feature-as-you-go.py

import matplotlib.pyplot as plt
import numpy as np

PRICE_SHEET = {
    "scale_amount": 1000,
    "base_price": 1,
    "feature_x": 0.1,
    "feature_y": 0.15,
    "feature_z": 0.20,
}


def compute_price(feature_list, base_unit_price, scale_amount):
    # 5 units * 10 cost = 50 cost
    base_price_at_scale_amount = base_unit_price * scale_amount
    for idx, premium in enumerate(feature_list):
        # safety check. if there are no feature premiums, the base price is valid.
        if len(feature_list) == 0:
            base_price_at_scale_amount = base_unit_price * scale_amount
        else:
            # add the premium cost to the base price.
            base_price_at_scale_amount += base_price_at_scale_amount * premium
    return base_price_at_scale_amount


def compute(local_price_sheet):
    results = {
        "no_features": [],
        "feature_x": [],
        "feature_y": [],
        "feature_z": []
    }
    for scale_unit in range(0, local_price_sheet["scale_amount"]):
        no_features_results = compute_price([], local_price_sheet["base_price"], scale_unit)
        results["no_features"].append(no_features_results)

        feature_x_results = compute_price(
            [
                local_price_sheet["feature_x"]
            ],
            local_price_sheet["base_price"],
            scale_unit
        )
        results["feature_x"].append(feature_x_results)

        feature_y_results = compute_price(
            [
                local_price_sheet["feature_x"],
                local_price_sheet["feature_y"]
            ],
            local_price_sheet["base_price"],
            scale_unit
        )
        results["feature_y"].append(feature_y_results)

        feature_z_results = compute_price(
            [
                local_price_sheet["feature_x"],
                local_price_sheet["feature_y"],
                local_price_sheet["feature_z"]
            ],
            local_price_sheet["base_price"],
            scale_unit
        )
        results["feature_z"].append(feature_z_results)
    return results


def main():
    for i in range(1, 100, 25):
        print("computing loop {}".format(i))
        local_price_sheet = PRICE_SHEET
        local_price_sheet["scale_amount"] = local_price_sheet["scale_amount"] * i
        feature_price_scale = compute(local_price_sheet)

        x = np.linspace(0, PRICE_SHEET["scale_amount"], PRICE_SHEET["scale_amount"])

        plt.figure()
        plt.suptitle("Feature Premium at Scale")
        plt.title("Feature Premium Max Diff Per Billing Cycle: {:.2f}".format(
            feature_price_scale["feature_z"][-1] - feature_price_scale["no_features"][-1]))

        plt.ylabel("Price in Currency Units")
        plt.xlabel("Units in Circulation")

        plt.plot(x, feature_price_scale["no_features"], label="no features", linestyle="-")
        plt.plot(x, feature_price_scale["feature_x"], label="feature set x", linestyle="--")
        plt.plot(x, feature_price_scale["feature_y"], label="feature set y", linestyle="-.")
        plt.plot(x, feature_price_scale["feature_z"], label="feature set z", linestyle=":")

        plt.legend(loc="upper left")
        plt.savefig("data/scale-{}".format(local_price_sheet["scale_amount"]), dpi=300)

        plt.close()


if __name__ == '__main__':
    main()