MultipleLocator and MaxNLocator

Is it possible to combine MultipleLocator and MaxNLocator? One seems
to erase the effect of the other.

They are for different situations. MultipleLocator is for when you know what you want your tick interval to be; MaxNLocator is for when you don't know that, but you do know roughly how many ticks you want, and what sort of numerical intervals are acceptable.

Eric

···

On 2015/02/13 3:29 PM, Tommy Carstensen wrote:

Is it possible to combine MultipleLocator and MaxNLocator? One seems
to erase the effect of the other.

Tommy,
Perhaps you might find it useful to look at the Python class that Justin Talbot wrote (http://www.justintalbot.com/research/axis-labeling/). I find this very useful in my own work.

···

On 14-Feb-2015 02:29, Tommy Carstensen wrote:

Is it possible to combine MultipleLocator and MaxNLocator? One seems
to erase the effect of the other.

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Thanks for you answer Eric. I had to get some sleep before trying out
things. I currently have the code below, but it does not remove the
zero value tick. It removes the tick at 5 and 10 however.

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
fig = plt.figure()
ax1.xaxis.set_major_locator(MultipleLocator(5))
xticks = ax1.xaxis.get_major_ticks()
#xticks[0].label1.set_visible(False)
#xticks[-1].label1.set_visible(False)
ax1.set_xticks(ax1.get_xticks()[1:-1])
ax1.plot(list(range(11)))
plt.show()

···

On Sat, Feb 14, 2015 at 2:01 AM, Eric Firing <efiring@...202...> wrote:

On 2015/02/13 3:29 PM, Tommy Carstensen wrote:

Is it possible to combine MultipleLocator and MaxNLocator? One seems
to erase the effect of the other.

They are for different situations. MultipleLocator is for when you know
what you want your tick interval to be; MaxNLocator is for when you
don't know that, but you do know roughly how many ticks you want, and
what sort of numerical intervals are acceptable.

Eric

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Thanks for you answer Eric. I had to get some sleep before trying out
things. I currently have the code below, but it does not remove the
zero value tick. It removes the tick at 5 and 10 however.

What is the effect you are trying to achieve? How would you describe the desired tick placement algorithm?

Eric

···

On 2015/02/14 5:47 AM, Tommy Carstensen wrote:

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
fig = plt.figure()
ax1.xaxis.set_major_locator(MultipleLocator(5))
xticks = ax1.xaxis.get_major_ticks()
#xticks[0].label1.set_visible(False)
#xticks[-1].label1.set_visible(False)
ax1.set_xticks(ax1.get_xticks()[1:-1])
ax1.plot(list(range(11)))
plt.show()

On Sat, Feb 14, 2015 at 2:01 AM, Eric Firing <efiring@...202...> wrote:

On 2015/02/13 3:29 PM, Tommy Carstensen wrote:

Is it possible to combine MultipleLocator and MaxNLocator? One seems
to erase the effect of the other.

They are for different situations. MultipleLocator is for when you know
what you want your tick interval to be; MaxNLocator is for when you
don't know that, but you do know roughly how many ticks you want, and
what sort of numerical intervals are acceptable.

Eric

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Tommy, (Sorry for the doubleup. I just realized I forgot to hit reply-all.)

Do you want to remove the tick at 0 and only have 5,10, etc.? Could you just do something like this instead:

import matplotlib.pyplot as plt

from matplotlib.ticker import MultipleLocator

fig = plt.figure()

ax1.set_xticks(range(5,11,5))

ax1.plot(range(11))

plt.show()

Ryan

···

On Sat, Feb 14, 2015 at 10:47 AM, Tommy Carstensen <tommy.carstensen@…287…> wrote:

Thanks for you answer Eric. I had to get some sleep before trying out

things. I currently have the code below, but it does not remove the

zero value tick. It removes the tick at 5 and 10 however.

import matplotlib.pyplot as plt

from matplotlib.ticker import MultipleLocator

fig = plt.figure()

ax1.xaxis.set_major_locator(MultipleLocator(5))

xticks = ax1.xaxis.get_major_ticks()

#xticks[0].label1.set_visible(False)

#xticks[-1].label1.set_visible(False)

ax1.set_xticks(ax1.get_xticks()[1:-1])

ax1.plot(list(range(11)))

plt.show()

On Sat, Feb 14, 2015 at 2:01 AM, Eric Firing <efiring@…202…> wrote:

On 2015/02/13 3:29 PM, Tommy Carstensen wrote:

Is it possible to combine MultipleLocator and MaxNLocator? One seems

to erase the effect of the other.

They are for different situations. MultipleLocator is for when you know

what you want your tick interval to be; MaxNLocator is for when you

don’t know that, but you do know roughly how many ticks you want, and

what sort of numerical intervals are acceptable.

Eric

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Thanks again Ryan. That's exactly what I want to achieve; i.e. remove
the tick at 0 and only keep 5 and 10. Your solution works, but it's a
bit of hack to use magic constants. I could however get those values
from the xlim.

Eric, I would describe the desired tick placement algorithm as
removing the first tick on the axis. It can be achieved like this:
ax1.xaxis.set_major_locator(MaxNLocator(prune='lower'))

But that then overrides this:
ax1.xaxis.set_major_locator(MultipleLocator(5))

···

On Sat, Feb 14, 2015 at 5:27 PM, Ryan Nelson <rnelsonchem@...287...> wrote:

Tommy, (Sorry for the doubleup. I just realized I forgot to hit reply-all.)

Do you want to remove the tick at 0 and only have 5,10, etc.? Could you just

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
fig = plt.figure()
ax1.set_xticks(range(5,11,5))
ax1.plot(range(11))
plt.show()

Ryan

On Sat, Feb 14, 2015 at 10:47 AM, Tommy Carstensen > <tommy.carstensen@...287...> wrote:

Thanks for you answer Eric. I had to get some sleep before trying out
things. I currently have the code below, but it does not remove the
zero value tick. It removes the tick at 5 and 10 however.

