I would be grateful if you can help me solve the problem
import matplotlib.pyplot as plt
import tifffile as tiff
import os
rows = 3
cols = 4
axes=[]
fig=plt.figure(figsize=[10,10])
i=["/images/1","/masks/1","/images/2","/masks/2"]
i=i+["/images/3","/masks/3","/images/4","/masks/4"]
p=1
m=0
for a in range(rows*cols):
if i[m].find("masks")!=-1:
b = plt.imread("/content/drive/MyDrive/PFE_MOHTICH/dataset/data/test{}.png".format(str(i[m])))
else:
b = tiff.imread("/content/drive/MyDrive/PFE_MOHTICH/dataset/data/test{}.tiff".format(str(i[m])))
m=m+1
axes.append( fig.add_subplot(rows, cols, a+1) )
plt.imshow(b)
plt.savefig("ex_val.png",cmap='binary_r')
fig.tight_layout()
plt.show()
The line which results in an error
(if i[m].find("masks")!=-1) :
the error message:
list index out of range
I don't know what's hard to see in this. Your for loop
for a in range(rows*cols): #rows*cols = (3*4) = 12
# In this loop you update m every iteration
m = m+1
so your m goes from 0 to 11 while your i has only 8 elements.
Like what is it that you can't see/get?
Related
I am trying to create a plot of arrays where one is calculated based on my x-axis calculated in a for loop. I've gone through my code multiple times and tested in between what exactly the lengths are for my arrays, but I can't seem to think of a solution that makes them equal length.
This is the code I have started with:
import numpy as np
import matplotlib.pyplot as plt
a = 1 ;b = 2 ;c = 3; d = 1; e = 2
t0 = 0
t_end = 10
dt = 0.05
t = np.arange(t0, t_end, dt)
n = len(t)
fout = 1
M = 1
Ca = np.zeros(n)
Ca[0] = a; Cb[0] = b
Cc[0] = 0;
k1 = 1
def rA(Ca, Cb, Cc, t):
-k1 * Ca**a * Cb**b * dt
return -k1 * Ca**a * Cb**b * dt
while e > 1e-3:
t = np.arange(t0, t_end, dt)
n = len(t)
for i in range(1,n-1):
Ca[i+1] = Ca[i] + rA(Ca[i], Cb[i], Cc[i], t[i])
e = abs((M-Ca[n-1])/M)
M = Ca[n-1]
dt = dt/2
plt.plot(t, Ca)
plt.grid()
plt.show()
Afterwards, I try to calculate a second function for different y-values. Within the for loop I added:
Cb[i+1] = Cb[i] + rB(Ca[i], Cb[i], Cc[i], t[i])
While also defining rB in a similar manner as rA. The error code I received at this point is:
IndexError: index 200 is out of bounds for axis 0 with size 200
I feel like it has to do with the way I'm initializing the arrays for my Ca. To put it in MatLab code, something I'm more familiar with, looks like this in MatLab:
Ca = zeros(1,n)
I have recreated the code I have written here in MatLab and I do receive a plot. So I'm wondering where I am going wrong here?
So I thought my best course of action was to change n to an int by just changing it in the while loop.
but after changing n = len(t) to n = 100 I received the following error message:
ValueError: x and y must have same first dimension, but have shapes (200,) and (400,)
As my previous question was something trivial I just kept on missing out on, I feel like this is the same. But I have spent over an hour looking and trying fixes without succes.
I think my code works well.
But the problem is that my code does not leave every answer on DataFrame R.
When I print R, only the last answer appeared.
What should I do to display every answer?
I want to add answer on the next column.
import numpy as np
import pandas as pd
DATA = pd.DataFrame()
DATA = pd.read_excel('C:\gskim\P4DS/Monthly Stock adjClose2.xlsx')
DATA = DATA.set_index("Date")
DATA1 = np.log(DATA/DATA.shift(1))
DATA2 = DATA1.drop(DATA1.index[0])*100
F = pd.DataFrame(index = DATA2.index)
for i in range (0, 276):
Q = DATA2.iloc[i].dropna()
W = sorted(abs(Q), reverse = False)
W_qcut = pd.qcut(W, 5, labels = ['A', 'B', 'C', 'D', 'E'])
F = Q.groupby(W_qcut).sum()
R = pd.DataFrame(F)
print(R)
the first table is the current result, I want to fill every blank tables on the second table as a result:
So, my question may not be exactly what is in the title.
