- {
- “cells”: [
- {
“cell_type”: “markdown”, “id”: “221ed2d7”, “metadata”: {
- “papermill”: {
“duration”: 0.010266, “end_time”: “2021-08-17T08:16:07.931063”, “exception”: false, “start_time”: “2021-08-17T08:16:07.920797”, “status”: “completed”
}, “tags”: []
}, “source”: [
“# Log uniform prior”
]
}, {
“cell_type”: “code”, “execution_count”: 1, “id”: “fb5ebe09”, “metadata”: {
- “execution”: {
“iopub.execute_input”: “2021-08-17T08:16:07.962112Z”, “iopub.status.busy”: “2021-08-17T08:16:07.960661Z”, “iopub.status.idle”: “2021-08-17T08:16:10.934418Z”, “shell.execute_reply”: “2021-08-17T08:16:10.938754Z”
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“duration”: 2.998155, “end_time”: “2021-08-17T08:16:10.939241”, “exception”: false, “start_time”: “2021-08-17T08:16:07.941086”, “status”: “completed”
}, “tags”: []
}, “outputs”: [], “source”: [
“%%capturen”, “n”, “import numpy as npn”, “n”, “import matplotlib.pyplot as pltn”, “n”, “import warningsn”, “warnings.simplefilter("ignore")n”, “n”, “from astromodels.functions.function import _known_functionsn”, “n”, “n”, “from jupyterthemes import jtplotn”, “jtplot.style(context="talk", fscale=1, ticks=True, grid=False)n”, “%matplotlib inline”
]
}, {
“cell_type”: “code”, “execution_count”: 2, “id”: “16507674”, “metadata”: {
- “execution”: {
“iopub.execute_input”: “2021-08-17T08:16:10.970889Z”, “iopub.status.busy”: “2021-08-17T08:16:10.969532Z”, “iopub.status.idle”: “2021-08-17T08:16:10.980558Z”, “shell.execute_reply”: “2021-08-17T08:16:10.981521Z”
}, “nbsphinx”: “hidden”, “papermill”: {
“duration”: 0.033394, “end_time”: “2021-08-17T08:16:10.982108”, “exception”: false, “start_time”: “2021-08-17T08:16:10.948714”, “status”: “completed”
}, “tags”: [
“parameters”
]
}, “outputs”: [], “source”: [
“func_name = "TbAbs"n”, “n”, “x_scale="log"n”, “y_scale="log"n”, “n”, “linear_range = Falsen”, “n”, “wide_energy_range = False”
]
}, {
“cell_type”: “code”, “execution_count”: 3, “id”: “8ae7d1e4”, “metadata”: {
- “execution”: {
“iopub.execute_input”: “2021-08-17T08:16:11.009519Z”, “iopub.status.busy”: “2021-08-17T08:16:11.008503Z”, “iopub.status.idle”: “2021-08-17T08:16:11.018231Z”, “shell.execute_reply”: “2021-08-17T08:16:11.019085Z”
}, “papermill”: {
“duration”: 0.027229, “end_time”: “2021-08-17T08:16:11.019453”, “exception”: false, “start_time”: “2021-08-17T08:16:10.992224”, “status”: “completed”
}, “tags”: [
“injected-parameters”
]
}, “outputs”: [], “source”: [
“# Parametersn”, “func_name = "Log_uniform_prior"n”, “wide_energy_range = Truen”, “x_scale = "linear"n”, “y_scale = "linear"n”, “linear_range = Truen”
]
}, {
“cell_type”: “code”, “execution_count”: 4, “id”: “044b5536”, “metadata”: {
- “execution”: {
“iopub.execute_input”: “2021-08-17T08:16:11.048896Z”, “iopub.status.busy”: “2021-08-17T08:16:11.047760Z”, “iopub.status.idle”: “2021-08-17T08:16:11.055950Z”, “shell.execute_reply”: “2021-08-17T08:16:11.057514Z”
}, “lines_to_next_cell”: 0, “nbsphinx”: “hidden”, “papermill”: {
