868 lines
734 KiB
Plaintext
868 lines
734 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 312,
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"metadata": {},
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"outputs": [],
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"source": [
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"import wntr\n",
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"import math\n",
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"import matplotlib.pyplot as plt"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 124,
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"metadata": {},
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"outputs": [],
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"source": [
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"def to_cbs(lbs):\n",
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" \"\"\" convert l/s in m³/s\"\"\"\n",
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" \n",
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" return lbs/1000.\n",
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" "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Einheiten\n",
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"\n",
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"Demand = m3/s"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Beispiel 1"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 320,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 1440x576 with 5 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
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"source": [
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"# neues Modell erstellen\n",
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"wn = wntr.network.WaterNetworkModel()\n",
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"\n",
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"tage = 4\n",
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"\n",
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"wn.add_pattern('pat', [1])\n",
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"\n",
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"Qdm = 80 #m³/d\n",
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"Qsm = Qdm/3600.\n",
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"\n",
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"# Knoten generieren\n",
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"wn.add_junction('3', base_demand=to_cbs(Qsm), demand_pattern='pat', elevation=0, coordinates=(0,0))\n",
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"wn.add_junction('4', base_demand=to_cbs(Qsm), demand_pattern='pat', elevation=0, coordinates=(1,0))\n",
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"wn.add_junction('5', base_demand=to_cbs(Qsm), demand_pattern='pat', elevation=0, coordinates=(1,1))\n",
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"wn.add_junction('6', base_demand=to_cbs(Qsm), demand_pattern='pat', elevation=0, coordinates=(2,0))\n",
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"wn.add_junction('7', base_demand=to_cbs(Qsm), demand_pattern='pat', elevation=0, coordinates=(2,-1))\n",
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"\n",
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"# Reservoir\n",
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"wn.add_reservoir('res', base_head=20, head_pattern='pat', coordinates=(-4,2))\n",
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"\n",
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"# Rohrnetzwerk\n",
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"r = 0.1\n",
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"wn.add_pipe('B', '3', '4', length=200, diameter=1.0, roughness=r, minor_loss=0.0, status='OPEN')\n",
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"wn.add_pipe('C', '4', '5', length=100, diameter=0.4, roughness=r, minor_loss=0.0, status='OPEN')\n",
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"wn.add_pipe('D', '4', '6', length=200, diameter=0.8, roughness=r, minor_loss=0.0, status='OPEN')\n",