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
fig = plt.figure()
ax1.xaxis.set_major_locator(MultipleLocator(5))
xticks = ax1.xaxis.get_major_ticks()
#xticks[0].label1.set_visible(False)
#xticks[-1].label1.set_visible(False)
ax1.set_xticks(ax1.get_xticks()[1:-1])
ax1.plot(list(range(11)))
plt.show()

On Sat, Feb 14, 2015 at 2:01 AM, Eric Firing <efiring@...202...> wrote:
> On 2015/02/13 3:29 PM, Tommy Carstensen wrote:
>> Is it possible to combine MultipleLocator and MaxNLocator? One seems
>> to erase the effect of the other.
>
> They are for different situations. MultipleLocator is for when you know
> what you want your tick interval to be; MaxNLocator is for when you
> don't know that, but you do know roughly how many ticks you want, and
> what sort of numerical intervals are acceptable.
>
> Eric
>
>
>
> ------------------------------------------------------------------------------
> Dive into the World of Parallel Programming. The Go Parallel Website,
> sponsored by Intel and developed in partnership with Slashdot Media, is
> your
> hub for all things parallel software development, from weekly thought
> leadership blogs to news, videos, case studies, tutorials and more. Take
> a
> look and join the conversation now. http://goparallel.sourceforge.net/
> _______________________________________________
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> Matplotlib-users@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

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Thanks again Ryan. That's exactly what I want to achieve; i.e. remove
the tick at 0 and only keep 5 and 10. Your solution works, but it's a
bit of hack to use magic constants. I could however get those values
from the xlim.

Eric, I would describe the desired tick placement algorithm as
removing the first tick on the axis. It can be achieved like this:
ax1.xaxis.set_major_locator(MaxNLocator(prune='lower'))

Aha! The problem is that the MaxNLocator is the only one with the prune kwarg. It could be added to the MultipleLocator. For now, though, you can make your own specialized Locator, hardwired to omit the first tick, like this:

from matplotlib.ticker import MultipleLocator

class TrimmedMultipleLocator(MultipleLocator):
def tick_values(self, vmin, vmax):
return MultipleLocator.tick_values(self, vmin, vmax)[1:]

then just use

ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))

I haven't tested it--but give it a try. What it is doing is making a subclass of MultipleLocator, and altering only the one little bit of its behavior that you want to modify. Everything else is automatically inherited from the base class, MultipleLocator.

Eric

···

On 2015/02/14 7:33 AM, Tommy Carstensen wrote:

But that then overrides this:
ax1.xaxis.set_major_locator(MultipleLocator(5))

On Sat, Feb 14, 2015 at 5:27 PM, Ryan Nelson <rnelsonchem@...287...> wrote:

Tommy, (Sorry for the doubleup. I just realized I forgot to hit reply-all.)

Do you want to remove the tick at 0 and only have 5,10, etc.? Could you just

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
fig = plt.figure()
ax1.set_xticks(range(5,11,5))
ax1.plot(range(11))
plt.show()

Ryan

On Sat, Feb 14, 2015 at 10:47 AM, Tommy Carstensen >> <tommy.carstensen@...287...> wrote:

Thanks for you answer Eric. I had to get some sleep before trying out
things. I currently have the code below, but it does not remove the
zero value tick. It removes the tick at 5 and 10 however.

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
fig = plt.figure()
ax1.xaxis.set_major_locator(MultipleLocator(5))
xticks = ax1.xaxis.get_major_ticks()
#xticks[0].label1.set_visible(False)
#xticks[-1].label1.set_visible(False)
ax1.set_xticks(ax1.get_xticks()[1:-1])
ax1.plot(list(range(11)))
plt.show()

On Sat, Feb 14, 2015 at 2:01 AM, Eric Firing <efiring@...202...> wrote:

On 2015/02/13 3:29 PM, Tommy Carstensen wrote:

Is it possible to combine MultipleLocator and MaxNLocator? One seems
to erase the effect of the other.

They are for different situations. MultipleLocator is for when you know
what you want your tick interval to be; MaxNLocator is for when you
don't know that, but you do know roughly how many ticks you want, and
what sort of numerical intervals are acceptable.

Eric

------------------------------------------------------------------------------
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a
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Erik, that doesn't seem to work either. I tried this:

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
class TrimmedMultipleLocator(MultipleLocator):
def tick_values(self, vmin, vmax):
return MultipleLocator.tick_values(self, vmin, vmax)[2:]
fig = plt.figure()
ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))
#xticks[0].label1.set_visible(False)
#xticks[-1].label1.set_visible(False)
#ax1.set_xticks(ax1.xaxis.get_major_ticks()[1:-1])
ax1.plot(list(range(21)))
plt.show()

Here is an example of the use of prune='lower', but it does not allow
one to set the tick step size:
http://stackoverflow.com/questions/9422587/overlapping-y-axis-tick-label-and-x-axis-tick-label-in-matplotlib

I think my best bet is to just set those ticks manually.

···

On Sat, Feb 14, 2015 at 6:19 PM, Eric Firing <efiring@...202...> wrote:

On 2015/02/14 7:33 AM, Tommy Carstensen wrote:

Thanks again Ryan. That's exactly what I want to achieve; i.e. remove
the tick at 0 and only keep 5 and 10. Your solution works, but it's a
bit of hack to use magic constants. I could however get those values
from the xlim.

Eric, I would describe the desired tick placement algorithm as
removing the first tick on the axis. It can be achieved like this:
ax1.xaxis.set_major_locator(MaxNLocator(prune='lower'))

Aha! The problem is that the MaxNLocator is the only one with the prune
kwarg. It could be added to the MultipleLocator. For now, though, you
can make your own specialized Locator, hardwired to omit the first tick,
like this:

from matplotlib.ticker import MultipleLocator

class TrimmedMultipleLocator(MultipleLocator):
def tick_values(self, vmin, vmax):
return MultipleLocator.tick_values(self, vmin, vmax)[1:]

then just use

ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))

I haven't tested it--but give it a try. What it is doing is making a
subclass of MultipleLocator, and altering only the one little bit of its
behavior that you want to modify. Everything else is automatically
inherited from the base class, MultipleLocator.

Eric

But that then overrides this:
ax1.xaxis.set_major_locator(MultipleLocator(5))

On Sat, Feb 14, 2015 at 5:27 PM, Ryan Nelson <rnelsonchem@...287...> wrote:

Tommy, (Sorry for the doubleup. I just realized I forgot to hit reply-all.)

Do you want to remove the tick at 0 and only have 5,10, etc.? Could you just

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
fig = plt.figure()
ax1.set_xticks(range(5,11,5))
ax1.plot(range(11))
plt.show()

Ryan

On Sat, Feb 14, 2015 at 10:47 AM, Tommy Carstensen >>> <tommy.carstensen@...287...> wrote:

Thanks for you answer Eric. I had to get some sleep before trying out
things. I currently have the code below, but it does not remove the
zero value tick. It removes the tick at 5 and 10 however.

