Difference between revisions of "Matplotlib DPL94 R1rho R2eff"

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Line 52: Line 52:
 
x_w_eff = []
 
x_w_eff = []
 
x_theta = []
 
x_theta = []
 +
x_disp_point = []
 
y = []
 
y = []
  
Line 58: Line 59:
 
     R1 = cdp.myspin.ri_data['R1']
 
     R1 = cdp.myspin.ri_data['R1']
 
     R1_rho = cdp.myspin.r2eff[dic_key]
 
     R1_rho = cdp.myspin.r2eff[dic_key]
 +
    print(dic_key.split("_"))
 +
 +
    # Get disp_point, the Spin-lock field strength
 +
    x_disp_point.append(float(dic_key.split("_")[-1]))
  
 
     # Get w_eff
 
     # Get w_eff
Line 70: Line 75:
 
     R1rho_R2eff = (R1_rho - R1*cos(theta)*cos(theta)) / (sin(theta) * sin(theta))
 
     R1rho_R2eff = (R1_rho - R1*cos(theta)*cos(theta)) / (sin(theta) * sin(theta))
 
     y.append(R1rho_R2eff)
 
     y.append(R1rho_R2eff)
 +
 +
print x_disp_point
  
 
# Modify data
 
# Modify data
Line 90: Line 97:
 
plt.ylim([0,16])
 
plt.ylim([0,16])
 
plt.title("%s \n %s as function of %s"%(spin_inte,ylabel, xlabel))
 
plt.title("%s \n %s as function of %s"%(spin_inte,ylabel, xlabel))
plt.savefig("matplotlib_%s_%s_w_eff.png"%(spin_inte_rep, plotlabel) )
+
#plt.savefig("matplotlib_%s_%s_w_eff.png"%(spin_inte_rep, plotlabel) )
  
 
# Plot R1rho_R2eff as function of w_eff
 
# Plot R1rho_R2eff as function of w_eff
Line 104: Line 111:
 
plt.ylim([0,16])
 
plt.ylim([0,16])
 
plt.title("%s \n %s as function of %s"%(spin_inte,ylabel, xlabel))
 
plt.title("%s \n %s as function of %s"%(spin_inte,ylabel, xlabel))
plt.savefig("matplotlib_%s_%s_theta.png"%(spin_inte_rep, plotlabel) )
+
#plt.savefig("matplotlib_%s_%s_theta.png"%(spin_inte_rep, plotlabel) )
 +
 
 +
# Plot R1rho_R2eff as function of disp_point, the Spin-lock field strength
 +
plt.figure()
 +
plotlabel = 'R1rho_R2eff'
 +
plt.plot(x_disp_point, y, 'o', label='R1rho_R2eff')
 +
xlabel = 'Spin-lock field strength [Hz]'
 +
plt.xlabel(xlabel)
 +
ylabel = 'R1rho_R2eff [rad.s^-1]'
 +
plt.ylabel(ylabel)
 +
plt.legend(loc='best')
 +
plt.grid(True)
 +
#plt.ylim([0,16])
 +
plt.title("%s \n %s as function of %s"%(spin_inte,ylabel, xlabel))
 +
plt.savefig("matplotlib_%s_%s_disp.png"%(spin_inte_rep, plotlabel) )
 +
 
 +
 
 
plt.show()
 
plt.show()
 
</source>
 
</source>

Revision as of 19:01, 13 March 2014

About

Code

File: r1rhor2eff.py

### python imports
import sys
import os
from math import cos, sin

### plotting facility.
import matplotlib.pyplot as plt

### relax modules
# Import some tools to loop over the spins.
from pipe_control.mol_res_spin import return_spin, spin_loop
# Import method to calculate the R1rho offset data
from specific_analyses.relax_disp.disp_data import calc_rotating_frame_params, generate_r20_key, loop_exp_frq

###############

# You have to provide a DPL94 results state file
res_folder = "resultsR1"
res_state = os.path.join(res_folder, "DPL94", "results")
spin_inte = ":52@N"
spin_inte_rep = spin_inte.replace('#', '_').replace(':', '_').replace('@', '_')