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"wn.add_pipe('E', '6', '7', length=200, diameter=.8, roughness=r, minor_loss=0.0, status='OPEN')\n",
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"\n",
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"\n",
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"# Hochbehälter\n",
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"wn.add_tank('HB', elevation=60.0, init_level=10, min_level=0.0, max_level=10, diameter=50, overflow=False, coordinates=(-3,2))\n",
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"wn.add_pipe('A', 'HB', '3', length=3000, diameter=1.4, roughness=0.1, minor_loss=0.0, status='OPEN')\n",
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"\n",
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"# Pumpe\n",
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"#wn.add_curve('curve1', 'HEAD', [(400,300)])\n",
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"#wn.add_pump('P', 'res', '8', pump_type='HEAD', pump_parameter='curve1', pattern=None)\n",
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"\n",
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"\n",
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"# Simulate hydraulics\n",
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"wn.options.time.duration = tage*24*3600\n",
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"sim = wntr.sim.EpanetSimulator(wn)\n",
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"results = sim.run_sim()\n",
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"\n",
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"fig,axs = plt.subplots(2,2, figsize=(20,8))\n",
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"\n",
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"# Netzplan\n",
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"nodes, edges = wntr.graphics.plot_network(wn, node_attribute='elevation', node_colorbar_label='Elevation (m)', node_labels=True, ax=axs[0,0])\n",
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"results.node['demand'].drop(columns=['res', 'HB']).mul(1000).plot(ax=axs[0,1])\n",
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"\n",
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"\n",
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"p = results.node['pressure'].div(10)\n",
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"p.drop(columns=['res', 'HB']).plot(ax=axs[1,0])\n",
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"\n",
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"results.link['velocity'].plot(ax=axs[1,1])\n",
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"\n",
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"axs[0,1].set_ylabel('Verbrauch in l/s')\n",
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"axs[1,0].set_ylabel('Versorgungsdruck in bar')\n",
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"axs[1,1].set_ylabel('Fließgeschwindigkeit in m/s')\n",
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"\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 316,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"2.2222222222222223e-05"
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]
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},
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"execution_count": 316,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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|
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"# Beispiel 2"
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]
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},
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{
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"cell_type": "code",
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|
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"execution_count": 311,
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"metadata": {},
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"outputs": [