“duration”: 0.028788, “end_time”: “2021-08-17T08:16:11.057883”, “exception”: false, “start_time”: “2021-08-17T08:16:11.029095”, “status”: “completed”
}, “tags”: []
}, “outputs”: [], “source”: [
“func = _known_functions[func_name]()n”, “n”, “if wide_energy_range:n”, “n”, ” energy_grid = np.geomspace(1e2,1e4,500)n”, ” n”, “else:n”, ” n”, ” energy_grid = np.geomspace(2e-1,1e1,1000)n”, “n”, “if linear_range:n”, “n”, “tenergy_grid = np.linspace(-5,5,1000)n”, “n”, ” n”, “blue = "#4152E3"n”, “red = "#E3414B"n”, “green = "#41E39E"”
]
}, {
“cell_type”: “markdown”, “id”: “bec34b20”, “metadata”: {
“lines_to_next_cell”: 0, “papermill”: {
“duration”: 0.009893, “end_time”: “2021-08-17T08:16:11.078312”, “exception”: false, “start_time”: “2021-08-17T08:16:11.068419”, “status”: “completed”
}, “tags”: []
}, “source”: [
“## Description”
]
}, {
“cell_type”: “code”, “execution_count”: 5, “id”: “1d4fe9b2”, “metadata”: {
- “execution”: {
“iopub.execute_input”: “2021-08-17T08:16:11.110864Z”, “iopub.status.busy”: “2021-08-17T08:16:11.109659Z”, “iopub.status.idle”: “2021-08-17T08:16:11.116385Z”, “shell.execute_reply”: “2021-08-17T08:16:11.119229Z”
}, “papermill”: {
“duration”: 0.031571, “end_time”: “2021-08-17T08:16:11.119605”, “exception”: false, “start_time”: “2021-08-17T08:16:11.088034”, “status”: “completed”
}, “tags”: []
}, “outputs”: [
- {
- “data”: {
- “text/html”: [
“<ul>n”, “n”, “<li>description: A function which is K/x on the interval lower_bound - upper_bound and 0 outside the interval. The extremes of the interval are NOT counted as part of the interval. Lower_bound must be >= 0.</li>n”, “n”, “<li>formula: $ f(x)=K~\begin{cases}0 & x \le \text{lower_bound} \\\frac{1}{x} & \text{lower_bound} < x < \text{upper_bound} \\ 0 & x \ge \text{upper_bound} \end{cases}$</li>n”, “n”, “<li>parameters: n”, “<ul>n”, “n”, “<li>lower_bound: n”, “<ul>n”, “n”, “<li>value: 1e-20</li>n”, “n”, “<li>desc: Lower bound for the interval</li>n”, “n”, “<li>min_value: 1e-30</li>n”, “n”, “<li>max_value: inf</li>n”, “n”, “<li>unit: </li>n”, “n”, “<li>is_normalization: False</li>n”, “n”, “<li>delta: 1e-21</li>n”, “n”, “<li>free: True</li>n”, “n”, “</ul>n”, “n”, “</li>n”, “n”, “<li>upper_bound: n”, “<ul>n”, “n”, “<li>value: 100.0</li>n”, “n”, “<li>desc: Upper bound for the interval</li>n”, “n”, “<li>min_value: 1e-30</li>n”, “n”, “<li>max_value: inf</li>n”, “n”, “<li>unit: </li>n”, “n”, “<li>is_normalization: False</li>n”, “n”, “<li>delta: 10.0</li>n”, “n”, “<li>free: True</li>n”, “n”, “</ul>n”, “n”, “</li>n”, “n”, “<li>K: n”, “<ul>n”, “n”, “<li>value: 1.0</li>n”, “n”, “<li>desc: Normalization</li>n”, “n”, “<li>min_value: None</li>n”, “n”, “<li>max_value: None</li>n”, “n”, “<li>unit: </li>n”, “n”, “<li>is_normalization: False</li>n”, “n”, “<li>delta: 0.1</li>n”, “n”, “<li>free: False</li>n”, “n”, “</ul>n”, “n”, “</li>n”, “n”, “</ul>n”, “n”, “</li>n”, “n”, “</ul>n”
], “text/plain”: [