I have a function
y = a*x + b
And I want to plot y whith different values of b.
I know that I can do the following:
import numpy as np
import matplotlib.pyplot as plt
a = 2
x = np.array([0,1,2,3,4])
b = 0
for i in range(10):
y = a*x + b
b = b+1
plt.plot(x,y)
And that returns exactly what I want.
But, there is someway that I can make this by using
b = np.array([0,1,2,3,4,5,6,7,8,9])? So, then my code could look something like:
import numpy as np
import matplotlib.pyplot as plt
a = 2
x = np.array([0,1,2,3,4])
b = np.array([0,1,2,3,4,5,6,7,8,9])
y = a*x + b
plt.plot(x,y)
Yes, you can use matrix operations to create a 2D matrix with the result of the operation y = a*x + b.
a = 2
x = np.array([0,1,2,3,4])
b = np.array([0,1,2,3,4,5,6,7,8,9])
y = a*x[:,None]+b
plt.plot(x, y)
EDIT: I'm shwing the solution provided by #Quang Hoang which is much simpler than mine.
original code was:
y = np.tile(a*x, (b.size,1)) + b[:,np.newaxis]
plt.plot(x, y.T)
I am wondering if anybody has a quick fix for a memory error that appears when doing the same thing as in the below example on larger data?
Example:
import pandas as pd
import numpy as np
nRows = 2
nCols = 3
df = pd.DataFrame(index=range(nRows ), columns=range(1))
df2 = df.apply(lambda row: [np.random.rand(nCols)], axis=1)
df3 = pd.concat(df2.apply(pd.DataFrame, columns=range(nCols)).tolist())
It is when creating df3 I get memory error.
The DF's in the example:
df
0
0 NaN
1 NaN
df2
0 [[0.6704675101784022, 0.41730480236712697, 0.5...
1 [[0.14038693859523377, 0.1981014890848788, 0.8...
dtype: object
df3
0 1 2
0 0.670468 0.417305 0.558690
0 0.140387 0.198101 0.800745
First I think working with lists in pandas is not good idea, if possible, you can avoid it.
So I believe you can simplify your code a lot:
nRows = 2
nCols = 3
np.random.seed(2019)
df3 = pd.DataFrame(np.random.rand(nRows, nCols))
print (df3)
0 1 2
0 0.903482 0.393081 0.623970
1 0.637877 0.880499 0.299172
Here's an example with a solution of the problem (note that in this example lists are not used in the columns, but arrays instead. This I cannot avoid, since my original problem comes with lists or array in a column).
import pandas as pd
import numpy as np
import time
np.random.seed(1)
nRows = 25000
nCols = 10000
numberOfChunks = 5
df = pd.DataFrame(index=range(nRows ), columns=range(1))
df2 = df.apply(lambda row: np.random.rand(nCols), axis=1)
for start, stop in zip(np.arange(0, nRows , int(round(nRows/float(numberOfChunks)))),
np.arange(int(round(nRows/float(numberOfChunks))), nRows + int(round(nRows/float(numberOfChunks))), int(round(nRows/float(numberOfChunks))))):
df2tmp = df2.iloc[start:stop]
if start == 0:
df3 = pd.DataFrame(df2tmp.tolist(), index=df2tmp.index).astype('float16')
continue
df3tmp = pd.DataFrame(df2tmp.tolist(), index=df2tmp.index).astype('float16')
df3 = pd.concat([df3, df3tmp])
I am trying to plot a histogram but the x ticks does not seem to get right.
The plot is intended to get a histogram of frequency counts ( 1 to 13 ) and total rows in 10000.
d1 = []
for i in np.arange(1, 10000):
tmp = np.random.randint(1, 13)
d1.append(tmp)
d2 = pd.DataFrame(d1)
d2.hist(width = 0.5)
plt.xticks(np.arange(1, 14, 1))
I am trying to plot frequency count of values and not ranges.
You would need to set the bin edges which should be used by the histogram.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
d1 = np.random.randint(1, 13, size=1000)
d2 = pd.DataFrame(d1)
bins = np.arange(0,13)+0.5
d2.hist(bins=bins, ec ="k")
plt.xticks(np.arange(1, 13))
plt.show()