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{
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"data": {
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|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1440x576 with 4 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# neues Modell erstellen\n",
|
||
|
|
"wn = wntr.network.WaterNetworkModel()\n",
|
||
|
|
"\n",
|
||
|
|
"tage = 4\n",
|
||
|
|
"\n",
|
||
|
|
"x = list(range(0,tage*24*60*60, 3600))\n",
|
||
|
|
"v = 2\n",
|
||
|
|
"w = 3\n",
|
||
|
|
"y = [v*math.sin(2*math.pi/(24*3600)*(i-6*3600)) + w for i in x]\n",
|
||
|
|
"\n",
|
||
|
|
"wn.add_pattern('pat2', y)\n",
|
||
|
|
"fire = y.copy()\n",
|
||
|
|
"for i in range(30,40):\n",
|
||
|
|
" fire[i] += 2\n",
|
||
|
|
"wn.add_pattern('fire', fire)\n",
|
||
|
|
"\n",
|
||
|
|
"# Knoten generieren\n",
|
||
|
|
"wn.add_junction('3', base_demand=to_cbs(1), demand_pattern='pat2', elevation=0, coordinates=(0,0))\n",
|
||
|
|
"wn.add_junction('4', base_demand=to_cbs(1), demand_pattern='pat2', elevation=0, coordinates=(1,0))\n",
|
||
|
|
"wn.add_junction('5', base_demand=to_cbs(1), demand_pattern='pat2', elevation=0, coordinates=(1,1))\n",
|
||
|
|
"wn.add_junction('6', base_demand=to_cbs(1), demand_pattern='pat2', elevation=0, coordinates=(2,0))\n",
|
||
|
|
"wn.add_junction('7', base_demand=to_cbs(1), demand_pattern='fire', elevation=0, coordinates=(2,-1))\n",
|
||
|
|
"\n",
|
||
|
|
"#wn.add_junction('8', base_demand=0, elevation=50, coordinates=(-2,2))\n",
|
||
|
|
"\n",
|
||
|
|
"# Reservoir\n",
|
||
|
|
"wn.add_reservoir('res', base_head=20, head_pattern='pat1', coordinates=(-4,2))\n",
|
||
|
|
"\n",
|
||
|
|
"# Rohrnetzwerk\n",
|
||
|
|
"r = 100\n",
|
||
|
|
"wn.add_pipe('B', '3', '4', length=200, diameter=1.0, roughness=r, minor_loss=0.0, status='OPEN')\n",
|
||
|
|
"wn.add_pipe('C', '4', '5', length=100, diameter=0.4, roughness=r, minor_loss=0.0, status='OPEN')\n",
|
||
|
|
"wn.add_pipe('D', '4', '6', length=200, diameter=0.8, roughness=r, minor_loss=0.0, status='OPEN')\n",
|
||
|
|
"wn.add_pipe('E', '6', '7', length=200, diameter=.8, roughness=r, minor_loss=0.0, status='OPEN')\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
"# Hochbehälter\n",
|
||
|
|
"wn.add_tank('HB', elevation=60.0, init_level=10, min_level=0.0, max_level=10, diameter=50, overflow=False, coordinates=(-3,2))\n",
|
||
|
|
"wn.add_pipe('A', 'HB', '3', length=3000, diameter=1.4, roughness=0.1, minor_loss=0.0, status='OPEN')\n",
|
||
|
|
"\n",
|
||
|
|
"# Pumpe\n",
|
||
|
|
"#wn.add_curve('curve1', 'HEAD', [(400,300)])\n",
|
||
|
|
"#wn.add_pump('P', 'res', '8', pump_type='HEAD', pump_parameter='curve1', pattern=None)\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
"# Simulate hydraulics\n",
|
||
|
|
"wn.options.time.duration = tage*24*3600\n",
|
||
|
|
"sim = wntr.sim.EpanetSimulator(wn)\n",
|
||
|
|
"results = sim.run_sim()\n",
|
||
|
|
"\n",
|
||
|
|
"fig,axs = plt.subplots(2,2, figsize=(20,8))\n",
|
||
|
|
"\n",
|
||
|
|
"results.node['demand'].drop(columns=['res', 'HB']).mul(1000).plot(ax=axs[0,0])\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
"p = results.node['pressure'].div(10)\n",
|
||
|
|
"p.drop(columns=['res', 'HB']).plot(ax=axs[1,0])\n",
|
||
|
|
"\n",
|
||
|
|
"results.link['velocity'].plot(ax=axs[1,1])\n",
|
||
|
|
"\n",
|
||
|
|
"axs[0,0].set_ylabel('Verbrauch in l/s')\n",
|
||
|
|
"axs[1,0].set_ylabel('Versorgungsdruck in bar')\n",
|
||
|
|
"axs[1,1].set_ylabel('Fließgeschwindigkeit in m/s')\n",
|
||
|
|
"\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Beispiel 3"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 405,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1440x576 with 5 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# neues Modell erstellen\n",
|
||
|
|
"wn = wntr.network.WaterNetworkModel()\n",
|
||
|
|
"\n",
|
||
|
|
"tage = 4\n",
|
||
|
|
"\n",
|
||
|
|
"x = list(range(0,tage*24*60*60, 3600))\n",
|
||
|
|
"v = 4\n",
|
||
|
|
"w = 3\n",
|
||
|
|
"y = [v*math.sin(2*math.pi/(24*3600)*(i-6*3600)) + w for i in x]\n",
|
||
|
|
"\n",
|
||
|
|