” * description: A function which is K/x on the interval lower_bound - upper_bound andn”, ” * 0 outside the interval. The extremes of the interval are NOT counted as part ofn”, ” * the interval. Lower_bound must be >= 0.n”, ” * formula: $ f(x)=K~\begin{cases}0 & x \le \text{lower_bound} \\\frac{1}{x} & \text{lower_bound}n”, ” * < x < \text{upper_bound} \\ 0 & x \ge \text{upper_bound} \end{cases}$n”, ” * parameters:n”, ” * lower_bound:n”, ” * value: 1.0e-20n”, ” * desc: Lower bound for the intervaln”, ” * min_value: 1.0e-30n”, ” * max_value: .infn”, ” * unit: ‘’n”, ” * is_normalization: falsen”, ” * delta: 1.0e-21n”, ” * free: truen”, ” * upper_bound:n”, ” * value: 100.0n”, ” * desc: Upper bound for the intervaln”, ” * min_value: 1.0e-30n”, ” * max_value: .infn”, ” * unit: ‘’n”, ” * is_normalization: falsen”, ” * delta: 10.0n”, ” * free: truen”, ” * K:n”, ” * value: 1.0n”, ” * desc: Normalizationn”, ” * min_value: nulln”, ” * max_value: nulln”, ” * unit: ‘’n”, ” * is_normalization: falsen”, ” * delta: 0.1n”, ” * free: false”
]
}, “metadata”: {}, “output_type”: “display_data”
}
], “source”: [
“func.display()”
]
}, {
“cell_type”: “markdown”, “id”: “ad724d48”, “metadata”: {
- “papermill”: {
“duration”: 0.01104, “end_time”: “2021-08-17T08:16:11.141289”, “exception”: false, “start_time”: “2021-08-17T08:16:11.130249”, “status”: “completed”
}, “tags”: []
}, “source”: [
“## Shape n”, “n”, “The shape of the function. n”, “n”, “If this is not a photon model but a prior or linear function then ignore the units as these docs are auto-generated”
]
}, {
“cell_type”: “code”, “execution_count”: 6, “id”: “2e833c72”, “metadata”: {
- “execution”: {
“iopub.execute_input”: “2021-08-17T08:16:11.225170Z”, “iopub.status.busy”: “2021-08-17T08:16:11.223502Z”, “iopub.status.idle”: “2021-08-17T08:16:11.371746Z”, “shell.execute_reply”: “2021-08-17T08:16:11.372937Z”
}, “papermill”: {
“duration”: 0.220994, “end_time”: “2021-08-17T08:16:11.373344”, “exception”: false, “start_time”: “2021-08-17T08:16:11.152350”, “status”: “completed”
}, “tags”: [
“nbsphinx-thumbnail”
]
}, “outputs”: [
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”, “text/plain”: [
“<Figure size 432x288 with 1 Axes>”
]
}, “metadata”: {
“needs_background”: “light”
}, “output_type”: “display_data”
}
], “source”: [
“fig, ax = plt.subplots()n”, “n”, “n”, “ax.plot(energy_grid, func(energy_grid), color=blue)n”, “n”, “ax.set_xlabel("energy (keV)")n”, “ax.set_ylabel("photon flux")n”, “ax.set_xscale(x_scale)n”, “ax.set_yscale(y_scale)n”
]
}, {
“cell_type”: “markdown”, “id”: “6ba49336”, “metadata”: {
“lines_to_next_cell”: 0, “papermill”: {
“duration”: 0.011484, “end_time”: “2021-08-17T08:16:11.396643”, “exception”: false, “start_time”: “2021-08-17T08:16:11.385159”, “status”: “completed”
}, “tags”: []
}, “source”: [
“## F$_{\nu}$n”, “n”, “The F$_{\nu}$ shape of the photon modeln”, “if this is not a photon model, please ignore this auto-generated plot”
]
}, {
“cell_type”: “code”, “execution_count”: 7, “id”: “a0c46826”, “metadata”: {
- “execution”: {
“iopub.execute_input”: “2021-08-17T08:16:11.443536Z”, “iopub.status.busy”: “2021-08-17T08:16:11.428925Z”, “iopub.status.idle”: “2021-08-17T08:16:11.841146Z”, “shell.execute_reply”: “2021-08-17T08:16:11.841851Z”
