I have defined an array that contains 1000 points, to illustrate, something like this:
x = np.zeros([1000, 2])
for i in range(1001):
x = 'int + [i , i] / 2'
How do I plot the points with plt.scatter()? I have tried with just inserting x, but it doent work.
Thank you in advance!
I think you're trying to do something like this:
import matplotlib.pyplot as plt
x = np.zeros([1000, 2])
for i in range(len(x)):
x[i] = [i/2 , i/2]
plt.scatter(x[:,0],x[:,1])
plt.show()
If anything isn't clear, don't hesitate to ask!
Related
I have a following function with takes 2 arguments psi,lam and returns 1 array y.
lam=np.arange(0,1,0.1)
psi=np.deg2rad(np.arange(0,361,1))
def test(psi,lam):
y=[]
for i in range(len(lam)):
sin_psi = np.sin(psi)
cos_psi = np.cos(psi)
sin_beta = lam*sin_psi
cos_beta = np.sqrt(1.0 - sin_beta**2)
ssin_pb = sin_psi*sin_beta
y.append((lam*(cos_psi/cos_beta)**2 - ssin_pb)/cos_beta + cos_psi)
plt.plot(psi,y[i])
return y
I would like the function to return range(len(lam))=10 plots of y on the vertical axis against psi on x axis.
However, it seems to be only plotting the same curve multiple times. Not sure what I am missing?
import matplotlib.pyplot as plt
import numpy as np
lam=np.arange(0,1,0.1)
psi=np.deg2rad(np.arange(0,361,1))
def test(angle,var):
sin_psi = np.sin(psi)
cos_psi = np.cos(psi)
sin_beta = var*sin_psi
cos_beta = np.sqrt(1.0 - sin_beta**2)
ssin_pb = sin_psi*sin_beta
return ((var*(cos_psi/cos_beta)**2 - ssin_pb)/cos_beta + cos_psi)
for i in lam:
plt.plot(psi,test(psi,i))
plt.show()
I moved the variable outside of the function, this way you may also use it for other cases. The only other thing is that you should call plt.show() after you're done drawing.
Your code has several problems the main being that the return function was inside the loop interrupting it after the first iteration. Imitating your code structure as closely as possible, we can rewrite the code as:
import numpy as np
import matplotlib.pyplot as plt
def test(psi,lam):
y=[]
for curr_lam in lam:
sin_psi = np.sin(psi)
cos_psi = np.cos(psi)
sin_beta = curr_lam*sin_psi
cos_beta = np.sqrt(1.0 - sin_beta**2)
ssin_pb = sin_psi*sin_beta
val = (curr_lam * (cos_psi/cos_beta)**2 - ssin_pb)/cos_beta + cos_psi
y.append(val)
plt.plot(psi, val)
plt.show()
return y
lam=np.arange(0, 1, 0.1)
psi=np.deg2rad(np.arange(0,361,1))
y = test(psi, lam)
print(y)
Sample output:
As Johan mentioned in the comments, you should also directly iterate over list/arrays. If you need to combine arrays, use
for x1, x2 in zip(arr1, arr2):
If you absolutely need the index value, use
for i, x in enumerate(arr):
So i made this code to create a plot that should look like this[This image was done in Mathematica] 1 but for some reason nothing shows up on the plot plot i made.does it have to something with the gam(x_2) or gam itself because i tried defining that as a range but still nothing. please teach me. From the plot made in matematica it seems like he set both the x and y ranges all the way up to 10,000.
import matplotlib.pyplot as plt
import numpy as np
import math
import pylab
%matplotlib inline
gam0 = 72.8
temp = 293.15
def gam(x_2):
return gam0 - 0.0187 * temp * math.log10(1+628.14*55.556*x_2)
x = range(0, 10000)
x_2= x
plt.plot('gam(x_2), x_2')
plt.xlabel('Log_10x_2')
plt.ylabel('gamma (erg cm^2)')
A few fixes needed; defining your function, there's an indent missing, also multiplying the whole array with ' * ' isn't working, so you can save up the values in a separate array through a for loop:
EDIT: Oh, and also while plotting, you don't put the variable names as strings, you just call them as they are.
import matplotlib.pyplot as plt
import numpy as np
import math
import pylab
%matplotlib inline
gam0 = 72.8
temp = 293.15
x = range(0, 10000)
x_2= x
def gam(x_2):
returns = []
for x_i in x_2:
returns.append(gam0 - 0.0187 * temp * math.log10(1+628.14*55.556*x_i))
return returns
plt.plot(gam(x_2), x_2)
plt.xlabel('Log_10x_2')
plt.ylabel('gamma (erg cm^2)')
plt.show()
Indent your function
def gam(x_2):
return gam0 - 0.0187 * temp * math.log10(1+628.14*55.556*x_2)
Find gam(x_2) for each item(x_2) in list x
gam_x = [gam(x_2) for x_2 in x]
Finally, plot and show.
plt.plot(gam_x, x)
plt.xlabel('Log_10x_2')
plt.ylabel('gamma (erg cm^2)')
plt.show()
So I made my list but after that I don't know how to take out of it my x and y so I can use it later to create a graph
import random
import numpy as np
import matplotlib.pyplot as plt
tabuletson = []
for i in range(0, 10):
x = round(random.uniform(-1000,1000),2)
y = (2*x+1)
tabuletson.append([x,y])
print(tabuletson)
wielomian = np.poly1d(np.polyfit(x,y,3))
linia = np.linspace(-2000,2000,2000)
plt.scatter(x,y)
plt.plot(linia,wielomian(linia))
plt.show()
All you have to do is to add one line of code after and outside your for loop. This command will create two lists containing x and y values. You can use the same variable names x and y.
x, y = zip(*tabuletson)
I think that this is a better way to do what you want according of how plt.scatter and plt.plot work. Hope it works as you want!
import random
import numpy as np
import matplotlib.pyplot as plt
x = []; y = []
for i in range(10):
x.append(round(random.uniform(-1000,1000),2))
y.append(2*x[i]+1)
wielomian = np.poly1d(np.polyfit(x,y,3))
linia = np.linspace(-2000,2000,2000)
plt.scatter(x,y)
plt.plot(linia,wielomian(linia))
plt.show()
The np.polyfit and plt.scatter functions you are using require separate lists of X and Y coordinates.