"wn.add_pattern('pat', y)\n",
|
||
|
|
"\n",
|
||
|
|
"Qdm = 80 #m³/d\n",
|
||
|
|
"Qsm = Qdm/3600.\n",
|
||
|
|
"\n",
|
||
|
|
"# Knoten generieren\n",
|
||
|
|
"x=10\n",
|
||
|
|
"y=4\n",
|
||
|
|
"for i in range(1,x):\n",
|
||
|
|
" for j in range(1,y):\n",
|
||
|
|
" wn.add_junction('{}-{}'.format(i,j), base_demand=to_cbs(Qsm), demand_pattern='pat', elevation=0, coordinates=(float(i),float(j)))\n",
|
||
|
|
"#horizontal pipes\n",
|
||
|
|
"for i in range(1,x-1):\n",
|
||
|
|
" for j in range(1,y): \n",
|
||
|
|
" wn.add_pipe('h-{}-{}'.format(i,j), '{}-{}'.format(i,j), '{}-{}'.format(i+1,j), length=200, diameter=0.4, roughness=0.4, minor_loss=0.0, status='OPEN')\n",
|
||
|
|
"#vertical pipes\n",
|
||
|
|
"for i in range(1,x):\n",
|
||
|
|
" for j in range(1,y-1): \n",
|
||
|
|
" wn.add_pipe('v-{}-{}'.format(i,j), '{}-{}'.format(i,j), '{}-{}'.format(i,j+1), length=200, diameter=0.4, roughness=0.4, minor_loss=0.0, status='OPEN')\n",
|
||
|
|
"\n",
|
||
|
|
"# Reservoir\n",
|
||
|
|
"wn.add_reservoir('res', base_head=20, head_pattern='pat', coordinates=(-2,0))\n",
|
||
|
|
"\n",
|
||
|
|
"# Pumpe\n",
|
||
|
|
"wn.add_curve('curve1', 'HEAD', [(200,100)])\n",
|
||
|
|
"wn.add_pump('P', 'res', '1-1', pump_type='HEAD', pump_parameter='curve1', pattern=None)\n",
|
||
|
|
"\n",
|
||
|
|
"# Hochbehälter\n",
|
||
|
|
"wn.add_tank('HB', elevation=10.0, init_level=10, min_level=0.0, max_level=10, diameter=10, overflow=True, coordinates=(x,y))\n",
|
||
|
|
"wn.add_pipe('pipe_HB', 'HB', '{}-{}'.format(x-1,y-1), length=200, diameter=0.4, roughness=0.1, minor_loss=0.0, status='OPEN')\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
"# Simulate hydraulics\n",
|
||
|
|
"wn.options.time.duration = tage*24*3600\n",
|
||
|
|
"sim = wntr.sim.EpanetSimulator(wn)\n",
|
||
|
|
"results = sim.run_sim()\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
"fig,axs = plt.subplots(2,2, figsize=(20,8))\n",
|
||
|
|
"\n",
|
||
|
|
"# Netzplan\n",
|
||
|
|
"nodes, edges = wntr.graphics.plot_network(wn, node_attribute='elevation', node_colorbar_label='Elevation (m)', node_labels=True, ax=axs[0,0])\n",
|
||
|
|
"results.node['demand'].drop(columns=['res', 'HB']).mul(1000).plot(ax=axs[0,1], legend=False)\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
"p = results.node['pressure'].div(10)\n",
|
||
|
|
"p.drop(columns=['res', 'HB']).plot(ax=axs[1,0], legend=False)\n",
|
||
|
|
"\n",
|
||
|
|
"results.link['velocity'].plot(ax=axs[1,1], legend=False)\n",
|
||
|
|
"\n",
|
||
|
|
"axs[0,1].set_ylabel('Verbrauch in l/s')\n",
|
||
|
|
"axs[1,0].set_ylabel('Versorgungsdruck in bar')\n",
|
||
|
|
"axs[1,1].set_ylabel('Fließgeschwindigkeit in m/s')\n",
|
||
|
|
"\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 406,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 406,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 576x396 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"results.link['flowrate']['pipe_HB'].plot()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 407,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 407,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 576x396 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"results.node['pressure']['HB'].plot()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 403,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"flowrate\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1440x720 with 3 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"pressure = results.node['pressure'].div(10).iloc[0]\n",
|
||
|
|
"\n",
|
||
|
|
"for par in ['flowrate', 'velocity']:\n",
|
||
|
|
" print(par)\n",
|
||
|
|
" p = results.link[par].iloc[0]\n",
|
||
|
|
" \n",
|
||
|
|
" fig,ax = plt.subplots(figsize=(20,10))\n",
|
||
|
|
" wntr.graphics.plot_network(wn, link_attribute=p, node_attribute=pressure, link_width=3, node_size=60,link_labels=False,node_labels=False, ax=ax, \n",
|
||
|
|
" link_cmap=plt.get_cmap('Reds'))#\n",
|
||
|
|
" plt.show()\n",
|
||
|
|
" \n",
|
||
|
|
" break"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Plots"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Eingabewerte"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 352,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 576x396 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Netzplan\n",
|
||
|
|
"nodes, edges = wntr.graphics.plot_network(wn, node_attribute='elevation', node_colorbar_label='Elevation (m)', node_labels=True)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 172,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:title={'center':'Pump curve'}, xlabel='Flow (m$^3$/s)', ylabel='Head (m)'>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 172,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 576x288 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Pumpenkennlinie\n",
|
||
|
|
"pump = wn.get_link('P')\n",
|
||
|
|
"wntr.graphics.plot_pump_curve(pump)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Ergebnisse"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 182,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 182,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 576x396 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"results.node['pressure']['7'].plot()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 185,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 185,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 576x396 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"results.node['head']['7'].plot()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 192,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<AxesSubplot:>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 192,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 576x396 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"results.link['flowrate']['E'].plot()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 178,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"name\n",
|
||
|
|
"3 1.286086e+01\n",
|
||
|
|
"4 1.148826e+01\n",
|
||
|
|
"5 1.098139e+01\n",
|
||
|
|
"6 8.737446e+00\n",
|
||
|
|
"7 5.986635e+00\n",
|
||
|
|
"8 3.700020e+01\n",
|
||
|
|
"res 1.526679e-08\n",
|
||
|
|
"Name: 43200, dtype: float32"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 178,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"results.node['pressure'].div(10).loc[12*3600]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 179,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"(<matplotlib.collections.PathCollection at 0x7f473410c370>,\n",
|
||
|
|
" <matplotlib.collections.LineCollection at 0x7f473410ce20>)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 179,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAFJCAYAAADOqrnnAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAAjXklEQVR4nO3de1hVZcL38d9ig4iKIBqIp/RRCkd9PFT6enwtJJ0u08bMEyiesxkbS5s8lTI2qdNjZaVWHlIUrbQ8lE29WWlnNcdTZjlqaSpoJB5QBDms94+KZxy3Aro399qb72eu+7pk773W/oGNP+57rb2WZdu2LQAAHCbAdAAAANyhoAAAjkRBAQAciYICADgSBQUAcCQKCgDgSBQUfF5ycrISExNNx3CrSZMm2rRpkyRn5wSciIKCV9SvX18hISEKDQ1VeHi42rVrp5deekmFhYWmo10Xy7J04MCBEr/+m2++UefOnb0XCPBjFBS85u2331ZWVpYOHz6sCRMm6O9//7uGDRvm9rUFBQVlnK508vPzTUcAyh0KCl4XFhamHj166PXXX1dKSor27NmjwYMH64EHHtBdd92lypUra+PGjercubMWLlxYtN2SJUvUoUOHoq+/+eYbxcfHKyIiQlFRUZo+ffpl75WXl6f+/fvr3nvv1Y8//qiQkBBlZmYWPb9jxw7VqFFDeXl5kqRXXnlFjRs3VrVq1dS1a1cdPny46LWWZWnu3LmKiYlRTEyMOnXqJElq3ry5qlSpotdff12StH79erVo0aJoprh79+6ifdSvX18ffPDBZTk3bdqkOnXqXPLYv782OTlZffr00aBBgxQaGqomTZpo27ZtRa/dvn27WrZsqdDQUN13333q27evHnvssRL8bQC+g4JCmWndurXq1KmjTz/9VJK0YsUKTZ48WVlZWZcUkTtZWVnq0qWLunXrprS0NB04cEBxcXGXvObChQu65557FBwcrJUrV6pevXpq27at3nzzzaLXrFixQr1791ZQUJDWrl2r6dOna/Xq1crIyFDHjh3Vv3//S/a5du1abdmyRXv37tUnn3wiSdq1a5fOnTunvn37avv27Ro6dKhefvllnTx5Uvfff7969Oih3Nzc6/55vfXWW+rXr59Onz6tHj16aPTo0ZKkixcv6g9/+IMGDx6szMxM9e/fX2vWrLnu9wOchoJCmapVq1bRjKZnz55q3769AgICVLFixatut379etWsWVPjxo1TxYoVFRoaqjZt2hQ9f/bsWXXr1k0NGzbU4sWL5XK5JEkDBgzQq6++KkmybVuvvfaaBgwYIEl6+eWXNXHiRDVu3FiBgYGaNGmSdu7cecksauLEiYqIiFBISIjbXAsWLND999+vNm3ayOVyKSkpScHBwdq8efO1/5B+1aFDB911111yuVwaOHCgdu3aJUnavHmz8vPz9ec//1lBQUHq1auXWrdufd3vBzgNBYUydezYMUVEREiS6tatW+Ltjhw5ooYNG17x+c2bN2v37t2aMGGCLMsqerx379768ssvlZaWpk8++USWZaljx46SpMOHD2vMmDEKDw9XeHi4IiIiZNu2jh07VrR9cRkPHz6sp59+umgf4eHhOnLkiNLS0kr8vV1JzZo1i/5cqVIl5eTkKD8/X2lpaapdu/Yl32dpfpaAr6CgUGa++uorHTt2rGg579//gZWkypUrKzs7u+jr48ePF/25bt26Onjw4BX3feedd2rixImKi4vTiRMnih4PDw/XnXfeqZUrV2rFihXq379/0fvWrVtXL7/8sk6fPl00Lly4oHbt2hVt/58Z/1PdunU1efLkS/aRnZ192VLhf/rP77WgoEAZGRlX3eY30dHROnbsmP79RgRHjhwp0baAL6Gg4HVnz57V+vXr1a9fPyUmJqpZs2ZuX9eiRQutXr1a2dnZOnDggBYtWlT0XPfu3XX8+HHNnj1bubm5ysrK0pYtWy7Z/tFHH9WAAQMUFxenn3/+uejxAQMGaOnSpXrzzTeLlvckadSoUZoxY4a++eYbSdKZM2e0atWqq34vUVFR+v7774u+HjFihF566SVt2bJFtm3r/Pnzeuedd5SVlXXV/dx0003KycnRO++8o7y8PP3tb38r8XGrtm3byuVyac6cOcrPz9e6deu0devWEm0L+BIKCl5z9913KzQ0VHXr1tWTTz6psWPHavHixVd8/cMPP6wKFSooKipKSUlJSkhIKHouNDRUGzZs0Ntvv62aNWsqJiZGGzduvGwfjz/+uO655x516dKl6FhXjx49tH//fkVFRal58+ZFr/3DH/6g8ePHq1+/fqpataqaNm2qd99996rfU3JyspKSkhQeHq6VK1fq1ltv1YIFCzR69GhVq1ZNjRo10pIlS4r92YSFhWnevHkaPny4ateurcqVK192Vt+VVKhQQatXr9aiRYsUHh6u1NRUde/eXcHBwSXaHvAVFjcsBHxfmzZtNGrUKA0ZMsR0FMBjmEEBPujjjz/W8ePHlZ+fr5SUFO3evVvdunUzHQvwqEDTAQCU3r59+9SnTx+dO3dODRs21BtvvKHo6GjTsQCPYokPAOBILPEBAByJggIAOBIFBQBwJAoKAOBIFBQAwJEoKACAI1FQAABHoqAAAI5EQQEAHImCAgA4EgUFAHAkCgoA4EheLaiME1navuWITmdmF/9iOFrW92k6vO5zZR/PNB0FQDnhtdttvL3qa7356i7ZhbZcgQEaPKqNOnVp5K23gxftnLZUO/66VLJtBQQFqv2CcWo06E7TsQD4Oa/MoE5mnNfqX8tJkgryC7V80TblXMjzxtvBi7IOHdfOacukX+/KUpiXry0PzVV+do7hZAD8nVdmUGlHz6iw8NLbTOVcyFPNqAY6k3XMG28JL2mm6nrYan7JYxdPn9P5oxkKu6muoVQAygOvFNR/xdRQhWCXLuYWFD0WXi1EJ0/9KJeL8zJ8Sc7JM1pZt58Kci4WPVapzg0KbVjLYCoA5YFX2qJylQoaOaa9QsOCJUkRNSrpgXEdKScfVLF6mDouGa/gGmGSpNOufJ1PaKEAl8twMgD+zqu3fM/PK9CpzGxVr1FZAZSTTyvIvajstJPaeWS/et5zjw4cOKCIiAjTsQD4Ma8WFPxTUlKSsrKytHr1atNRAPgxCgqllpWVpYYNG2rp0qXq1q2b6TgA/BTrbii10NBQzZ07V8OHD9eFCxdMxwHgp5hB4ZrFx8fr5ptv1pw5c0xHAeCHKChcs7S0NDVu3FgbN25Uq1atTMcB4GdY4sM1q1WrlpKTkzVw4EAVFBQUvwEAlAIFhesyZswYVahQQU899ZTpKAD8DEt8uG579uxR+/bt9fXXX6tevXqm4wDwExQUPGLcuHHatm2bNm3aJMuyTMcB4AdY4oNHTJ8+XYcPH1ZqaqrpKAD8BDMoeMzGjRt133336cCBAwoPDzcdB4CPo6DgUf3791dhYaFef/1101EA+DgKCh515swZNWrUSK+99pri4uJMxwHgwzgGBY8KCwvT7NmzNXToUOXm5pqOA8CHMYOCx9m2rTvuuEMtW7bUM888YzoOAB9FQcErjhw5oqZNm+rzzz9X06ZNTccB4INY4oNX1K1bV5MmTVJCQoIKCwtNxwHggygoeM0jjzyigoICPfvss6ajAPBBLPHBq3bt2qVOnTpp7969ql27tuk4AHwIBQWv+/Of/6xvv/1WGzZsMB0FgA9hiQ9e99RTT+m7777jw7sASoUZFMrE+++/r4SEBB08eFBVq1Y1HQeAD6CgUGZ69+6tkJAQLVu2zHQUAD6AgkKZyczMVExMjNasWaNOnTqZjgPA4TgGhTITERGhWbNmafDgwbp48aLpOAAcjhkUypRt2+rYsaPat2+vv//976bjAHAwCgpl7tChQ2revLm2bNmi2NhY03EAOBRLfChz9evX11/+8hclJCSI348AXAkFBSMmTpyo7OxszZkzx3QUAA7FEh+M2bZtm7p06aLvvvtONWvWNB0HgMNQUDBq1KhROnz4sN59913TUQA4DAUFo7Kzs9WoUSPNmTNHvXr1Mh0HgINQUDBu/fr1GjZsmA4ePKg
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 576x396 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# Plot results on the network\n",
|
||
|
|
"pressure = results.node['pressure'].div(10).loc[12*3600]\n",
|
||
|
|
"wntr.graphics.plot_network(wn, node_attribute=pressure, node_size=30, title='Druckverteilung', node_colorbar_label='in bar')#\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 132,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"plt.style.use('seaborn-notebook')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 133,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"flowrate\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1440x720 with 3 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"pressure = results.node['pressure'].div(10).iloc[0]\n",
|
||
|
|
"\n",
|
||
|
|
"for par in ['flowrate', 'velocity']:\n",
|
||
|
|
" print(par)\n",
|
||
|
|
" p = results.link[par].iloc[0]\n",
|
||
|
|
" \n",
|
||
|
|
" fig,ax = plt.subplots(figsize=(20,10))\n",
|
||
|
|
" wntr.graphics.plot_network(wn, link_attribute=p, node_attribute=pressure, node_size=30,link_labels=True,node_labels=False, ax=ax, \n",
|
||
|
|
" link_cmap=plt.get_cmap('Reds'))#\n",
|
||
|
|
" plt.show()\n",
|
||
|
|
" \n",
|
||
|
|
" break"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 134,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"flowrate\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
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"<Figure size 576x396 with 2 Axes>"
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},
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"metadata": {},
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"output_type": "display_data"
|
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},
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{
|
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|
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"name": "stdout",
|
||
|
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"output_type": "stream",
|
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|
|
"text": [
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||
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|
"velocity\n"
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]
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},
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"text/plain": [
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"<Figure size 576x396 with 2 Axes>"
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|
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"metadata": {},
|
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|
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|
||
|
|
}
|
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|
|
],
|
||
|
|
"source": [
|
||
|
|
"for par in ['flowrate', 'velocity']:\n",
|
||
|
|
" print(par)\n",
|
||
|
|
" p = results.link[par].iloc[0]\n",
|
||
|
|
" \n",
|
||
|
|
" wntr.graphics.plot_network(wn, link_attribute=p, node_size=30)#\n",
|
||
|
|
" plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
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"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
" nodes, edges = wntr.graphics.plot_network(wn, node_attribute='elevation',\n",
|
||
|
|
"... node_colorbar_label='Elevation (m)')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 85,
|
||
|
|
"metadata": {},
|
||
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"outputs": [
|
||
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|
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|
|
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|
||
|
|
" <th>name</th>\n",
|
||
|
|
" <th>B</th>\n",
|
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|
|
" <th>C</th>\n",
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
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|
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|
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|
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|
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|
||
|
|
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|
||
|
|
" <td>-0.013</td>\n",
|
||
|
|
" <td>0.013</td>\n",
|
||
|
|
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|
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|
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|
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|
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|
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|
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||
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|
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|
||
|
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|
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|
||
|
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}
|
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|
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|
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"source": [
|
||
|
|
"results.link['flowrate']"
|
||
|
|
]
|
||
|
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},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"# Plot results on the network\n",
|
||
|
|
"pressure = results.node['pressure'].div(10).loc[0, :]\n",
|
||
|
|
"wntr.graphics.plot_network(wn, node_attribute=pressure, node_size=30, title='Druckverteilung', node_colorbar_label='in bar')#\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"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": "3.8.5"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 4
|
||
|
|
}
|