I've been trying to suppress scientific notation in pyplot for a few hours now. After trying multiple solutions without success, I would like some help.
plt.plot(range(2003,2012,1),range(200300,201200,100))
# several solutions from other questions have not worked, including
# plt.ticklabel_format(style='sci', axis='x', scilimits=(-1000000,1000000))
# ax.get_xaxis().get_major_formatter().set_useOffset(False)
plt.show()
Is ticklabel_format broken? does not resolve the issue of actually removing the offset.
plt.plot(np.arange(1e6, 3 * 1e7, 1e6))
plt.ticklabel_format(useOffset=False)
In your case, you're actually wanting to disable the offset. Using scientific notation is a separate setting from showing things in terms of an offset value.
However, ax.ticklabel_format(useOffset=False) should have worked (though you've listed it as one of the things that didn't).
For example:
fig, ax = plt.subplots()
ax.plot(range(2003,2012,1),range(200300,201200,100))
ax.ticklabel_format(useOffset=False)
plt.show()
If you want to disable both the offset and scientific notaion, you'd use ax.ticklabel_format(useOffset=False, style='plain').
Difference between "offset" and "scientific notation"
In matplotlib axis formatting, "scientific notation" refers to a multiplier for the numbers show, while the "offset" is a separate term that is added.
Consider this example:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(1000, 1001, 100)
y = np.linspace(1e-9, 1e9, 100)
fig, ax = plt.subplots()
ax.plot(x, y)
plt.show()
The x-axis will have an offset (note the + sign) and the y-axis will use scientific notation (as a multiplier -- No plus sign).
We can disable either one separately. The most convenient way is the ax.ticklabel_format method (or plt.ticklabel_format).
For example, if we call:
ax.ticklabel_format(style='plain')
We'll disable the scientific notation on the y-axis:
And if we call
ax.ticklabel_format(useOffset=False)
We'll disable the offset on the x-axis, but leave the y-axis scientific notation untouched:
Finally, we can disable both through:
ax.ticklabel_format(useOffset=False, style='plain')
Related
I've been trying to suppress scientific notation in pyplot for a few hours now. After trying multiple solutions without success, I would like some help.
plt.plot(range(2003,2012,1),range(200300,201200,100))
# several solutions from other questions have not worked, including
# plt.ticklabel_format(style='sci', axis='x', scilimits=(-1000000,1000000))
# ax.get_xaxis().get_major_formatter().set_useOffset(False)
plt.show()
Is ticklabel_format broken? does not resolve the issue of actually removing the offset.
plt.plot(np.arange(1e6, 3 * 1e7, 1e6))
plt.ticklabel_format(useOffset=False)
In your case, you're actually wanting to disable the offset. Using scientific notation is a separate setting from showing things in terms of an offset value.
However, ax.ticklabel_format(useOffset=False) should have worked (though you've listed it as one of the things that didn't).
For example:
fig, ax = plt.subplots()
ax.plot(range(2003,2012,1),range(200300,201200,100))
ax.ticklabel_format(useOffset=False)
plt.show()
If you want to disable both the offset and scientific notaion, you'd use ax.ticklabel_format(useOffset=False, style='plain').
Difference between "offset" and "scientific notation"
In matplotlib axis formatting, "scientific notation" refers to a multiplier for the numbers show, while the "offset" is a separate term that is added.
Consider this example:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(1000, 1001, 100)
y = np.linspace(1e-9, 1e9, 100)
fig, ax = plt.subplots()
ax.plot(x, y)
plt.show()
The x-axis will have an offset (note the + sign) and the y-axis will use scientific notation (as a multiplier -- No plus sign).
We can disable either one separately. The most convenient way is the ax.ticklabel_format method (or plt.ticklabel_format).
