Update light_curve_flare.ipynb
"\n",
"We have seen in the general presentation of the light curve estimator, see [light curve notebook](light_curve.ipynb), Gammapy produces datasets in a given time interval, by default that of the parent observation. To be able to produce datasets on smaller time steps, it is necessary to split the observations into the required time intervals. \n",
"\n",
- "This is easily performed with the `select_time` method of `~gammapy.Observations`. If you pass it a list of time intervals it will produce a list of time filtered observations in a new `~gammapy.Observations` object. Data reduction can then be performed and will result in datasets defined on the required time intervals and light curve estimation can proceed directly.\n",
+ "This is easily performed with the `select_time` method of `~gammapy.data.Observations`. If you pass it a list of time intervals it will produce a list of time filtered observations in a new `~gammapy.data.Observations` object. Data reduction can then be performed and will result in datasets defined on the required time intervals and light curve estimation can proceed directly.\n",
"\n",
"In summary, we have to:\n",
+ "\n",
"- Select relevant `~gammapy.data.Observations` from the `~gammapy.data.DataStore`\n",
"- Apply the time selection in our predefined time intervals to obtain a new `~gammapy.data.Observations`\n",
"- Perform the data reduction (in 1D or 3D)\n",
"- Define the source model\n",
"- Extract the light curve from the reduced dataset\n",
"\n",
- "Here, we will use the PKS 2155-304 observations from the H.E.S.S. first public test data release. We will use time intervals of 5 minutes duration. We use here the intermediate API.\n",
+ "Here, we will use the PKS 2155-304 observations from the H.E.S.S. first public test data release. We will use time intervals of 5 minutes duration. The tutorial is implemented with the intermediate level API.\n",
"\n",
"## Setup \n",
"\n",