Try:
import random
import numpy as np
import matplotlib.pyplot as plt
tabuletson_x = []
tabuletson_y = []
for i in range(0, 10):
x = round(random.uniform(-1000,1000),2)
y = (2*x+1)
tabuletson_x.append(x)
tabuletson_y.append(y)
print(tabuletson_x)
print(tabuletson_y)
wielomian = np.poly1d(np.polyfit(tabuletson_x,tabuletson_y,3))
linia = np.linspace(-2000,2000,2000)
plt.scatter(tabuletson_x,tabuletson_y)
plt.plot(linia,wielomian(linia))
plt.show()
Note: referencing x and y after the for cycle will give you the last values from the randomly generated list:
list of x vals: [-8.78, 554.81, -693.22, 955.8, 88.95, 235.55, -108.67, -804.08, 494.65, 754.58]
list of y vals: [-16.56, 1110.62, -1385.44, 1912.6, 178.9, 472.1, -216.34, -1607.16, 990.3, 1510.16]
x: 754.58
y: 1510.16
For more info:
PyPlot Scatter documentation
PolyFit documentation
Your x and y are stored in your list tabuletson. Like this: [[x0,y0], [x1,y1], ..., [x,y]]
So you can, for example, get the value of x1 and y1 with x1 = tabuletson[1][0] and y1 = tabuletson[1][1]
Is that your question ?
tabuletson = np.array(tabuletson)
X, Y = tabuletson[:,0], tabuletson[:,1]
X will have all your xs from list
And, Y will have all your ys from list
I have some data I want to plot, x and y is in the same format as this small piece of example code.
import matplotlib.pyplot as plt
y = [1,1,3,4]
x = [1,4,2,3]
plt.plot(x,y,'-o')
plt.show()
This results in quite a weird graph.
What pyplot does is drawing a line from the first point inserted to the second, then to the third etc.
I want it to draw a line from low-x to high-x, but I can seem to find a nice way to do this. I want my line to be like this.
What is the easiest way to achieve this, given my x and y data is in the same format but more complex than this example?
To get the graph as you mentioned, you need to have values in x in sorted order, which you can achieve like this:
z = sorted(zip(x,y))
x=[i[0] for i in z]
y=[i[1] for i in z]
and now using x and y for ploting (not tested).
you can sort your x list with simultaneously changing the y,
import matplotlib.pyplot as plt
y = [1,1,3,4]
x = [1,4,2,3]
for i in range(len(x)):
for k in range( len( x ) - 1, i, -1 ):
if ( x[k] < x[k - 1] ):
x[k-1],x[k]=x[k],x[k-1]
y[k-1],y[k]= y[k],y[k-1]
print x,y
plt.plot(x,y,'-o')
plt.show()
I've got a 900 x 650 2D numpy array which I'd like to split into 10 x 10 blocks, which will be checked for nonzero elements. Is there a Pythonic way that I can achieve this with numpy?
I'm looking for functionality similar to the following:
blocks_that_have_stuff = []
my_array = getArray()
my_array.cut_into_blocks((10, 10))
for block_no, block in enumerate(my_array):
if numpy.count_nonzero(block) > 5:
blocks_that_have_stuff.append(block_no)
I wrote a routine that cut your matrix in blocks. The example is very easy to understand. I wrote it in an easy form to display the result (only for checking purpose). If you are interested in it, you could include in the output the number of blocks or anything.
import matplotlib.pyplot as plt
import numpy as np
def cut_array2d(array, shape):
arr_shape = np.shape(array)
xcut = np.linspace(0,arr_shape[0],shape[0]+1).astype(np.int)
ycut = np.linspace(0,arr_shape[1],shape[1]+1).astype(np.int)
blocks = []; xextent = []; yextent = []
for i in range(shape[0]):
for j in range(shape[1]):
blocks.append(array[xcut[i]:xcut[i+1],ycut[j]:ycut[j+1]])
xextent.append([xcut[i],xcut[i+1]])
yextent.append([ycut[j],ycut[j+1]])
return xextent,yextent,blocks
nx = 900; ny = 650
X, Y = np.meshgrid(np.linspace(-5,5,nx), np.linspace(-5,5,ny))
arr = X**2+Y**2
x,y,blocks = cut_array2d(arr,(10,10))
n = 0
for x,y,block in zip(x,y,blocks):
n += 1
plt.imshow(block,extent=[y[0],y[1],x[0],x[1]],
interpolation='nearest',origin='lower',
vmin = arr.min(), vmax=arr.max(),
cmap=plt.cm.Blues_r)
plt.text(0.5*(y[0]+y[1]),0.5*(x[0]+x[1]),str(n),
horizontalalignment='center',
verticalalignment='center')
plt.xlim([0,900])
plt.ylim([0,650])
plt.savefig("blocks.png",dpi=72)
plt.show()
The output is:
Regards
Note: I think you could optimize this routine using np.meshgrid instead a lot of appends with the xextent & yextent.