For example, if we call:
ax.ticklabel_format(style='plain')
We'll disable the scientific notation on the y-axis:
And if we call
ax.ticklabel_format(useOffset=False)
We'll disable the offset on the x-axis, but leave the y-axis scientific notation untouched:
Finally, we can disable both through:
ax.ticklabel_format(useOffset=False, style='plain')
I've been trying to suppress scientific notation in pyplot for a few hours now. After trying multiple solutions without success, I would like some help.
plt.plot(range(2003,2012,1),range(200300,201200,100))
# several solutions from other questions have not worked, including
# plt.ticklabel_format(style='sci', axis='x', scilimits=(-1000000,1000000))
# ax.get_xaxis().get_major_formatter().set_useOffset(False)
plt.show()
Is ticklabel_format broken? does not resolve the issue of actually removing the offset.
plt.plot(np.arange(1e6, 3 * 1e7, 1e6))
plt.ticklabel_format(useOffset=False)
In your case, you're actually wanting to disable the offset. Using scientific notation is a separate setting from showing things in terms of an offset value.
However, ax.ticklabel_format(useOffset=False) should have worked (though you've listed it as one of the things that didn't).
For example:
fig, ax = plt.subplots()
ax.plot(range(2003,2012,1),range(200300,201200,100))
ax.ticklabel_format(useOffset=False)
plt.show()
If you want to disable both the offset and scientific notaion, you'd use ax.ticklabel_format(useOffset=False, style='plain').
Difference between "offset" and "scientific notation"
In matplotlib axis formatting, "scientific notation" refers to a multiplier for the numbers show, while the "offset" is a separate term that is added.
Consider this example:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(1000, 1001, 100)
y = np.linspace(1e-9, 1e9, 100)
fig, ax = plt.subplots()
ax.plot(x, y)
plt.show()
The x-axis will have an offset (note the + sign) and the y-axis will use scientific notation (as a multiplier -- No plus sign).
We can disable either one separately. The most convenient way is the ax.ticklabel_format method (or plt.ticklabel_format).
For example, if we call:
ax.ticklabel_format(style='plain')
We'll disable the scientific notation on the y-axis:
And if we call
ax.ticklabel_format(useOffset=False)
We'll disable the offset on the x-axis, but leave the y-axis scientific notation untouched:
Finally, we can disable both through:
ax.ticklabel_format(useOffset=False, style='plain')
I've been trying to suppress scientific notation in pyplot for a few hours now. After trying multiple solutions without success, I would like some help.
plt.plot(range(2003,2012,1),range(200300,201200,100))
# several solutions from other questions have not worked, including
# plt.ticklabel_format(style='sci', axis='x', scilimits=(-1000000,1000000))
# ax.get_xaxis().get_major_formatter().set_useOffset(False)
plt.show()
Is ticklabel_format broken? does not resolve the issue of actually removing the offset.
plt.plot(np.arange(1e6, 3 * 1e7, 1e6))
plt.ticklabel_format(useOffset=False)
In your case, you're actually wanting to disable the offset. Using scientific notation is a separate setting from showing things in terms of an offset value.
However, ax.ticklabel_format(useOffset=False) should have worked (though you've listed it as one of the things that didn't).
For example:
fig, ax = plt.subplots()
ax.plot(range(2003,2012,1),range(200300,201200,100))
ax.ticklabel_format(useOffset=False)
plt.show()
If you want to disable both the offset and scientific notaion, you'd use ax.ticklabel_format(useOffset=False, style='plain').
Difference between "offset" and "scientific notation"
In matplotlib axis formatting, "scientific notation" refers to a multiplier for the numbers show, while the "offset" is a separate term that is added.
Consider this example:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(1000, 1001, 100)
y = np.linspace(1e-9, 1e9, 100)
fig, ax = plt.subplots()
ax.plot(x, y)
plt.show()
The x-axis will have an offset (note the + sign) and the y-axis will use scientific notation (as a multiplier -- No plus sign).
We can disable either one separately. The most convenient way is the ax.ticklabel_format method (or plt.ticklabel_format).
