I'm trying to use plt.text to plot temperature values at their associated lat/lon points on a plot.
After reviewing the plt.text documentation, it appears that the plotted value (third arg) has to be a number and that the number has to be a whole number, NOT a number with decimals.
Below is the code that I'm trying to work with and the associated traceback error that I'm receiving:
Script Code:
data = np.loadtxt('/.../.../.../tmax_day0', delimiter=',', skiprows=1)
grid_x, grid_y = np.mgrid[-85:64:dx, 34:49:dx]
temp = data[:,2]
#print temp
grid_z = griddata((data[:,1],data[:,0]), data[:,2], (grid_x,grid_y), method='linear')
x,y = m(data[:,1], data[:,0]) # flip lat/lon
grid_x,grid_y = m(grid_x,grid_y)
#m.plot(x,y, 'ko', markersize=2)
def str_to_float(str):
try:
number = float(str)
except ValueError:
number = 0.0
return number
fmt = str_to_float(temp)
#annotate point temperature on plot
plt.text(grid_x, grid_y, fmt, fontdict=None)
Traceback Error:
Traceback (most recent call last):
File "plotpoints.py", line 56, in <module>
fmt = str_to_float(temp)
File "plotpoints.py", line 51, in str_to_float
number = float(str)
TypeError: only length-1 arrays can be converted to Python scalars
Data sample from text file tmax_day0:
latitude,longitude,value
36.65408,-83.21783,90
41.00928,-74.73628,92.02
43.77714,-71.75598,90
44.41944,-72.01944,88.8
39.5803,-79.3394,79
38.3154,-76.5501,86
38.91444,-82.09833,94
40.64985,-75.44771,92.6
41.25389,-70.05972,81.2
39.45202,-74.56699,90.88
I was able to achieve plotting data values only by using the following code:
for i in range(len(temp)):
plt.text(x[i], y[i], temp[i], va="top", family="monospace")
Result:
You aren't using a "proper" array, and are instead using a numpy array. Numpy arrays don't play well with non-numpy functions.
Going from your comment, this has been edited.
You would first need to fix the string so it's a proper array.
fmt = fmt[0].split()
I think should work to create a new (normal) array of strings. And then this to map that to an array of floats:
list_of_floats = np.array(map(float, fmt))
Related
I am trying to create N-Dimensional histogram from 2D array which has complex values. I want to count the number of occurrences in real and imaginary parts of the array given the bins and store the result in a 3D array. It only runs for the first iteration when I hard code i=0 and remove the for loop. I have never used histograms in python before and I just cannot understand the error. The code is given below.
xsoft is defined as 2d array of complex type and I somehow compute bnd_edges by finding max, min values from xsoft and create edges to be given as bins.
xsoft = np.empty((M, MAX,), dtype=complex) # e.g has dims 4*100
xsoft[:] = np.nan
edges = np.linspace(-bnd_edges, bnd_edges, numbin) #numbin=10
pSOFT = np.empty((len(edges)-1, M, len(edges)-1)) # len(edges)= 10
pSOFT[:] = np.nan
for i in range(M):
pSOFT[:, i, :], edges = np.histogramdd((xsoft[i, :].real, xsoft[i, :].imag), bins=(edges, edges))
The code results in the following error
Traceback (most recent call last):
File " ", line 194, in <module>
pSOFT[:, i, :], edges = np.histogramdd((xsoft[i, :].real, xsoft[i, :].imag), bins=(edges, edges))
File "<__array_function__ internals>", line 5, in histogramdd
File " " line 1066, in histogramdd
raise ValueError(
ValueError: `bins[0]` must be a scalar or 1d array
Process finished with exit code 1
You are getting this error because you are overriding the original definition of edges with the second return value of histogramdd.
Replace the last line in your code with this:
pSOFT[:, i, :], edges_i = np.histogramdd((xsoft[i, :].real, xsoft[i, :].imag), bins=(edges, edges))
I am trying to create a flight route map using cartopy. I have to add the destination names on the map and to achieve it i am using this code:
origin_lat = 59.41329956
origin_lon= 24.83279991
data = pd.read_csv("merged.csv", skiprows=[1])
This csv file has few columns and one column is called IATA from where I am trying to extract those location strings.
for i in range(len(data)):
lon = data['Longitude'][i]
lat = data['Latitude'][i]
label = data['IATA'][i]
plt.plot([origin_lon, lon], [origin_lat, lat],
color='red', linewidth=1,
transform=ccrs.Geodetic(),
)
print(label) # when i use only print it shows all the strings available in IATA column
plt.text(lon, lat, label[i],
horizontalalignment='right',
transform=ccrs.Geodetic())
But when I plot in map it shows the error
[36 rows x 15 columns]
AMS
ATH
TXL
BRU
Traceback (most recent call last):
File "D:\spyderPython\hw3\readCSV.py", line 65, in <module>
plt.text(lon, lat, label[i],
IndexError: string index out of range
can someone advise please what i am doing wrong?
You are trying to get the label again here:
plt.text(lon, lat, label[i],
horizontalalignment='right',
transform=ccrs.Geodetic())
which I assume your label is already a string, and range(len(data)) is bigger than the len of your label. That is why you get an IndexError, simply switch that code with this:
plt.text(lon, lat, label,
horizontalalignment='right',
transform=ccrs.Geodetic())
for i=1:n
centersX(:,i)=linspace(min(xData)+dX/2,max(xData)-dX/2,nbins)';
centersY(:,i)=linspace(min(yData)+dY/2,max(phase)-dY/2,nbins)';
centers = {centersX(:,i),centersY(:,i)};
H(:,:,i) = hist3([xData yData],centers);
end
In each iteration, I construct centersX and centersY with linspace function. I then store them in a 2x1 cell array called centers. H is a nbins X nbins X n struct. In each iteration I fill a nbins X nbins slice of H with the data from hist3.