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
fig = plt.figure()
ax1.xaxis.set_major_locator(MultipleLocator(5))
xticks = ax1.xaxis.get_major_ticks()
#xticks[0].label1.set_visible(False)
#xticks[-1].label1.set_visible(False)
ax1.set_xticks(ax1.get_xticks()[1:-1])
ax1.plot(list(range(11)))
plt.show()

On Sat, Feb 14, 2015 at 2:01 AM, Eric Firing <efiring@...202...> wrote:

On 2015/02/13 3:29 PM, Tommy Carstensen wrote:

Is it possible to combine MultipleLocator and MaxNLocator? One seems
to erase the effect of the other.

They are for different situations. MultipleLocator is for when you know
what you want your tick interval to be; MaxNLocator is for when you
don't know that, but you do know roughly how many ticks you want, and
what sort of numerical intervals are acceptable.

Eric

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hub for all things parallel software development, from weekly thought
leadership blogs to news, videos, case studies, tutorials and more. Take
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look and join the conversation now. http://goparallel.sourceforge.net/
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Tommy,

I’m sorry. I forgot to hit send all again. Below is my original message, but the function I wrote is updated because it wasn’t exactly correct…

Ah. I was working on something to help out, so I’m just seeing Eric’s very elegant solution, which I have yet to try. However, I feel like you might run into some problems if you always drop the first tick. For example, try this plot:

···

On Sat, Feb 14, 2015 at 1:45 PM, Tommy Carstensen <tommy.carstensen@…120…287…> wrote:

Erik, that doesn’t seem to work either. I tried this:

import matplotlib.pyplot as plt

from matplotlib.ticker import MultipleLocator

class TrimmedMultipleLocator(MultipleLocator):

`````` def tick_values(self, vmin, vmax):

return MultipleLocator.tick_values(self, vmin, vmax)[2:]
``````

fig = plt.figure()

ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))

#xticks[0].label1.set_visible(False)

#xticks[-1].label1.set_visible(False)

#ax1.set_xticks(ax1.xaxis.get_major_ticks()[1:-1])

ax1.plot(list(range(21)))

plt.show()

Here is an example of the use of prune=‘lower’, but it does not allow

one to set the tick step size:

http://stackoverflow.com/questions/9422587/overlapping-y-axis-tick-label-and-x-axis-tick-label-in-matplotlib

I think my best bet is to just set those ticks manually.

On Sat, Feb 14, 2015 at 6:19 PM, Eric Firing <efiring@…202…> wrote:

On 2015/02/14 7:33 AM, Tommy Carstensen wrote:

Thanks again Ryan. That’s exactly what I want to achieve; i.e. remove

the tick at 0 and only keep 5 and 10. Your solution works, but it’s a

bit of hack to use magic constants. I could however get those values

from the xlim.

Eric, I would describe the desired tick placement algorithm as

removing the first tick on the axis. It can be achieved like this:

ax1.xaxis.set_major_locator(MaxNLocator(prune=‘lower’))

Aha! The problem is that the MaxNLocator is the only one with the prune

kwarg. It could be added to the MultipleLocator. For now, though, you

can make your own specialized Locator, hardwired to omit the first tick,

like this:

from matplotlib.ticker import MultipleLocator

class TrimmedMultipleLocator(MultipleLocator):

`````` def tick_values(self, vmin, vmax):
``````
``````     return MultipleLocator.tick_values(self, vmin, vmax)[1:]
``````

then just use

ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))

I haven’t tested it–but give it a try. What it is doing is making a

subclass of MultipleLocator, and altering only the one little bit of its

behavior that you want to modify. Everything else is automatically

inherited from the base class, MultipleLocator.

Eric

But that then overrides this:

ax1.xaxis.set_major_locator(MultipleLocator(5))

On Sat, Feb 14, 2015 at 5:27 PM, Ryan Nelson <rnelsonchem@…287…> wrote:

Tommy, (Sorry for the doubleup. I just realized I forgot to hit reply-all.)

Do you want to remove the tick at 0 and only have 5,10, etc.? Could you just

import matplotlib.pyplot as plt

from matplotlib.ticker import MultipleLocator

fig = plt.figure()

ax1.set_xticks(range(5,11,5))

ax1.plot(range(11))

plt.show()

Ryan

On Sat, Feb 14, 2015 at 10:47 AM, Tommy Carstensen

<tommy.carstensen@…287…> wrote:

Thanks for you answer Eric. I had to get some sleep before trying out

things. I currently have the code below, but it does not remove the

zero value tick. It removes the tick at 5 and 10 however.

import matplotlib.pyplot as plt

from matplotlib.ticker import MultipleLocator

fig = plt.figure()

ax1.xaxis.set_major_locator(MultipleLocator(5))

xticks = ax1.xaxis.get_major_ticks()

#xticks[0].label1.set_visible(False)

#xticks[-1].label1.set_visible(False)

ax1.set_xticks(ax1.get_xticks()[1:-1])

ax1.plot(list(range(11)))

plt.show()

On Sat, Feb 14, 2015 at 2:01 AM, Eric Firing <efiring@…202…> wrote:

On 2015/02/13 3:29 PM, Tommy Carstensen wrote:

Is it possible to combine MultipleLocator and MaxNLocator? One seems

to erase the effect of the other.

They are for different situations. MultipleLocator is for when you know

what you want your tick interval to be; MaxNLocator is for when you

don’t know that, but you do know roughly how many ticks you want, and

what sort of numerical intervals are acceptable.

Eric

Dive into the World of Parallel Programming. The Go Parallel Website,

sponsored by Intel and developed in partnership with Slashdot Media, is

your

hub for all things parallel software development, from weekly thought

leadership blogs to news, videos, case studies, tutorials and more. Take

a

look and join the conversation now. http://goparallel.sourceforge.net/

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Are you sure? I tried it, and it works for me. See attached script and output.

