Python Matplotlib: Set axis as increments with respect to one value












1















Some times when a plot is zoomed in enough the axis change so showing something like this



enter image description here



which means that the x value is, in this case 1.565 + the value showed in the tick.



Is there a way to set the axis ticks in this format? And once there how can I set the offset (The 1.565 in this case) and format the ticks?










share|improve this question























  • So you would start with an offset and a list_of_ticks and want to show it in the way as in the picture?

    – ImportanceOfBeingErnest
    Nov 20 '18 at 16:03











  • @ImportanceOfBeingErnest yes, concretely what I want is to center the axes at pi/2 and then set the ticks at [..., pi/2 -0.02, pi/2 - 0.01, pi/2, pi/2 + 0.01, ...], so that it shows [..., -0.02, - 0.01, 0, 0.01, ...] and the offset = pi/2

    – Alex
    Nov 20 '18 at 16:11


















1















Some times when a plot is zoomed in enough the axis change so showing something like this



enter image description here



which means that the x value is, in this case 1.565 + the value showed in the tick.



Is there a way to set the axis ticks in this format? And once there how can I set the offset (The 1.565 in this case) and format the ticks?










share|improve this question























  • So you would start with an offset and a list_of_ticks and want to show it in the way as in the picture?

    – ImportanceOfBeingErnest
    Nov 20 '18 at 16:03











  • @ImportanceOfBeingErnest yes, concretely what I want is to center the axes at pi/2 and then set the ticks at [..., pi/2 -0.02, pi/2 - 0.01, pi/2, pi/2 + 0.01, ...], so that it shows [..., -0.02, - 0.01, 0, 0.01, ...] and the offset = pi/2

    – Alex
    Nov 20 '18 at 16:11
















1












1








1








Some times when a plot is zoomed in enough the axis change so showing something like this



enter image description here



which means that the x value is, in this case 1.565 + the value showed in the tick.



Is there a way to set the axis ticks in this format? And once there how can I set the offset (The 1.565 in this case) and format the ticks?










share|improve this question














Some times when a plot is zoomed in enough the axis change so showing something like this



enter image description here



which means that the x value is, in this case 1.565 + the value showed in the tick.



Is there a way to set the axis ticks in this format? And once there how can I set the offset (The 1.565 in this case) and format the ticks?







python matplotlib graphing






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Nov 20 '18 at 15:59









AlexAlex

253




253













  • So you would start with an offset and a list_of_ticks and want to show it in the way as in the picture?

    – ImportanceOfBeingErnest
    Nov 20 '18 at 16:03











  • @ImportanceOfBeingErnest yes, concretely what I want is to center the axes at pi/2 and then set the ticks at [..., pi/2 -0.02, pi/2 - 0.01, pi/2, pi/2 + 0.01, ...], so that it shows [..., -0.02, - 0.01, 0, 0.01, ...] and the offset = pi/2

    – Alex
    Nov 20 '18 at 16:11





















  • So you would start with an offset and a list_of_ticks and want to show it in the way as in the picture?

    – ImportanceOfBeingErnest
    Nov 20 '18 at 16:03











  • @ImportanceOfBeingErnest yes, concretely what I want is to center the axes at pi/2 and then set the ticks at [..., pi/2 -0.02, pi/2 - 0.01, pi/2, pi/2 + 0.01, ...], so that it shows [..., -0.02, - 0.01, 0, 0.01, ...] and the offset = pi/2

    – Alex
    Nov 20 '18 at 16:11



















So you would start with an offset and a list_of_ticks and want to show it in the way as in the picture?

– ImportanceOfBeingErnest
Nov 20 '18 at 16:03





So you would start with an offset and a list_of_ticks and want to show it in the way as in the picture?

– ImportanceOfBeingErnest
Nov 20 '18 at 16:03













@ImportanceOfBeingErnest yes, concretely what I want is to center the axes at pi/2 and then set the ticks at [..., pi/2 -0.02, pi/2 - 0.01, pi/2, pi/2 + 0.01, ...], so that it shows [..., -0.02, - 0.01, 0, 0.01, ...] and the offset = pi/2

– Alex
Nov 20 '18 at 16:11







@ImportanceOfBeingErnest yes, concretely what I want is to center the axes at pi/2 and then set the ticks at [..., pi/2 -0.02, pi/2 - 0.01, pi/2, pi/2 + 0.01, ...], so that it shows [..., -0.02, - 0.01, 0, 0.01, ...] and the offset = pi/2

– Alex
Nov 20 '18 at 16:11














1 Answer
1






active

oldest

votes


















1














A. Manually placing the offset



I think the easiest solution is to plot x-offset, instead of x itself. Then just add a text field with the offset below the axes.



