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working on stonewater alg
This commit is contained in:
Khalim Conn-Kowlessar
parent
2158ab2cd5
commit
4d021f0ba6
1 changed files with 86 additions and 16 deletions
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@ -3,6 +3,7 @@ import PyPDF2
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import re
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import pandas as pd
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import numpy as np
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from docutils.utils.math.tex2mathml_extern import blahtexml
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from tqdm import tqdm
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from collections import Counter
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@ -1681,19 +1682,15 @@ def propsed_wave_3_sample():
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for region in tqdm(unique_postal_regions):
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# Take all of the properties in that region
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region_assets = asset_list[asset_list["Postal Region"] == region].copy()
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archetypes = region_assets["Archetype ID"].unique()
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# We get the properties that have been surveyed
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region_surveyed = survey_results[
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survey_results["Archetype ID"].isin(archetypes) &
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(survey_results["Postal Region"] == region)
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][["Archetype ID", "Current EPC Band"]].drop_duplicates()
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if region_surveyed["Archetype ID"].duplicated().sum():
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raise NotImplementedError("Fix me")
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# We have a tier 1 match if the property itself was surveyed
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exact_surveyed = survey_results[
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survey_results["Address ID"].isin(region_assets["Address ID"])
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]
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region_assets = region_assets.merge(
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region_surveyed,
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on="Archetype ID",
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exact_surveyed[["Address ID", "Current EPC Band"]],
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on="Address ID",
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how="left"
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)
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@ -1701,22 +1698,95 @@ def propsed_wave_3_sample():
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region_assets["Confidence Tier"] = None
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region_assets["Confidence Tier"] = np.where(
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region_assets["Current EPC Band"].isin(["D", "E", "F", "G"]),
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"1", region_assets["Confidence Tier"]
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"1 - property was surveyed", region_assets["Confidence Tier"]
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)
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# TODO: Turn into a function
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missed_archetypes = set(archetypes) - set(region_surveyed["Archetype ID"])
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region_assets["Confidence Tier"] = np.where(
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region_assets["Current EPC Band"].isin(["C", "B", "A"]),
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"6 - property was surveyed", region_assets["Confidence Tier"]
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)
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archetypes = region_assets[
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pd.isnull(region_assets["Confidence Tier"])
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]["Archetype ID"].unique()
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# We get the properties that have been surveyed
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region_surveyed = survey_results[
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survey_results["Archetype ID"].isin(missed_archetypes)
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][["Archetype ID", "Current EPC Band"]].drop_duplicates()
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survey_results["Archetype ID"].isin(archetypes) &
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(survey_results["Postal Region"] == region)
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][["Archetype ID", "Current EPC Band"]].drop_duplicates()
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if region_surveyed["Archetype ID"].duplicated().sum():
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raise NotImplementedError("Fix me 2")
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# Take the duplicated archetypes
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duplicated_archetypes = region_surveyed[
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region_surveyed["Archetype ID"].duplicated()
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]["Archetype ID"].unique()
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duplicated_archetypes = region_surveyed[
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region_surveyed["Archetype ID"].isin(duplicated_archetypes)
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]
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# We need to select which one is the most relevant to these properties
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survey_data = survey_results_with_original_features[
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survey_results_with_original_features["Archetype ID"].isin(duplicated_archetypes["Archetype ID"].values)
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]
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raise NotImplementedError("Fix me")
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region_assets = region_assets.merge(
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region_surveyed,
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on="Archetype ID",
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how="left",
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suffixes=("", "_method1")
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)
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# Label the tier 1 properties
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region_assets["Confidence Tier"] = np.where(
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region_assets["Current EPC Band_method1"].isin(["D", "E", "F", "G"]) &
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pd.isnull(region_assets["Confidence Tier"]),
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"1 - Archetype surveyed", region_assets["Confidence Tier"]
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)
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region_assets = region_assets.drop(columns=["Current EPC Band_method1"])
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# TODO: Turn into a function
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missed_archetypes = set(archetypes) - set(region_surveyed["Archetype ID"])
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archetype_surveyed = survey_results[
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survey_results["Archetype ID"].isin(missed_archetypes)
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][["Archetype ID", "Current EPC Band"]].drop_duplicates()
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if archetype_surveyed["Archetype ID"].duplicated().sum():
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# We need to select which one is the most relevant to these properties
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duplicated_archetypes = archetype_surveyed[
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archetype_surveyed["Archetype ID"].duplicated()
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]["Archetype ID"].unique()
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survey_data = survey_results_with_original_features[
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survey_results_with_original_features["Archetype ID"].isin(duplicated_archetypes)
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]
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homes_with_these_archetypes = region_assets[
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region_assets["Archetype ID"].isin(duplicated_archetypes)
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]
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for _, home in homes_with_these_archetypes.iterrows():
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first_filter = survey_data[
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(survey_data["Postal Region"] == home["Postal Region"]) &
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(survey_data["Property Type"] == home["Property Type"]) &
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(survey_data["Wall Type"].str.split(":").str[0] == home["Wall Type"].split(":")[0])
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]
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if not first_filter.empty:
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NotImplementedError("Fix me 0")
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second_filter = survey_data[
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(survey_data["Property Type"].str.split(":").str[0] == home["Property Type"].split(":")[0]) &
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(survey_data["Wall Type"].str.split(":").str[0] == home["Wall Type"].split(":")[0])
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]
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raise NotImplementedError("Fix me 2")
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region_assets = region_assets.merge(
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archetype_surveyed,
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on="Archetype ID",
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how="left",
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suffixes=("", "_method2")
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)
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