Eric

test_loc.pdf (4.59 KB)

test_loc.py (369 Bytes)

···

On 2015/02/14 8:45 AM, Tommy Carstensen wrote:

Erik, that doesn't seem to work either. I tried this:

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
class TrimmedMultipleLocator(MultipleLocator):
def tick_values(self, vmin, vmax):
return MultipleLocator.tick_values(self, vmin, vmax)[2:]
fig = plt.figure()
ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))
#xticks[0].label1.set_visible(False)
#xticks[-1].label1.set_visible(False)
#ax1.set_xticks(ax1.xaxis.get_major_ticks()[1:-1])
ax1.plot(list(range(21)))
plt.show()

Eric, it works if I do:
return MultipleLocator.tick_values(self, vmin, vmax)[2:]

But not if I do as first suggested by you:
return MultipleLocator.tick_values(self, vmin, vmax)[1:]

I don't understand this behaviour. It should be [1:]. I'll just set
the ticks manually. Seems to be the easiest thing. It would be
awesome, if MPL had the same behaviour as gnuplot, which allows me to
simply do:
set xtics <start>, <incr>

···

On Sat, Feb 14, 2015 at 7:09 PM, Eric Firing <efiring@...202...> wrote:

On 2015/02/14 8:45 AM, Tommy Carstensen wrote:

Erik, that doesn't seem to work either. I tried this:

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
class TrimmedMultipleLocator(MultipleLocator):
def tick_values(self, vmin, vmax):
return MultipleLocator.tick_values(self, vmin, vmax)[2:]
fig = plt.figure()
ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))
#xticks[0].label1.set_visible(False)
#xticks[-1].label1.set_visible(False)
#ax1.set_xticks(ax1.xaxis.get_major_ticks()[1:-1])
ax1.plot(list(range(21)))
plt.show()

Are you sure? I tried it, and it works for me. See attached script and
output.

Eric

Ryan, my use case is indeed that I want to avoid overlapping ticks and
I want to avoid them by not displaying them. Here is a guy with the
same problem:
http://stackoverflow.com/questions/9422587/overlapping-y-axis-tick-label-and-x-axis-tick-label-in-matplotlib

Here is the problem at the top left of my plot:
www.tommycarstensen.com/matplotlib.png

I'll just set the ticks manually. Sadly seems like the easiest thing to do.

···

On Sat, Feb 14, 2015 at 7:01 PM, Ryan Nelson <rnelsonchem@...287...> wrote:

Tommy,

I'm sorry. I forgot to hit send all *again*. Below is my original message,
but the function I wrote is updated because it wasn't exactly correct....

Ah. I was working on something to help out, so I'm just seeing Eric's very
elegant solution, which I have yet to try. However, I feel like you might
run into some problems if you always drop the first tick. For example, try
this plot:
______________
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
import numpy as np
xs = np.linspace(2,12,1000)
ys = np.sin(xs)
n = 5
fig = plt.figure()
ax1.plot(xs, ys)
ax1.xaxis.set_major_locator(MultipleLocator(5))
plt.show()
_____________
In this case, dropping the first tick will result in only one tick on the
screen.

What is your use-case? Are you annoyed that the axis labels are overlapping
at the far left? If that's the case, here's a little function (trimticks)
that I whipped up that might help. It drops the far left or far right label
if it is exactly at the edge of the axes. Should work for y axes as well.
_____________
def trimticks(ax, n=5):
xmin, xmax = ax.get_xlim()
if xmin%n == 0:
xmin = xmin+n
else:
xmin = xmin + n - xmin%n

if not xmax%n == 0:
xmax = xmax + n - xmax%n

ticks = np.arange(xmin, xmax, n)
ax.set_xticks(ticks)

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
import numpy as np
xs = np.linspace(0,20,10000)
ys = np.sin(xs)
fig = plt.figure()
ax1.plot(xs, ys)
trimticks(ax1)
plt.show()

___________________

On Sat, Feb 14, 2015 at 1:45 PM, Tommy Carstensen > <tommy.carstensen@...287...> wrote:

Erik, that doesn't seem to work either. I tried this:

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
class TrimmedMultipleLocator(MultipleLocator):
def tick_values(self, vmin, vmax):
return MultipleLocator.tick_values(self, vmin, vmax)[2:]
fig = plt.figure()
ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))
#xticks[0].label1.set_visible(False)
#xticks[-1].label1.set_visible(False)
#ax1.set_xticks(ax1.xaxis.get_major_ticks()[1:-1])
ax1.plot(list(range(21)))
plt.show()

Here is an example of the use of prune='lower', but it does not allow
one to set the tick step size:

http://stackoverflow.com/questions/9422587/overlapping-y-axis-tick-label-and-x-axis-tick-label-in-matplotlib

I think my best bet is to just set those ticks manually.

