{
“cells”: [
{

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“duration”: 0.011503, “end_time”: “2021-08-17T08:13:05.658262”, “exception”: false, “start_time”: “2021-08-17T08:13:05.646759”, “status”: “completed”

}, “tags”: []

}, “source”: [

“# Powerlaw Eflux”

]

}, {

“cell_type”: “code”, “execution_count”: 1, “id”: “0a7656bc”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2021-08-17T08:13:05.688916Z”, “iopub.status.busy”: “2021-08-17T08:13:05.687873Z”, “iopub.status.idle”: “2021-08-17T08:13:08.614891Z”, “shell.execute_reply”: “2021-08-17T08:13:08.615967Z”

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}, “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”: “45ebcf02”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2021-08-17T08:13:08.644802Z”, “iopub.status.busy”: “2021-08-17T08:13:08.643748Z”, “iopub.status.idle”: “2021-08-17T08:13:08.653516Z”, “shell.execute_reply”: “2021-08-17T08:13:08.654348Z”

}, “nbsphinx”: “hidden”, “papermill”: {

“duration”: 0.02863, “end_time”: “2021-08-17T08:13:08.654744”, “exception”: false, “start_time”: “2021-08-17T08:13:08.626114”, “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”: “e1289a71”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2021-08-17T08:13:08.681840Z”, “iopub.status.busy”: “2021-08-17T08:13:08.680727Z”, “iopub.status.idle”: “2021-08-17T08:13:08.688331Z”, “shell.execute_reply”: “2021-08-17T08:13:08.689040Z”

}, “papermill”: {

“duration”: 0.024316, “end_time”: “2021-08-17T08:13:08.689446”, “exception”: false, “start_time”: “2021-08-17T08:13:08.665130”, “status”: “completed”

}, “tags”: [

“injected-parameters”

]

}, “outputs”: [], “source”: [

“# Parametersn”, “func_name = "Powerlaw_Eflux"n”, “wide_energy_range = Truen”, “x_scale = "log"n”, “y_scale = "log"n”, “linear_range = Falsen”

]

}, {

“cell_type”: “code”, “execution_count”: 4, “id”: “bbfc3b33”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2021-08-17T08:13:08.721003Z”, “iopub.status.busy”: “2021-08-17T08:13:08.719818Z”, “iopub.status.idle”: “2021-08-17T08:13:08.726984Z”, “shell.execute_reply”: “2021-08-17T08:13:08.727777Z”

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“duration”: 0.026976, “end_time”: “2021-08-17T08:13:08.728102”, “exception”: false, “start_time”: “2021-08-17T08:13:08.701126”, “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”: “c28a11ac”, “metadata”: {

“lines_to_next_cell”: 0, “papermill”: {

“duration”: 0.0103, “end_time”: “2021-08-17T08:13:08.748108”, “exception”: false, “start_time”: “2021-08-17T08:13:08.737808”, “status”: “completed”

}, “tags”: []

}, “source”: [

“## Description”

]

}, {

“cell_type”: “code”, “execution_count”: 5, “id”: “f36d95fe”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2021-08-17T08:13:08.781912Z”, “iopub.status.busy”: “2021-08-17T08:13:08.780823Z”, “iopub.status.idle”: “2021-08-17T08:13:08.790669Z”, “shell.execute_reply”: “2021-08-17T08:13:08.791869Z”

}, “papermill”: {

“duration”: 0.034072, “end_time”: “2021-08-17T08:13:08.792292”, “exception”: false, “start_time”: “2021-08-17T08:13:08.758220”, “status”: “completed”

}, “tags”: []

}, “outputs”: [

{
“data”: {
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” * description: A power-law where the normalization is the energy flux defined betweenn”, ” * a and bn”, ” * formula: $ F~\frac{x}{piv}^{index} $n”, ” * parameters:n”, ” * F:n”, ” * value: 1.0e-05n”, ” * desc: Normalization (energy flux at the between a and b) erg /cm2 sn”, ” * min_value: 1.0e-30n”, ” * max_value: 1000.0n”, ” * unit: ‘’n”, ” * is_normalization: truen”, ” * delta: 0.1n”, ” * free: truen”, ” * piv:n”, ” * value: 1.0n”, ” * desc: Pivot valuen”, ” * min_value: nulln”, ” * max_value: nulln”, ” * unit: ‘’n”, ” * is_normalization: falsen”, ” * delta: 0.1n”, ” * free: falsen”, ” * index:n”, ” * value: -2.0n”, ” * desc: Photon indexn”, ” * min_value: -10.0n”, ” * max_value: 10.0n”, ” * unit: ‘’n”, ” * is_normalization: falsen”, ” * delta: 0.2n”, ” * free: truen”, ” * a:n”, ” * value: 1.0n”, ” * desc: lower energy integral bound (keV)n”, ” * min_value: 0.0n”, ” * max_value: nulln”, ” * unit: ‘’n”, ” * is_normalization: falsen”, ” * delta: 0.1n”, ” * free: falsen”, ” * b:n”, ” * value: 100.0n”, ” * desc: upper energy integral bound (keV)n”, ” * min_value: 0.0n”, ” * max_value: nulln”, ” * unit: ‘’n”, ” * is_normalization: falsen”, ” * delta: 10.0n”, ” * free: false”