import numpy as np
import matplotlib.pyplot as plt

x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x - np.pi/2, y)
plt.text(1, -0.07, "$+pi / 2$", ha="right", va="top",
transform=plt.gca().transAxes)

plt.show()


enter image description here



B. Using a fixed formatter



Alternatively you can use a FixedFormatter and set its offset label manually.



import numpy as np
import matplotlib.pyplot as plt

x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x, y)

xticks = np.array([-0.02, -0.01, 0, 0.01, 0.02])

plt.gca().set(xticks = xticks + np.pi/2,
xticklabels = xticks)
plt.gca().xaxis.get_major_formatter().set_offset_string("$+pi / 2$")

plt.show()


enter image description here



The drawback of this is that the tick positions are fixed so you loose the nice labeling when zooming.



C. Using a custom locator and formatter with a fixed offset



This is possible but utterly complicated. The solution would look similar to Set scientific notation with fixed exponent and significant digits for multiple subplots but needs to use a Locator as well.



import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker

class OffsetLocator(matplotlib.ticker.AutoLocator):
def __init__(self, offset=0):
self.fixed_offset = offset
matplotlib.ticker.AutoLocator.__init__(self)
def tick_values(self, vmin, vmax):
v = np.array([vmin,vmax])-self.fixed_offset
ticks = matplotlib.ticker.AutoLocator.tick_values(self, *v)
return ticks + self.fixed_offset

class OffsetFormatter(matplotlib.ticker.ScalarFormatter):
def __init__(self, offset=0, offsettext = None, mathText=True):
self.fixed_offset = offset
self.offset_text = offsettext
matplotlib.ticker.ScalarFormatter.__init__(self,useOffset=offset,
useMathText=mathText)
def _set_orderOfMagnitude(self, nothing):
self.orderOfMagnitude = 0
def _compute_offset(self):
return self.fixed_offset
def get_offset(self):
return self.offset_text or matplotlib.ticker.ScalarFormatter.get_offset(self)


x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x, y)

plt.gca().xaxis.set_major_locator(OffsetLocator(np.pi/2))
plt.gca().xaxis.set_major_formatter(OffsetFormatter(np.pi/2, offsettext="$+pi / 2$"))

plt.show()


enter image description here



The result looks similar to the above, but behaves completely natural like in all other cases where some offset is used. One will probably observe the differences only when playing with figure size, zooming and panning etc.






share|improve this answer


























  • I updated the answer with the completely general solution now. Would be interesting to know which of those you decide to go with.

    – ImportanceOfBeingErnest
    Nov 21 '18 at 0:28











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1 Answer
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1 Answer
1






active

oldest

votes









active

oldest

votes






active

oldest

votes









1














A. Manually placing the offset



I think the easiest solution is to plot x-offset, instead of x itself. Then just add a text field with the offset below the axes.



import numpy as np
import matplotlib.pyplot as plt

x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x - np.pi/2, y)
plt.text(1, -0.07, "$+pi / 2$", ha="right", va="top",
transform=plt.gca().transAxes)

plt.show()


enter image description here



B. Using a fixed formatter



Alternatively you can use a FixedFormatter and set its offset label manually.



import numpy as np
import matplotlib.pyplot as plt

x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x, y)

xticks = np.array([-0.02, -0.01, 0, 0.01, 0.02])

plt.gca().set(xticks = xticks + np.pi/2,
xticklabels = xticks)
plt.gca().xaxis.get_major_formatter().set_offset_string("$+pi / 2$")

plt.show()


enter image description here



The drawback of this is that the tick positions are fixed so you loose the nice labeling when zooming.



C. Using a custom locator and formatter with a fixed offset



This is possible but utterly complicated. The solution would look similar to Set scientific notation with fixed exponent and significant digits for multiple subplots but needs to use a Locator as well.



import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker

class OffsetLocator(matplotlib.ticker.AutoLocator):
def __init__(self, offset=0):
self.fixed_offset = offset
matplotlib.ticker.AutoLocator.__init__(self)
def tick_values(self, vmin, vmax):
v = np.array([vmin,vmax])-self.fixed_offset
ticks = matplotlib.ticker.AutoLocator.tick_values(self, *v)
return ticks + self.fixed_offset

class OffsetFormatter(matplotlib.ticker.ScalarFormatter):
def __init__(self, offset=0, offsettext = None, mathText=True):
self.fixed_offset = offset
self.offset_text = offsettext
matplotlib.ticker.ScalarFormatter.__init__(self,useOffset=offset,
useMathText=mathText)
def _set_orderOfMagnitude(self, nothing):
self.orderOfMagnitude = 0
def _compute_offset(self):
return self.fixed_offset
def get_offset(self):
return self.offset_text or matplotlib.ticker.ScalarFormatter.get_offset(self)


x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x, y)

plt.gca().xaxis.set_major_locator(OffsetLocator(np.pi/2))
plt.gca().xaxis.set_major_formatter(OffsetFormatter(np.pi/2, offsettext="$+pi / 2$"))

plt.show()


enter image description here



The result looks similar to the above, but behaves completely natural like in all other cases where some offset is used. One will probably observe the differences only when playing with figure size, zooming and panning etc.






share|improve this answer


























  • I updated the answer with the completely general solution now. Would be interesting to know which of those you decide to go with.

