feat: add new variant of the state object with a history #70
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "3a5b711036c1580c", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# State Objects with History" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "4f3b8109e7e35d3a", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Some state objects use a history, rather than the fields direct in the state, to record changes in an experiment's \n", | ||
| "data over time." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "initial_id", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "AlternateDeltaHistory(history=[...], variables=None, conditions=None, experiment_data=None, model=None)" | ||
| ] | ||
| }, | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import random\n", | ||
| "from pprint import pp\n", | ||
| "\n", | ||
| "from autora.state import Delta\n", | ||
| "from autora.state_history_delta_alternative import AlternateDeltaHistory\n", | ||
| "\n", | ||
| "AlternateDeltaHistory()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "f6a614d39f993a06", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "We create an empty state and add initial data using Deltas. Each time this state is updated, the values in the fields `variables`, `conditions` etc. are replaced:" | ||
| ] | ||
| }, | ||
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| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "1af8d93494c5256d", | ||
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| { | ||
| "data": { | ||
| "text/html": [ | ||
| "<div>\n", | ||
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| "text/plain": [ | ||
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| "execution_count": null, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import pandas as pd\n", | ||
| "\n", | ||
| "s = AlternateDeltaHistory() + Delta(conditions=dict(x=range(5))) + Delta(conditions=dict(x=range(5, 10)))\n", | ||
| "s.conditions" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "3aed485655696cc8", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "But the history keeps a record of the changes: the initial state (emtpy), and then the two Deltas:" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "b4f746a8af05c195", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "History([AlternateDeltaHistory(history=[...], variables=None, conditions=None, experiment_data=None, model=None),\n", | ||
| " {'conditions': {'x': range(0, 5)}},\n", | ||
| " {'conditions': {'x': range(5, 10)}}])" | ||
| ] | ||
| }, | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "s.history" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "bef0879f430ea121", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "We can reconstruct the state at any point by slicing the history and using the `.reconstruct` method, here after the \n", | ||
| "first Delta but before the second:" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "cc7f9c6532f28f8d", | ||
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| " }\n", | ||
| "\n", | ||
| " .dataframe tbody tr th {\n", | ||
| " vertical-align: top;\n", | ||
| " }\n", | ||
| "\n", | ||
| " .dataframe thead th {\n", | ||
| " text-align: right;\n", | ||
| " }\n", | ||
| "</style>\n", | ||
| "<table border=\"1\" class=\"dataframe\">\n", | ||
| " <thead>\n", | ||
| " <tr style=\"text-align: right;\">\n", | ||
| " <th></th>\n", | ||
| " <th>x</th>\n", | ||
| " </tr>\n", | ||
| " </thead>\n", | ||
| " <tbody>\n", | ||
| " <tr>\n", | ||
| " <th>0</th>\n", | ||
| " <td>0</td>\n", | ||
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| " <th>1</th>\n", | ||
| " <td>1</td>\n", | ||
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| " <th>4</th>\n", | ||
| " <td>4</td>\n", | ||
| " </tr>\n", | ||
| " </tbody>\n", | ||
| "</table>\n", | ||
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| ], | ||
| "text/plain": [ | ||
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| "execution_count": null, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "s.history[:2].reconstruct().conditions" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "e72803574116a22f", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "By adding additional metadata to the Deltas, we can make it easier to find particular states. This might be useful in\n", | ||
| " a complex AutoRA cycle where different steps need different versions of the same data. " | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "9b6d6e76dad8beff", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "def apply_transformation_to_input_state(function):\n", | ||
| " \"\"\"Decorator which applies a transformation to the input state\"\"\"\n", | ||
| " " | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "1d187204c2e7a82a", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "Empty DataFrame\n", | ||
| "Columns: [x]\n", | ||
| "Index: []\n", | ||
| "[AlternateDeltaHistory(history=[...], variables=None, conditions=Empty DataFrame\n", | ||
| "Columns: [x]\n", | ||
| "Index: [], experiment_data=None, model=None), {'conditions': {'x': [0]}}]\n", | ||
| " x\n", | ||
| "0 0\n", | ||
| "[AlternateDeltaHistory(history=[...], variables=None, conditions=Empty DataFrame\n", | ||
| "Columns: [x]\n", | ||
| "Index: [], experiment_data=None, model=None), {'conditions': {'x': [0]}}, {'conditions': {'x': [1]}}]\n", | ||
| " x\n", | ||
| "0 1\n", | ||
| "[AlternateDeltaHistory(history=[...], variables=None, conditions=Empty DataFrame\n", | ||
| "Columns: [x]\n", | ||
| "Index: [], experiment_data=None, model=None), {'conditions': {'x': [0]}}, {'conditions': {'x': [1]}}, {'conditions': {'x': [0]}}]\n", | ||
| " x\n", | ||
| "0 0\n", | ||
| "[AlternateDeltaHistory(history=[...], variables=None, conditions=Empty DataFrame\n", | ||
| "Columns: [x]\n", | ||
| "Index: [], experiment_data=None, model=None), {'conditions': {'x': [0]}}, {'conditions': {'x': [1]}}, {'conditions': {'x': [0]}}, {'conditions': {'x': [1]}}]\n", | ||
| " x\n", | ||
| "0 1\n", | ||
| "[AlternateDeltaHistory(history=[...], variables=None, conditions=Empty DataFrame\n", | ||
| "Columns: [x]\n", | ||
| "Index: [], experiment_data=None, model=None), {'conditions': {'x': [0]}}, {'conditions': {'x': [1]}}, {'conditions': {'x': [0]}}, {'conditions': {'x': [1]}}, {'conditions': {'x': [0]}}]\n", | ||
| " x\n", | ||
| "0 0\n", | ||
| "[AlternateDeltaHistory(history=[...], variables=None, conditions=Empty DataFrame\n", | ||
| "Columns: [x]\n", | ||
| "Index: [], experiment_data=None, model=None), {'conditions': {'x': [0]}}, {'conditions': {'x': [1]}}, {'conditions': {'x': [0]}}, {'conditions': {'x': [1]}}, {'conditions': {'x': [0]}}, {'conditions': {'x': [1]}}]\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "from autora.state_history_delta import delta_to_state_transformed\n", | ||
| "from autora.state import inputs_from_state\n", | ||
| "\n", | ||
| "t = AlternateDeltaHistory(conditions=pd.DataFrame({\"x\": []}))\n", | ||
| "\n", | ||
| "# TODO: At this step we need a function which we can use to concatenate all of the \n", | ||
| "# TODO: raw condition data but return them as part of the state. We don't have the \n", | ||
| "# TODO: necessary helper functions on the History yet.\n", | ||
| "@delta_to_state_transformed(lambda s: s.where(meta=\"raw\")) \n", | ||
| "@inputs_from_state\n", | ||
| "def experimentalist(conditions):\n", | ||
| " possible_conditions = set(range(10))\n", | ||
| " print(conditions)\n", | ||
| " already_seen_conditions = set(conditions[\"x\"]) \n", | ||
| " allowed_conditions = possible_conditions - already_seen_conditions\n", | ||
| " conditions_out = min(allowed_conditions)\n", | ||
| " return Delta(conditions=dict(x=[conditions_out]))\n", | ||
| "\n", | ||
| "for i in range(6):\n", | ||
| " t = experimentalist(t)\n", | ||
| " print(t.history)\n", | ||
| "\n", | ||
| "\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "e42f5f53024068ff", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 2 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython2" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
|
There was a problem hiding this comment. These are changes to the basic state adding so that we don't have to emit a warning if there's a field missing in the Delta, which may often be the case for metadata fields. |
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Starting notebook on examples.