I would like my sybplots to be generated in 2x columns and 5x rows.
I've also tried adding ncols=2, nrows=5 to the code. didn't work.
And when I change the subplots to plt.subplots(5,2) instead of plt.subplots(10,1) it says (see added picture of code+error message):
AttributeError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_9844/709244097.py in
13
14 for ax, afstand, tid in zip(ax, afstande, tider):
---> 15 ax.plot(tid, afstand)
16 ax.set_title("x(t)", fontsize=12)
17 ax.set_xlabel("tid (s)", fontsize=12)
AttributeError: 'numpy.ndarray' object has no attribute 'plot'
My code:
from scipy.optimize import fmin
a = -75.64766759
b = 68.02691163
f = lambda x: a * x + b
afstand1, afstand2, afstand3, afstand4, afstand5, afstand6, afstand7, afstand8, afstand9, afstand10 = f(U1), f(U2), f(U3), f(U4), f(U5),f(U6), f(U7), f(U8), f(U9), f(U10)
afstande = [afstand1, afstand2, afstand3, afstand4, afstand5, afstand6, afstand7, afstand8, afstand9, afstand10]
tider = [tid1, tid2, tid3, tid4, tid5, tid6, tid7, tid8, tid9, tid10]
fig, ax = plt.subplots(10,1, figsize=(7,25))
plt.subplots_adjust(hspace=0.55)
#loop
for ax, afstand, tid in zip(ax, afstande, tider):
ax.plot(tid, afstand)
ax.set_title("x(t)", fontsize=12)
ax.set_xlabel("tid (s)", fontsize=12)
ax.set_ylabel("Position", fontsize=12)
enter image description here
First of all, you're using the same variable name for the array of axis and in the loop, you should change that. Subplot-axes are stored in numpy arrays. If you only have 1 row, then looping over the array gives you the elements, but in a x*y pattern of subplots, you loop over a two-dimensional array of axis, which yields the rows. You can solve that by using .flat to get a one-dimensional view.
fig, axs = plt.subplots(ncols=5, nrows=2)
for ax in axs.flat:
ax.plot(...)
Related
I want to generate colorplot subplots based on a numpy array's length which I call dets. I want to use the array length to determine the right number of columns and rows for the subplots. If square, plot a square matrix of subplots, if not square, add another row. For starters, I have written some code to check if the array's length would create a square matrix of subplots with the following:
data_f = np.random.rand(len(dets),2,5)
dets = np.arange(-5,-0.75,0.25)
x = np.array([1,5,6,3,8,9,2,3,10,12,3])
v = np.linspace(0,10,len(x))
square = np.sqrt(len(dets))
check_square = len(dets)%square
non_square = 1
print(len(data_f))
if check_square == 0:
nrows = int(np.sqrt(len(dets)))
ncols = int(np.sqrt(len(dets)))
else:
nrows = int(np.sqrt(len(dets)))+non_square
ncols = int(np.sqrt(len(dets)))
fig, ax = plt.subplots(nrows, ncols, sharex='col', sharey='row')
for i in range(nrows):
for j in range(ncols):
if i==0:
im = ax[i,j].imshow(data_f[j],extent=(x.min(), x.max(), v.min(), v.max()),origin='lower',aspect='auto')
else:
im = ax[i,j].imshow(data_f[j+ncols*i],extent=(x.min(), x.max(), v.min(), v.max()),origin='lower',aspect='auto')
The output plot:
This plots 17 plots but the resulting plots I cannot adjust because of the error
This plots everything I want, except it always smushes the plots together in a weird way because of the following error:
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
~\AppData\Local\Temp\1/ipykernel_4560/3817292743.py in <module>
6 im = ax[i,j].imshow(data_f[j],extent=(x.min(), x.max(), v.min(), v.max()),origin='lower',aspect='auto')
7 else:
----> 8 im = ax[i,j].imshow(data_f[j+ncols*i],extent=(x.min(), x.max(), v.min(), v.max()),origin='lower',aspect='auto')
9
IndexError: index 17 is out of bounds for axis 0 with size 17
It is because you have a total of 20 axes, and when you loop through ncols and nrows, you will get 20 iterations. But len(data_f) is only 17.
at the start of your iteration, add
if(j + ncols*i) == len(data_f):
break
I did this and it stopped the error
I'm doing a project for Udacity's AI with Python nanodegree.
