From a0b8ca98a99345fda1f0e69e0e970dd8937ca866 Mon Sep 17 00:00:00 2001 From: Brantegger Georg Date: Tue, 17 May 2022 10:43:16 +0200 Subject: [PATCH] created flow_pattern function with constant, linearly increasing and sawtooth flow patterns (incl outflux delay) --- functions/flow_patterns.ipynb | 3967 +++++++++++++++++++++++++++++++++ functions/flow_patterns.py | 67 + 2 files changed, 4034 insertions(+) create mode 100644 functions/flow_patterns.ipynb create mode 100644 functions/flow_patterns.py diff --git a/functions/flow_patterns.ipynb b/functions/flow_patterns.ipynb new file mode 100644 index 0000000..bc5be2a --- /dev/null +++ b/functions/flow_patterns.ipynb @@ -0,0 +1,3967 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import plotly.express as px\n", + "from plotly.subplots import make_subplots\n", + "import plotly.graph_objects as go\n", + "from flow_patterns import return_flux_profiles,make_flux_df" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "type": "scatter", + "x": [ + 0, + 1, + 2, + 3, + 4, + 5, + 6, + 7, + 8, + 9, + 10, + 11, + 12, + 13, + 14, + 15, + 16, + 17, + 18, + 19, + 20, + 21, + 22, + 23, + 24, + 25, + 26, + 27, + 28, + 29, + 30, + 31, + 32, + 33, + 34, + 35, + 36, + 37, + 38, + 39, + 40, + 41, + 42, + 43, + 44, + 45, + 46, + 47, + 48, + 49, + 50, + 51, + 52, + 53, + 54, + 55, + 56, + 57, + 58, + 59, + 60, + 61, + 62, + 63, + 64, + 65, + 66, + 67, + 68, + 69, + 70, + 71, + 72, + 73, + 74, + 75, + 76, + 77, + 78, + 79, + 80, + 81, + 82, + 83, + 84, + 85, + 86, + 87, + 88, + 89, + 90, + 91, + 92, + 93, + 94, + 95, + 96, + 97, + 98, + 99 + ], + "xaxis": "x", + "y": [ + 10, + 10, + 10, + 10, + 10, + 10, + 10, + 10, + 10, + 10, + 10, + 10, + 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10\n", + "#outflux delay\n", + "o_d = 10\n", + "\n", + "influx_profile,outflux_profile = return_flux_profiles(n,i_i_1,o_i_1,i_o,o_o,o_d)\n", + "flux_df = make_flux_df(influx_profile,outflux_profile)\n", + "\n", + "fig = make_subplots(2,1)\n", + "\n", + "fig.add_trace(go.Scatter(x=flux_df['time'],y=flux_df['influx']),row=1,col=1)\n", + "fig.add_trace(go.Scatter(x=flux_df['time'],y=flux_df['outflux']),row=2,col=1)\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "type": "scatter", + "x": [ + 0, + 1, + 2, + 3, + 4, + 5, + 6, + 7, + 8, + 9, + 10, + 11, + 12, + 13, + 14, + 15, + 16, + 17, + 18, + 19, + 20, + 21, + 22, + 23, + 24, + 25, + 26, + 27, + 28, + 29, + 30, + 31, + 32, + 33, + 34, + 35, + 36, + 37, + 38, + 39, + 40, + 41, + 42, + 43, + 44, + 45, + 46, + 47, + 48, + 49, + 50, + 51, + 52, + 53, 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identifiers\n", + "o_i_3 = 'st_0010_0010'\n", + "# influx and outflux offset\n", + "i_o = 10\n", + "o_o = 10\n", + "#outflux delay\n", + "o_d = 10\n", + "\n", + "influx_profile,outflux_profile = return_flux_profiles(n,i_i_3,o_i_3,i_o,o_o,o_d)\n", + "flux_df = make_flux_df(influx_profile,outflux_profile)\n", + "\n", + "fig = make_subplots(2,1)\n", + "\n", + "fig.add_trace(go.Scatter(x=flux_df['time'],y=flux_df['influx']),row=1,col=1)\n", + "fig.add_trace(go.Scatter(x=flux_df['time'],y=flux_df['outflux']),row=2,col=1)\n", + "fig.show()" + ] + } + ], + "metadata": { + "interpreter": { + "hash": "84fb123bdc47ab647d3782661abcbe80fbb79236dd2f8adf4cef30e8755eb2cd" + }, + "kernelspec": { + "display_name": "Python 3.8.13 ('Georg_DT_Slot3')", + "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": "3.8.13" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/functions/flow_patterns.py b/functions/flow_patterns.py new file mode 100644 index 0000000..e628047 --- /dev/null +++ b/functions/flow_patterns.py @@ -0,0 +1,67 @@ +import numpy as np +import pandas as pd +import plotly.express as px +from plotly.subplots import make_subplots +import plotly.graph_objects as go + + +def return_flux_profiles(number_of_steps = 1,influx_identifier = 0, outflux_identifier = 0,influx_offset=0,outflux_offset=0, outflux_delay = 0): + ''' Identifier patterns: + 0 ... constant + 'lin_SSSS' ... linear increase with slope int(SSSS) + 'st_SSSS_PPPP' ... sawtooth pattern with slope int(SSSS) and period int(PPPP) steps + ''' + + # case identifiers for if statment + i = influx_identifier + o = outflux_identifier + + n = number_of_steps + #starting value for the influx and outflux + i_o = influx_offset + o_o = outflux_offset + # number of steps, the outflux is held at 0 at the beginning + o_d = outflux_delay + + +# get base profile for the influx (offset will get applied later) + if i == 0: + influx_profile = np.zeros(n) + elif 'lin' in influx_identifier: + k = int(influx_identifier[-4:]) + influx_profile = np.linspace(0,k*(n-1),n) + elif 'st' in influx_identifier: + k = int(influx_identifier[3:7]) + p = int(influx_identifier[-4:]) + influx_profile = np.tile(np.linspace(0,k*(p-1),p),int(np.ceil(n/p))) + + +# apply influx offset + influx_profile = influx_offset + influx_profile + + if o == 0: + outflux_profile = np.zeros(n) + elif 'lin' in outflux_identifier: + k = int(outflux_identifier[-4:]) + outflux_profile = np.linspace(0,k*(n-1),n) + elif 'st' in outflux_identifier: + k = int(outflux_identifier[3:7]) + p = int(outflux_identifier[-4:]) + outflux_profile = np.tile(np.linspace(0,k*(p-1),p),int(np.ceil(n/p))) + +#apply outflux offset and delay (delay means, that the first o_d steps, the outflux will be 0) + outflux_profile = np.concatenate((np.zeros(o_d),outflux_profile[:-o_d]+o_o)) + + return influx_profile,outflux_profile + +def make_flux_df(influx_profile,outflux_profile, time = 0): + if time == 0: + time = np.arange(0,len(influx_profile)) + flux_df = pd.DataFrame(np.transpose([time, influx_profile, outflux_profile]), \ + columns=['time', 'influx', 'outflux']) + return flux_df + + +if __name__ == "__main__": + influx_profile,outflux_profile = return_flux_profiles(100,influx_identifier='st_0010_0010',influx_offset=10) + print(influx_profile) \ No newline at end of file