For example, if we call:
ax.ticklabel_format(style='plain')
We'll disable the scientific notation on the y-axis:
And if we call
ax.ticklabel_format(useOffset=False)
We'll disable the offset on the x-axis, but leave the y-axis scientific notation untouched:
Finally, we can disable both through:
ax.ticklabel_format(useOffset=False, style='plain')
I've been trying to suppress scientific notation in pyplot for a few hours now. After trying multiple solutions without success, I would like some help.
plt.plot(range(2003,2012,1),range(200300,201200,100))
# several solutions from other questions have not worked, including
# plt.ticklabel_format(style='sci', axis='x', scilimits=(-1000000,1000000))
# ax.get_xaxis().get_major_formatter().set_useOffset(False)
plt.show()
Is ticklabel_format broken? does not resolve the issue of actually removing the offset.
plt.plot(np.arange(1e6, 3 * 1e7, 1e6))
plt.ticklabel_format(useOffset=False)
In your case, you're actually wanting to disable the offset. Using scientific notation is a separate setting from showing things in terms of an offset value.
However, ax.ticklabel_format(useOffset=False) should have worked (though you've listed it as one of the things that didn't).
For example:
fig, ax = plt.subplots()
ax.plot(range(2003,2012,1),range(200300,201200,100))
ax.ticklabel_format(useOffset=False)
plt.show()
If you want to disable both the offset and scientific notaion, you'd use ax.ticklabel_format(useOffset=False, style='plain').
Difference between "offset" and "scientific notation"
In matplotlib axis formatting, "scientific notation" refers to a multiplier for the numbers show, while the "offset" is a separate term that is added.
Consider this example:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(1000, 1001, 100)
y = np.linspace(1e-9, 1e9, 100)
fig, ax = plt.subplots()
ax.plot(x, y)
plt.show()
The x-axis will have an offset (note the + sign) and the y-axis will use scientific notation (as a multiplier -- No plus sign).
We can disable either one separately. The most convenient way is the ax.ticklabel_format method (or plt.ticklabel_format).
For example, if we call:
ax.ticklabel_format(style='plain')
We'll disable the scientific notation on the y-axis:
And if we call
ax.ticklabel_format(useOffset=False)
We'll disable the offset on the x-axis, but leave the y-axis scientific notation untouched:
Finally, we can disable both through:
ax.ticklabel_format(useOffset=False, style='plain')
String formatting can by used to specify scientific notation for matplotlib.basemap colorbar labels:
cb = m.colorbar(cs, ax=ax1, format='%.4e')
But then each label is scientifically notated with the base.
If numbers are large enough, the colobar automatically reduces them to scientific notation, placing the base (i.e. x10^n) at the top of the color bar, leaving only the coefficient numbers as labels.
You can do this with a standard axis with the following:
ax.ticklabel_format(style='sci', axis='y', scilimits=(0,0))
Is there an equivalent method for matplotlib.basemap colorbars, or perhaps a standard matplotlib colorbar?
There's no one-line method, but you can do this by updating the colorbar's formatter and then calling colorbar.update_ticks().
import numpy as np
import matplotlib.pyplot as plt
z = np.random.random((10,10))
fig, ax = plt.subplots()
im = ax.imshow(z)
cb = fig.colorbar(im)
cb.formatter.set_powerlimits((0, 0))
cb.update_ticks()
plt.show()
The reason for the slightly odd way of doing things is that a colorbar actually has statically assigned ticks and ticklabels. The colorbar's axes (colorbar.ax) actually always ranges between 0 and 1. (Therefore, altering colorbar.ax.yaxis.formatter doesn't do anything useful.) The tick positions and labels are calculated from colorbar.locator and colorbar.formatter and are assigned when the colorbar is created. Therefore, if you need precise control over a colorbar's ticks/ticklables, you need to explicitly call colorbar.update_ticks() after customizing how the ticks are displayed. The colorbar's convenience functions do this for you behind the scenes, but as far as I know, what you want can't be done through another method.