On Sat, Feb 14, 2015 at 6:19 PM, Eric Firing <efiring@...202...> wrote:
> On 2015/02/14 7:33 AM, Tommy Carstensen wrote:
>> Thanks again Ryan. That's exactly what I want to achieve; i.e. remove
>> the tick at 0 and only keep 5 and 10. Your solution works, but it's a
>> bit of hack to use magic constants. I could however get those values
>> from the xlim.
>>
>> Eric, I would describe the desired tick placement algorithm as
>> removing the first tick on the axis. It can be achieved like this:
>> ax1.xaxis.set_major_locator(MaxNLocator(prune='lower'))
>
> Aha! The problem is that the MaxNLocator is the only one with the prune
> kwarg. It could be added to the MultipleLocator. For now, though, you
> can make your own specialized Locator, hardwired to omit the first tick,
> like this:
>
> from matplotlib.ticker import MultipleLocator
>
> class TrimmedMultipleLocator(MultipleLocator):
> def tick_values(self, vmin, vmax):
> return MultipleLocator.tick_values(self, vmin, vmax)[1:]
>
> then just use
>
> ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))
>
> I haven't tested it--but give it a try. What it is doing is making a
> subclass of MultipleLocator, and altering only the one little bit of its
> behavior that you want to modify. Everything else is automatically
> inherited from the base class, MultipleLocator.
>
> Eric
>
>
>>
>> But that then overrides this:
>> ax1.xaxis.set_major_locator(MultipleLocator(5))
>>
>> On Sat, Feb 14, 2015 at 5:27 PM, Ryan Nelson <rnelsonchem@...287...> >> >> wrote:
>>> Tommy, (Sorry for the doubleup. I just realized I forgot to hit
>>>
>>> Do you want to remove the tick at 0 and only have 5,10, etc.? Could
>>> you just
>>> do something like this instead:
>>>
>>> import matplotlib.pyplot as plt
>>> from matplotlib.ticker import MultipleLocator
>>> fig = plt.figure()
>>> ax1.set_xticks(range(5,11,5))
>>> ax1.plot(range(11))
>>> plt.show()
>>>
>>> Ryan
>>>
>>>
>>> On Sat, Feb 14, 2015 at 10:47 AM, Tommy Carstensen >> >>> <tommy.carstensen@...287...> wrote:
>>>>
>>>> Thanks for you answer Eric. I had to get some sleep before trying out
>>>> things. I currently have the code below, but it does not remove the
>>>> zero value tick. It removes the tick at 5 and 10 however.
>>>>
>>>> import matplotlib.pyplot as plt
>>>> from matplotlib.ticker import MultipleLocator
>>>> fig = plt.figure()
>>>> ax1.xaxis.set_major_locator(MultipleLocator(5))
>>>> xticks = ax1.xaxis.get_major_ticks()
>>>> #xticks[0].label1.set_visible(False)
>>>> #xticks[-1].label1.set_visible(False)
>>>> ax1.set_xticks(ax1.get_xticks()[1:-1])
>>>> ax1.plot(list(range(11)))
>>>> plt.show()
>>>>
>>>> On Sat, Feb 14, 2015 at 2:01 AM, Eric Firing <efiring@...202...> >> >>>> wrote:
>>>>> On 2015/02/13 3:29 PM, Tommy Carstensen wrote:
>>>>>> Is it possible to combine MultipleLocator and MaxNLocator? One
>>>>>> seems
>>>>>> to erase the effect of the other.
>>>>>
>>>>> They are for different situations. MultipleLocator is for when you
>>>>> know
>>>>> what you want your tick interval to be; MaxNLocator is for when you
>>>>> don't know that, but you do know roughly how many ticks you want,
>>>>> and
>>>>> what sort of numerical intervals are acceptable.
>>>>>
>>>>> Eric
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> ------------------------------------------------------------------------------
>>>>> Dive into the World of Parallel Programming. The Go Parallel
>>>>> Website,
>>>>> sponsored by Intel and developed in partnership with Slashdot Media,
>>>>> is
>>>>> your
>>>>> hub for all things parallel software development, from weekly
>>>>> thought
>>>>> leadership blogs to news, videos, case studies, tutorials and more.
>>>>> Take
>>>>> a
>>>>> look and join the conversation now.
>>>>> http://goparallel.sourceforge.net/
>>>>> _______________________________________________
>>>>> Matplotlib-users mailing list
>>>>> Matplotlib-users@lists.sourceforge.net
>>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>> Dive into the World of Parallel Programming. The Go Parallel Website,
>>>> sponsored by Intel and developed in partnership with Slashdot Media,
>>>> is
>>>> your
>>>> hub for all things parallel software development, from weekly thought
>>>> leadership blogs to news, videos, case studies, tutorials and more.
>>>> Take a
>>>> look and join the conversation now.
>>>> http://goparallel.sourceforge.net/
>>>> _______________________________________________
>>>> Matplotlib-users mailing list
>>>> Matplotlib-users@lists.sourceforge.net
>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>>
>>
>>
>> ------------------------------------------------------------------------------
>> Dive into the World of Parallel Programming. The Go Parallel Website,
>> sponsored by Intel and developed in partnership with Slashdot Media, is
>> your
>> hub for all things parallel software development, from weekly thought
>> leadership blogs to news, videos, case studies, tutorials and more.
>> Take a
>> look and join the conversation now. http://goparallel.sourceforge.net/
>> _______________________________________________
>> Matplotlib-users mailing list
>> Matplotlib-users@lists.sourceforge.net
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
>
>
> ------------------------------------------------------------------------------
> Dive into the World of Parallel Programming. The Go Parallel Website,
> sponsored by Intel and developed in partnership with Slashdot Media, is
> your
> hub for all things parallel software development, from weekly thought
> leadership blogs to news, videos, case studies, tutorials and more. Take
> a
> look and join the conversation now. http://goparallel.sourceforge.net/
> _______________________________________________
> Matplotlib-users mailing list
> Matplotlib-users@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

------------------------------------------------------------------------------
Dive into the World of Parallel Programming. The Go Parallel Website,
sponsored by Intel and developed in partnership with Slashdot Media, is
your
hub for all things parallel software development, from weekly thought
leadership blogs to news, videos, case studies, tutorials and more. Take a
look and join the conversation now. http://goparallel.sourceforge.net/
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users

------------------------------------------------------------------------------
Dive into the World of Parallel Programming. The Go Parallel Website,
sponsored by Intel and developed in partnership with Slashdot Media, is your
hub for all things parallel software development, from weekly thought
leadership blogs to news, videos, case studies, tutorials and more. Take a
look and join the conversation now. http://goparallel.sourceforge.net/
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Eric, it works if I do:
return MultipleLocator.tick_values(self, vmin, vmax)[2:]

But not if I do as first suggested by you:
return MultipleLocator.tick_values(self, vmin, vmax)[1:]

Are you using my test script but getting a different result? If not, what is the difference in your test script?

I don't understand this behaviour. It should be [1:]. I'll just set
the ticks manually. Seems to be the easiest thing. It would be
awesome, if MPL had the same behaviour as gnuplot, which allows me to
simply do:
set xtics <start>, <incr>

def xtics(ax, start, incr):
stop = ax.dataLim.x1 + 0.01 * incr
ax.xaxis.set_ticks(np.arange(start, stop, incr))

Now invoke that function *after* all your plot calls, so that the dataLim bounding box includes all the data in your plot.

Eric

···

On 2015/02/14 9:15 AM, Tommy Carstensen wrote:

Thanks Eric. I decided to get peace of mind and just set the tick
labels manually. I can't afford to spend several hours on all of my
plots. I appreciate your help a lot.

···

On Sat, Feb 14, 2015 at 7:37 PM, Eric Firing <efiring@...202...> wrote:

On 2015/02/14 9:15 AM, Tommy Carstensen wrote:

Eric, it works if I do:
return MultipleLocator.tick_values(self, vmin, vmax)[2:]

But not if I do as first suggested by you:
return MultipleLocator.tick_values(self, vmin, vmax)[1:]

Are you using my test script but getting a different result? If not, what
is the difference in your test script?