I'm trying to display a torch.cuda.FloatTensor that I obtained from an image file path. Below that image will be a bar chart showing the top 5 most likely flower names with their associated probabilities.
plt.figure(figsize=(3,3))
path = 'flowers/test/1/image_06743.jpg'
top5_probs, top5_class_names = predict(path, model,5)
print(top5_probs)
print(top5_class_names)
flower_np_image = process_image(Image.open(path))
flower_tensor_image = torch.from_numpy(flower_np_image).type(torch.cuda.FloatTensor)
flower_tensor_image = flower_tensor_image.unsqueeze_(0)
axs = imshow(flower_tensor_image, ax = plt)
axs.axis('off')
axs.title(top5_class_names[0])
axs.show()
fig, ax = plt.subplots()
y_pos = np.arange(len(top5_class_names))
plt.barh(y_pos, list(reversed(top5_probs)))
plt.yticks(y_pos, list(reversed(top5_class_names)))
plt.ylabel('Flower Type')
plt.xlabel('Class Probability')
The imshow function was given to me as
def imshow(image, ax=None, title=None):
if ax is None:
fig, ax = plt.subplots()
# PyTorch tensors assume the color channel is the first dimension
# but matplotlib assumes is the third dimension
image = image.transpose((1, 2, 0))
# Undo preprocessing
mean = np.array([0.485, 0.456, 0.406])
std = np.array([0.229, 0.224, 0.225])
image = std * image + mean
# Image needs to be clipped between 0 and 1 or it looks like noise when displayed
image = np.clip(image, 0, 1)
ax.imshow(image)
return ax
But I get this output
[0.8310797810554504, 0.14590543508529663, 0.013837042264640331, 0.005048676859587431, 0.0027143193874508142]
['petunia', 'pink primrose', 'balloon flower', 'hibiscus', 'tree mallow']
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-17-f54be68feb7a> in <module>()
12 flower_tensor_image = flower_tensor_image.unsqueeze_(0)
13
---> 14 axs = imshow(flower_tensor_image, ax = plt)
15 axs.axis('off')
16 axs.title(top5_class_names[0])
<ipython-input-15-9c543acc89cc> in imshow(image, ax, title)
5 # PyTorch tensors assume the color channel is the first dimension
6 # but matplotlib assumes is the third dimension
----> 7 image = image.transpose((1, 2, 0))
8
9 # Undo preprocessing
TypeError: transpose(): argument 'dim0' (position 1) must be int, not tuple
<matplotlib.figure.Figure at 0x7f5855792160>
My predict function works, but the imshow just chokes with the call to transpose. Any ideas on how to fix this? I think it vaguely has something to do with converting back to a numpy array.
The notebook that I'm working on can be found at https://github.com/BozSteinkalt/ImageClassificationProject
Thanks!
You are trying to apply numpy.transpose to a torch.Tensor object, thus calling tensor.transpose instead.
You should convert flower_tensor_image to numpy first, using .numpy()
axs = imshow(flower_tensor_image.detach().cpu().numpy(), ax = plt)
I am trying to plot three lines from different Pandas Dataframes to the same subplot in matplotlib. But, when I did this I found one of the plots shifted along the xaxis (The xrange is different for each line). However, when I plot each line individually the xlimits are correct and none of them are shifted. I have tried to reproduce my problem here:
def plot_dH1(title1, title_sim, a, b, c):
fig = plt.figure(figsize=(4,4))
plt.style.use(‘ggplot’)
sns.set_style(‘ticks’)
plt.rcParams[‘font.size’] = 15
n = 0
for i in range(len(a)):
ax = fig.add_subplot(1,1,n+1)
ax = a[i].groupby(level=(0, 1)).mean()[0].plot(label=‘$\chi_{180}$‘)
ax = b[i].groupby(level=(0, 1)).mean()[0].plot(label=‘All’)
ax = c[i].groupby(level=(0, 1)).mean()[0].plot(label=‘$\chi_{90}$‘)
ax.set_ylabel(‘$dH$‘)
ax.set_xlabel(‘$\lambda_{0}$, $\lambda_{1}$‘)
ax.set_title(title_sim[i])
title = title_sim[i]
sns.despine(offset=10, ax=ax)
plt.xticks(rotation=90)
# plt.yticks(range(0,350,20),range(0,350,20))
n = n+1
lgd = ax.legend(loc=‘upper center’, bbox_to_anchor=(0.35, -0.8),fancybox=True, shadow=True, ncol=3)
# plt.tight_layout()
# fig.savefig(‘{}.pdf’.format(‘dHdl_all’))
fig.savefig(‘{}.pdf’.format(‘dHdl_all’),bbox_extra_artists=(lgd,), bbox_inches=‘tight’)
array = [range(10), range(10,20)]
tuples = list(zip(*array))
index = pd.MultiIndex.from_tuples(tuples)
a = [pd.DataFrame(np.random.randn(10,1), index=index)]
b = [pd.DataFrame(np.random.randn(5,1), index=index[5:])]
c = [pd.DataFrame(np.random.randn(8,1), index=index[2:])]
plot_dH1(title1, title_sim, a, b, c)
a, b, c are lists of Pandas Data Frame. I am not able to upload an image. But if you run it you will see the problem. Does anyone knows why one of the lines is shifted along the xaxis?