}, “papermill”: {
“duration”: 0.434459, “end_time”: “2021-08-17T08:16:11.842199”, “exception”: false, “start_time”: “2021-08-17T08:16:11.407740”, “status”: “completed”
}, “tags”: []
}, “outputs”: [
- {
- “data”: {
“image/png”: “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”, “text/plain”: [
“<Figure size 432x288 with 1 Axes>”
]
}, “metadata”: {
“needs_background”: “light”
}, “output_type”: “display_data”
}
], “source”: [
“fig, ax = plt.subplots()n”, “n”, “ax.plot(energy_grid, energy_grid * func(energy_grid), red)n”, “n”, “n”, “ax.set_xlabel("energy (keV)")n”, “ax.set_ylabel(r"energy flux (F$_{\nu}$)")n”, “ax.set_xscale(x_scale)n”, “ax.set_yscale(y_scale)n”, “n”
]
}, {
“cell_type”: “markdown”, “id”: “5a115b53”, “metadata”: {
- “papermill”: {
“duration”: 0.01223, “end_time”: “2021-08-17T08:16:11.866667”, “exception”: false, “start_time”: “2021-08-17T08:16:11.854437”, “status”: “completed”
}, “tags”: []
}, “source”: [
“## $\nu$F$_{\nu}$n”, “n”, “The $\nu$F$_{\nu}$ shape of the photon modeln”, “if this is not a photon model, please ignore this auto-generated plot”
]
}, {
“cell_type”: “code”, “execution_count”: 8, “id”: “b26e0b2c”, “metadata”: {
- “execution”: {
“iopub.execute_input”: “2021-08-17T08:16:11.950402Z”, “iopub.status.busy”: “2021-08-17T08:16:11.924834Z”, “iopub.status.idle”: “2021-08-17T08:16:12.101741Z”, “shell.execute_reply”: “2021-08-17T08:16:12.102919Z”
}, “papermill”: {
“duration”: 0.224161, “end_time”: “2021-08-17T08:16:12.103279”, “exception”: false, “start_time”: “2021-08-17T08:16:11.879118”, “status”: “completed”
}, “tags”: []
}, “outputs”: [
- {
- “data”: {
“image/png”: 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n”, “text/plain”: [
“<Figure size 432x288 with 1 Axes>”
]
}, “metadata”: {
“needs_background”: “light”
}, “output_type”: “display_data”
}
], “source”: [
“fig, ax = plt.subplots()n”, “n”, “ax.plot(energy_grid, energy_grid**2 * func(energy_grid), color=green)n”, “n”, “n”, “ax.set_xlabel("energy (keV)")n”, “ax.set_ylabel(r"$\nu$F$_{\nu}$")n”, “ax.set_xscale(x_scale)n”, “ax.set_yscale(y_scale)n”
]
}
], “metadata”: {
- “jupytext”: {
“formats”: “ipynb,md”
}, “kernelspec”: {
“display_name”: “Python 3”, “language”: “python”, “name”: “python3”
}, “language_info”: {
- “codemirror_mode”: {
“name”: “ipython”, “version”: 3
}, “file_extension”: “.py”, “mimetype”: “text/x-python”, “name”: “python”, “nbconvert_exporter”: “python”, “pygments_lexer”: “ipython3”, “version”: “3.7.11”
}, “papermill”: {
“default_parameters”: {}, “duration”: 6.357108, “end_time”: “2021-08-17T08:16:13.307941”, “environment_variables”: {}, “exception”: null, “input_path”: “Log_uniform_prior.ipynb”, “output_path”: “../docs/notebooks/Log_uniform_prior.ipynb”, “parameters”: {
“func_name”: “Log_uniform_prior”, “linear_range”: true, “wide_energy_range”: true, “x_scale”: “linear”, “y_scale”: “linear”
}, “start_time”: “2021-08-17T08:16:06.950833”, “version”: “2.3.3”
}
}, “nbformat”: 4, “nbformat_minor”: 5
}