def process_pie():
df = process_input()
df[df.columns[1]] = pd.to_numeric(df[df.columns[1]])
df[df.columns[2]] = pd.to_numeric(df[df.columns[2]])
df[df.columns[3]] = pd.to_numeric(df[df.columns[3]])
col1 = df[df.columns[1]].values
col2 = df[df.columns[2]].values
col3 = df[df.columns[3]].values
Plotly.plot(document.getElementById('plot1'), [{
'values': [
df[df.columns[1]].sum(), df[df.columns[2]].sum(),
df[df.columns[3]].sum()
],
'labels': [
df[df.columns[1]].name, df[df.columns[2]].name,
df[df.columns[3]].name
],
'type':
'pie'
}], {
'height': 350,
'width': 500
})
async def plot(UR, Sawyer, inst, state_flags_enum):
xs = []
ys = []
# Add x and y to lists
for obj in await inst.async_get_objects(None):
xs.append(obj.x/1000.)
ys.append(obj.y/1000.)
sawyer_state = await Sawyer.robot_state.AsyncPeekInValue(None)
ur_state = await UR.robot_state.AsyncPeekInValue(None)
pose_Sawyer=sawyer_state[0].kin_chain_tcp
q_Sawyer=sawyer_state[0].joint_position
q_UR=ur_state[0].joint_position
pose_UR=ur_state[0].kin_chain_tcp
# Draw x and y lists
pose_Sawyer_C=np.dot(H_S_C,np.array([[pose_Sawyer[0]['position']['x']],[pose_Sawyer[0]['position']['y']],[1]]))
pose_UR_C=np.dot(H_UR_C,np.array([[pose_UR[0]['position']['x']],[pose_UR[0]['position']['y']],[1]]))
objects={ 'y': ys, 'x': xs ,'mode':'markers','name':'objects','type':'scatter','marker':{'size':10,'color':'#000000'}}
UR5_robot={ 'y': pose_UR_C[1], 'x': pose_UR_C[0] ,'mode':'markers','name':'UR5_robot','type':'scatter','marker':{'size':10,'color':'#27e3d3'}}
Sawyer_robot={ 'y': pose_Sawyer_C[1], 'x': pose_Sawyer_C[0] ,'mode':'markers','name':'Sawyer_robot','type':'scatter','marker':{'size':10,'color':'#e31010'}}
Plotly.react('plot',[objects,UR5_robot, Sawyer_robot])
def process_scatter():
df = process_input()
col1 = df[df.columns[0]].values
col2 = df[df.columns[1]].values
Plotly.plot(document.getElementById('plot2'),
[{
'x': col1,
'y': col2,
'type': 'scatter',
'mode': 'markers+lines',
'hoverinfo': 'label',
'label': 'Zoom Background Interest'
}])
def process_geo_map():
df = process_input()
df[df.columns[1]] = pd.to_numeric(df[df.columns[1]])
df[df.columns[2]] = pd.to_numeric(df[df.columns[2]])
col1 = df[df.columns[1]].values
col2 = df[df.columns[2]].values
col3 = df[df.columns[3]].values
Plotly.plot(document.getElementById('plot4'), [{
'type': 'scattergeo',
'lon': col2,
'lat': col1,
'text': col3
}])
def process_3d_maps():
df = process_input()
col0 = df[df.columns[0]].values
col1 = df[df.columns[1]].values
col2 = df[df.columns[2]].values
col3 = df[df.columns[3]].values
col4 = df[df.columns[4]].values
col5 = df[df.columns[5]].values
Plotly.plot(document.getElementById('plot6'), [{
'x': col0,
'y': col1,
'z': col2,
'mode': 'markers',
'marker': {
'size': 12,
'line': {
'color': 'rgba(217, 217, 217, 0.14)',
'width': 0.5
},
'opacity': 0.8
},
'type': 'scatter3d'
}, {
'x': col3,
'y': col4,
'z': col5,
'mode': 'markers',
'marker': {
'color': 'rgb(127, 127, 127)',
'size': 12,
'symbol': 'circle',
'line': {
'color': 'rgb(204, 204, 204)',
'width': 1
},
'opacity': 0.8
},
'type': 'scatter3d'
}], {'margin': {
'l': 0,
'r': 0,
'b': 0,
't': 0
}})
def process_heat_maps():
df = process_input()
df[df.columns[0]] = pd.to_numeric(df[df.columns[0]])
df[df.columns[1]] = pd.to_numeric(df[df.columns[1]])
df[df.columns[2]] = pd.to_numeric(df[df.columns[2]])
col0 = df[df.columns[0]].values
col1 = df[df.columns[1]].values
col2 = df[df.columns[2]].values
col3 = df[df.columns[3]].values
col4 = df[df.columns[4]].values
Plotly.plot(document.getElementById('plot5'), [{
'z': [col0, col1, col2],
'x': col3,
'y': col4,
'type': 'heatmap',
'hoverongaps': 'false'
}])
def process_time_series():
df = process_input()
df[df.columns[1]] = pd.to_numeric(df[df.columns[1]])
df[df.columns[2]] = pd.to_numeric(df[df.columns[2]])
df[df.columns[3]] = pd.to_numeric(df[df.columns[3]])
col1 = df[df.columns[0]].values
col2 = df[df.columns[1]].values
col3 = df[df.columns[2]].values
col4 = df[df.columns[3]].values
Plotly.plot(document.getElementById('plot3'), [{
'x': col1,
'y': col2,
'type': 'scatter',
'mode': "lines",
'name': 'Pho',
'line': {
'color': '#17BECF'
}
}, {
'x': col1,
'y': col3,
'type': "scatter",
'mode': "lines",
'name': 'Ramen',
'line': {
'color': '#7F7F7F'
}
}, {
'x': col1,
'y': col4,
'type': "scatter",
'mode': "lines",
'name': 'Soba',
'line': {
'color': '#7C19E2'
}
}])