You'll get answers quicker and more reliably if you can provide a minimal, working example. Your supplied code was missing several imports that were renamed, the title definitions, and had several commented lines cluttering things. Using the following code, I see that all of the lines start with the same x shift:
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
def plot_dH1(title1, title_sim, a, b, c):
fig = plt.figure(figsize=(4,4))
plt.style.use('ggplot')
sns.set_style('ticks')
plt.rcParams['font.size'] = 15
n = 0
for i in range(len(a)):
ax = fig.add_subplot(1,1,n+1)
ax = a[i].groupby(level=(0, 1)).mean()[0].plot(label='$\chi_{180}$')
ax = b[i].groupby(level=(0, 1)).mean()[0].plot(label='All')
ax = c[i].groupby(level=(0, 1)).mean()[0].plot(label='$\chi_{90}$')
ax.set_ylabel('$dH$')
ax.set_xlabel('$\lambda_{0}$, $\lambda_{1}$')
ax.set_title(title_sim[i])
sns.despine(offset=10, ax=ax)
plt.xticks(rotation=90)
n = n+1
lgd = ax.legend(loc='upper center', bbox_to_anchor=(0.35, -0.8),fancybox=True, shadow=True, ncol=3)
fig.savefig('{}.pdf'.format('dHdl_all'),bbox_extra_artists=(lgd,), bbox_inches='tight')
array = [range(10), range(10,20)]
tuples = list(zip(*array))
index = pd.MultiIndex.from_tuples(tuples)
a = [pd.DataFrame(np.random.randn(10,1), index=index)]
b = [pd.DataFrame(np.random.randn(5,1), index=index[5:])]
c = [pd.DataFrame(np.random.randn(8,1), index=index[2:])]
title_sim = np.arange(10)
title1 = ''
plot_dH1(title1, title_sim, a, b, c)
produces the following plot using Python 3.5.2:
I don't see an x shift of one of the three curves plotted relative to the other two. An x offset is defined, and is controlled by the offset parameter of the line sns.despine(offset=10, ax=ax). Setting it to zero makes all of the lines adjacent to the y-axis:
No, Dataframe b is acutually shifted. Look at the blue curve. Its index are defined as index[5:] which means that it should have these values:
[ 0
5 15 1.398019
6 16 0.325211
7 17 0.113059
8 18 0.814993
9 19 0.402437]
So it should start from (5 15) along the X axis, but it is actually starting from (2, 12), which means that it is shifted.
I have the following:
import matplotlib.pyplot as plt
fig = plt.figure()
for i in range(10):
ax = fig.add_subplot(551 + i)
ax.plot([1,2,3,4,5], [10,5,10,5,10], 'r-')
I was imagining that the 55 means that it is creating a grid that is 5 subplots wide and 5 subplots deep - so can cater for 25 subplots?