I'm looking for the Python equivalent. I'm having trouble with passing the arguments for numpy.histogram2d:
H[:,:,i] = numpy.histogram2d(xData,yData,centers)
I get the following error:
Traceback (most recent call last):
line 714, in histogramdd
N, D = sample.shape
AttributeError: 'list' object has no attribute 'shape'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
line 36, in <module>
H[:,:,i] = numpy.histogram2d(xData, yData, centers)
line 714, in histogram2d
hist, edges = histogramdd([x, y], bins, range, normed, weights)
line 718, in histogramdd
N, D = sample.shape
ValueError: too many values to unpack (expected 2)
Since Python doesn't have cell arrays, I changed centers to be an array of arrays where centers[0] = centersX and centers[1] = centersY. What do I need to change such that that assuming the data are the same between matlab and python that the outputs will match?
EDIT:
I have also tried H[:,:,i] = numpy.histogram2d(xData,yData, bins=(centersX,centersY)) to cutout the combining step into centers but no luck.
Have you tried combing them with square brackets?
Maybe you can also use matplotlib.pyplot.hist2d.
H[:,:,i], *_ = numpy.histogram2d(xData,yData,bins=[centers[0], centers[1]])
H[:,:,i], *_ = matplotlib.pyplot.hist2d(xData,yData,bins=[centers[0], centers[1]])
In both, the values in centers are the bin edges, not the centers. You have to adjust the calculation. I think it is enough to remove the dX/2:
centersX(:,i)=linspace(min(xData),max(xData),nbins)';
centersY(:,i)=linspace(min(yData),max(phase),nbins)';
I have 974 data points located on the surface of the unit sphere. The points are not ordered in any particular way. I wish to read in these data points, along with their corresponding polar coordinates (phi, theta). I then wish to interpolate onto a regular latitude-longitude grid using scipy.interpolate.SmoothSphereBivariateSpline. So far I have the following code:
import numpy as np
from scipy.interpolate import SmoothSphereBivariateSpline
#Read in the unorganized grid points
# and also shift so that phi in [0,pi] and theta in [0,2*pi)
leb = np.genfromtxt('grid.txt')
u, v = np.hsplit(leb, 2)
phi, theta = u[:,0], v[:,0]
theta += np.pi
#Read in the unorganized data values
data1 = np.genfromtxt('0p0_97p03.txt')
#Create the interpolator object
lut = SmoothSphereBivariateSpline(phi, theta, data1, s=350)
#Generate a regular lat-long grid to interpolate onto
N = 100
lat = np.linspace(0.0, np.pi, N)
lon = np.linspace(0.0, 2.0*np.pi, N)
lat, lon = np.meshgrid(lat, lon)
#Now interpolate onto the regular grid
data_inerp = lut(lat, lon)
In the above code, the arrays phi, theta and data1 are the unorganized data points, with each of these three arrays having a shape (974,). When i run this code I get the error message:
Traceback (most recent call last):
File "spherebiv.py", line 25, in <module>
data_inerp = lut(lat, lon)
File "/usr/lib/python2.7/dist-packages/scipy/interpolate/fitpack2.py", line 958, in __call__
raise ValueError("Error code returned by bispev: %s" % ier)
ValueError: Error code returned by bispev: 10
Now I don't understand this error code - it seems to be something to do with the underlying Fortran routine. Is there anything obvious I'm doing wrong here?
I'm trying to make a histogram of some data that is being stored in an ndarray. The histogram is part of a set of analysis which I've made into a class in a python program. The part of the code that isn't working is below.
def histogram(self, iters):
samples = T.MCMC(iters) #Returns an [iters,3,4] ndarray
histAC = plt.figure(self.ip) #plt is matplotlib's pyplot
self.ip+=1 #defined at the beginning of the class to start at 0
for l in range(0,4):
h = histAC.add_subplot(2,(iters+1)/2,l+1)
for i in range(0,0.5*self.chan_num):
intAvg = mean(samples[:,i,l])
print intAvg
for k in range(0,iters):
samples[k,i,l]=samples[k,i,l]-intAvg
print "Samples is ",samples
h.hist(samples,bins=5000,range=[-6e-9,6e-9],histtype='step')
h.legend(loc='upper right')
h.set_title("AC Pulse Integral Histograms: "+str(l))
figname = 'ACHistograms.png'
figpath = 'plot'+str(self.ip)
print "Finished!"
#plt.savefig(figpath + figname, format = 'png')
This gives me the following error message:
File "johnmcmc.py", line 257, in histogram
h.hist(samples,bins=5000,range=[-6e-9,6e-9],histtype='step') #removed label=apdlabel
File "/x/tsfit/local/lib/python2.6/site-packages/matplotlib/axes.py", line 7238, in hist
ymin = np.amin(m[m!=0]) # filter out the 0 height bins
File "/x/tsfit/local/lib/python2.6/site-packages/numpy/core/fromnumeric.py", line 1829, in amin
return amin(axis, out)
ValueError: zero-size array to ufunc.reduce without identity
The only search results I've found have been multiple copies of the same two conversations, from which the only thing I learned was that python histograms don't like getting fed empty arrays, which is why I added the print statement right above the line that's giving me trouble to make sure the array isn't empty.
Has anyone else come across this error before?