I don't understand this behaviour. It should be [1:]. I'll just set
the ticks manually. Seems to be the easiest thing. It would be
awesome, if MPL had the same behaviour as gnuplot, which allows me to
simply do:
set xtics <start>, <incr>

def xtics(ax, start, incr):
stop = ax.dataLim.x1 + 0.01 * incr
ax.xaxis.set_ticks(np.arange(start, stop, incr))

Now invoke that function *after* all your plot calls, so that the dataLim
bounding box includes all the data in your plot.

Eric

Yep. I see your problem. My function and Eric’s object should help here.

A sore-spot with many folks coming over to Matplotlib from “X” is the fact that MPL does not calculate the size of text until the plot is generated. That means it doesn’t always get text positioning, etc. exactly correct. That takes a little getting used to, and for me, it is minor.

Admit it, Gnuplot as it’s quirks as well I always hated that it wouldn’t cut off some markers at the edge of the screen. For example, with Gnuplot 4.6rev5 the following

plot x with points ps 7

Leads to a bunch of markers running over the axes limits. (Maybe there is a way to fix this now. Many years ago that was not the case.)

Ryan

···

On Sat, Feb 14, 2015 at 2:18 PM, Tommy Carstensen <tommy.carstensen@…287…> wrote:

Ryan, my use case is indeed that I want to avoid overlapping ticks and

I want to avoid them by not displaying them. Here is a guy with the

same problem:

http://stackoverflow.com/questions/9422587/overlapping-y-axis-tick-label-and-x-axis-tick-label-in-matplotlib

Here is the problem at the top left of my plot:

www.tommycarstensen.com/matplotlib.png

I’ll just set the ticks manually. Sadly seems like the easiest thing to do.

On Sat, Feb 14, 2015 at 7:01 PM, Ryan Nelson <rnelsonchem@…287…> wrote:

Tommy,

I’m sorry. I forgot to hit send all again. Below is my original message,

but the function I wrote is updated because it wasn’t exactly correct…

Ah. I was working on something to help out, so I’m just seeing Eric’s very

elegant solution, which I have yet to try. However, I feel like you might

run into some problems if you always drop the first tick. For example, try

this plot:

import matplotlib.pyplot as plt

from matplotlib.ticker import MultipleLocator

import numpy as np

xs = np.linspace(2,12,1000)

ys = np.sin(xs)

n = 5

fig = plt.figure()

ax1.plot(xs, ys)

ax1.xaxis.set_major_locator(MultipleLocator(5))

plt.show()

In this case, dropping the first tick will result in only one tick on the

screen.

What is your use-case? Are you annoyed that the axis labels are overlapping

at the far left? If that’s the case, here’s a little function (trimticks)

that I whipped up that might help. It drops the far left or far right label

if it is exactly at the edge of the axes. Should work for y axes as well.

def trimticks(ax, n=5):

``````xmin, xmax = ax.get_xlim()
``````
``````if xmin%n == 0:
``````
``````    xmin = xmin+n
``````
``````else:
``````
``````    xmin = xmin + n - xmin%n
``````
``````if not xmax%n == 0:
``````
``````    xmax = xmax + n - xmax%n
``````
``````ticks = np.arange(xmin, xmax, n)
``````
``````ax.set_xticks(ticks)
``````

import matplotlib.pyplot as plt

from matplotlib.ticker import MultipleLocator

import numpy as np

xs = np.linspace(0,20,10000)

ys = np.sin(xs)

fig = plt.figure()

ax1.plot(xs, ys)

trimticks(ax1)

plt.show()

On Sat, Feb 14, 2015 at 1:45 PM, Tommy Carstensen

<tommy.carstensen@…83…287…> wrote:

Erik, that doesn’t seem to work either. I tried this:

import matplotlib.pyplot as plt

from matplotlib.ticker import MultipleLocator

class TrimmedMultipleLocator(MultipleLocator):

`````` def tick_values(self, vmin, vmax):
``````
``````     return MultipleLocator.tick_values(self, vmin, vmax)[2:]
``````

fig = plt.figure()

ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))

#xticks[0].label1.set_visible(False)

#xticks[-1].label1.set_visible(False)

#ax1.set_xticks(ax1.xaxis.get_major_ticks()[1:-1])

ax1.plot(list(range(21)))

plt.show()

Here is an example of the use of prune=‘lower’, but it does not allow

one to set the tick step size:

http://stackoverflow.com/questions/9422587/overlapping-y-axis-tick-label-and-x-axis-tick-label-in-matplotlib

I think my best bet is to just set those ticks manually.

On Sat, Feb 14, 2015 at 6:19 PM, Eric Firing <efiring@…202…> wrote:

On 2015/02/14 7:33 AM, Tommy Carstensen wrote:

Thanks again Ryan. That’s exactly what I want to achieve; i.e. remove

the tick at 0 and only keep 5 and 10. Your solution works, but it’s a

bit of hack to use magic constants. I could however get those values

from the xlim.

Eric, I would describe the desired tick placement algorithm as

removing the first tick on the axis. It can be achieved like this:

ax1.xaxis.set_major_locator(MaxNLocator(prune=‘lower’))

Aha! The problem is that the MaxNLocator is the only one with the prune

kwarg. It could be added to the MultipleLocator. For now, though, you

can make your own specialized Locator, hardwired to omit the first tick,

like this:

from matplotlib.ticker import MultipleLocator

class TrimmedMultipleLocator(MultipleLocator):

`````` def tick_values(self, vmin, vmax):
``````
``````     return MultipleLocator.tick_values(self, vmin, vmax)[1:]
``````

then just use

ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))

I haven’t tested it–but give it a try. What it is doing is making a

subclass of MultipleLocator, and altering only the one little bit of its

behavior that you want to modify. Everything else is automatically

inherited from the base class, MultipleLocator.