    – ImportanceOfBeingErnest
    Nov 21 '18 at 0:28
















1














A. Manually placing the offset



I think the easiest solution is to plot x-offset, instead of x itself. Then just add a text field with the offset below the axes.



import numpy as np
import matplotlib.pyplot as plt

x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x - np.pi/2, y)
plt.text(1, -0.07, "$+pi / 2$", ha="right", va="top",
transform=plt.gca().transAxes)

plt.show()


enter image description here



B. Using a fixed formatter



Alternatively you can use a FixedFormatter and set its offset label manually.



import numpy as np
import matplotlib.pyplot as plt

x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x, y)

xticks = np.array([-0.02, -0.01, 0, 0.01, 0.02])

plt.gca().set(xticks = xticks + np.pi/2,
xticklabels = xticks)
plt.gca().xaxis.get_major_formatter().set_offset_string("$+pi / 2$")

plt.show()


enter image description here



The drawback of this is that the tick positions are fixed so you loose the nice labeling when zooming.



C. Using a custom locator and formatter with a fixed offset



This is possible but utterly complicated. The solution would look similar to Set scientific notation with fixed exponent and significant digits for multiple subplots but needs to use a Locator as well.



import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker

class OffsetLocator(matplotlib.ticker.AutoLocator):
def __init__(self, offset=0):
self.fixed_offset = offset
matplotlib.ticker.AutoLocator.__init__(self)
def tick_values(self, vmin, vmax):
v = np.array([vmin,vmax])-self.fixed_offset
ticks = matplotlib.ticker.AutoLocator.tick_values(self, *v)
return ticks + self.fixed_offset

class OffsetFormatter(matplotlib.ticker.ScalarFormatter):
def __init__(self, offset=0, offsettext = None, mathText=True):
self.fixed_offset = offset
self.offset_text = offsettext
matplotlib.ticker.ScalarFormatter.__init__(self,useOffset=offset,
useMathText=mathText)
def _set_orderOfMagnitude(self, nothing):
self.orderOfMagnitude = 0
def _compute_offset(self):
return self.fixed_offset
def get_offset(self):
return self.offset_text or matplotlib.ticker.ScalarFormatter.get_offset(self)


x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x, y)

plt.gca().xaxis.set_major_locator(OffsetLocator(np.pi/2))
plt.gca().xaxis.set_major_formatter(OffsetFormatter(np.pi/2, offsettext="$+pi / 2$"))

plt.show()


enter image description here



The result looks similar to the above, but behaves completely natural like in all other cases where some offset is used. One will probably observe the differences only when playing with figure size, zooming and panning etc.






share|improve this answer


























  • I updated the answer with the completely general solution now. Would be interesting to know which of those you decide to go with.

    – ImportanceOfBeingErnest
    Nov 21 '18 at 0:28














1












1








1







A. Manually placing the offset



I think the easiest solution is to plot x-offset, instead of x itself. Then just add a text field with the offset below the axes.



import numpy as np
import matplotlib.pyplot as plt

x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x - np.pi/2, y)
plt.text(1, -0.07, "$+pi / 2$", ha="right", va="top",
transform=plt.gca().transAxes)

plt.show()


enter image description here



B. Using a fixed formatter



Alternatively you can use a FixedFormatter and set its offset label manually.



import numpy as np
import matplotlib.pyplot as plt

x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x, y)

xticks = np.array([-0.02, -0.01, 0, 0.01, 0.02])

plt.gca().set(xticks = xticks + np.pi/2,
xticklabels = xticks)
plt.gca().xaxis.get_major_formatter().set_offset_string("$+pi / 2$")

plt.show()


enter image description here



The drawback of this is that the tick positions are fixed so you loose the nice labeling when zooming.