# Load the state
state.load(res_state, force=True)

# Show pipes
pipe.display()
pipe.current()

# Get the spin of interest and save it in cdp, to access it after execution of script.
cdp.myspin = return_spin(spin_inte)

# Calculate the offset data
theta_spin_dic, Domega_spin_dic, w_eff_spin_dic, dic_key_list = calc_rotating_frame_params(spin=cdp.myspin, spin_id=spin_inte, verbosity=1)
# Save the data in cdp to access it after execution of script.
cdp.myspin.theta_spin_dic = theta_spin_dic
cdp.myspin.w_eff_spin_dic = w_eff_spin_dic
cdp.myspin.dic_key_list = dic_key_list

# Create spin.r2 keys
r2keys = []
for exp_type, frq in loop_exp_frq():
    r2keys.append(generate_r20_key(exp_type=exp_type, frq=frq) )
# Save the keys
cdp.r2keys = r2keys

x_w_eff = []
x_theta = []
x_disp_point = []
y = []

for dic_key in cdp.myspin.dic_key_list:
    R1_rho_prime = cdp.myspin.r2[cdp.r2keys[0]]
    R1 = cdp.myspin.ri_data['R1']
    R1_rho = cdp.myspin.r2eff[dic_key]
    print(dic_key.split("_"))

    # Get disp_point, the Spin-lock field strength
    x_disp_point.append(float(dic_key.split("_")[-1]))

    # Get w_eff
    w_eff = cdp.myspin.w_eff_spin_dic[dic_key]
    x_w_eff.append(w_eff)

    # Get theta
    theta = cdp.myspin.theta_spin_dic[dic_key]
    x_theta.append(theta)

    # Calculate y value
    R1rho_R2eff = (R1_rho - R1*cos(theta)*cos(theta)) / (sin(theta) * sin(theta))
    y.append(R1rho_R2eff)

print x_disp_point

# Modify data
w_eff_div = 10**4
rem_points = 2
x_w_eff_mod = [x/w_eff_div for x in x_w_eff[:-rem_points]]
y_mod = y[:-rem_points]


# Plot R1rho_R2eff as function of w_eff
plt.figure()
plotlabel = 'R1rho_R2eff'
plt.plot(x_w_eff_mod, y_mod, 'o', label='R1rho_R2eff')
xlabel = 'Effective field in rotating frame [%s rad.s^-1]'%(str(w_eff_div))
plt.xlabel(xlabel)
ylabel = 'R1rho_R2eff [rad.s^-1]'
plt.ylabel(ylabel)
plt.legend(loc='best')
plt.grid(True)
plt.ylim([0,16])
plt.title("%s \n %s as function of %s"%(spin_inte,ylabel, xlabel))
#plt.savefig("matplotlib_%s_%s_w_eff.png"%(spin_inte_rep, plotlabel) )

# Plot R1rho_R2eff as function of w_eff
plt.figure()
plotlabel = 'R1rho_R2eff'
plt.plot(x_theta, y, 'o', label='R1rho_R2eff')
xlabel = 'Rotating frame tilt angle [rad]'
plt.xlabel(xlabel)
ylabel = 'R1rho_R2eff [rad.s^-1]'
plt.ylabel(ylabel)
plt.legend(loc='best')
plt.grid(True)
plt.ylim([0,16])
plt.title("%s \n %s as function of %s"%(spin_inte,ylabel, xlabel))
#plt.savefig("matplotlib_%s_%s_theta.png"%(spin_inte_rep, plotlabel) )

# Plot R1rho_R2eff as function of disp_point, the Spin-lock field strength
plt.figure()
plotlabel = 'R1rho_R2eff'
plt.plot(x_disp_point, y, 'o', label='R1rho_R2eff')
xlabel = 'Spin-lock field strength [Hz]'
plt.xlabel(xlabel)
ylabel = 'R1rho_R2eff [rad.s^-1]'
plt.ylabel(ylabel)
plt.legend(loc='best')
plt.grid(True)
#plt.ylim([0,16])
plt.title("%s \n %s as function of %s"%(spin_inte,ylabel, xlabel))
plt.savefig("matplotlib_%s_%s_disp.png"%(spin_inte_rep, plotlabel) )


plt.show()

To run

relax -p r1rhor2eff.py

See also