Eric

But that then overrides this:

ax1.xaxis.set_major_locator(MultipleLocator(5))

On Sat, Feb 14, 2015 at 5:27 PM, Ryan Nelson <rnelsonchem@…287…>

wrote:

Tommy, (Sorry for the doubleup. I just realized I forgot to hit

Do you want to remove the tick at 0 and only have 5,10, etc.? Could

you just

import matplotlib.pyplot as plt

from matplotlib.ticker import MultipleLocator

fig = plt.figure()

ax1.set_xticks(range(5,11,5))

ax1.plot(range(11))

plt.show()

Ryan

On Sat, Feb 14, 2015 at 10:47 AM, Tommy Carstensen

<tommy.carstensen@…287…> wrote:

Thanks for you answer Eric. I had to get some sleep before trying out

things. I currently have the code below, but it does not remove the

zero value tick. It removes the tick at 5 and 10 however.

import matplotlib.pyplot as plt

from matplotlib.ticker import MultipleLocator

fig = plt.figure()

ax1.xaxis.set_major_locator(MultipleLocator(5))

xticks = ax1.xaxis.get_major_ticks()

#xticks[0].label1.set_visible(False)

#xticks[-1].label1.set_visible(False)

ax1.set_xticks(ax1.get_xticks()[1:-1])

ax1.plot(list(range(11)))

plt.show()

On Sat, Feb 14, 2015 at 2:01 AM, Eric Firing <efiring@…202…>

wrote:

On 2015/02/13 3:29 PM, Tommy Carstensen wrote:

Is it possible to combine MultipleLocator and MaxNLocator? One

seems

to erase the effect of the other.

They are for different situations. MultipleLocator is for when you

know

what you want your tick interval to be; MaxNLocator is for when you

don’t know that, but you do know roughly how many ticks you want,

and

what sort of numerical intervals are acceptable.

Eric

Dive into the World of Parallel Programming. The Go Parallel

Website,

sponsored by Intel and developed in partnership with Slashdot Media,

is

your

hub for all things parallel software development, from weekly

thought

leadership blogs to news, videos, case studies, tutorials and more.

Take

a

look and join the conversation now.

http://goparallel.sourceforge.net/

Matplotlib-users mailing list

Matplotlib-users@lists.sourceforge.net

https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Dive into the World of Parallel Programming. The Go Parallel Website,

sponsored by Intel and developed in partnership with Slashdot Media,

is

your

hub for all things parallel software development, from weekly thought

leadership blogs to news, videos, case studies, tutorials and more.

Take a

look and join the conversation now.

http://goparallel.sourceforge.net/

Matplotlib-users mailing list

Matplotlib-users@lists.sourceforge.net

https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Dive into the World of Parallel Programming. The Go Parallel Website,

sponsored by Intel and developed in partnership with Slashdot Media, is

your

hub for all things parallel software development, from weekly thought

leadership blogs to news, videos, case studies, tutorials and more.

Take a

look and join the conversation now. http://goparallel.sourceforge.net/

Matplotlib-users mailing list

Matplotlib-users@lists.sourceforge.net

https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Dive into the World of Parallel Programming. The Go Parallel Website,

sponsored by Intel and developed in partnership with Slashdot Media, is

your

hub for all things parallel software development, from weekly thought

leadership blogs to news, videos, case studies, tutorials and more. Take

a

look and join the conversation now. http://goparallel.sourceforge.net/

Matplotlib-users mailing list

Matplotlib-users@lists.sourceforge.net

https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Dive into the World of Parallel Programming. The Go Parallel Website,

sponsored by Intel and developed in partnership with Slashdot Media, is

your

hub for all things parallel software development, from weekly thought

leadership blogs to news, videos, case studies, tutorials and more. Take a

look and join the conversation now. http://goparallel.sourceforge.net/

Matplotlib-users mailing list

Matplotlib-users@lists.sourceforge.net

https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Dive into the World of Parallel Programming. The Go Parallel Website,

sponsored by Intel and developed in partnership with Slashdot Media, is your

hub for all things parallel software development, from weekly thought

leadership blogs to news, videos, case studies, tutorials and more. Take a

look and join the conversation now. http://goparallel.sourceforge.net/

Matplotlib-users mailing list

Matplotlib-users@lists.sourceforge.net

https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Ryan, I stopped using gnuplot, because it requires the data to be
formatted in very specific ways I remember having functions just to
format the input data correctly for heat plots and the wrapper scripts
I wrote were quite convoluted. Matplotlib has its advantages for sure.
Otherwise I would not have switched. I'm just frustrated with being
back at the start line. Thanks for your help and bearing with my
impatience.

···

On Sat, Feb 14, 2015 at 7:42 PM, Ryan Nelson <rnelsonchem@...287...> wrote:

Yep. I see your problem. My function and Eric's object should help here.

A sore-spot with many folks coming over to Matplotlib from "X" is the fact
that MPL does not calculate the size of text until the plot is generated.
That means it doesn't always get text positioning, etc. exactly correct.
That takes a little getting used to, and for me, it is minor.

Admit it, Gnuplot as it's quirks as well I always hated that it wouldn't
cut off some markers at the edge of the screen. For example, with Gnuplot
4.6rev5 the following
plot x with points ps 7
Leads to a bunch of markers running over the axes limits. (Maybe there is a
way to fix this now. Many years ago that was not the case.)

Ryan

On Sat, Feb 14, 2015 at 2:18 PM, Tommy Carstensen > <tommy.carstensen@...287...> wrote:

Ryan, my use case is indeed that I want to avoid overlapping ticks and
I want to avoid them by not displaying them. Here is a guy with the
same problem:

http://stackoverflow.com/questions/9422587/overlapping-y-axis-tick-label-and-x-axis-tick-label-in-matplotlib

Here is the problem at the top left of my plot:
www.tommycarstensen.com/matplotlib.png

I'll just set the ticks manually. Sadly seems like the easiest thing to
do.