C. Using a custom locator and formatter with a fixed offset



This is possible but utterly complicated. The solution would look similar to Set scientific notation with fixed exponent and significant digits for multiple subplots but needs to use a Locator as well.



import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker

class OffsetLocator(matplotlib.ticker.AutoLocator):
def __init__(self, offset=0):
self.fixed_offset = offset
matplotlib.ticker.AutoLocator.__init__(self)
def tick_values(self, vmin, vmax):
v = np.array([vmin,vmax])-self.fixed_offset
ticks = matplotlib.ticker.AutoLocator.tick_values(self, *v)
return ticks + self.fixed_offset

class OffsetFormatter(matplotlib.ticker.ScalarFormatter):
def __init__(self, offset=0, offsettext = None, mathText=True):
self.fixed_offset = offset
self.offset_text = offsettext
matplotlib.ticker.ScalarFormatter.__init__(self,useOffset=offset,
useMathText=mathText)
def _set_orderOfMagnitude(self, nothing):
self.orderOfMagnitude = 0
def _compute_offset(self):
return self.fixed_offset
def get_offset(self):
return self.offset_text or matplotlib.ticker.ScalarFormatter.get_offset(self)


x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x, y)

plt.gca().xaxis.set_major_locator(OffsetLocator(np.pi/2))
plt.gca().xaxis.set_major_formatter(OffsetFormatter(np.pi/2, offsettext="$+pi / 2$"))

plt.show()


enter image description here



The result looks similar to the above, but behaves completely natural like in all other cases where some offset is used. One will probably observe the differences only when playing with figure size, zooming and panning etc.






share|improve this answer















A. Manually placing the offset



I think the easiest solution is to plot x-offset, instead of x itself. Then just add a text field with the offset below the axes.



import numpy as np
import matplotlib.pyplot as plt

x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x - np.pi/2, y)
plt.text(1, -0.07, "$+pi / 2$", ha="right", va="top",
transform=plt.gca().transAxes)

plt.show()


enter image description here



B. Using a fixed formatter



Alternatively you can use a FixedFormatter and set its offset label manually.



import numpy as np
import matplotlib.pyplot as plt

x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x, y)

xticks = np.array([-0.02, -0.01, 0, 0.01, 0.02])

plt.gca().set(xticks = xticks + np.pi/2,
xticklabels = xticks)
plt.gca().xaxis.get_major_formatter().set_offset_string("$+pi / 2$")

plt.show()


enter image description here



The drawback of this is that the tick positions are fixed so you loose the nice labeling when zooming.



C. Using a custom locator and formatter with a fixed offset



This is possible but utterly complicated. The solution would look similar to Set scientific notation with fixed exponent and significant digits for multiple subplots but needs to use a Locator as well.



import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker

class OffsetLocator(matplotlib.ticker.AutoLocator):
def __init__(self, offset=0):
self.fixed_offset = offset
matplotlib.ticker.AutoLocator.__init__(self)
def tick_values(self, vmin, vmax):
v = np.array([vmin,vmax])-self.fixed_offset
ticks = matplotlib.ticker.AutoLocator.tick_values(self, *v)
return ticks + self.fixed_offset

class OffsetFormatter(matplotlib.ticker.ScalarFormatter):
def __init__(self, offset=0, offsettext = None, mathText=True):
self.fixed_offset = offset
self.offset_text = offsettext
matplotlib.ticker.ScalarFormatter.__init__(self,useOffset=offset,
useMathText=mathText)
def _set_orderOfMagnitude(self, nothing):
self.orderOfMagnitude = 0
def _compute_offset(self):
return self.fixed_offset
def get_offset(self):
return self.offset_text or matplotlib.ticker.ScalarFormatter.get_offset(self)


x = np.array([-0.02+np.pi/2, +0.02+np.pi/2])
y = [1,1]

plt.plot(x, y)

plt.gca().xaxis.set_major_locator(OffsetLocator(np.pi/2))
plt.gca().xaxis.set_major_formatter(OffsetFormatter(np.pi/2, offsettext="$+pi / 2$"))

plt.show()


enter image description here



The result looks similar to the above, but behaves completely natural like in all other cases where some offset is used. One will probably observe the differences only when playing with figure size, zooming and panning etc.







share|improve this answer














share|improve this answer



share|improve this answer








edited Nov 21 '18 at 0:26

























answered Nov 20 '18 at 16:56









ImportanceOfBeingErnestImportanceOfBeingErnest

135k13150225




135k13150225













  • I updated the answer with the completely general solution now. Would be interesting to know which of those you decide to go with.

    – ImportanceOfBeingErnest
    Nov 21 '18 at 0:28



















  • I updated the answer with the completely general solution now. Would be interesting to know which of those you decide to go with.

    – ImportanceOfBeingErnest
    Nov 21 '18 at 0:28

















I updated the answer with the completely general solution now. Would be interesting to know which of those you decide to go with.

– ImportanceOfBeingErnest
Nov 21 '18 at 0:28





I updated the answer with the completely general solution now. Would be interesting to know which of those you decide to go with.

– ImportanceOfBeingErnest
Nov 21 '18 at 0:28




















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