def _testBasic():
print "Init"
Nutmeg.init()
print "Sending Figure"
fig = Nutmeg.figure('fig', "figure1.qml")
print "Sending Data"
fig.set('ax[1].red.y', np.random.standard_normal(10))
def _testFonts():
Nutmeg.init()
fig = Nutmeg.figure('fig', 'figureFont.qml')
fig.set('ax[1].red.y', np.random.standard_normal(10))
# fig.set('ax[1].title', "Axis2")
for i in range(3):
fig.set('ax[' + str(i) + '].title', "Axis" + str(i+1))
def _testImages():
import cv2
Nutmeg.init()
fig = Nutmeg.figure('fig', "figureIm.qml")
im = open("img.jpg")
imData = im.read()
fig.set('ax.im.binary', imData)
def _testButton():
Nutmeg.init()
fig = Nutmeg.figure('fig', 'figure_single.qml')
fig.setGui('gui1.qml')
print (fig.parameters)
time.sleep(0.1)
buttonParam = fig.parameter("button")
while True:
if buttonParam.changed:
changes = buttonParam.changed
print("Button: %d (clicked %d times)" % (changes, buttonParam.read()))
break
time.sleep(0.1)
def _testParams():
Nutmeg.init()
fig = Nutmeg.figure('fig', 'figure1.qml')
print "Sending GUI..."
success = fig.setGui('gui1.qml')
N = 100
data = np.random.standard_normal((3, N*10))
data2 = np.random.standard_normal((3, N))
update = lambda params: applyBlur(data, params['sigma'])
update2 = lambda params: applyBlur(data2, params['sigma'])
fig.set('ax[:].blue.x', np.arange(N*10,dtype=float)/10)
fig.set('ax[:].red.x', np.arange(N, dtype=float))
fig.set('ax[:].blue.y', Updater(['sigma'], update=update))
fig.set('ax[:].red.y', Updater(['sigma'], update=update2))
# for i in range(100):
# fig.set('ax[:].red', update2({'sigma': i*0.05}))
# time.sleep(0.025)
print("Data set")
def customAdvancedBar():
fig = Nutmeg.figure('customAdvancedBar', 'customAdvancedBarPlot.qml')
fig.set('ax.barPlot', data=[[1,2,3, -2,0.5,6,1],[-0.5,7]], barWidth=1)
fig.set('legend', labels=["Hey", "There", "Labels", "I", "Love", "Lamp"])
def _testGrid():
Nutmeg.init()
fig = Nutmeg.figure('fig', 'figureGrid.qml')
fig.set('ax[1].red.y', np.random.standard_normal(10))
def _testDelta():
Nutmeg.init()
fig = Nutmeg.figure('fig', 'figure1.qml')
fig.set('ax[1].red.y', np.random.standard_normal(10))
fig.set('ax[1].red.y[5]', -10)
# Code starts
import Nutmeg
import numpy as np
# Initialise the Nutmeg module. This connects to the core.
Nutmeg.init()
# Create the figure from a qml file
fig = Nutmeg.figure('basic02', "figure_triple.qml")
# Set the data
randomData = np.random.standard_normal(10)
fig.set('ax[1].red.y', randomData)
x = np.r_[0:10.:0.01]
ySin = np.sin(x)
fig.set('ax[0].green', {'x': x, 'y': ySin})
yTan = np.tan(x)
fig.set('ax[2].blue', {'x': x, 'y': yTan})
import Nutmeg
def basics():
Nutmeg.figure('basicCanvas', 'canvasPlotBasic.qml')
def customBar():
fig = Nutmeg.figure('customBar', 'customBarPlot.qml')
fig.set('ax.barPlot', data=[1, 2, 3, -0.5, 7], barWidth=1.5, spacing=3)
def customAdvancedBar():
fig = Nutmeg.figure('customAdvancedBar', 'customAdvancedBarPlot.qml')
fig.set('ax.barPlot',
data=[[1, 2, 3, -2, 0.5, 6, 1], [-0.5, 7]],
barWidth=1)
fig.set('legend', labels=["Hey", "There", "Labels", "I", "Love", "Lamp"])
if __name__ == '__main__':
Nutmeg.init()
# basics()
# customBar()
customAdvancedBar()
import Nutmeg
from numpy import sin, cos, pi, r_
# Assuming the core is on port 43686 (default)
Nutmeg.init()
x = r_[0:1:0.01]
y1 = sin(10*pi*x)
y2 = 10*pi*cos(10*pi*x)
fig = Nutmeg.figure("myFigure", "myFigure.qml")
fig.set("axis1.data", x=x, y=y1)
fig.set("axis2.data", x=x, y=y2)
def _testValidateHandle():
Nutmeg.init()
fig = Nutmeg.figure('fig', 'figure_single.qml')
print(Nutmeg.isValidHandle('fig.ax.redPlot'))