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}, “metadata”: {}, “output_type”: “display_data”

}

], “source”: [

“func.display()”

]

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}, “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”: “4132c288”, “metadata”: {

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“nbsphinx-thumbnail”

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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”, “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”: “84010cfe”, “metadata”: {

“lines_to_next_cell”: 0, “papermill”: {

“duration”: 0.017663, “end_time”: “2021-08-17T08:13:10.435455”, “exception”: false, “start_time”: “2021-08-17T08:13:10.417792”, “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”: “6e8fbfa9”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2021-08-17T08:13:10.502624Z”, “iopub.status.busy”: “2021-08-17T08:13:10.497586Z”, “iopub.status.idle”: “2021-08-17T08:13:11.279239Z”, “shell.execute_reply”: “2021-08-17T08:13:11.284407Z”

}, “papermill”: {

“duration”: 0.833973, “end_time”: “2021-08-17T08:13:11.286126”, “exception”: false, “start_time”: “2021-08-17T08:13:10.452153”, “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 * 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”: “a8529382”, “metadata”: {

“papermill”: {

“duration”: 0.012427, “end_time”: “2021-08-17T08:13:11.313300”, “exception”: false, “start_time”: “2021-08-17T08:13:11.300873”, “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”: “fb061deb”, “metadata”: {

“execution”: {

“iopub.execute_input”: “2021-08-17T08:13:11.470712Z”, “iopub.status.busy”: “2021-08-17T08:13:11.465457Z”, “iopub.status.idle”: “2021-08-17T08:13:12.106774Z”, “shell.execute_reply”: “2021-08-17T08:13:12.107651Z”

}, “papermill”: {

“duration”: 0.756957, “end_time”: “2021-08-17T08:13:12.108017”, “exception”: false, “start_time”: “2021-08-17T08:13:11.351060”, “status”: “completed”

}, “tags”: []

}, “outputs”: [

{
“data”: {

“image/png”: 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UmUPA3sCvZeaO3azz5el12vWO4KmhmLad5s3qac+avpGZDwH/Afx2+3X9LOsPA0Pt17StNIfEvgS8o2NMn+oYzyqaQ2L3tdv6PvAZmnicwE9f5XCK5mJDUtecgWiluwa4OSI+QfOx1otoZhLHz7HOl4ADIuK1wOdofiBfCvziLM/9PPDGiLiG5t/bW2g+jjvtWuBC4OuZ+b+zrP9dmjff96OZJQBsz8wnIuKtwD0RcQVNHC6OiKOBe4FzgNdl5q93vNbG9vvbn+YDAZ32o/nAgNQ1ZyBa0TLzv2g+IXUd8C3aQ1q7WWcHzZvhf0bzA/5NwAmZ+aNZnv53wD/TvMdwS3t7suPxa2lmL/+4i21NAl8GnjfLY18D/h64vJ3N/D7Np7AeBl4BnDxjlRtpDmlNvz/T6TCaMEpd83ogUg9FxIHw5OEqIuIs4JjMPLldHqZ5P2NdZj64i9d4K7BvZr6th+O8g+bjy1/p1TY0eJyBSL31CuCmiDgwIp5L85HezwFExM8Cp9B8+mrWeLQ+DLyyjc2ii4jDgEeNh+bLgEi9dTXNG+X3Af9Gcwjro+1j7wMupvnI7S61H8v9ED99SGqxnEdzGE+aFw9hSZJKnIFIkkoMiCSpxIBIkkoMiCSpxIBIkkoMiCSp5P8BVqbJHhcpe4oAAAAASUVORK5CYII=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”: 7.966831, “end_time”: “2021-08-17T08:13:12.722523”, “environment_variables”: {}, “exception”: null, “input_path”: “Powerlaw_Eflux.ipynb”, “output_path”: “../docs/notebooks/Powerlaw_Eflux.ipynb”, “parameters”: {

“func_name”: “Powerlaw_Eflux”, “linear_range”: false, “wide_energy_range”: true, “x_scale”: “log”, “y_scale”: “log”

}, “start_time”: “2021-08-17T08:13:04.755692”, “version”: “2.3.3”

}

}, “nbformat”: 4, “nbformat_minor”: 5

}