read a file of \"typical\" text, and count how many times each segment is used. A `Workload` is a `dict` of the form `{segment: proportion, ...},` e.g. `{'AB': 0.02}`, where each key is a two-letter string (or *bigram*) representing a segment, and each value is the proportion of time that segment appears in the workload. Since the distance from `A` to `B` on a keyboard is the same as the distance from `B` to `A`, we can combine them together into one count;\n",
"I'll arbitrarily choose count them both under the alohabetically first one. I make a `Counter` of all two-letter segments, and `normalize` it so that the counts sum to 1 (and are thus probabilities)." "I'll arbitrarily choose count them both under the alphabetically first one. I make a `Counter` of all two-letter segments, and `normalize` it so that the counts sum to 1 (and are thus probabilities)."
] ]
}, },
{ {