Parse the data with the index information



In [1]:

    
from xrdtools import parse_data, heatmap



In [2]:

    
%matplotlib inline

parse the data



In [3]:

    
m = parse_data('../data/result_slice01.txt', colnum=1)

show the data



In [4]:

    
m.head()









    Out[4]:







  
    
      ind_y
      3
      4
      5
      6
      7
      8
      9
      10
      11
      12
      ...
      51
      52
      53
      54
      55
      56
      57
      58
      59
      60
    
    
      ind_x
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
    
  
  
    
      3
      65.14323
      49.69298
      48.79670
      56.63807
      47.02948
      50.46613
      78.54695
      48.17240
      43.33721
      69.29522
      ...
      339.49859
      236.19234
      87.30356
      59.35334
      74.26702
      85.25973
      78.98063
      74.70566
      51.93228
      54.88132
    
    
      4
      69.85600
      48.23067
      49.13857
      46.81142
      50.08756
      42.50936
      83.23597
      73.79040
      44.87992
      51.33915
      ...
      356.65583
      200.61550
      128.84925
      116.39241
      89.90483
      80.54440
      52.29518
      65.01838
      62.95591
      61.35586
    
    
      5
      76.40160
      42.57160
      50.38175
      51.80404
      47.59427
      41.18479
      50.88559
      55.47304
      50.64592
      50.03333
      ...
      515.90239
      228.68634
      550.69584
      372.03552
      121.54316
      90.09829
      69.64879
      96.32019
      63.56461
      56.37973
    
    
      6
      58.80151
      50.78167
      54.44780
      63.54956
      56.18738
      46.49468
      49.04318
      51.76220
      63.22538
      85.78638
      ...
      697.16494
      655.78041
      484.59225
      539.28921
      443.63649
      252.27457
      129.93238
      95.94847
      55.74373
      59.90149
    
    
      7
      61.91512
      37.68067
      35.86701
      50.08186
      84.66419
      82.76149
      71.15154
      65.06230
      56.12031
      90.97828
      ...
      614.41857
      641.84395
      646.67456
      446.08255
      588.31174
      669.10054
      180.65144
      106.53503
      69.29114
      79.08854
    
  

5 rows × 58 columns



In [5]:

    
heatmap(m)

different colum and colormap



In [7]:

    
m = parse_data('../data/result_slice01.txt', colnum=6)
heatmap(m, 10, cmap='Greens_r')

same thing but using the heatmap method from seaborn



In [10]:

    
import matplotlib.pyplot as plt
import seaborn as sns



In [11]:

    
plt.figure(figsize=(14, 10))
sns.heatmap(m, cmap='viridis', xticklabels=False, yticklabels=False)









    Out[11]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f6e8c31f358>



In [12]:

    
%version_information









    Out[12]:




Software Version
Python 3.6.3 64bit [GCC 7.2.0]
IPython 6.1.0
OS Linux 4.9.0 4 amd64 x86_64 with debian 9.1
Tue Oct 17 18:59:09 2017 CEST

ind_y	3	4	5	6	7	8	9	10	11	12	...	51	52	53	54	55	56	57	58	59	60
ind_x
3	65.14323	49.69298	48.79670	56.63807	47.02948	50.46613	78.54695	48.17240	43.33721	69.29522	...	339.49859	236.19234	87.30356	59.35334	74.26702	85.25973	78.98063	74.70566	51.93228	54.88132
4	69.85600	48.23067	49.13857	46.81142	50.08756	42.50936	83.23597	73.79040	44.87992	51.33915	...	356.65583	200.61550	128.84925	116.39241	89.90483	80.54440	52.29518	65.01838	62.95591	61.35586
5	76.40160	42.57160	50.38175	51.80404	47.59427	41.18479	50.88559	55.47304	50.64592	50.03333	...	515.90239	228.68634	550.69584	372.03552	121.54316	90.09829	69.64879	96.32019	63.56461	56.37973
6	58.80151	50.78167	54.44780	63.54956	56.18738	46.49468	49.04318	51.76220	63.22538	85.78638	...	697.16494	655.78041	484.59225	539.28921	443.63649	252.27457	129.93238	95.94847	55.74373	59.90149
7	61.91512	37.68067	35.86701	50.08186	84.66419	82.76149	71.15154	65.06230	56.12031	90.97828	...	614.41857	641.84395	646.67456	446.08255	588.31174	669.10054	180.65144	106.53503	69.29114	79.08854

Software	Version
Python	3.6.3 64bit [GCC 7.2.0]
IPython	6.1.0
OS	Linux 4.9.0 4 amd64 x86_64 with debian 9.1
Tue Oct 17 18:59:09 2017 CEST