On Sat, Feb 14, 2015 at 7:01 PM, Ryan Nelson <rnelsonchem@...287...> >> wrote:
> Tommy,
>
> I'm sorry. I forgot to hit send all *again*. Below is my original
> message,
> but the function I wrote is updated because it wasn't exactly
> correct....
>
> Ah. I was working on something to help out, so I'm just seeing Eric's
> very
> elegant solution, which I have yet to try. However, I feel like you
> might
> run into some problems if you always drop the first tick. For example,
> try
> this plot:
> ______________
> import matplotlib.pyplot as plt
> from matplotlib.ticker import MultipleLocator
> import numpy as np
> xs = np.linspace(2,12,1000)
> ys = np.sin(xs)
> n = 5
> fig = plt.figure()
> ax1.plot(xs, ys)
> ax1.xaxis.set_major_locator(MultipleLocator(5))
> plt.show()
> _____________
> In this case, dropping the first tick will result in only one tick on
> the
> screen.
>
> What is your use-case? Are you annoyed that the axis labels are
> overlapping
> at the far left? If that's the case, here's a little function
> (trimticks)
> that I whipped up that might help. It drops the far left or far right
> label
> if it is exactly at the edge of the axes. Should work for y axes as
> well.
> _____________
> def trimticks(ax, n=5):
> xmin, xmax = ax.get_xlim()
> if xmin%n == 0:
> xmin = xmin+n
> else:
> xmin = xmin + n - xmin%n
>
> if not xmax%n == 0:
> xmax = xmax + n - xmax%n
>
> ticks = np.arange(xmin, xmax, n)
> ax.set_xticks(ticks)
>
> import matplotlib.pyplot as plt
> from matplotlib.ticker import MultipleLocator
> import numpy as np
> xs = np.linspace(0,20,10000)
> ys = np.sin(xs)
> fig = plt.figure()
> ax1.plot(xs, ys)
> trimticks(ax1)
> plt.show()
>
> ___________________
>
>
> On Sat, Feb 14, 2015 at 1:45 PM, Tommy Carstensen >> > <tommy.carstensen@...287...> wrote:
>>
>> Erik, that doesn't seem to work either. I tried this:
>>
>> import matplotlib.pyplot as plt
>> from matplotlib.ticker import MultipleLocator
>> class TrimmedMultipleLocator(MultipleLocator):
>> def tick_values(self, vmin, vmax):
>> return MultipleLocator.tick_values(self, vmin, vmax)[2:]
>> fig = plt.figure()
>> ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))
>> #xticks[0].label1.set_visible(False)
>> #xticks[-1].label1.set_visible(False)
>> #ax1.set_xticks(ax1.xaxis.get_major_ticks()[1:-1])
>> ax1.plot(list(range(21)))
>> plt.show()
>>
>> Here is an example of the use of prune='lower', but it does not allow
>> one to set the tick step size:
>>
>>
>> http://stackoverflow.com/questions/9422587/overlapping-y-axis-tick-label-and-x-axis-tick-label-in-matplotlib
>>
>> I think my best bet is to just set those ticks manually.
>>
>> On Sat, Feb 14, 2015 at 6:19 PM, Eric Firing <efiring@...202...> >> >> wrote:
>> > On 2015/02/14 7:33 AM, Tommy Carstensen wrote:
>> >> Thanks again Ryan. That's exactly what I want to achieve; i.e.
>> >> remove
>> >> the tick at 0 and only keep 5 and 10. Your solution works, but it's
>> >> a
>> >> bit of hack to use magic constants. I could however get those values
>> >> from the xlim.
>> >>
>> >> Eric, I would describe the desired tick placement algorithm as
>> >> removing the first tick on the axis. It can be achieved like this:
>> >> ax1.xaxis.set_major_locator(MaxNLocator(prune='lower'))
>> >
>> > Aha! The problem is that the MaxNLocator is the only one with the
>> > prune
>> > kwarg. It could be added to the MultipleLocator. For now, though,
>> > you
>> > can make your own specialized Locator, hardwired to omit the first
>> > tick,
>> > like this:
>> >
>> > from matplotlib.ticker import MultipleLocator
>> >
>> > class TrimmedMultipleLocator(MultipleLocator):
>> > def tick_values(self, vmin, vmax):
>> > return MultipleLocator.tick_values(self, vmin, vmax)[1:]
>> >
>> > then just use
>> >
>> > ax1.xaxis.set_major_locator(TrimmedMultipleLocator(5))
>> >
>> > I haven't tested it--but give it a try. What it is doing is making a
>> > subclass of MultipleLocator, and altering only the one little bit of
>> > its
>> > behavior that you want to modify. Everything else is automatically
>> > inherited from the base class, MultipleLocator.
>> >
>> > Eric
>> >
>> >
>> >>
>> >> But that then overrides this:
>> >> ax1.xaxis.set_major_locator(MultipleLocator(5))
>> >>
>> >> On Sat, Feb 14, 2015 at 5:27 PM, Ryan Nelson <rnelsonchem@...287...> >> >> >> wrote:
>> >>> Tommy, (Sorry for the doubleup. I just realized I forgot to hit
>> >>>
>> >>> Do you want to remove the tick at 0 and only have 5,10, etc.? Could
>> >>> you just
>> >>> do something like this instead:
>> >>>
>> >>> import matplotlib.pyplot as plt
>> >>> from matplotlib.ticker import MultipleLocator
>> >>> fig = plt.figure()
>> >>> ax1.set_xticks(range(5,11,5))
>> >>> ax1.plot(range(11))
>> >>> plt.show()
>> >>>
>> >>> Ryan
>> >>>
>> >>>
>> >>> On Sat, Feb 14, 2015 at 10:47 AM, Tommy Carstensen >> >> >>> <tommy.carstensen@...287...> wrote:
>> >>>>
>> >>>> Thanks for you answer Eric. I had to get some sleep before trying
>> >>>> out
>> >>>> things. I currently have the code below, but it does not remove
>> >>>> the
>> >>>> zero value tick. It removes the tick at 5 and 10 however.
>> >>>>
>> >>>> import matplotlib.pyplot as plt
>> >>>> from matplotlib.ticker import MultipleLocator
>> >>>> fig = plt.figure()
>> >>>> ax1.xaxis.set_major_locator(MultipleLocator(5))
>> >>>> xticks = ax1.xaxis.get_major_ticks()
>> >>>> #xticks[0].label1.set_visible(False)
>> >>>> #xticks[-1].label1.set_visible(False)
>> >>>> ax1.set_xticks(ax1.get_xticks()[1:-1])
>> >>>> ax1.plot(list(range(11)))
>> >>>> plt.show()
>> >>>>
>> >>>> On Sat, Feb 14, 2015 at 2:01 AM, Eric Firing <efiring@...202...> >> >> >>>> wrote:
>> >>>>> On 2015/02/13 3:29 PM, Tommy Carstensen wrote:
>> >>>>>> Is it possible to combine MultipleLocator and MaxNLocator? One
>> >>>>>> seems
>> >>>>>> to erase the effect of the other.
>> >>>>>
>> >>>>> They are for different situations. MultipleLocator is for when
>> >>>>> you
>> >>>>> know
>> >>>>> what you want your tick interval to be; MaxNLocator is for when
>> >>>>> you
>> >>>>> don't know that, but you do know roughly how many ticks you want,
>> >>>>> and
>> >>>>> what sort of numerical intervals are acceptable.
>> >>>>>
>> >>>>> Eric
>> >>>>>
>> >>>>>
>> >>>>>
>> >>>>>
>> >>>>>
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