# Code starts
import Nutmeg
import numpy as np
# Initialise the Nutmeg module. This connects to the core.
Nutmeg.init()
# Create the figure from a qml file
fig = Nutmeg.figure('basic01', "figure_single.qml")
# Set the data
randomData = np.random.standard_normal(10)
fig.set('ax.redPlot.bars', randomData)
x = np.r_[0:10.:0.01]
ySin = np.sin(x)
fig.set('ax.greenPlot', {'x': x, 'y': ySin})
yTan = np.tan(x)
fig.set('ax.bluePlot', {'x': x, 'y': yTan})
import Nutmeg
def basics():
Nutmeg.figure('basicCanvas', 'canvasPlotBasic.qml')
def customBar():
fig = Nutmeg.figure('customBar', 'customBarPlot.qml')
fig.set('ax.barPlot', data=[1,2,3,-0.5,7], barWidth=1.5, spacing=3)
def customAdvancedBar():
fig = Nutmeg.figure('customAdvancedBar', 'customAdvancedBarPlot.qml')
fig.set('ax.barPlot', data=[[1,2,3, -2,0.5,6,1],[-0.5,7]], barWidth=1)
fig.set('legend', labels=["Hey", "There", "Labels", "I", "Love", "Lamp"])
if __name__ == '__main__':
Nutmeg.init()
# basics()
# customBar()
customAdvancedBar()
# Code starts
import Nutmeg
import numpy as np
# Initialise the Nutmeg module. This connects to the core.
Nutmeg.init()
# Create the figure from a qml file
fig = Nutmeg.figure('fig', "figure1.qml")
# Set the data
randomData = np.random.standard_normal(10)
fig.set('ax[1].red.y', randomData)
x = np.r_[0:10.:0.01]
ySin = np.sin(x)
fig.set('ax[0].green', {'x': x, 'y': ySin})
yTan = np.tan(x)
fig.set('ax[2].blue', {'x': x, 'y': yTan})
def customBar():
fig = Nutmeg.figure('customBar', 'customBarPlot.qml')
fig.set('ax.barPlot', data=[1, 2, 3, -0.5, 7], barWidth=1.5, spacing=3)
def basics():
Nutmeg.figure('basicCanvas', 'canvasPlotBasic.qml')
def customAdvancedBar():
fig = Nutmeg.figure('customAdvancedBar', 'customAdvancedBarPlot.qml')
fig.set('ax.barPlot',
data=[[1, 2, 3, -2, 0.5, 6, 1], [-0.5, 7]],
barWidth=1)
fig.set('legend', labels=["Hey", "There", "Labels", "I", "Love", "Lamp"])
def basics():
Nutmeg.figure('basicCanvas', 'canvasPlotBasic.qml')
def customBar():
fig = Nutmeg.figure('customBar', 'customBarPlot.qml')
fig.set('ax.barPlot', data=[1,2,3,-0.5,7], barWidth=1.5, spacing=3)
import Nutmeg
import time
from scipy import ndimage
import numpy as np
# Init the figure
Nutmeg.init()
fig = Nutmeg.figure('paramExample', 'figure1.qml')
# Set the GUI as described in the qml file
success = fig.setGui('gui1.qml')
sigmaParam = fig.parameter("sigma")
N = 100
data = np.random.standard_normal((3, N*10))
def applyBlur(dataIn, sigma):
return ndimage.gaussian_filter1d(dataIn, sigma, axis=1)
while True:
if sigmaParam.changed:
sigma = sigmaParam.read()
print "Sigma Changed:", sigma
dataBlur = applyBlur(data, sigma)
fig.set('ax.blue', y=dataBlur)
import Nutmeg
Nutmeg.init()
fig = Nutmeg.figure('imageExample', "figureIm.qml")
im = open("img.jpg")
imData = im.read()
fig.set('ax.im.binary', imData)
fig.set('ax.data', {'x': [0, 1, 2, 800, 1500], 'y': [0, 500, 100, 800, 1000]})
# fig.set('ax.data2', {'x': [0, 1, 2, 800, 1500], 'y': [0, 300, 200, 900, 1000]})