The for loop will just iterate 10 times - so I thought (obviously wrongly) that 25 possible plots would accomodate those iterations ok but I get the following:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-118-5775a5ea6c46> in <module>()
10
11 for i in range(10):
---> 12 ax = fig.add_subplot(551 + i)
13 ax.plot([1,2,3,4,5], [10,5,10,5,10], 'r-')
14
/home/blah/anaconda/lib/python2.7/site-packages/matplotlib/figure.pyc in add_subplot(self, *args, **kwargs)
1003 self._axstack.remove(ax)
1004
-> 1005 a = subplot_class_factory(projection_class)(self, *args, **kwargs)
1006
1007 self._axstack.add(key, a)
/home/blah/anaconda/lib/python2.7/site-packages/matplotlib/axes/_subplots.pyc in __init__(self, fig, *args, **kwargs)
62 raise ValueError(
63 "num must be 1 <= num <= {maxn}, not {num}".format(
---> 64 maxn=rows*cols, num=num))
65 self._subplotspec = GridSpec(rows, cols)[int(num) - 1]
66 # num - 1 for converting from MATLAB to python indexing
ValueError: num must be 1 <= num <= 30, not 0
In the convience shorthand notation, the 55 does mean there are 5 rows and 5 columns. However, the shorthand notation only works for single-digit integers (i.e. for nrows, ncols and plot_number all less than 10).
You can expand it to full notation (i.e. use commas: add_subplot(nrows, ncols, plot_number)) and then all will work fine for you:
for i in range(10):
ax = fig.add_subplot(5, 5, 1 + i)
ax.plot([1,2,3,4,5], [10,5,10,5,10], 'r-')
From the docs for plt.subplot (which uses the same args as fig.add_subplot) :
Typical call signature:
subplot(nrows, ncols, plot_number)
Where nrows and ncols are used to notionally split the figure into nrows * ncols sub-axes, and
plot_number is used to identify the particular subplot that this
function is to create within the notional grid. plot_number starts at
1, increments across rows first and has a maximum of nrows * ncols.
In the case when nrows, ncols and plot_number are all less than 10, a convenience exists, such that the a 3 digit number can be given
instead, where the hundreds represent nrows, the tens represent ncols
and the units represent plot_number.
Although tom answered your question, in this sort of situation you should be using fig, axs = plt.subplots(n, m). This will create a new figure with the n rows and m columns of subplots. fig is the figure created. axs is a 2D numpy array where each element in the array is the subplot in the corresponding location in the figure. So the top-right element axs is the top-right subplot in the figure. You can access the subplots through normal indexing, or loop over them.
So in your case you can do
import matplotlib.pyplot as plt
# axs is a 5x5 numpy array of axes objects
fig, axs = plt.subplots(5, 5)
# "ravel" flattens the numpy array without making a copy
for ax in axs.ravel():
ax.plot([1,2,3,4,5], [10,5,10,5,10], 'r-')
I have a FPR and TPR plot. In here I want to ask how to arangge spacing value between the x-axis. My code is following below:
In [85]:
fig, ax = plt.subplots(figsize=(8,6), dpi=80)
ax.plot(x_iter1_TF , y_iter1_TF, label='Iter1', marker='o')
ax.plot(x_iter5_TF, y_iter5_TF ,label='Iter5', marker='v')
ax.plot(x_iter10_TF, y_iter10_TF , label='Iter10', marker='x')
ax.plot(x_iter25_TF, y_iter25_TF , label='Iter20', marker='+')
ax.plot(x_iter50_TF, y_iter50_TF , label='Iter50',marker='D')
ax.legend(loc=1); # upper left corner
ax.set_xlabel('FPR')
ax.set_ylabel('TPR')
ax.set_xlim([0,1, 0.001])
ax.set_ylim([0,1, 0.001])
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-85-87b9ef379a9b> in <module>()
8 ax.set_xlabel('FPR')
9 ax.set_ylabel('TPR')
---> 10 ax.set_xlim([0,1, 0.001])
11 ax.set_ylim([0,1, 0.001])
C:\Python27\lib\site-packages\matplotlib\axes\_base.pyc in set_xlim(self, left, right, emit, auto, **kw)
2524
2525 if right is None and iterable(left):
-> 2526 left, right = left
2527
2528 self._process_unit_info(xdata=(left, right))
ValueError: too many values to unpack
In here I used ax.set_xlim([0,1, 0.001]) where 0.001 is spacing value between x-axis. Unfortunately, i faced an error. I think i did the wrong way to set those thing
As mentioned in my comment, set_xlim does not accept a "step" parameter. Also, the method I think you want is set_xticks, which can be used as follows:
In [13]: import numpy as np
...: ticks = np.arange(0, 2, 0.1)
...: ax.set_xticks(ticks)
...: fig
And gives the following result: